When should prophylactic anticoagulation begin after a hip fracture?

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Three-in-One Pill for HIV

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Soft Tissue Augmentation

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You must justify D&C with fibroid resection

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Q I performed a resection of a submucous fibroid and also did uterine curettage. I will report code 58561 (Hysteroscopy, surgical; with removal of leiomyomata) for the primary procedure, but can I also bill for the curettage?

A Yes. Code 58120 (Dilation and curettage, diagnostic and/or therapeutic [nonobstetrical]) is not bundled with code 58561 under the National Correct Coding Initiative (NCCI). But to avoid denial you must establish medical justification for doing the curettage by indicating a diagnosis other than submucous fibroid (218.0).

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Q I performed a resection of a submucous fibroid and also did uterine curettage. I will report code 58561 (Hysteroscopy, surgical; with removal of leiomyomata) for the primary procedure, but can I also bill for the curettage?

A Yes. Code 58120 (Dilation and curettage, diagnostic and/or therapeutic [nonobstetrical]) is not bundled with code 58561 under the National Correct Coding Initiative (NCCI). But to avoid denial you must establish medical justification for doing the curettage by indicating a diagnosis other than submucous fibroid (218.0).

Q I performed a resection of a submucous fibroid and also did uterine curettage. I will report code 58561 (Hysteroscopy, surgical; with removal of leiomyomata) for the primary procedure, but can I also bill for the curettage?

A Yes. Code 58120 (Dilation and curettage, diagnostic and/or therapeutic [nonobstetrical]) is not bundled with code 58561 under the National Correct Coding Initiative (NCCI). But to avoid denial you must establish medical justification for doing the curettage by indicating a diagnosis other than submucous fibroid (218.0).

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HPV-positive test in a pregnant woman

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Q How do you code a positive test for human papillomavirus high-risk DNA (795.05) in a pregnant patient?

A The most accurate code for this finding would be 647.63 (Other viral diseases). This code includes conditions classifiable to HPV. Your secondary diagnosis will be 795.05.

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Q How do you code a positive test for human papillomavirus high-risk DNA (795.05) in a pregnant patient?

A The most accurate code for this finding would be 647.63 (Other viral diseases). This code includes conditions classifiable to HPV. Your secondary diagnosis will be 795.05.

Q How do you code a positive test for human papillomavirus high-risk DNA (795.05) in a pregnant patient?

A The most accurate code for this finding would be 647.63 (Other viral diseases). This code includes conditions classifiable to HPV. Your secondary diagnosis will be 795.05.

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More RVUs for 3 office hysteroscopy procedures

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Q We perform diagnostic and operative hysteroscopy in our office. How do we recoup our loss compared with the hospital? Can we bill a separate physician and technical component?

A The Medicare Resource-Based Relative Value Scale (RBRVS) normally allows a practice expense increase for procedures that may be performed in the office and require expensive equipment, but are more typically performed in the hospital. The Medicare Relative Value Unit (RVU) is 9.42 for code 58558 (Hysteroscopy, surgical; with sampling [biopsy] of endometrium and/or polypectomy, with or without D & C). For hysteroscopy procedures, there is no difference in the RVU for site of service—with 3 exceptions:

  • Diagnostic hysteroscopy carries .65 more (RVUs) for the office setting.
  • Endometrial ablation has 63.25 RVUs for the office setting, but only 9.66 for the hospital setting.
  • Essure, a new hysteroscopic sterilization technology, carries 57.91 RVUs in the office setting.

The vastly increased RVU for the latter 2 procedures in the office setting covers the more expensive equipment needed.

Hysteroscopic procedures do not have a professional and technical component in the typical sense. Although you may have additional practice costs such as a dedicated treatment room or special equipment, these may not be accurately reflected in the allowable for the hysteroscopic procedure you perform in the office setting. The current RVU system does not allow for separate payment of a “facility fee”; all practice costs associated with performing the procedure are added into the practice expense portion of the RVU for each procedure. Although all payers bundle the surgical tray into the reimbursement for the procedure, consider negotiating for a “facility fee” that adequately covers your additional expenses, by pointing out that money will be saved when the hysteroscopy is performed in the office.

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Q We perform diagnostic and operative hysteroscopy in our office. How do we recoup our loss compared with the hospital? Can we bill a separate physician and technical component?

A The Medicare Resource-Based Relative Value Scale (RBRVS) normally allows a practice expense increase for procedures that may be performed in the office and require expensive equipment, but are more typically performed in the hospital. The Medicare Relative Value Unit (RVU) is 9.42 for code 58558 (Hysteroscopy, surgical; with sampling [biopsy] of endometrium and/or polypectomy, with or without D & C). For hysteroscopy procedures, there is no difference in the RVU for site of service—with 3 exceptions:

  • Diagnostic hysteroscopy carries .65 more (RVUs) for the office setting.
  • Endometrial ablation has 63.25 RVUs for the office setting, but only 9.66 for the hospital setting.
  • Essure, a new hysteroscopic sterilization technology, carries 57.91 RVUs in the office setting.

The vastly increased RVU for the latter 2 procedures in the office setting covers the more expensive equipment needed.

Hysteroscopic procedures do not have a professional and technical component in the typical sense. Although you may have additional practice costs such as a dedicated treatment room or special equipment, these may not be accurately reflected in the allowable for the hysteroscopic procedure you perform in the office setting. The current RVU system does not allow for separate payment of a “facility fee”; all practice costs associated with performing the procedure are added into the practice expense portion of the RVU for each procedure. Although all payers bundle the surgical tray into the reimbursement for the procedure, consider negotiating for a “facility fee” that adequately covers your additional expenses, by pointing out that money will be saved when the hysteroscopy is performed in the office.

Q We perform diagnostic and operative hysteroscopy in our office. How do we recoup our loss compared with the hospital? Can we bill a separate physician and technical component?

A The Medicare Resource-Based Relative Value Scale (RBRVS) normally allows a practice expense increase for procedures that may be performed in the office and require expensive equipment, but are more typically performed in the hospital. The Medicare Relative Value Unit (RVU) is 9.42 for code 58558 (Hysteroscopy, surgical; with sampling [biopsy] of endometrium and/or polypectomy, with or without D & C). For hysteroscopy procedures, there is no difference in the RVU for site of service—with 3 exceptions:

  • Diagnostic hysteroscopy carries .65 more (RVUs) for the office setting.
  • Endometrial ablation has 63.25 RVUs for the office setting, but only 9.66 for the hospital setting.
  • Essure, a new hysteroscopic sterilization technology, carries 57.91 RVUs in the office setting.

The vastly increased RVU for the latter 2 procedures in the office setting covers the more expensive equipment needed.

Hysteroscopic procedures do not have a professional and technical component in the typical sense. Although you may have additional practice costs such as a dedicated treatment room or special equipment, these may not be accurately reflected in the allowable for the hysteroscopic procedure you perform in the office setting. The current RVU system does not allow for separate payment of a “facility fee”; all practice costs associated with performing the procedure are added into the practice expense portion of the RVU for each procedure. Although all payers bundle the surgical tray into the reimbursement for the procedure, consider negotiating for a “facility fee” that adequately covers your additional expenses, by pointing out that money will be saved when the hysteroscopy is performed in the office.

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Strategies for a Safe and Effective Resident Sign‐Out

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Managing discontinuity in academic medical centers: Strategies for a safe and effective resident sign‐out

Modern‐day continuity of patient care in teaching hospitals, once remarkably high because of a cadre of sleep‐deprived residents, is now peppered with breaks, each accompanied by the transfer of patient care responsibility from one resident to another; a process often referred to as a handoff. Such transitions have long been a part of medical practice but have recently received increased attention because of restrictions in the duty hours of house staff. In July 2003 the Accreditation Council for Graduate Medical Education (ACGME) mandated reduced duty hours for all trainees in hopes of improving resident education and well‐being and patient safety.1 In fact, some studies have shown improved resident well‐being2 and fewer medical errors with reductions in duty hours,3, 4 but the growing consensus about the negative consequences of resident fatigue on patient safety has been accompanied by parallel concerns about the potential for information loss with each break in the continuity of care.5, 6

Although the tradeoff of increased discontinuity of care for fewer hours worked is sometimes characterized as an unintended consequence of duty hour regulations, it is in fact predictable and essential. As individuals work fewer hours, discontinuity must necessarily increase (assuming 24‐hour coverage).7 The extent to which this occurs may vary, but the link is consistent. At the University of California, San Francisco (UCSF), for example, we found that compliance with new duty hour requirements for internal medicine resulted in an average of 15 handoffs per patient during a 5‐day hospitalization. Each individual intern was involved in more than 300 handoffs in an average month‐long rotation, an increase of 40% since system changes were introduced to decrease duty hours. We found similar increases at Brigham and Women's Hospital (BWH) and the University of Chicago. Because U.S. teaching hospitals care for more than 6 million patients each year,8 the impact of these handoffs on the quality and efficiency of care is tremendous.

Discontinuity of care is currently managed by sign‐out, or the transfer of patient information from one physician to another. Recognizing the importance of information transfer at these vulnerable transition times for patients, the Joint Commission on Accreditation of Hospital Organizations (JCAHO) issued the 2006 National Patient Safety Goal 2E: Implement a standardized approach to hand off communications, including an opportunity to ask and respond to questions.9 Hospitals have little data to draw on to determine how to comply with this mandate and even less data to guide them in how to achieve its intended goals of improving communication and thus patient safety.

In an effort to better understand sign‐outs and ways to improve this process for house staff on in‐patient services, we reviewed data from the fields of aviation, communications, systems engineering, and human factors research, and we also searched the medical literature using key words pass‐off, handoff, sign‐out, duty hours, work hours, and discontinuity of care and MeSH headings Continuity of Patient Care Internship and Residency/*organization & administration, Personnel Staffing and Scheduling/*organization & administration, and Quality of Health Care. We also searched the websites of the Agency of Healthcare Quality and Research and the National Patient Safety Foundation. On the basis of these reviews, our experiences as hospitalist medical educators organizing resident sign‐out efforts at the University of California, San Francisco, the University of Chicago, and Brigham and Women's Hospital, and our efforts leading national training sessions on sign‐outs at the Society of General Internal Medicine (2004 and 2005), the Society of Hospital Medicine (2004), and the Association of Program Directors in Internal Medicine (2005, 2006), we propose a set of best practices regarding the content and process of sign‐out in an effort to improve communication between residents caring for hospitalized patients, assist programs in building safe and effective sign‐out systems, and improve the quality of patient care.

Effects of Discontinuity on Patient Safety

Research on the effects of discontinuity of care, although limited, suggests it has a negative impact on patient safety. In a study that investigated the institution of code 405 (the regulation that reduced duty hours in New York State), researchers found that the presumed increase in discontinuity with decreased duty hours resulted in delayed test ordering and an increased number of hospital complications.10 Another study found that the number of potentially preventable adverse events doubled when patients were under the care of a physician from a nonprimary team (eg, the cross‐covering intern).11 Studies have also linked resident discontinuity with longer length of stay, increased laboratory testing, and increased medication errors.12, 13

Managing Discontinuity: Sign‐Out as the Means of Information Transfer

In theory, more effective sign‐out systems should mitigate the potential for patient harm, but there is little in the literature describing current effective sign‐out practices or the best ways to design and implement such systems in the health care field. Examining information transfer mechanisms used in fields outside health care can assist in developing these systems.

Information Transfer in Other Industries

Although there is a paucity of data on sign‐out in the medical literature, information transfer has been the subject of substantial research in other industries in which safety depends on effective communication.

Aviation, for example, created systems and processes to improve handoff communication in response to accidents linked to failures in information transfer. One example, the 1977 collision of 2 747s on an airport runway in Tenerife, the Canary Islands, occurred after a garbled transmission from an air traffic controller to the cockpit of one of the aircraft. It was determined that a culture of adherence to a steep hierarchy prevented subordinates from questioning the captain's mistaken certainty that a runway was clear,14 an erroneous belief that was the basis for his decision to continue the aircraft on its course, resulting in its collision with the other airplane.

Subsequently, commercial aviation designed systems that standardized and formalized the process of information transfer and improved teamwork and coordination. These interventions were developed on the basis of detailed observations of cockpit interactions, reviews of communication errors, and focus groups.15 Because of these efforts, today's pilots use standardized checklists to transfer information content, communicate at designated times in specific undistracted environments, and use standard language and read‐backs to enhance understanding.16 The result has been a remarkable decrease in the risk of aviation crashes, one that most experts attribute in large part to these efforts to improve communication.17

Observation of how communication occurs in other high‐risk industries has informed the arena of effective information transfer. For example, direct observation of information transfer at NASA, in nuclear power plants, and in the railway industry identified specific strategies for effective handoffs/sign‐outs such as standardizing the information transferred, ensuring information is up to date, limiting interruptions, and having a structured face‐to‐face verbal interchange.18

Other strategies noted to be effective in diminishing errors are the use of a standardized phonetic alphabet to ensure that information is correctly heard and understood4 and having interactive verbal communication occur at a whiteboard.19

Information Transfer in Health Care

Those in the discipline of nursing have vast experience in the transfer of patient care information. The sign‐out process employed by nurses includes face‐to‐face discussions, typed information, and, most commonly, taped verbal communication.20 Interestingly, this process has not been subject to detailed scrutiny, and there is little information in the literature about best practices in sign‐out. Most articles in the literature on nursing handoffs are ethnographic descriptions of patient care responsibilities,21 on the basis of which, the authors advocate standardization of the information to be transferred, formalization of the channel used to communicate, and attention to increasing a culture of professionalism during sign‐out in order to improve efficiency.20, 22

There is little in the literature on transfer of care among physicians. Improvements in sign‐out have been suggested as part of broad strategies, such as increased training and information technology support,4, 7, 23, 24 and specific strategies have been offered such as managing barriers to communication, including specific types of data when transferring care,25 and involving nurses and senior physicians in sign‐outs.26 Specific outcomes data in this area have focused primarily on the use of computerized systems to improve information transfer. For example, the use of a computerized sign‐out system at Brigham and Women's Hospital (BWH), linked to the hospital's information system to ensure up‐to‐date information on patient demographics, medications, and laboratory values, has resulted in fewer errors,27 as have other similar systems.28 At the University of Washington, use of a similarly linked computerized sign‐out system resulted in fewer patients being missed on rounds and improvement in the quality of sign‐out and continuity of care according to resident self‐reports.29 Unfortunately, fewer than 10% of hospitals have such integrated hospitalwide information systems to support the sign‐out function.30

It has been noted that verbal communication, in concert with advances in technological communication, is important in information transfer in health care,18, 31 especially in emergent or urgent conditions.32 For example, eliminating the phoned‐in report from the lab to the ER and replacing it with delivery by an electronic reporting system lacking verbal communicationresulted in 45% of emergent lab results going unchecked.32 Structured verbal communication tools have been efficacious in improving information transfer outside the formal sign‐outfor example, read‐backs, which reduced errors in the reporting of critical laboratory values,33 and the SBAR (situation, background, assessment, recommendation) tool (designed to frame the transfer of critical information), which improved physician and nurse patient care information transfer in the in‐patient setting of the Kaiser Permanente health system.34

In focus groups and in response to formal and informal surveys, residents at our 3 sites suggested inclusion of the following information, provided in writing and orally, to improve sign‐outs: up‐to‐date administrative information (eg, room number, primary care physician); patient's recent cognitive or cardiopulmonary status; problems the patient had already experienced and treatments previously tried, both successfully and unsuccessfully; patient's code status and discussions on level of care; test results or consultation recommendations that were likely to come back while covering the patient and what to do with the results; and relevant psychosocial information (eg, complex family dynamics).35

The Current Practice of Sign‐Out

In examining sign‐outs at our 3 institutions, we found them to be unstructured and unstandardized. From discussion with faculty participating in national workshops on sign‐out, we found that most sign‐outs are conducted by interns, usually with little or no formal training. Templates, checklists, or other methods to standardize the content of the information transferred were rarely used.

We also noted that the vehicle for written sign‐out is highly variable. At UCSF, different residency training programs used a variety of modalities for written sign‐outs, including index cards, Excel spreadsheets, Word documents, and loose sheets of paper. Recently, the UCSF Department of Medicine designed a simple database (on Filemaker Pro) that allows members of the house staff to update their sign‐out information, share it with other house staff and nurses, and access it at locations throughout the hospital (Fig. 1). Although this database is not yet linked to the hospital information system (planned for 2006), anecdotally resident satisfaction with sign‐out has vastly improved since its implementation. The cost of design and implementation was approximately $10,000. At the University of Chicago, interns used Microsoft Word to create sign‐out sheets containing patient summaries to transfer information. However, during structured interviews, 95% of the interns reported that these sheets were frequently lost or misplaced.7 Although medicine residents at BWH use a computerized system to produce sign‐out sheets, this system did not guarantee complete and structured information. For example, a survey at BWH found that 56% of cross‐covering residents said that when paged about a patient overnight, the relevant information needed to care for that patient was present less than half the time; and 27% of residents reported being paged more than 3 times in the previous 2 weeks about a test result or consultant recommendation that they did not know was pending.36

Figure 1
UCSF Filemaker Pro written sign‐out vehicle.

The process of sign‐out also varied across disciplines and institutions. From our experiences at our sites and at the sites of faculty nationally, we found limited standardization about whether sign‐out was verbal, the data transmitted, and the setting in which it was transmitted. In fact, at UCSF most residents signed out verbally on the fly, wherever and whenever they could find the cross‐coverage intern. At BWH, only 37% of residents said that sign‐out occurred in a quiet place most of the time, and only 52% signed out on every patient both orally and in writing.36 At the University of Chicago, the sign‐out process was characterized by outright failures in communication because of omission of needed information (ie, medications, active or anticipated medical problems, etc.) or by failure‐prone communication (ie, lack of face‐to‐face communication, illegible writing). These failures often led to uncertainty in making patient care decisions, potentially resulting in inefficient or suboptimal care.35

Strategies for Safe and Effective Sign‐Out

Given the current landscape of variability in sign‐outs, the recognition that information lost during sign‐out may result in harm to patients, and evidence of improvements in information transfer in areas outside health care, we aimed to develop mechanisms to improve the sign‐out process for residents working in a hospital setting. These strategies are based on our review of the existing literature supplemented by our experiences at our 3 institutions.

Content of Sign‐Out

The elements of content necessary for safe and effective sign‐out can be divided into 5 broad categories (Table 1), contained in the mnemonic ANTICipate: Administrative information, New clinical information, specific Tasks to be performed, assessment of severity of Illness, and Contingency plans or anticipated problems (Table 1, Fig. 2).

Checklist for Elements of a Safe and Effective Written Sign‐outANTICipate
Administrative data
□ Patient name, age, sex
□ Medical record number
□ Room number
□ Admission date
□ Primary inpatient medical team, primary care physician
□ Family contact information
New information (clinical update)
□ Chief complaint, brief HPI, and diagnosis (or differential diagnosis)
□ Updated list of medications with doses, updated allergies
□ Updated, brief assessment by system/problem, with dates
□ Current baseline status (eg, mental status, cardiopulmonary, vital signs, especially if abnormal but stable)
□ Recent procedures and significant events
Tasks (what needs to be done)
□ Specific, using if‐then statements
□ Prepare cross‐coverage (eg, patient consent for blood transfusion)
□ Alert to incoming information (eg, study results, consultant recommendations), and what action, if any, needs to be taken during the cross‐coverage
Illness
□ Is the patient sick?
Contingency planning/Code status
□ What may go wrong and what to do about it
□ What has or has not worked before (eg, responds to 40 mg IV furosemide)
□ Difficult family or psychosocial situations
□ Code status, especially recent changes or family discussions
Figure 2
Example of a written sign‐out.

Several general points about this list should be noted. First, the sign‐out content is not meant to replace the chart. The information included reflects the goal of a sign‐out, namely, to provide enough information to allow for a safe transition in patient care. Information we believe is not essential to the sign‐out includes: a complete history and physical exam from the day of admission, a list of tasks already completed, and data necessary only to complete a discharge summary.

Sign‐out must be also be a closed loopthe process of signing in is as important as the process of signing out. This usually entails members of the primary team obtaining information from the cross‐covering physician when they resume care of the patient. The information conveyed in this case is different and includes details on events during cross‐coverage such as: 1) time called to assess patient; 2) reason for call; 3) a brief assessment of the patient, including vital signs; 4) actions taken, for example, medications given and tests ordered; and 5) rationale for those actions. Some of this information may also be included in the chart as an event note (see Fig. 3).

Figure 3
Example of patient event note.

The Vehicle for Sign‐Out

We recommend a computer‐assisted vehicle for patient information transfer. Ideally, this would be linked to the hospital information system to ensure accurate and up‐to‐date information Easy access to the computerized sign‐out is essential (eg, using a hospitalwide computer system, shared hard drive service, intranet, or PDA linked to the computer system), and it should be customizable for the varied needs of different services and departments. The system should have templates to standardize the content of sign‐out, contain robust backup systems, and be HIPAA compliant (ie, restrict access to required health care personnel). However, the perfect should not be the enemy of the good: systems that do not meet these criteria may still help to protect patients by providing legible, predictable, and accessible information.

Sign‐Out Processes

Verbal communication.

Although electronic solutions can facilitate the standardization of written content, face‐to‐face verbal communication adds additional value.19 We recommend that each patient be reviewed separately. Identification of each patient verbally ensures that those engaged in the sign‐out are discussing the same patient. Reiterating the major medical problems gives a snapshot of the patient and frames the sign‐out. The to‐do list, the list of tasks that the cross‐cover resident needs to complete during cross coverage, should be specific and articulated as if, then statements (eg, if the urine output is less than 1 L, then give 40 mg of IV furosemide). The receiver of sign‐out should read back to the person giving the sign‐out each item on the to‐do list (eg, So, I should check the ins and outs at about 10:00 pm, and give 40 of furosemide if the patient is not 1 L negative, right?).

Anticipated problems should also be verbally communicated to promote a dialogue. Points that cannot be adequately transferred in the written sign‐out are particularly important to transmit verbally. Examples include previous code discussions, unusual responses to treatment, and psychosocial and family issues. When delivering verbal sign‐out, it is important to consider the a priori knowledge of the recipient. How much knowledge about a patient is already shared between the outgoing and incoming physicians and the level of experience of the physicians may affect the extent to which information needs be transmitted.37 For instance, 2 experienced physicians who already have been working to cover the same patient will likely have an abbreviated discussion, in contrast to the lengthier sign‐out necessary if the outgoing and incoming physicians are interns, and the incoming intern has no prior knowledge of the patient. Similarly, it is likely the level of detail transmitted will need to be greater during a permanent transfer of patient care (ie, at the end of a resident's rotation) than during a brief, temporary transition (eg, overnight coverage).

The challenges of a busy inpatient service may preclude a complete verbal sign‐out for all patients; we contend, though, it is best to use these practices to the extent possible, especially for patients with treatment plans in flux, those whose status is tenuous, and those who have anticipated changes in status during cross‐coverage. One tool that may be effectively used in signing out such patients is the SBAR tool, according to which a brief description of the situation is given, followed by the background and the physician's specific assessment and complete recommendation.38 For example, a resident signing out might begin by stating, I have 18 patients to sign‐out to you. I'm going to describe 6 active patients in detail. Twelve others are fairly stable, and I will give you basic information about them, and the details are in the written sign‐out. One patient has a plan in flux. The situation is Mr. S. is having trouble breathing, the background is that he has both CHF and COPD, my assessment is that this is more cardiac than pulmonary, and I recommend that you see him first and discuss with the cardiology consultant. Using the tools described here (Table 2), a sign‐out of 15 patients of variable acuity could be verbally signed out in less than 10 minutes.

Checklist for Verbal Communication During Sign‐Out: The Who, What, Where, When, and How
WHO should participate in the sign‐out process?
□ Outgoing clinician primarily responsible for patient's care
□ Oncoming clinician who will be primarily responsible for patient's care (avoid passing this task to someone else, even if busy)
□ Consider supervision by experienced clinicians if early in training
WHAT content needs to be verbally communicated?
Use situation briefing model, or SBAR, technique:
SituationIdentify each patient (name, age, sex, chief complaint) and briefly state any major problems (active and those that may become active during cross‐coverage).
Backgroundpertinent information relevant to current care (eg, recent vitals and/or baseline exam, labs, test results, etc).
Assessmentworking diagnosis, response to treatment, anticipated problems during cross‐coverage including anything not adequately described using written form (eg, complex family discussions).
Recommendationto‐do lists and if/then recommendations.
WHERE should sign‐out occur?
□ Designated room or place for sign‐out (eg, avoid patient areas because of HIPPA requirements)
□ Proper lighting
□ Avoid excessive noise (eg, high‐traffic areas)
□ Minimize disruptions (eg, hand over pagers)
□ Ensure systems support for sign‐out (eg, computers, printer, paper, etc.)
WHEN is the optimal time for sign‐out?
□ Designated time when both parties can be present and pay attention (eg, beware of clinic, other obligations)
□ Have enough time for interactive questions at the end (eg, avoid rush at the end of the shift)
HOW should verbal communication be performed?
□ Face to face, allowing for questions
□ Verbalize data in the same order for each patient at each sign‐out
□ Read back all to‐do items
□ Adjust length and depth of review according to baseline knowledge of parties involved and type of transition in care

The Environment and setting.

To improve the setting of sign‐out, we recommend: a designated space that is well lit, quiet, and respects patient confidentiality and a designated time when sign‐out will occur. To limit known distractions and interruptions39, 40 in the hospital, we also recommend the outgoing physician hand off his or her pager to someone else during sign‐out. Also key to an environment conducive to information transfer is ensuring adequate computer support for electronic sign‐out and access to updated clinical information.

Organizational culture and institutional leadership.

The way residents transfer patient care information reflects the culture of the institution. Changing the culture to one in which interactive questioning is valued regardless of position in the hierarchy has been shown to reduce errors in aviation.41 Educating residents on the impact of sign‐outs on patient care is a first step toward improving the culture of sign‐out. Resident commitment to the new sign‐out can be gained by engaging residents in development of the process itself. To cement these changes into the culture, practitioners at all levels should be aware of and support the new system. The role of an institution's leaders in achieving these changes cannot be overlooked. Leaders will need to be creative in order to support sign‐out as described within the obvious constraints of money, time, personnel, and space. Gaining institutional buy‐in can start with heightening the awareness of leaders of the issues surrounding sign‐out, including patient safety, resident efficiency, and the financial impact of discontinuity. Ongoing evaluation of efforts to improve sign‐out is also crucial and can be accomplished with surveys, focus groups, and direct observation. Feeding back the positive impact of the changes to all involved stakeholders will promote confidence in the new systems and pride in their efforts.

CONCLUSIONS

Sign‐outs are a part of the current landscape of academic medical centers as well as hospitals at large. Interns, residents, and consulting fellows, not to mention nurses, physical therapists, and nutritionists, transfer patient care information at each transition point. There are few resources that can assist these caregivers in identifying and implementing the most effective ways to transfer patient care information. Hospitals and other care facilities are now mandated to develop standards and systems to improve sign‐out. On the basis of the limited literature to date and our own experiences, we have proposed standards and best practices to assist hospitals, training programs, and institutional leaders in designing safe and usable sign‐out systems. Effective implementation of the standards must include appropriate allocation of resources, individualization to meet specific needs of each program or institution, intensive training, and ongoing evaluation. Future research should focus on developing valid surrogate measures of continuity of care, conducting rigorous trials to determine the elements of sign‐out that lead to the best patient outcomes, and studying the most effective ways of implementing these improvements. By improving the content and process of sign‐out, we can meet the challenges of the new health care landscape while putting patient safety at the forefront.

References
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Article PDF
Issue
Journal of Hospital Medicine - 1(4)
Page Number
257-266
Legacy Keywords
systems of care, medical education, patient safety
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Article PDF
Article PDF

Modern‐day continuity of patient care in teaching hospitals, once remarkably high because of a cadre of sleep‐deprived residents, is now peppered with breaks, each accompanied by the transfer of patient care responsibility from one resident to another; a process often referred to as a handoff. Such transitions have long been a part of medical practice but have recently received increased attention because of restrictions in the duty hours of house staff. In July 2003 the Accreditation Council for Graduate Medical Education (ACGME) mandated reduced duty hours for all trainees in hopes of improving resident education and well‐being and patient safety.1 In fact, some studies have shown improved resident well‐being2 and fewer medical errors with reductions in duty hours,3, 4 but the growing consensus about the negative consequences of resident fatigue on patient safety has been accompanied by parallel concerns about the potential for information loss with each break in the continuity of care.5, 6

Although the tradeoff of increased discontinuity of care for fewer hours worked is sometimes characterized as an unintended consequence of duty hour regulations, it is in fact predictable and essential. As individuals work fewer hours, discontinuity must necessarily increase (assuming 24‐hour coverage).7 The extent to which this occurs may vary, but the link is consistent. At the University of California, San Francisco (UCSF), for example, we found that compliance with new duty hour requirements for internal medicine resulted in an average of 15 handoffs per patient during a 5‐day hospitalization. Each individual intern was involved in more than 300 handoffs in an average month‐long rotation, an increase of 40% since system changes were introduced to decrease duty hours. We found similar increases at Brigham and Women's Hospital (BWH) and the University of Chicago. Because U.S. teaching hospitals care for more than 6 million patients each year,8 the impact of these handoffs on the quality and efficiency of care is tremendous.

Discontinuity of care is currently managed by sign‐out, or the transfer of patient information from one physician to another. Recognizing the importance of information transfer at these vulnerable transition times for patients, the Joint Commission on Accreditation of Hospital Organizations (JCAHO) issued the 2006 National Patient Safety Goal 2E: Implement a standardized approach to hand off communications, including an opportunity to ask and respond to questions.9 Hospitals have little data to draw on to determine how to comply with this mandate and even less data to guide them in how to achieve its intended goals of improving communication and thus patient safety.

In an effort to better understand sign‐outs and ways to improve this process for house staff on in‐patient services, we reviewed data from the fields of aviation, communications, systems engineering, and human factors research, and we also searched the medical literature using key words pass‐off, handoff, sign‐out, duty hours, work hours, and discontinuity of care and MeSH headings Continuity of Patient Care Internship and Residency/*organization & administration, Personnel Staffing and Scheduling/*organization & administration, and Quality of Health Care. We also searched the websites of the Agency of Healthcare Quality and Research and the National Patient Safety Foundation. On the basis of these reviews, our experiences as hospitalist medical educators organizing resident sign‐out efforts at the University of California, San Francisco, the University of Chicago, and Brigham and Women's Hospital, and our efforts leading national training sessions on sign‐outs at the Society of General Internal Medicine (2004 and 2005), the Society of Hospital Medicine (2004), and the Association of Program Directors in Internal Medicine (2005, 2006), we propose a set of best practices regarding the content and process of sign‐out in an effort to improve communication between residents caring for hospitalized patients, assist programs in building safe and effective sign‐out systems, and improve the quality of patient care.

Effects of Discontinuity on Patient Safety

Research on the effects of discontinuity of care, although limited, suggests it has a negative impact on patient safety. In a study that investigated the institution of code 405 (the regulation that reduced duty hours in New York State), researchers found that the presumed increase in discontinuity with decreased duty hours resulted in delayed test ordering and an increased number of hospital complications.10 Another study found that the number of potentially preventable adverse events doubled when patients were under the care of a physician from a nonprimary team (eg, the cross‐covering intern).11 Studies have also linked resident discontinuity with longer length of stay, increased laboratory testing, and increased medication errors.12, 13

Managing Discontinuity: Sign‐Out as the Means of Information Transfer

In theory, more effective sign‐out systems should mitigate the potential for patient harm, but there is little in the literature describing current effective sign‐out practices or the best ways to design and implement such systems in the health care field. Examining information transfer mechanisms used in fields outside health care can assist in developing these systems.

Information Transfer in Other Industries

Although there is a paucity of data on sign‐out in the medical literature, information transfer has been the subject of substantial research in other industries in which safety depends on effective communication.

Aviation, for example, created systems and processes to improve handoff communication in response to accidents linked to failures in information transfer. One example, the 1977 collision of 2 747s on an airport runway in Tenerife, the Canary Islands, occurred after a garbled transmission from an air traffic controller to the cockpit of one of the aircraft. It was determined that a culture of adherence to a steep hierarchy prevented subordinates from questioning the captain's mistaken certainty that a runway was clear,14 an erroneous belief that was the basis for his decision to continue the aircraft on its course, resulting in its collision with the other airplane.

Subsequently, commercial aviation designed systems that standardized and formalized the process of information transfer and improved teamwork and coordination. These interventions were developed on the basis of detailed observations of cockpit interactions, reviews of communication errors, and focus groups.15 Because of these efforts, today's pilots use standardized checklists to transfer information content, communicate at designated times in specific undistracted environments, and use standard language and read‐backs to enhance understanding.16 The result has been a remarkable decrease in the risk of aviation crashes, one that most experts attribute in large part to these efforts to improve communication.17

Observation of how communication occurs in other high‐risk industries has informed the arena of effective information transfer. For example, direct observation of information transfer at NASA, in nuclear power plants, and in the railway industry identified specific strategies for effective handoffs/sign‐outs such as standardizing the information transferred, ensuring information is up to date, limiting interruptions, and having a structured face‐to‐face verbal interchange.18

Other strategies noted to be effective in diminishing errors are the use of a standardized phonetic alphabet to ensure that information is correctly heard and understood4 and having interactive verbal communication occur at a whiteboard.19

Information Transfer in Health Care

Those in the discipline of nursing have vast experience in the transfer of patient care information. The sign‐out process employed by nurses includes face‐to‐face discussions, typed information, and, most commonly, taped verbal communication.20 Interestingly, this process has not been subject to detailed scrutiny, and there is little information in the literature about best practices in sign‐out. Most articles in the literature on nursing handoffs are ethnographic descriptions of patient care responsibilities,21 on the basis of which, the authors advocate standardization of the information to be transferred, formalization of the channel used to communicate, and attention to increasing a culture of professionalism during sign‐out in order to improve efficiency.20, 22

There is little in the literature on transfer of care among physicians. Improvements in sign‐out have been suggested as part of broad strategies, such as increased training and information technology support,4, 7, 23, 24 and specific strategies have been offered such as managing barriers to communication, including specific types of data when transferring care,25 and involving nurses and senior physicians in sign‐outs.26 Specific outcomes data in this area have focused primarily on the use of computerized systems to improve information transfer. For example, the use of a computerized sign‐out system at Brigham and Women's Hospital (BWH), linked to the hospital's information system to ensure up‐to‐date information on patient demographics, medications, and laboratory values, has resulted in fewer errors,27 as have other similar systems.28 At the University of Washington, use of a similarly linked computerized sign‐out system resulted in fewer patients being missed on rounds and improvement in the quality of sign‐out and continuity of care according to resident self‐reports.29 Unfortunately, fewer than 10% of hospitals have such integrated hospitalwide information systems to support the sign‐out function.30

It has been noted that verbal communication, in concert with advances in technological communication, is important in information transfer in health care,18, 31 especially in emergent or urgent conditions.32 For example, eliminating the phoned‐in report from the lab to the ER and replacing it with delivery by an electronic reporting system lacking verbal communicationresulted in 45% of emergent lab results going unchecked.32 Structured verbal communication tools have been efficacious in improving information transfer outside the formal sign‐outfor example, read‐backs, which reduced errors in the reporting of critical laboratory values,33 and the SBAR (situation, background, assessment, recommendation) tool (designed to frame the transfer of critical information), which improved physician and nurse patient care information transfer in the in‐patient setting of the Kaiser Permanente health system.34

In focus groups and in response to formal and informal surveys, residents at our 3 sites suggested inclusion of the following information, provided in writing and orally, to improve sign‐outs: up‐to‐date administrative information (eg, room number, primary care physician); patient's recent cognitive or cardiopulmonary status; problems the patient had already experienced and treatments previously tried, both successfully and unsuccessfully; patient's code status and discussions on level of care; test results or consultation recommendations that were likely to come back while covering the patient and what to do with the results; and relevant psychosocial information (eg, complex family dynamics).35

The Current Practice of Sign‐Out

In examining sign‐outs at our 3 institutions, we found them to be unstructured and unstandardized. From discussion with faculty participating in national workshops on sign‐out, we found that most sign‐outs are conducted by interns, usually with little or no formal training. Templates, checklists, or other methods to standardize the content of the information transferred were rarely used.

We also noted that the vehicle for written sign‐out is highly variable. At UCSF, different residency training programs used a variety of modalities for written sign‐outs, including index cards, Excel spreadsheets, Word documents, and loose sheets of paper. Recently, the UCSF Department of Medicine designed a simple database (on Filemaker Pro) that allows members of the house staff to update their sign‐out information, share it with other house staff and nurses, and access it at locations throughout the hospital (Fig. 1). Although this database is not yet linked to the hospital information system (planned for 2006), anecdotally resident satisfaction with sign‐out has vastly improved since its implementation. The cost of design and implementation was approximately $10,000. At the University of Chicago, interns used Microsoft Word to create sign‐out sheets containing patient summaries to transfer information. However, during structured interviews, 95% of the interns reported that these sheets were frequently lost or misplaced.7 Although medicine residents at BWH use a computerized system to produce sign‐out sheets, this system did not guarantee complete and structured information. For example, a survey at BWH found that 56% of cross‐covering residents said that when paged about a patient overnight, the relevant information needed to care for that patient was present less than half the time; and 27% of residents reported being paged more than 3 times in the previous 2 weeks about a test result or consultant recommendation that they did not know was pending.36

Figure 1
UCSF Filemaker Pro written sign‐out vehicle.

The process of sign‐out also varied across disciplines and institutions. From our experiences at our sites and at the sites of faculty nationally, we found limited standardization about whether sign‐out was verbal, the data transmitted, and the setting in which it was transmitted. In fact, at UCSF most residents signed out verbally on the fly, wherever and whenever they could find the cross‐coverage intern. At BWH, only 37% of residents said that sign‐out occurred in a quiet place most of the time, and only 52% signed out on every patient both orally and in writing.36 At the University of Chicago, the sign‐out process was characterized by outright failures in communication because of omission of needed information (ie, medications, active or anticipated medical problems, etc.) or by failure‐prone communication (ie, lack of face‐to‐face communication, illegible writing). These failures often led to uncertainty in making patient care decisions, potentially resulting in inefficient or suboptimal care.35

Strategies for Safe and Effective Sign‐Out

Given the current landscape of variability in sign‐outs, the recognition that information lost during sign‐out may result in harm to patients, and evidence of improvements in information transfer in areas outside health care, we aimed to develop mechanisms to improve the sign‐out process for residents working in a hospital setting. These strategies are based on our review of the existing literature supplemented by our experiences at our 3 institutions.

Content of Sign‐Out

The elements of content necessary for safe and effective sign‐out can be divided into 5 broad categories (Table 1), contained in the mnemonic ANTICipate: Administrative information, New clinical information, specific Tasks to be performed, assessment of severity of Illness, and Contingency plans or anticipated problems (Table 1, Fig. 2).

Checklist for Elements of a Safe and Effective Written Sign‐outANTICipate
Administrative data
□ Patient name, age, sex
□ Medical record number
□ Room number
□ Admission date
□ Primary inpatient medical team, primary care physician
□ Family contact information
New information (clinical update)
□ Chief complaint, brief HPI, and diagnosis (or differential diagnosis)
□ Updated list of medications with doses, updated allergies
□ Updated, brief assessment by system/problem, with dates
□ Current baseline status (eg, mental status, cardiopulmonary, vital signs, especially if abnormal but stable)
□ Recent procedures and significant events
Tasks (what needs to be done)
□ Specific, using if‐then statements
□ Prepare cross‐coverage (eg, patient consent for blood transfusion)
□ Alert to incoming information (eg, study results, consultant recommendations), and what action, if any, needs to be taken during the cross‐coverage
Illness
□ Is the patient sick?
Contingency planning/Code status
□ What may go wrong and what to do about it
□ What has or has not worked before (eg, responds to 40 mg IV furosemide)
□ Difficult family or psychosocial situations
□ Code status, especially recent changes or family discussions
Figure 2
Example of a written sign‐out.

Several general points about this list should be noted. First, the sign‐out content is not meant to replace the chart. The information included reflects the goal of a sign‐out, namely, to provide enough information to allow for a safe transition in patient care. Information we believe is not essential to the sign‐out includes: a complete history and physical exam from the day of admission, a list of tasks already completed, and data necessary only to complete a discharge summary.

Sign‐out must be also be a closed loopthe process of signing in is as important as the process of signing out. This usually entails members of the primary team obtaining information from the cross‐covering physician when they resume care of the patient. The information conveyed in this case is different and includes details on events during cross‐coverage such as: 1) time called to assess patient; 2) reason for call; 3) a brief assessment of the patient, including vital signs; 4) actions taken, for example, medications given and tests ordered; and 5) rationale for those actions. Some of this information may also be included in the chart as an event note (see Fig. 3).

Figure 3
Example of patient event note.

The Vehicle for Sign‐Out

We recommend a computer‐assisted vehicle for patient information transfer. Ideally, this would be linked to the hospital information system to ensure accurate and up‐to‐date information Easy access to the computerized sign‐out is essential (eg, using a hospitalwide computer system, shared hard drive service, intranet, or PDA linked to the computer system), and it should be customizable for the varied needs of different services and departments. The system should have templates to standardize the content of sign‐out, contain robust backup systems, and be HIPAA compliant (ie, restrict access to required health care personnel). However, the perfect should not be the enemy of the good: systems that do not meet these criteria may still help to protect patients by providing legible, predictable, and accessible information.

Sign‐Out Processes

Verbal communication.

Although electronic solutions can facilitate the standardization of written content, face‐to‐face verbal communication adds additional value.19 We recommend that each patient be reviewed separately. Identification of each patient verbally ensures that those engaged in the sign‐out are discussing the same patient. Reiterating the major medical problems gives a snapshot of the patient and frames the sign‐out. The to‐do list, the list of tasks that the cross‐cover resident needs to complete during cross coverage, should be specific and articulated as if, then statements (eg, if the urine output is less than 1 L, then give 40 mg of IV furosemide). The receiver of sign‐out should read back to the person giving the sign‐out each item on the to‐do list (eg, So, I should check the ins and outs at about 10:00 pm, and give 40 of furosemide if the patient is not 1 L negative, right?).

Anticipated problems should also be verbally communicated to promote a dialogue. Points that cannot be adequately transferred in the written sign‐out are particularly important to transmit verbally. Examples include previous code discussions, unusual responses to treatment, and psychosocial and family issues. When delivering verbal sign‐out, it is important to consider the a priori knowledge of the recipient. How much knowledge about a patient is already shared between the outgoing and incoming physicians and the level of experience of the physicians may affect the extent to which information needs be transmitted.37 For instance, 2 experienced physicians who already have been working to cover the same patient will likely have an abbreviated discussion, in contrast to the lengthier sign‐out necessary if the outgoing and incoming physicians are interns, and the incoming intern has no prior knowledge of the patient. Similarly, it is likely the level of detail transmitted will need to be greater during a permanent transfer of patient care (ie, at the end of a resident's rotation) than during a brief, temporary transition (eg, overnight coverage).

The challenges of a busy inpatient service may preclude a complete verbal sign‐out for all patients; we contend, though, it is best to use these practices to the extent possible, especially for patients with treatment plans in flux, those whose status is tenuous, and those who have anticipated changes in status during cross‐coverage. One tool that may be effectively used in signing out such patients is the SBAR tool, according to which a brief description of the situation is given, followed by the background and the physician's specific assessment and complete recommendation.38 For example, a resident signing out might begin by stating, I have 18 patients to sign‐out to you. I'm going to describe 6 active patients in detail. Twelve others are fairly stable, and I will give you basic information about them, and the details are in the written sign‐out. One patient has a plan in flux. The situation is Mr. S. is having trouble breathing, the background is that he has both CHF and COPD, my assessment is that this is more cardiac than pulmonary, and I recommend that you see him first and discuss with the cardiology consultant. Using the tools described here (Table 2), a sign‐out of 15 patients of variable acuity could be verbally signed out in less than 10 minutes.

Checklist for Verbal Communication During Sign‐Out: The Who, What, Where, When, and How
WHO should participate in the sign‐out process?
□ Outgoing clinician primarily responsible for patient's care
□ Oncoming clinician who will be primarily responsible for patient's care (avoid passing this task to someone else, even if busy)
□ Consider supervision by experienced clinicians if early in training
WHAT content needs to be verbally communicated?
Use situation briefing model, or SBAR, technique:
SituationIdentify each patient (name, age, sex, chief complaint) and briefly state any major problems (active and those that may become active during cross‐coverage).
Backgroundpertinent information relevant to current care (eg, recent vitals and/or baseline exam, labs, test results, etc).
Assessmentworking diagnosis, response to treatment, anticipated problems during cross‐coverage including anything not adequately described using written form (eg, complex family discussions).
Recommendationto‐do lists and if/then recommendations.
WHERE should sign‐out occur?
□ Designated room or place for sign‐out (eg, avoid patient areas because of HIPPA requirements)
□ Proper lighting
□ Avoid excessive noise (eg, high‐traffic areas)
□ Minimize disruptions (eg, hand over pagers)
□ Ensure systems support for sign‐out (eg, computers, printer, paper, etc.)
WHEN is the optimal time for sign‐out?
□ Designated time when both parties can be present and pay attention (eg, beware of clinic, other obligations)
□ Have enough time for interactive questions at the end (eg, avoid rush at the end of the shift)
HOW should verbal communication be performed?
□ Face to face, allowing for questions
□ Verbalize data in the same order for each patient at each sign‐out
□ Read back all to‐do items
□ Adjust length and depth of review according to baseline knowledge of parties involved and type of transition in care

The Environment and setting.

To improve the setting of sign‐out, we recommend: a designated space that is well lit, quiet, and respects patient confidentiality and a designated time when sign‐out will occur. To limit known distractions and interruptions39, 40 in the hospital, we also recommend the outgoing physician hand off his or her pager to someone else during sign‐out. Also key to an environment conducive to information transfer is ensuring adequate computer support for electronic sign‐out and access to updated clinical information.

Organizational culture and institutional leadership.

The way residents transfer patient care information reflects the culture of the institution. Changing the culture to one in which interactive questioning is valued regardless of position in the hierarchy has been shown to reduce errors in aviation.41 Educating residents on the impact of sign‐outs on patient care is a first step toward improving the culture of sign‐out. Resident commitment to the new sign‐out can be gained by engaging residents in development of the process itself. To cement these changes into the culture, practitioners at all levels should be aware of and support the new system. The role of an institution's leaders in achieving these changes cannot be overlooked. Leaders will need to be creative in order to support sign‐out as described within the obvious constraints of money, time, personnel, and space. Gaining institutional buy‐in can start with heightening the awareness of leaders of the issues surrounding sign‐out, including patient safety, resident efficiency, and the financial impact of discontinuity. Ongoing evaluation of efforts to improve sign‐out is also crucial and can be accomplished with surveys, focus groups, and direct observation. Feeding back the positive impact of the changes to all involved stakeholders will promote confidence in the new systems and pride in their efforts.

CONCLUSIONS

Sign‐outs are a part of the current landscape of academic medical centers as well as hospitals at large. Interns, residents, and consulting fellows, not to mention nurses, physical therapists, and nutritionists, transfer patient care information at each transition point. There are few resources that can assist these caregivers in identifying and implementing the most effective ways to transfer patient care information. Hospitals and other care facilities are now mandated to develop standards and systems to improve sign‐out. On the basis of the limited literature to date and our own experiences, we have proposed standards and best practices to assist hospitals, training programs, and institutional leaders in designing safe and usable sign‐out systems. Effective implementation of the standards must include appropriate allocation of resources, individualization to meet specific needs of each program or institution, intensive training, and ongoing evaluation. Future research should focus on developing valid surrogate measures of continuity of care, conducting rigorous trials to determine the elements of sign‐out that lead to the best patient outcomes, and studying the most effective ways of implementing these improvements. By improving the content and process of sign‐out, we can meet the challenges of the new health care landscape while putting patient safety at the forefront.

Modern‐day continuity of patient care in teaching hospitals, once remarkably high because of a cadre of sleep‐deprived residents, is now peppered with breaks, each accompanied by the transfer of patient care responsibility from one resident to another; a process often referred to as a handoff. Such transitions have long been a part of medical practice but have recently received increased attention because of restrictions in the duty hours of house staff. In July 2003 the Accreditation Council for Graduate Medical Education (ACGME) mandated reduced duty hours for all trainees in hopes of improving resident education and well‐being and patient safety.1 In fact, some studies have shown improved resident well‐being2 and fewer medical errors with reductions in duty hours,3, 4 but the growing consensus about the negative consequences of resident fatigue on patient safety has been accompanied by parallel concerns about the potential for information loss with each break in the continuity of care.5, 6

Although the tradeoff of increased discontinuity of care for fewer hours worked is sometimes characterized as an unintended consequence of duty hour regulations, it is in fact predictable and essential. As individuals work fewer hours, discontinuity must necessarily increase (assuming 24‐hour coverage).7 The extent to which this occurs may vary, but the link is consistent. At the University of California, San Francisco (UCSF), for example, we found that compliance with new duty hour requirements for internal medicine resulted in an average of 15 handoffs per patient during a 5‐day hospitalization. Each individual intern was involved in more than 300 handoffs in an average month‐long rotation, an increase of 40% since system changes were introduced to decrease duty hours. We found similar increases at Brigham and Women's Hospital (BWH) and the University of Chicago. Because U.S. teaching hospitals care for more than 6 million patients each year,8 the impact of these handoffs on the quality and efficiency of care is tremendous.

Discontinuity of care is currently managed by sign‐out, or the transfer of patient information from one physician to another. Recognizing the importance of information transfer at these vulnerable transition times for patients, the Joint Commission on Accreditation of Hospital Organizations (JCAHO) issued the 2006 National Patient Safety Goal 2E: Implement a standardized approach to hand off communications, including an opportunity to ask and respond to questions.9 Hospitals have little data to draw on to determine how to comply with this mandate and even less data to guide them in how to achieve its intended goals of improving communication and thus patient safety.

In an effort to better understand sign‐outs and ways to improve this process for house staff on in‐patient services, we reviewed data from the fields of aviation, communications, systems engineering, and human factors research, and we also searched the medical literature using key words pass‐off, handoff, sign‐out, duty hours, work hours, and discontinuity of care and MeSH headings Continuity of Patient Care Internship and Residency/*organization & administration, Personnel Staffing and Scheduling/*organization & administration, and Quality of Health Care. We also searched the websites of the Agency of Healthcare Quality and Research and the National Patient Safety Foundation. On the basis of these reviews, our experiences as hospitalist medical educators organizing resident sign‐out efforts at the University of California, San Francisco, the University of Chicago, and Brigham and Women's Hospital, and our efforts leading national training sessions on sign‐outs at the Society of General Internal Medicine (2004 and 2005), the Society of Hospital Medicine (2004), and the Association of Program Directors in Internal Medicine (2005, 2006), we propose a set of best practices regarding the content and process of sign‐out in an effort to improve communication between residents caring for hospitalized patients, assist programs in building safe and effective sign‐out systems, and improve the quality of patient care.

Effects of Discontinuity on Patient Safety

Research on the effects of discontinuity of care, although limited, suggests it has a negative impact on patient safety. In a study that investigated the institution of code 405 (the regulation that reduced duty hours in New York State), researchers found that the presumed increase in discontinuity with decreased duty hours resulted in delayed test ordering and an increased number of hospital complications.10 Another study found that the number of potentially preventable adverse events doubled when patients were under the care of a physician from a nonprimary team (eg, the cross‐covering intern).11 Studies have also linked resident discontinuity with longer length of stay, increased laboratory testing, and increased medication errors.12, 13

Managing Discontinuity: Sign‐Out as the Means of Information Transfer

In theory, more effective sign‐out systems should mitigate the potential for patient harm, but there is little in the literature describing current effective sign‐out practices or the best ways to design and implement such systems in the health care field. Examining information transfer mechanisms used in fields outside health care can assist in developing these systems.

Information Transfer in Other Industries

Although there is a paucity of data on sign‐out in the medical literature, information transfer has been the subject of substantial research in other industries in which safety depends on effective communication.

Aviation, for example, created systems and processes to improve handoff communication in response to accidents linked to failures in information transfer. One example, the 1977 collision of 2 747s on an airport runway in Tenerife, the Canary Islands, occurred after a garbled transmission from an air traffic controller to the cockpit of one of the aircraft. It was determined that a culture of adherence to a steep hierarchy prevented subordinates from questioning the captain's mistaken certainty that a runway was clear,14 an erroneous belief that was the basis for his decision to continue the aircraft on its course, resulting in its collision with the other airplane.

Subsequently, commercial aviation designed systems that standardized and formalized the process of information transfer and improved teamwork and coordination. These interventions were developed on the basis of detailed observations of cockpit interactions, reviews of communication errors, and focus groups.15 Because of these efforts, today's pilots use standardized checklists to transfer information content, communicate at designated times in specific undistracted environments, and use standard language and read‐backs to enhance understanding.16 The result has been a remarkable decrease in the risk of aviation crashes, one that most experts attribute in large part to these efforts to improve communication.17

Observation of how communication occurs in other high‐risk industries has informed the arena of effective information transfer. For example, direct observation of information transfer at NASA, in nuclear power plants, and in the railway industry identified specific strategies for effective handoffs/sign‐outs such as standardizing the information transferred, ensuring information is up to date, limiting interruptions, and having a structured face‐to‐face verbal interchange.18

Other strategies noted to be effective in diminishing errors are the use of a standardized phonetic alphabet to ensure that information is correctly heard and understood4 and having interactive verbal communication occur at a whiteboard.19

Information Transfer in Health Care

Those in the discipline of nursing have vast experience in the transfer of patient care information. The sign‐out process employed by nurses includes face‐to‐face discussions, typed information, and, most commonly, taped verbal communication.20 Interestingly, this process has not been subject to detailed scrutiny, and there is little information in the literature about best practices in sign‐out. Most articles in the literature on nursing handoffs are ethnographic descriptions of patient care responsibilities,21 on the basis of which, the authors advocate standardization of the information to be transferred, formalization of the channel used to communicate, and attention to increasing a culture of professionalism during sign‐out in order to improve efficiency.20, 22

There is little in the literature on transfer of care among physicians. Improvements in sign‐out have been suggested as part of broad strategies, such as increased training and information technology support,4, 7, 23, 24 and specific strategies have been offered such as managing barriers to communication, including specific types of data when transferring care,25 and involving nurses and senior physicians in sign‐outs.26 Specific outcomes data in this area have focused primarily on the use of computerized systems to improve information transfer. For example, the use of a computerized sign‐out system at Brigham and Women's Hospital (BWH), linked to the hospital's information system to ensure up‐to‐date information on patient demographics, medications, and laboratory values, has resulted in fewer errors,27 as have other similar systems.28 At the University of Washington, use of a similarly linked computerized sign‐out system resulted in fewer patients being missed on rounds and improvement in the quality of sign‐out and continuity of care according to resident self‐reports.29 Unfortunately, fewer than 10% of hospitals have such integrated hospitalwide information systems to support the sign‐out function.30

It has been noted that verbal communication, in concert with advances in technological communication, is important in information transfer in health care,18, 31 especially in emergent or urgent conditions.32 For example, eliminating the phoned‐in report from the lab to the ER and replacing it with delivery by an electronic reporting system lacking verbal communicationresulted in 45% of emergent lab results going unchecked.32 Structured verbal communication tools have been efficacious in improving information transfer outside the formal sign‐outfor example, read‐backs, which reduced errors in the reporting of critical laboratory values,33 and the SBAR (situation, background, assessment, recommendation) tool (designed to frame the transfer of critical information), which improved physician and nurse patient care information transfer in the in‐patient setting of the Kaiser Permanente health system.34

In focus groups and in response to formal and informal surveys, residents at our 3 sites suggested inclusion of the following information, provided in writing and orally, to improve sign‐outs: up‐to‐date administrative information (eg, room number, primary care physician); patient's recent cognitive or cardiopulmonary status; problems the patient had already experienced and treatments previously tried, both successfully and unsuccessfully; patient's code status and discussions on level of care; test results or consultation recommendations that were likely to come back while covering the patient and what to do with the results; and relevant psychosocial information (eg, complex family dynamics).35

The Current Practice of Sign‐Out

In examining sign‐outs at our 3 institutions, we found them to be unstructured and unstandardized. From discussion with faculty participating in national workshops on sign‐out, we found that most sign‐outs are conducted by interns, usually with little or no formal training. Templates, checklists, or other methods to standardize the content of the information transferred were rarely used.

We also noted that the vehicle for written sign‐out is highly variable. At UCSF, different residency training programs used a variety of modalities for written sign‐outs, including index cards, Excel spreadsheets, Word documents, and loose sheets of paper. Recently, the UCSF Department of Medicine designed a simple database (on Filemaker Pro) that allows members of the house staff to update their sign‐out information, share it with other house staff and nurses, and access it at locations throughout the hospital (Fig. 1). Although this database is not yet linked to the hospital information system (planned for 2006), anecdotally resident satisfaction with sign‐out has vastly improved since its implementation. The cost of design and implementation was approximately $10,000. At the University of Chicago, interns used Microsoft Word to create sign‐out sheets containing patient summaries to transfer information. However, during structured interviews, 95% of the interns reported that these sheets were frequently lost or misplaced.7 Although medicine residents at BWH use a computerized system to produce sign‐out sheets, this system did not guarantee complete and structured information. For example, a survey at BWH found that 56% of cross‐covering residents said that when paged about a patient overnight, the relevant information needed to care for that patient was present less than half the time; and 27% of residents reported being paged more than 3 times in the previous 2 weeks about a test result or consultant recommendation that they did not know was pending.36

Figure 1
UCSF Filemaker Pro written sign‐out vehicle.

The process of sign‐out also varied across disciplines and institutions. From our experiences at our sites and at the sites of faculty nationally, we found limited standardization about whether sign‐out was verbal, the data transmitted, and the setting in which it was transmitted. In fact, at UCSF most residents signed out verbally on the fly, wherever and whenever they could find the cross‐coverage intern. At BWH, only 37% of residents said that sign‐out occurred in a quiet place most of the time, and only 52% signed out on every patient both orally and in writing.36 At the University of Chicago, the sign‐out process was characterized by outright failures in communication because of omission of needed information (ie, medications, active or anticipated medical problems, etc.) or by failure‐prone communication (ie, lack of face‐to‐face communication, illegible writing). These failures often led to uncertainty in making patient care decisions, potentially resulting in inefficient or suboptimal care.35

Strategies for Safe and Effective Sign‐Out

Given the current landscape of variability in sign‐outs, the recognition that information lost during sign‐out may result in harm to patients, and evidence of improvements in information transfer in areas outside health care, we aimed to develop mechanisms to improve the sign‐out process for residents working in a hospital setting. These strategies are based on our review of the existing literature supplemented by our experiences at our 3 institutions.

Content of Sign‐Out

The elements of content necessary for safe and effective sign‐out can be divided into 5 broad categories (Table 1), contained in the mnemonic ANTICipate: Administrative information, New clinical information, specific Tasks to be performed, assessment of severity of Illness, and Contingency plans or anticipated problems (Table 1, Fig. 2).

Checklist for Elements of a Safe and Effective Written Sign‐outANTICipate
Administrative data
□ Patient name, age, sex
□ Medical record number
□ Room number
□ Admission date
□ Primary inpatient medical team, primary care physician
□ Family contact information
New information (clinical update)
□ Chief complaint, brief HPI, and diagnosis (or differential diagnosis)
□ Updated list of medications with doses, updated allergies
□ Updated, brief assessment by system/problem, with dates
□ Current baseline status (eg, mental status, cardiopulmonary, vital signs, especially if abnormal but stable)
□ Recent procedures and significant events
Tasks (what needs to be done)
□ Specific, using if‐then statements
□ Prepare cross‐coverage (eg, patient consent for blood transfusion)
□ Alert to incoming information (eg, study results, consultant recommendations), and what action, if any, needs to be taken during the cross‐coverage
Illness
□ Is the patient sick?
Contingency planning/Code status
□ What may go wrong and what to do about it
□ What has or has not worked before (eg, responds to 40 mg IV furosemide)
□ Difficult family or psychosocial situations
□ Code status, especially recent changes or family discussions
Figure 2
Example of a written sign‐out.

Several general points about this list should be noted. First, the sign‐out content is not meant to replace the chart. The information included reflects the goal of a sign‐out, namely, to provide enough information to allow for a safe transition in patient care. Information we believe is not essential to the sign‐out includes: a complete history and physical exam from the day of admission, a list of tasks already completed, and data necessary only to complete a discharge summary.

Sign‐out must be also be a closed loopthe process of signing in is as important as the process of signing out. This usually entails members of the primary team obtaining information from the cross‐covering physician when they resume care of the patient. The information conveyed in this case is different and includes details on events during cross‐coverage such as: 1) time called to assess patient; 2) reason for call; 3) a brief assessment of the patient, including vital signs; 4) actions taken, for example, medications given and tests ordered; and 5) rationale for those actions. Some of this information may also be included in the chart as an event note (see Fig. 3).

Figure 3
Example of patient event note.

The Vehicle for Sign‐Out

We recommend a computer‐assisted vehicle for patient information transfer. Ideally, this would be linked to the hospital information system to ensure accurate and up‐to‐date information Easy access to the computerized sign‐out is essential (eg, using a hospitalwide computer system, shared hard drive service, intranet, or PDA linked to the computer system), and it should be customizable for the varied needs of different services and departments. The system should have templates to standardize the content of sign‐out, contain robust backup systems, and be HIPAA compliant (ie, restrict access to required health care personnel). However, the perfect should not be the enemy of the good: systems that do not meet these criteria may still help to protect patients by providing legible, predictable, and accessible information.

Sign‐Out Processes

Verbal communication.

Although electronic solutions can facilitate the standardization of written content, face‐to‐face verbal communication adds additional value.19 We recommend that each patient be reviewed separately. Identification of each patient verbally ensures that those engaged in the sign‐out are discussing the same patient. Reiterating the major medical problems gives a snapshot of the patient and frames the sign‐out. The to‐do list, the list of tasks that the cross‐cover resident needs to complete during cross coverage, should be specific and articulated as if, then statements (eg, if the urine output is less than 1 L, then give 40 mg of IV furosemide). The receiver of sign‐out should read back to the person giving the sign‐out each item on the to‐do list (eg, So, I should check the ins and outs at about 10:00 pm, and give 40 of furosemide if the patient is not 1 L negative, right?).

Anticipated problems should also be verbally communicated to promote a dialogue. Points that cannot be adequately transferred in the written sign‐out are particularly important to transmit verbally. Examples include previous code discussions, unusual responses to treatment, and psychosocial and family issues. When delivering verbal sign‐out, it is important to consider the a priori knowledge of the recipient. How much knowledge about a patient is already shared between the outgoing and incoming physicians and the level of experience of the physicians may affect the extent to which information needs be transmitted.37 For instance, 2 experienced physicians who already have been working to cover the same patient will likely have an abbreviated discussion, in contrast to the lengthier sign‐out necessary if the outgoing and incoming physicians are interns, and the incoming intern has no prior knowledge of the patient. Similarly, it is likely the level of detail transmitted will need to be greater during a permanent transfer of patient care (ie, at the end of a resident's rotation) than during a brief, temporary transition (eg, overnight coverage).

The challenges of a busy inpatient service may preclude a complete verbal sign‐out for all patients; we contend, though, it is best to use these practices to the extent possible, especially for patients with treatment plans in flux, those whose status is tenuous, and those who have anticipated changes in status during cross‐coverage. One tool that may be effectively used in signing out such patients is the SBAR tool, according to which a brief description of the situation is given, followed by the background and the physician's specific assessment and complete recommendation.38 For example, a resident signing out might begin by stating, I have 18 patients to sign‐out to you. I'm going to describe 6 active patients in detail. Twelve others are fairly stable, and I will give you basic information about them, and the details are in the written sign‐out. One patient has a plan in flux. The situation is Mr. S. is having trouble breathing, the background is that he has both CHF and COPD, my assessment is that this is more cardiac than pulmonary, and I recommend that you see him first and discuss with the cardiology consultant. Using the tools described here (Table 2), a sign‐out of 15 patients of variable acuity could be verbally signed out in less than 10 minutes.

Checklist for Verbal Communication During Sign‐Out: The Who, What, Where, When, and How
WHO should participate in the sign‐out process?
□ Outgoing clinician primarily responsible for patient's care
□ Oncoming clinician who will be primarily responsible for patient's care (avoid passing this task to someone else, even if busy)
□ Consider supervision by experienced clinicians if early in training
WHAT content needs to be verbally communicated?
Use situation briefing model, or SBAR, technique:
SituationIdentify each patient (name, age, sex, chief complaint) and briefly state any major problems (active and those that may become active during cross‐coverage).
Backgroundpertinent information relevant to current care (eg, recent vitals and/or baseline exam, labs, test results, etc).
Assessmentworking diagnosis, response to treatment, anticipated problems during cross‐coverage including anything not adequately described using written form (eg, complex family discussions).
Recommendationto‐do lists and if/then recommendations.
WHERE should sign‐out occur?
□ Designated room or place for sign‐out (eg, avoid patient areas because of HIPPA requirements)
□ Proper lighting
□ Avoid excessive noise (eg, high‐traffic areas)
□ Minimize disruptions (eg, hand over pagers)
□ Ensure systems support for sign‐out (eg, computers, printer, paper, etc.)
WHEN is the optimal time for sign‐out?
□ Designated time when both parties can be present and pay attention (eg, beware of clinic, other obligations)
□ Have enough time for interactive questions at the end (eg, avoid rush at the end of the shift)
HOW should verbal communication be performed?
□ Face to face, allowing for questions
□ Verbalize data in the same order for each patient at each sign‐out
□ Read back all to‐do items
□ Adjust length and depth of review according to baseline knowledge of parties involved and type of transition in care

The Environment and setting.

To improve the setting of sign‐out, we recommend: a designated space that is well lit, quiet, and respects patient confidentiality and a designated time when sign‐out will occur. To limit known distractions and interruptions39, 40 in the hospital, we also recommend the outgoing physician hand off his or her pager to someone else during sign‐out. Also key to an environment conducive to information transfer is ensuring adequate computer support for electronic sign‐out and access to updated clinical information.

Organizational culture and institutional leadership.

The way residents transfer patient care information reflects the culture of the institution. Changing the culture to one in which interactive questioning is valued regardless of position in the hierarchy has been shown to reduce errors in aviation.41 Educating residents on the impact of sign‐outs on patient care is a first step toward improving the culture of sign‐out. Resident commitment to the new sign‐out can be gained by engaging residents in development of the process itself. To cement these changes into the culture, practitioners at all levels should be aware of and support the new system. The role of an institution's leaders in achieving these changes cannot be overlooked. Leaders will need to be creative in order to support sign‐out as described within the obvious constraints of money, time, personnel, and space. Gaining institutional buy‐in can start with heightening the awareness of leaders of the issues surrounding sign‐out, including patient safety, resident efficiency, and the financial impact of discontinuity. Ongoing evaluation of efforts to improve sign‐out is also crucial and can be accomplished with surveys, focus groups, and direct observation. Feeding back the positive impact of the changes to all involved stakeholders will promote confidence in the new systems and pride in their efforts.

CONCLUSIONS

Sign‐outs are a part of the current landscape of academic medical centers as well as hospitals at large. Interns, residents, and consulting fellows, not to mention nurses, physical therapists, and nutritionists, transfer patient care information at each transition point. There are few resources that can assist these caregivers in identifying and implementing the most effective ways to transfer patient care information. Hospitals and other care facilities are now mandated to develop standards and systems to improve sign‐out. On the basis of the limited literature to date and our own experiences, we have proposed standards and best practices to assist hospitals, training programs, and institutional leaders in designing safe and usable sign‐out systems. Effective implementation of the standards must include appropriate allocation of resources, individualization to meet specific needs of each program or institution, intensive training, and ongoing evaluation. Future research should focus on developing valid surrogate measures of continuity of care, conducting rigorous trials to determine the elements of sign‐out that lead to the best patient outcomes, and studying the most effective ways of implementing these improvements. By improving the content and process of sign‐out, we can meet the challenges of the new health care landscape while putting patient safety at the forefront.

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  21. Vidyarthi A,Auerbach A.Is 80 the cost of saving lives? Reduced duty hours, errors, and cost.J Gen Intern Med.2005;20:969970.
  22. Solet DJ,Norvell JM,Rutan GH,Frankel RM.Lost in translation: challenges and opportunities in physician‐to‐physician communication during patient handoffs.Acad Med.2005;80:10941099.
  23. British Medical Association.Safe Handover: Safe Patients: Guidance on Clinical Handover for Clinicians and Managers.London:British Medical Association, Junior Doctors Committee;2004.
  24. Petersen LA,Orav EJ,Teich JM,O'Neil AC,Brennan TA.Using a computerized sign‐out program to improve continuity of inpatient care and prevent adverse events.Jt Comm J Qual Improv.1998;24(2):7787.
  25. Van Eaton EG,Horvath KD,Lober WB,Pellegrini CA.Organizing the transfer of patient care information: the development of a computerized resident sign‐out system.Surgery.2004;136:513.
  26. Van Eaton EG,Horvath KD,Lober WB,Rossini AJ,Pellegrini CA.A randomized, controlled trial evaluating the impact of a computerized rounding and sign‐out system on continuity of care and resident work hours.J Am Coll Surg.2005;200:538545.
  27. Ash JS,Gorman PN,Seshadri V,Hersh WR.Computerized physician order entry in U.S. hospitals: results of a 2002 survey.J Am Med Inform Assoc.2004;11:9599.
  28. Martin K,Carter L,Balciunas D,Sotoudeh F,Moore D,Westerfield J.The impact of verbal communication on physician prescribing patterns in hospitalized patients with diabetes.Diabetes Educ.2003;29:827836.
  29. Kilpatrick ES,Holding S.Use of computer terminals on wards to access emergency test results: a retrospective audit.Br Med J.2001;322:11011103.
  30. Barenfanger J,Sautter RL,Lang DL,Collins SM,Hacek DM,Peterson LR.Improving patient safety by repeating (read‐back) telephone reports of critical information.Am J Clin Pathol.2004;121:801803.
  31. Leonard M GS,Bonacum D.The human factor: the critical importance of effective teamwork and communication in providing safe care.Qual Saf Health Care.2004;13(Suppl 1):i85i90.
  32. Arora V,Johnson J,Lovinger D,Humphrey HJ,Meltzer DO.Communication failures in patient sign‐out and suggestions for improvement: a critical incident analysis.Qual Saf Health Care.2005;14:401407.
  33. Carty M,Smith C,Schnipper JL.Intern curriculum: the impact of a focused training program on the process and content of signout out patients. Harvard Medical School Education Day, Boston, MA;2004.
  34. Coiera E.When conversation is better than computation.J Am Med Inform Assoc.2000;7:277286.
  35. SBAR technique for communication: a situational briefing model. Available at: http://www.ihi.org/IHI/Topics/PatientSafety/SafetyGeneral/Tools/SBARTechniqueforCommunicationASituationalBriefingModel.htm. Accessed December2005.
  36. Vidyarthi AKP,Katz PP,Wall SD,Wachter RM,Auerbach AD.Impact of reduced duty hours on residents' educational satisfaction at the University of California, San Francisco.Acad Med.2006;81:7681.
  37. Coiera E,Tombs V.Communication behaviours in a hospital setting: an observational study.Br Med J.1998;316:673676.
  38. Sutcliffe KM,Lewton E,Rosenthal MM.Communication failures: an insidious contributor to medical mishapsAcad Med.2004;79(2):186194.
References
  1. Philibert I,Friedmann P,Williams WT.New requirements for resident duty hours.JAMA.2002;288:11121114.
  2. Barden CB,Specht MC,McCarter MD,Daly JM,Fahey TJ.Effects of limited work hours on surgical training.J Am Coll Surg.2002;195:531538.
  3. Lockley SW,Cronin JW,Evans EE, et al.Effect of reducing interns' weekly work hours on sleep and attentional failures.N Engl J Med.2004;351:18291837.
  4. Landrigan CP,Rothschild JM,Cronin JW, et al.Effect of reducing interns' work hours on serious medical errors in intensive care units.N Engl J Med.2004;351:18381848.
  5. Mukherjee S.A precarious exchange.N Engl J Med.2004;351:18221824.
  6. Drazen JM.Awake and informed.N Engl J Med.2004;351:1884.
  7. Vidyarthi A. Fumbled handoff: missed communication between teams. Cases and Commentary: Hospital Medicine, Morbidity 269:374378.
  8. Petersen LA,Brennan TA,O'Neil AC,Cook EF,Lee TH.Does housestaff discontinuity of care increase the risk for preventable adverse events?Ann Intern Med.1994;121:866872.
  9. Lofgren RP,Gottlieb D,Williams RA,Rich EC.Post‐call transfer of resident responsibility: its effect on patient care.J Gen Intern Med.1990;5:501505.
  10. Gottlieb DJ,Parenti CM,Peterson CA,Lofgren RP.Effect of a change in house staff work schedule on resource utilization and patient care.Arch Intern Med.1991;151:20652070.
  11. Wachter RM,Shojania KG.Internal Bleeding: the Truth behind America's Terrifying Epidemic of Medical Mistakes.New York City:Rugged Land, LLC;2004:448.
  12. Pizzi L,Goldfarb NI,Nash DB.Crew resource management and its applications in medicine. In:Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Evidence Report/Technology Assessment Number 43, AHRQ Publication 01‐E058.Rockville, MD:Agency for Healthcare Research and Quality;2001.
  13. Helmreich RL,Klineet JR,Wilhelm JA.System safety and threat and error management: the line operations safety audit (LOSA). In:Jensen RS, ed. Proceedings of the Eleventh International Symposium on Aviation Psychology.Columbus, OH:Ohio State University;2001:16.
  14. Thomas EJ,Sexton JB,Helmreich RL.Translating teamwork behaviours from aviation to healthcare: development of behavioural markers for neonatal resuscitation.Qual Saf Health Care.2004;13(Suppl 1):i57i64.
  15. Patterson ES RB,Woods DD,Chow R,Gomoes JO.Handoff strategies in settings with high consequences for failure: lessons for healthcare operations.Intl J Qual Health Care.2004;16:125132.
  16. Ambler S. Available at: http://www.agilemodeling.com/essays/communication.htm. Accessed December 15,2005.
  17. Miller C.Ensuring continuing care: styles and efficiency of the handover process.Aust J Adv Nurs.1998;16:2327.
  18. Manias E,Street A.The handover: uncovering the hidden practices of nurses.Intensive Crit Care Nurs.2000;16:373383.
  19. Sherlock C.The patient handover: a study of its form, function and efficiency.Nurs Stand.1995;9(52):3336.
  20. Volpp KGM,Grande D.Residents' suggestions for reducing errors in teaching hospitals.N Engl J Med.2003;348:851855.
  21. Vidyarthi A,Auerbach A.Is 80 the cost of saving lives? Reduced duty hours, errors, and cost.J Gen Intern Med.2005;20:969970.
  22. Solet DJ,Norvell JM,Rutan GH,Frankel RM.Lost in translation: challenges and opportunities in physician‐to‐physician communication during patient handoffs.Acad Med.2005;80:10941099.
  23. British Medical Association.Safe Handover: Safe Patients: Guidance on Clinical Handover for Clinicians and Managers.London:British Medical Association, Junior Doctors Committee;2004.
  24. Petersen LA,Orav EJ,Teich JM,O'Neil AC,Brennan TA.Using a computerized sign‐out program to improve continuity of inpatient care and prevent adverse events.Jt Comm J Qual Improv.1998;24(2):7787.
  25. Van Eaton EG,Horvath KD,Lober WB,Pellegrini CA.Organizing the transfer of patient care information: the development of a computerized resident sign‐out system.Surgery.2004;136:513.
  26. Van Eaton EG,Horvath KD,Lober WB,Rossini AJ,Pellegrini CA.A randomized, controlled trial evaluating the impact of a computerized rounding and sign‐out system on continuity of care and resident work hours.J Am Coll Surg.2005;200:538545.
  27. Ash JS,Gorman PN,Seshadri V,Hersh WR.Computerized physician order entry in U.S. hospitals: results of a 2002 survey.J Am Med Inform Assoc.2004;11:9599.
  28. Martin K,Carter L,Balciunas D,Sotoudeh F,Moore D,Westerfield J.The impact of verbal communication on physician prescribing patterns in hospitalized patients with diabetes.Diabetes Educ.2003;29:827836.
  29. Kilpatrick ES,Holding S.Use of computer terminals on wards to access emergency test results: a retrospective audit.Br Med J.2001;322:11011103.
  30. Barenfanger J,Sautter RL,Lang DL,Collins SM,Hacek DM,Peterson LR.Improving patient safety by repeating (read‐back) telephone reports of critical information.Am J Clin Pathol.2004;121:801803.
  31. Leonard M GS,Bonacum D.The human factor: the critical importance of effective teamwork and communication in providing safe care.Qual Saf Health Care.2004;13(Suppl 1):i85i90.
  32. Arora V,Johnson J,Lovinger D,Humphrey HJ,Meltzer DO.Communication failures in patient sign‐out and suggestions for improvement: a critical incident analysis.Qual Saf Health Care.2005;14:401407.
  33. Carty M,Smith C,Schnipper JL.Intern curriculum: the impact of a focused training program on the process and content of signout out patients. Harvard Medical School Education Day, Boston, MA;2004.
  34. Coiera E.When conversation is better than computation.J Am Med Inform Assoc.2000;7:277286.
  35. SBAR technique for communication: a situational briefing model. Available at: http://www.ihi.org/IHI/Topics/PatientSafety/SafetyGeneral/Tools/SBARTechniqueforCommunicationASituationalBriefingModel.htm. Accessed December2005.
  36. Vidyarthi AKP,Katz PP,Wall SD,Wachter RM,Auerbach AD.Impact of reduced duty hours on residents' educational satisfaction at the University of California, San Francisco.Acad Med.2006;81:7681.
  37. Coiera E,Tombs V.Communication behaviours in a hospital setting: an observational study.Br Med J.1998;316:673676.
  38. Sutcliffe KM,Lewton E,Rosenthal MM.Communication failures: an insidious contributor to medical mishapsAcad Med.2004;79(2):186194.
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Managing discontinuity in academic medical centers: Strategies for a safe and effective resident sign‐out
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More steroids or less? That is the question!

A 45‐year‐old man who immigrated to Canada from Ghana at the age of 33 presented with a 2‐year history of progressive cognitive changes. He had bifrontal headache, right‐sided scalp paresthesias, and a 40‐pound weight loss. He was unable to perform his job as an auto parts worker. His wife noticed short‐ and long‐term memory problems and poor concentration. On physical exam he had no focal neurological findings but his score on the Mini‐Mental Status Exam (MMSE) was 23/30, with deficits in attention and recall.

The first important element of this illness is its chronicity. His symptoms progressed slowly over 2 years. Second, aside from his neurological problems, he is an otherwise healthy young, African‐born male. This clinical picture could be the early presentation of a demyelinating, infiltrative, or vascular illness. If vascular, it is more likely a vasculitis than atherosclerotic disease. Malignancy and infection are definitely in the differential, but at this point, I think they are less likely to be the cause, given the tempo of presentation. I would begin my investigations with basic blood work and a computerized tomography (CT) scan of his brain.

A CT scan of the head with contrast demonstrated an enlarged left lateral ventricle with no evidence of obstruction in the foramen of Munro.

The radiological findings of communicating hydrocephalus with normal parenchyma imply a disease that affects the leptomeningeal space. Given that we are looking at an illness that can change cerebral spinal fluid (CSF) flow rather than primary parenchymal disease, demyelinating and vascular illnesses are less likely etiologies, and infiltrative diseases move up on my list. Malignancy and infectious diseases remain in the differential.

He disappeared to follow up for 1 year, during which he returned to Ghana and experienced progressive neurological deterioration, with incontinence, gait instability, and inability to converse clearly and perform activities of daily living. On his return to Canada, an urgent CT scan and magnetic resonance imaging (MRI) of the brain demonstrated ongoing and unchanged hydrocephalus with aqueductal stenosis. A referral was made to a neurosurgeon for insertion of a ventriculoperitoneal shunt. A routine preoperative chest radiograph demonstrated new bilateral upper‐zone reticulonodular changes.

He had no respiratory symptoms, fevers, or lymphadenopathy. His occupational history revealed no exposure to asbestos, silica, farms, or mines. He had no history of either respiratory or neurological illness in the past and no travel other than to Ghana and Toronto. When he immigrated to Toronto, Canada, 12 years before, he had a normal chest radiograph and negative PPD tuberculin skin test.

Many illnesses produce asymptomatic changes on chest x‐ray. Oslerian principles would suggest that we should think of a single diagnosis to explain both nodular lung disease and more than 3 years of a progressive disease affecting the leptomeninges. It is unlikely that tuberculosis, other fungal diseases, or malignancy would result in the chest and brain pathology over a 3‐year period without other sequelae. Sarcoidosis could cause both chronic leptomeningeal changes and the radiographic lung findings. The next steps in investigating this patient should include measurement of angiotensin‐converting enzyme (ACE) and serum calcium and pulmonary function tests. I would ultimately send him for a pathological biopsy of his lung tissue to confirm noncaseating granuloma and exclude infection and malignancy.

Complete blood count, renal and liver biochemistry, and calcium were normal. An ACE level was elevated at 69 g/L (normal < 40 g/L). A human immunodeficiency virus (HIV‐1 and HIV‐2) test, tuberculin skin test, and syphilis serology were negative. A CT scan of the chest demonstrated bilateral upper‐zone reticulonodular changes and diffuse lymphadenopathy (Fig. 1). Pulmonary function tests (PFTs) demonstrated a forced expiratory volume 1 (FEV1) of 3.4 L (94%), forced vital capacity (FVC) of 4.0 L (83%), an FEV1/FVC of 87%, total lung capacity (TLC) of 92% predicted, and diffusion capacity (DLCO) of 67% predicted. An MRI with gadolinium (Fig. 2) demonstrated hydrocephalus, mild basal leptomeningeal enhancement around the perivascular spaces into the subinsular region, and an increased T2 signal in periventricular white matter.

Figure 1
CT scan of the thorax showing bilateral reticulonodular disease.
Figure 2
MRI with gadolinium T2‐weighted imaging showing hydrocephalus and increased periventricular white matter signal.

A bronchoscopy with bronchoalveolar lavage and transbronchial biopsies were performed. Pathology (Fig. 3) demonstrated non‐caseating epitheliod granulomas, with negative special stains for acid‐fast bacilli (AFB) and fungus, and negative fungal and AFB cultures of the bronchial alveolar lavage.

With negative tests for infectious causes such as tuberculosis, I think there is now enough evidence that this patient has sarcoidosis involving the lung and leptomeninges. At this point I would start therapy with steroids.

Figure 3
H and E stain of lung biopsy at 40× showing non‐caseating granuloma.

The patient was started on prednisone 40 mg po qd, and his neurological symptoms improved markedly over the course of 1‐2 months, with normalization of his MMSE and a return to cognitive baseline. As his symptoms stabilized with no change in CT imaging, he returned to work, and over the course of 2 years his prednisone dosage was tapered to 10 mg po od. While on prednisone he developed hypertension and hyperglycemia. He continued to have no respiratory symptoms.

He was cognitively at baseline until 20 months later, when he was readmitted to the hospital with a 2‐week history of worsening headache, increased confusion, poor memory, and wandering. His MMSE had deteriorated to 19/30, with deficits again in memory and attention.

First, we can say with reasonable confidence that the diagnosis of sarcoid was correct. His long and sustained response to steroids, plus the absence of the unmasking of an infectious or malignant disease, supports this conclusion. However, he is now exhibiting an apparent relapse that mimics his presentation 3 years earlier. The question is whether he is suffering from a flare of his disease or whether a second illness has occurred. The most obvious second illness is an opportunistic infection after years of steroid use. I would certainly repeat the angiotensin‐converting enzyme and serum calcium tests and repeat the imaging of his lungs and central nervous system. He also warrants a lumbar puncture with CSF culture, stain, and PCR for opportunistic infections. If these studies are inconclusive and do not specifically suggest relapsing sarcoid, I would once again consider biopsy of tissue from either a lung or leptomeninges.

An MRI with gadolinium looked unchanged from the previous one. A lumbar puncture was performed, and his CSF demonstrated 3 WBCs, no RBCs, normal glucose, and elevated protein at 1.17 g/L, and tests for bacteria, TB, fungi, and viruses were all negative. Repeat blood work was unremarkable, and the ACE level was 2 g/L.

A chest radiograph (Fig. 4a) and CT chest (Fig. 4b) showed marked deterioration, with increased diffuse airspace opacities, interstitial nodularity, and small apical bullae. His PFTs showed some deterioration, with FEV1 2.52 L (73%), FVC 3.29 L (73%), FEV1/FVC 76%, TLC 70% predicted, DLCO 72% predicted. However, he still had no respiratory symptoms.

Figure 4
(a) Plain chest radiograph showing worsening bilateral upper lobe reticulonodular infiltrates; (b) CT of thorax showing worsening bilateral upper lobe reticulonodular infiltrates.

The changes on lumbar puncture are nonspecific. The ACE level is now very low, making sarcoidosis unlikely but not impossible. The chest imaging shows features, specifically interstitial nodularity, consistent with ongoing or relapsing sarcoidosis, but the extensive apical bullae are not characteristic. My best guess is that this patient's illness is not simply relapsing sarcoid but represents superimposed opportunistic infectious disease. I would not reintroduce steroids without pursuing a definitive diagnosis with tissue pathology.

He was placed on prednisone 60 mg po qd and started on trimethoprim‐sulfamethoxazole for Pneumocystis pneumonia (PCP) prophylaxis. He showed modest improvement in his neurological status. A repeat bronchoscopy was not performed. Four months later he was seen by his pulmonologist. He remained without respiratory symptoms and was neurologically unchanged, and a chest radiograph showed no change. He was continued on prednisone 60 mg po qd.

Three weeks later, he was admitted to the hospital with a 2‐week history of anorexia, fatigue, night sweats, right‐sided pleuritic chest pain with productive cough, increasing dyspnea, and no hemoptysis. On admission he was hypoxic with evidence of respiratory distress, and his chest radiograph showed evidence of new right‐sided airspace disease with an associated large right pleural effusion. Initial labs demonstrated a leukocytosis.

I am now very suspicious that this illness is not relapsed sarcoidosis based on his prior clinical response to high‐dose prednisone and that he currently is showing no neurological improvement. His recent clinical deterioration on this very high dose of prednisone makes me think that opportunistic lung infection or disseminated disease is definitely the cause, although the differential is broad. In addition to the typical viral and bacterial causes of community‐acquired pneumonia, this could be caused by unusual bacterial pathogens, tuberculosis, nontuberculous mycobacteria, or fungal diseases including Candida, Aspergillus and dimorphic fungi. I would begin empiric therapy with antibiotics, obtain pleural fluid for examination and culture, and blood cultures.

The patient was treated with a respiratory fluoroquinolone, and blood and sputum cultures were performed. A right thoracentesis removed 300 cc of yellow exudate, with negative gram stain and initial culture. Over the next 24 hours, the patient deteriorated rapidly, with progressive hypoxia and clinical and radiological (Fig. 5) evidence of acute respiratory distress syndrome (ARDS). He required endotracheal intubation with mechanical ventilation.

Figure 5
Plain chest radiograph showing ARDS and right pleural effusion..

He has a progressive illness not responsive to broad‐spectrum antibiotics, and he has deteriorated. At this point it is imperative that he undergo bronchoscopy and transbronchial biopsy.

Bronchoscopy demonstrated secretions from the right lower lobe. Gram stain from a bronchoalveolar lavage from the right lower lobe was negative, and cultures showed no growth after 24 hours. Immediately after bronchoscopy a third‐generation cephalosporin was empirically added. The next day the patient developed hypotension and was started on norepinephrine. Over the subsequent 48 hours, he developed progressive multiorgan failure. Despite multiple vasopressors, high‐frequency oscillator ventilation, broad‐spectrum antimicrobials, and activated protein C, he died in the intensive care unit. At the time of death, all blood cultures were negative, abdominal CT scans showed no intraabdominal infections, and the BAL performed on admission demonstrated negative gram stain, fungal stain, AFB stain, and PCP and no growth from fungal or bacterial cultures.

I think it is an unavoidable conclusion that this man's progressive systemic inflammatory response syndrome and ultimate multiorgan failure was caused by an opportunistic pathogen that was not antibiotic responsive and not identified from the extensive range of infectious disease studies performed. Despite all the negative studies, there still might be either mycobacterial illness or fungal illness. With negative cultures, Candida or Aspergillus infection is unlikely. Other opportunistic fungi like Blastomyces, Histoplasma, and Cryptococcus are certainly in the differential because these organisms can be notoriously difficult to detect on routine surveying such as bronchoalveolar lavage or lumbar puncture. Blastomyces and Histoplasma are both endemic in the area of Canada where the patient resided. I would also keep the zygomycoses in the differential.

Five days after death, fungal culture was reported demonstrating Blastomyces dermatitidis. Postmortem demonstrated disseminated blastomycosis causing severe bilateral pneumonia (Fig. 6a), empyema of right lung, and involvement of the thyroid, heart, liver, spleen, and kidneys. There was also evidence of active CNS blastomycosis involving the meninges and cerebral cortex and diencephalon (Fig. 6b). As well as active blastomycosis, the leptomeninges demonstrated fibrosis and old granulomas that did not contain an organism.

Figure 6
(a) Lung Gomori‐methanamine‐silver (GMS) stain 100× showing multiple yeast forms with broad‐based budding consistent with blastomycosis; (b) Brain GMS stain 40× showing CNS blastomycosis with involvement of the leptomeninges and cortex.

COMMENTARY

This case describes a 45‐year‐old man who presented with chronic cognitive symptoms associated with hydrocephalus. The first step in establishing the diagnosis was made by realizing that a communicating hydrocephalus with no parenchymal CNS disease was highly suggestive of a leptomeningeal process. This narrowed the differential diagnosis to an infiltrative disease affecting the leptomeninges. The next step involved the discovery of an upper‐lobe interstitial lung process, establishing sarcoidosis as the most likely unifying diagnosis. This was confirmed with transbronchial biopsies showing noncaseating granulomas and by the sustained response to treatment with corticosteroids. Unfortunately, after a 2‐year remission, he developed a recurrence of both the neurological and respiratory findings. When his symptoms progressed despite higher doses of corticosteroids, it became apparent that the etiology of his clinical deterioration was not recurrent disease. Instead, the deterioration was caused by disseminated blastomycosis, an opportunistic infection that developed as a result of the immunosuppressants used to treat the sarcoidosis.

With the final diagnosis of blastomycosis, one question about this case becomes: Could it have been blastomycosis and not sarcoid that was responsible for his original neurological presentation? Blastomyces dermatitidis is a thermally dimorphic fungus that causes disease from inhalation of airborne spores found in soil. Areas of North America in which it is endemic include regions bordering the Mississipi and Ohio rivers, as well as the areas bordering the Great Lakes.1 The patient in this case lived in metropolitan Toronto, on Lake Ontario, where blastomycosis is an important yet underreported disease.24 He likely was exposed to blastomyces in Toronto, which in immunocompromised patients may be followed after weeks to months by dissemination to other body sites including the dermis, bones, joints, urogenital system, and, rarely, the central nervous system (CNS) and liver.5 Like sarcoidosis, infection with blastomycosis can produce pathologic evidence of noncaseating granulomatous inflammation. However, as the discussant astutely pointed out, it would be unusual for this patient to have clinically inapparent blastomycosis for almost 2 years while on high‐dose prednisone. The initial diagnosis of sarcoid likely was correct.

CNS disease caused by Blastomyces dermatitidis is quite rare, with only 22 reported cases of meningoencephalitis in the literature.6 As this case demonstrates, CNS blastomycosis is very difficult to diagnose because of the absence of sensitive serologic markers and the difficulty of isolating the organism from blood and cerebrospinal fluid. CSF sampling from lumbar puncture led to its diagnosis in only 2 of the 22 reported cases.7 Furthermore, reliable CSF cultures are usually only obtained via ventricular sampling or tissue biopsy, which itself is limited by the organism's predilection for deep structures of the cerebrum, midbrain, and basal meninges.6 Blastomyces involving the CNS rarely occurs in isolation. In the patient's case, during his neurological deterioration, there was clear radiological evidence of progressive pulmonary pathology despite his being asymptomatic, and as the discussant suggests, pulmonary investigations were warranted.

Pulmonary manifestations of blastomycosis are variable. Acute infections most commonly resemble pneumonia, whereas chronic disease may show reticulonodular changes indistinguishable from sarcoidosis. Severe cases have been shown to progress to respiratory failure with acute respiratory distress syndrome (ARDS).1 The diagnosis is usually established through culture of noninvasive (sensitivity 86%) or bronchoalveolar lavage (sensitivity 92%) specimens.8 However, blastomyces will take between 5 and 30 days to grow in culture.1 In cases where the diagnosis needs to be established quickly, a KOH smear can be done looking for broad‐based budding yeast. Although the yield of this test is lower (0%‐50%), the results can be available within 24 hours.9 As these tests are not always routinely performed, direct communication with the pathologist is recommended if a rapid diagnosis is needed.

The major challenge of this case lay in distinguishing between the recurrence of an old disease and the complications of its treatment. In this case the discussant addresses strategies that might be useful in differentiating recurrent sarcoidosis from an opportunistic infection like blastomycosis. The first issue is the steroid therapy. The exact dose of steroids required to compromise the immune system enough to yield infections is not known. However, in a meta‐analysis of 71 controlled clinical trials performed with steroids, Stuck et. al. were able to show that the occurrence of opportunistic infections depended on both the amount of daily steroid and the cumulative dose.10 Opportunistic infections were unlikely to occur in patients given a mean daily dose of less than 10 mg/day or a cumulative dose of less than 700 mg of prednisone. Although the patient in the present case was only on 10 mg/day of prednisone, his mean daily dose was more than 10 mg/day, and his cumulative dose far exceeded 700 mg. Therefore, an opportunistic infection should have been strongly considered.

The other item used to help distinguish between the 2 diseases was serum angiotensin‐converting enzyme (ACE) level. ACE is an enzyme produced by the epithelial cells of the granulomas in sarcoidosis. ACE alone is inadequate for diagnosis, with a reported sensitivity of 40%‐90%, depending on the population studied and on the definition of normal.1114 Even an ACE level more than twice the normal is not diagnostic for sarcoidosis, with elevated levels found in histoplasmosis, silicosis, tuberculosis, Gaucher's disease, and other disorders.15 Rather than as a diagnostic test, ACE level instead is used to follow disease activity in sarcoidosis, as ACE level often reflects the granuloma burden.1618 The low levels at the initial recurrence suggests the symptoms were not a result of active sarcoid, especially considering that if ACE levels are originally elevated with sarcoidosis, they are almost always elevated again when the disease recurs.14 Normal levels of ACE in sarcoid patients with previously elevated ACE levels should therefore prompt a search for an alternate diagnosis.

This case is an example of the therapy causing a complication that mimics the disease it was intended to cure. When any patient deteriorates while on steroids, the clinician must ask the age‐old question: should more steroids be prescribed or less? As in this case, the answer is not always apparent. Safe decisions in these situations demand awareness of the opportunistic infections endemic to the area and a willingness to perform early invasive procedures (in this case bronchoscopy) to obtain samples to make a definitive diagnosis. By doing so, the devastating chain of events that occurred here hopefully can be avoided.

Acknowledgements

The authors would like to acknowledge Dr. Eleanor Latta and Dr. Serge Jothy, Department of Pathology, St. Michael's Hospital, University of Toronto, for contributing the pathological images.

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  14. Ainslie GM,Benatar SR.Serum angiotensin converting enzyme in sarcoidosis: sensitivity and specificity in diagnosis: correlations with disease activity, duration, extra‐thoracic involvement, radiographic type and therapy.Q J Med.1985;55(218):253270.
  15. Statement on sarcoidosis.Joint Statement of the American Thoracic Society (ATS), theEuropean Respiratory Society (ERS) and theWorld Association of Sarcoidosis and Other Granulomatous Disorders (WASOG) adopted by the ATS Board of Directors and by the ERS Executive Committee, February 1999.Am J Respir Crit Care Med.1999;160:736755.
  16. Rohatgi PK,Ryan JW,Lindeman P.Value of serial measurement of serum angiotensin converting enzyme in the management of sarcoidosis.Am J Med.1981;70(1):4450.
  17. Muthuswamy PP,Lopez‐Majano V,Ranginwala M,Trainor WD.Serum angiotensin‐converting enzyme (SACE) activity as an indicator of total body granuloma load and prognosis in sarcoidosis.Sarcoidosis.1987;4(2):142148.
  18. Silverstein E,Friedland J,Lyons HA.Serum angiotensin converting enzyme in sarcoidosis: clinical significance.Isr J Med Sci.1977;13:10011006.
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A 45‐year‐old man who immigrated to Canada from Ghana at the age of 33 presented with a 2‐year history of progressive cognitive changes. He had bifrontal headache, right‐sided scalp paresthesias, and a 40‐pound weight loss. He was unable to perform his job as an auto parts worker. His wife noticed short‐ and long‐term memory problems and poor concentration. On physical exam he had no focal neurological findings but his score on the Mini‐Mental Status Exam (MMSE) was 23/30, with deficits in attention and recall.

The first important element of this illness is its chronicity. His symptoms progressed slowly over 2 years. Second, aside from his neurological problems, he is an otherwise healthy young, African‐born male. This clinical picture could be the early presentation of a demyelinating, infiltrative, or vascular illness. If vascular, it is more likely a vasculitis than atherosclerotic disease. Malignancy and infection are definitely in the differential, but at this point, I think they are less likely to be the cause, given the tempo of presentation. I would begin my investigations with basic blood work and a computerized tomography (CT) scan of his brain.

A CT scan of the head with contrast demonstrated an enlarged left lateral ventricle with no evidence of obstruction in the foramen of Munro.

The radiological findings of communicating hydrocephalus with normal parenchyma imply a disease that affects the leptomeningeal space. Given that we are looking at an illness that can change cerebral spinal fluid (CSF) flow rather than primary parenchymal disease, demyelinating and vascular illnesses are less likely etiologies, and infiltrative diseases move up on my list. Malignancy and infectious diseases remain in the differential.

He disappeared to follow up for 1 year, during which he returned to Ghana and experienced progressive neurological deterioration, with incontinence, gait instability, and inability to converse clearly and perform activities of daily living. On his return to Canada, an urgent CT scan and magnetic resonance imaging (MRI) of the brain demonstrated ongoing and unchanged hydrocephalus with aqueductal stenosis. A referral was made to a neurosurgeon for insertion of a ventriculoperitoneal shunt. A routine preoperative chest radiograph demonstrated new bilateral upper‐zone reticulonodular changes.

He had no respiratory symptoms, fevers, or lymphadenopathy. His occupational history revealed no exposure to asbestos, silica, farms, or mines. He had no history of either respiratory or neurological illness in the past and no travel other than to Ghana and Toronto. When he immigrated to Toronto, Canada, 12 years before, he had a normal chest radiograph and negative PPD tuberculin skin test.

Many illnesses produce asymptomatic changes on chest x‐ray. Oslerian principles would suggest that we should think of a single diagnosis to explain both nodular lung disease and more than 3 years of a progressive disease affecting the leptomeninges. It is unlikely that tuberculosis, other fungal diseases, or malignancy would result in the chest and brain pathology over a 3‐year period without other sequelae. Sarcoidosis could cause both chronic leptomeningeal changes and the radiographic lung findings. The next steps in investigating this patient should include measurement of angiotensin‐converting enzyme (ACE) and serum calcium and pulmonary function tests. I would ultimately send him for a pathological biopsy of his lung tissue to confirm noncaseating granuloma and exclude infection and malignancy.

Complete blood count, renal and liver biochemistry, and calcium were normal. An ACE level was elevated at 69 g/L (normal < 40 g/L). A human immunodeficiency virus (HIV‐1 and HIV‐2) test, tuberculin skin test, and syphilis serology were negative. A CT scan of the chest demonstrated bilateral upper‐zone reticulonodular changes and diffuse lymphadenopathy (Fig. 1). Pulmonary function tests (PFTs) demonstrated a forced expiratory volume 1 (FEV1) of 3.4 L (94%), forced vital capacity (FVC) of 4.0 L (83%), an FEV1/FVC of 87%, total lung capacity (TLC) of 92% predicted, and diffusion capacity (DLCO) of 67% predicted. An MRI with gadolinium (Fig. 2) demonstrated hydrocephalus, mild basal leptomeningeal enhancement around the perivascular spaces into the subinsular region, and an increased T2 signal in periventricular white matter.

Figure 1
CT scan of the thorax showing bilateral reticulonodular disease.
Figure 2
MRI with gadolinium T2‐weighted imaging showing hydrocephalus and increased periventricular white matter signal.

A bronchoscopy with bronchoalveolar lavage and transbronchial biopsies were performed. Pathology (Fig. 3) demonstrated non‐caseating epitheliod granulomas, with negative special stains for acid‐fast bacilli (AFB) and fungus, and negative fungal and AFB cultures of the bronchial alveolar lavage.

With negative tests for infectious causes such as tuberculosis, I think there is now enough evidence that this patient has sarcoidosis involving the lung and leptomeninges. At this point I would start therapy with steroids.

Figure 3
H and E stain of lung biopsy at 40× showing non‐caseating granuloma.

The patient was started on prednisone 40 mg po qd, and his neurological symptoms improved markedly over the course of 1‐2 months, with normalization of his MMSE and a return to cognitive baseline. As his symptoms stabilized with no change in CT imaging, he returned to work, and over the course of 2 years his prednisone dosage was tapered to 10 mg po od. While on prednisone he developed hypertension and hyperglycemia. He continued to have no respiratory symptoms.

He was cognitively at baseline until 20 months later, when he was readmitted to the hospital with a 2‐week history of worsening headache, increased confusion, poor memory, and wandering. His MMSE had deteriorated to 19/30, with deficits again in memory and attention.

First, we can say with reasonable confidence that the diagnosis of sarcoid was correct. His long and sustained response to steroids, plus the absence of the unmasking of an infectious or malignant disease, supports this conclusion. However, he is now exhibiting an apparent relapse that mimics his presentation 3 years earlier. The question is whether he is suffering from a flare of his disease or whether a second illness has occurred. The most obvious second illness is an opportunistic infection after years of steroid use. I would certainly repeat the angiotensin‐converting enzyme and serum calcium tests and repeat the imaging of his lungs and central nervous system. He also warrants a lumbar puncture with CSF culture, stain, and PCR for opportunistic infections. If these studies are inconclusive and do not specifically suggest relapsing sarcoid, I would once again consider biopsy of tissue from either a lung or leptomeninges.

An MRI with gadolinium looked unchanged from the previous one. A lumbar puncture was performed, and his CSF demonstrated 3 WBCs, no RBCs, normal glucose, and elevated protein at 1.17 g/L, and tests for bacteria, TB, fungi, and viruses were all negative. Repeat blood work was unremarkable, and the ACE level was 2 g/L.

A chest radiograph (Fig. 4a) and CT chest (Fig. 4b) showed marked deterioration, with increased diffuse airspace opacities, interstitial nodularity, and small apical bullae. His PFTs showed some deterioration, with FEV1 2.52 L (73%), FVC 3.29 L (73%), FEV1/FVC 76%, TLC 70% predicted, DLCO 72% predicted. However, he still had no respiratory symptoms.

Figure 4
(a) Plain chest radiograph showing worsening bilateral upper lobe reticulonodular infiltrates; (b) CT of thorax showing worsening bilateral upper lobe reticulonodular infiltrates.

The changes on lumbar puncture are nonspecific. The ACE level is now very low, making sarcoidosis unlikely but not impossible. The chest imaging shows features, specifically interstitial nodularity, consistent with ongoing or relapsing sarcoidosis, but the extensive apical bullae are not characteristic. My best guess is that this patient's illness is not simply relapsing sarcoid but represents superimposed opportunistic infectious disease. I would not reintroduce steroids without pursuing a definitive diagnosis with tissue pathology.

He was placed on prednisone 60 mg po qd and started on trimethoprim‐sulfamethoxazole for Pneumocystis pneumonia (PCP) prophylaxis. He showed modest improvement in his neurological status. A repeat bronchoscopy was not performed. Four months later he was seen by his pulmonologist. He remained without respiratory symptoms and was neurologically unchanged, and a chest radiograph showed no change. He was continued on prednisone 60 mg po qd.

Three weeks later, he was admitted to the hospital with a 2‐week history of anorexia, fatigue, night sweats, right‐sided pleuritic chest pain with productive cough, increasing dyspnea, and no hemoptysis. On admission he was hypoxic with evidence of respiratory distress, and his chest radiograph showed evidence of new right‐sided airspace disease with an associated large right pleural effusion. Initial labs demonstrated a leukocytosis.

I am now very suspicious that this illness is not relapsed sarcoidosis based on his prior clinical response to high‐dose prednisone and that he currently is showing no neurological improvement. His recent clinical deterioration on this very high dose of prednisone makes me think that opportunistic lung infection or disseminated disease is definitely the cause, although the differential is broad. In addition to the typical viral and bacterial causes of community‐acquired pneumonia, this could be caused by unusual bacterial pathogens, tuberculosis, nontuberculous mycobacteria, or fungal diseases including Candida, Aspergillus and dimorphic fungi. I would begin empiric therapy with antibiotics, obtain pleural fluid for examination and culture, and blood cultures.

The patient was treated with a respiratory fluoroquinolone, and blood and sputum cultures were performed. A right thoracentesis removed 300 cc of yellow exudate, with negative gram stain and initial culture. Over the next 24 hours, the patient deteriorated rapidly, with progressive hypoxia and clinical and radiological (Fig. 5) evidence of acute respiratory distress syndrome (ARDS). He required endotracheal intubation with mechanical ventilation.

Figure 5
Plain chest radiograph showing ARDS and right pleural effusion..

He has a progressive illness not responsive to broad‐spectrum antibiotics, and he has deteriorated. At this point it is imperative that he undergo bronchoscopy and transbronchial biopsy.

Bronchoscopy demonstrated secretions from the right lower lobe. Gram stain from a bronchoalveolar lavage from the right lower lobe was negative, and cultures showed no growth after 24 hours. Immediately after bronchoscopy a third‐generation cephalosporin was empirically added. The next day the patient developed hypotension and was started on norepinephrine. Over the subsequent 48 hours, he developed progressive multiorgan failure. Despite multiple vasopressors, high‐frequency oscillator ventilation, broad‐spectrum antimicrobials, and activated protein C, he died in the intensive care unit. At the time of death, all blood cultures were negative, abdominal CT scans showed no intraabdominal infections, and the BAL performed on admission demonstrated negative gram stain, fungal stain, AFB stain, and PCP and no growth from fungal or bacterial cultures.

I think it is an unavoidable conclusion that this man's progressive systemic inflammatory response syndrome and ultimate multiorgan failure was caused by an opportunistic pathogen that was not antibiotic responsive and not identified from the extensive range of infectious disease studies performed. Despite all the negative studies, there still might be either mycobacterial illness or fungal illness. With negative cultures, Candida or Aspergillus infection is unlikely. Other opportunistic fungi like Blastomyces, Histoplasma, and Cryptococcus are certainly in the differential because these organisms can be notoriously difficult to detect on routine surveying such as bronchoalveolar lavage or lumbar puncture. Blastomyces and Histoplasma are both endemic in the area of Canada where the patient resided. I would also keep the zygomycoses in the differential.

Five days after death, fungal culture was reported demonstrating Blastomyces dermatitidis. Postmortem demonstrated disseminated blastomycosis causing severe bilateral pneumonia (Fig. 6a), empyema of right lung, and involvement of the thyroid, heart, liver, spleen, and kidneys. There was also evidence of active CNS blastomycosis involving the meninges and cerebral cortex and diencephalon (Fig. 6b). As well as active blastomycosis, the leptomeninges demonstrated fibrosis and old granulomas that did not contain an organism.

Figure 6
(a) Lung Gomori‐methanamine‐silver (GMS) stain 100× showing multiple yeast forms with broad‐based budding consistent with blastomycosis; (b) Brain GMS stain 40× showing CNS blastomycosis with involvement of the leptomeninges and cortex.

COMMENTARY

This case describes a 45‐year‐old man who presented with chronic cognitive symptoms associated with hydrocephalus. The first step in establishing the diagnosis was made by realizing that a communicating hydrocephalus with no parenchymal CNS disease was highly suggestive of a leptomeningeal process. This narrowed the differential diagnosis to an infiltrative disease affecting the leptomeninges. The next step involved the discovery of an upper‐lobe interstitial lung process, establishing sarcoidosis as the most likely unifying diagnosis. This was confirmed with transbronchial biopsies showing noncaseating granulomas and by the sustained response to treatment with corticosteroids. Unfortunately, after a 2‐year remission, he developed a recurrence of both the neurological and respiratory findings. When his symptoms progressed despite higher doses of corticosteroids, it became apparent that the etiology of his clinical deterioration was not recurrent disease. Instead, the deterioration was caused by disseminated blastomycosis, an opportunistic infection that developed as a result of the immunosuppressants used to treat the sarcoidosis.

With the final diagnosis of blastomycosis, one question about this case becomes: Could it have been blastomycosis and not sarcoid that was responsible for his original neurological presentation? Blastomyces dermatitidis is a thermally dimorphic fungus that causes disease from inhalation of airborne spores found in soil. Areas of North America in which it is endemic include regions bordering the Mississipi and Ohio rivers, as well as the areas bordering the Great Lakes.1 The patient in this case lived in metropolitan Toronto, on Lake Ontario, where blastomycosis is an important yet underreported disease.24 He likely was exposed to blastomyces in Toronto, which in immunocompromised patients may be followed after weeks to months by dissemination to other body sites including the dermis, bones, joints, urogenital system, and, rarely, the central nervous system (CNS) and liver.5 Like sarcoidosis, infection with blastomycosis can produce pathologic evidence of noncaseating granulomatous inflammation. However, as the discussant astutely pointed out, it would be unusual for this patient to have clinically inapparent blastomycosis for almost 2 years while on high‐dose prednisone. The initial diagnosis of sarcoid likely was correct.

CNS disease caused by Blastomyces dermatitidis is quite rare, with only 22 reported cases of meningoencephalitis in the literature.6 As this case demonstrates, CNS blastomycosis is very difficult to diagnose because of the absence of sensitive serologic markers and the difficulty of isolating the organism from blood and cerebrospinal fluid. CSF sampling from lumbar puncture led to its diagnosis in only 2 of the 22 reported cases.7 Furthermore, reliable CSF cultures are usually only obtained via ventricular sampling or tissue biopsy, which itself is limited by the organism's predilection for deep structures of the cerebrum, midbrain, and basal meninges.6 Blastomyces involving the CNS rarely occurs in isolation. In the patient's case, during his neurological deterioration, there was clear radiological evidence of progressive pulmonary pathology despite his being asymptomatic, and as the discussant suggests, pulmonary investigations were warranted.

Pulmonary manifestations of blastomycosis are variable. Acute infections most commonly resemble pneumonia, whereas chronic disease may show reticulonodular changes indistinguishable from sarcoidosis. Severe cases have been shown to progress to respiratory failure with acute respiratory distress syndrome (ARDS).1 The diagnosis is usually established through culture of noninvasive (sensitivity 86%) or bronchoalveolar lavage (sensitivity 92%) specimens.8 However, blastomyces will take between 5 and 30 days to grow in culture.1 In cases where the diagnosis needs to be established quickly, a KOH smear can be done looking for broad‐based budding yeast. Although the yield of this test is lower (0%‐50%), the results can be available within 24 hours.9 As these tests are not always routinely performed, direct communication with the pathologist is recommended if a rapid diagnosis is needed.

The major challenge of this case lay in distinguishing between the recurrence of an old disease and the complications of its treatment. In this case the discussant addresses strategies that might be useful in differentiating recurrent sarcoidosis from an opportunistic infection like blastomycosis. The first issue is the steroid therapy. The exact dose of steroids required to compromise the immune system enough to yield infections is not known. However, in a meta‐analysis of 71 controlled clinical trials performed with steroids, Stuck et. al. were able to show that the occurrence of opportunistic infections depended on both the amount of daily steroid and the cumulative dose.10 Opportunistic infections were unlikely to occur in patients given a mean daily dose of less than 10 mg/day or a cumulative dose of less than 700 mg of prednisone. Although the patient in the present case was only on 10 mg/day of prednisone, his mean daily dose was more than 10 mg/day, and his cumulative dose far exceeded 700 mg. Therefore, an opportunistic infection should have been strongly considered.

The other item used to help distinguish between the 2 diseases was serum angiotensin‐converting enzyme (ACE) level. ACE is an enzyme produced by the epithelial cells of the granulomas in sarcoidosis. ACE alone is inadequate for diagnosis, with a reported sensitivity of 40%‐90%, depending on the population studied and on the definition of normal.1114 Even an ACE level more than twice the normal is not diagnostic for sarcoidosis, with elevated levels found in histoplasmosis, silicosis, tuberculosis, Gaucher's disease, and other disorders.15 Rather than as a diagnostic test, ACE level instead is used to follow disease activity in sarcoidosis, as ACE level often reflects the granuloma burden.1618 The low levels at the initial recurrence suggests the symptoms were not a result of active sarcoid, especially considering that if ACE levels are originally elevated with sarcoidosis, they are almost always elevated again when the disease recurs.14 Normal levels of ACE in sarcoid patients with previously elevated ACE levels should therefore prompt a search for an alternate diagnosis.

This case is an example of the therapy causing a complication that mimics the disease it was intended to cure. When any patient deteriorates while on steroids, the clinician must ask the age‐old question: should more steroids be prescribed or less? As in this case, the answer is not always apparent. Safe decisions in these situations demand awareness of the opportunistic infections endemic to the area and a willingness to perform early invasive procedures (in this case bronchoscopy) to obtain samples to make a definitive diagnosis. By doing so, the devastating chain of events that occurred here hopefully can be avoided.

Acknowledgements

The authors would like to acknowledge Dr. Eleanor Latta and Dr. Serge Jothy, Department of Pathology, St. Michael's Hospital, University of Toronto, for contributing the pathological images.

A 45‐year‐old man who immigrated to Canada from Ghana at the age of 33 presented with a 2‐year history of progressive cognitive changes. He had bifrontal headache, right‐sided scalp paresthesias, and a 40‐pound weight loss. He was unable to perform his job as an auto parts worker. His wife noticed short‐ and long‐term memory problems and poor concentration. On physical exam he had no focal neurological findings but his score on the Mini‐Mental Status Exam (MMSE) was 23/30, with deficits in attention and recall.

The first important element of this illness is its chronicity. His symptoms progressed slowly over 2 years. Second, aside from his neurological problems, he is an otherwise healthy young, African‐born male. This clinical picture could be the early presentation of a demyelinating, infiltrative, or vascular illness. If vascular, it is more likely a vasculitis than atherosclerotic disease. Malignancy and infection are definitely in the differential, but at this point, I think they are less likely to be the cause, given the tempo of presentation. I would begin my investigations with basic blood work and a computerized tomography (CT) scan of his brain.

A CT scan of the head with contrast demonstrated an enlarged left lateral ventricle with no evidence of obstruction in the foramen of Munro.

The radiological findings of communicating hydrocephalus with normal parenchyma imply a disease that affects the leptomeningeal space. Given that we are looking at an illness that can change cerebral spinal fluid (CSF) flow rather than primary parenchymal disease, demyelinating and vascular illnesses are less likely etiologies, and infiltrative diseases move up on my list. Malignancy and infectious diseases remain in the differential.

He disappeared to follow up for 1 year, during which he returned to Ghana and experienced progressive neurological deterioration, with incontinence, gait instability, and inability to converse clearly and perform activities of daily living. On his return to Canada, an urgent CT scan and magnetic resonance imaging (MRI) of the brain demonstrated ongoing and unchanged hydrocephalus with aqueductal stenosis. A referral was made to a neurosurgeon for insertion of a ventriculoperitoneal shunt. A routine preoperative chest radiograph demonstrated new bilateral upper‐zone reticulonodular changes.

He had no respiratory symptoms, fevers, or lymphadenopathy. His occupational history revealed no exposure to asbestos, silica, farms, or mines. He had no history of either respiratory or neurological illness in the past and no travel other than to Ghana and Toronto. When he immigrated to Toronto, Canada, 12 years before, he had a normal chest radiograph and negative PPD tuberculin skin test.

Many illnesses produce asymptomatic changes on chest x‐ray. Oslerian principles would suggest that we should think of a single diagnosis to explain both nodular lung disease and more than 3 years of a progressive disease affecting the leptomeninges. It is unlikely that tuberculosis, other fungal diseases, or malignancy would result in the chest and brain pathology over a 3‐year period without other sequelae. Sarcoidosis could cause both chronic leptomeningeal changes and the radiographic lung findings. The next steps in investigating this patient should include measurement of angiotensin‐converting enzyme (ACE) and serum calcium and pulmonary function tests. I would ultimately send him for a pathological biopsy of his lung tissue to confirm noncaseating granuloma and exclude infection and malignancy.

Complete blood count, renal and liver biochemistry, and calcium were normal. An ACE level was elevated at 69 g/L (normal < 40 g/L). A human immunodeficiency virus (HIV‐1 and HIV‐2) test, tuberculin skin test, and syphilis serology were negative. A CT scan of the chest demonstrated bilateral upper‐zone reticulonodular changes and diffuse lymphadenopathy (Fig. 1). Pulmonary function tests (PFTs) demonstrated a forced expiratory volume 1 (FEV1) of 3.4 L (94%), forced vital capacity (FVC) of 4.0 L (83%), an FEV1/FVC of 87%, total lung capacity (TLC) of 92% predicted, and diffusion capacity (DLCO) of 67% predicted. An MRI with gadolinium (Fig. 2) demonstrated hydrocephalus, mild basal leptomeningeal enhancement around the perivascular spaces into the subinsular region, and an increased T2 signal in periventricular white matter.

Figure 1
CT scan of the thorax showing bilateral reticulonodular disease.
Figure 2
MRI with gadolinium T2‐weighted imaging showing hydrocephalus and increased periventricular white matter signal.

A bronchoscopy with bronchoalveolar lavage and transbronchial biopsies were performed. Pathology (Fig. 3) demonstrated non‐caseating epitheliod granulomas, with negative special stains for acid‐fast bacilli (AFB) and fungus, and negative fungal and AFB cultures of the bronchial alveolar lavage.

With negative tests for infectious causes such as tuberculosis, I think there is now enough evidence that this patient has sarcoidosis involving the lung and leptomeninges. At this point I would start therapy with steroids.

Figure 3
H and E stain of lung biopsy at 40× showing non‐caseating granuloma.

The patient was started on prednisone 40 mg po qd, and his neurological symptoms improved markedly over the course of 1‐2 months, with normalization of his MMSE and a return to cognitive baseline. As his symptoms stabilized with no change in CT imaging, he returned to work, and over the course of 2 years his prednisone dosage was tapered to 10 mg po od. While on prednisone he developed hypertension and hyperglycemia. He continued to have no respiratory symptoms.

He was cognitively at baseline until 20 months later, when he was readmitted to the hospital with a 2‐week history of worsening headache, increased confusion, poor memory, and wandering. His MMSE had deteriorated to 19/30, with deficits again in memory and attention.

First, we can say with reasonable confidence that the diagnosis of sarcoid was correct. His long and sustained response to steroids, plus the absence of the unmasking of an infectious or malignant disease, supports this conclusion. However, he is now exhibiting an apparent relapse that mimics his presentation 3 years earlier. The question is whether he is suffering from a flare of his disease or whether a second illness has occurred. The most obvious second illness is an opportunistic infection after years of steroid use. I would certainly repeat the angiotensin‐converting enzyme and serum calcium tests and repeat the imaging of his lungs and central nervous system. He also warrants a lumbar puncture with CSF culture, stain, and PCR for opportunistic infections. If these studies are inconclusive and do not specifically suggest relapsing sarcoid, I would once again consider biopsy of tissue from either a lung or leptomeninges.

An MRI with gadolinium looked unchanged from the previous one. A lumbar puncture was performed, and his CSF demonstrated 3 WBCs, no RBCs, normal glucose, and elevated protein at 1.17 g/L, and tests for bacteria, TB, fungi, and viruses were all negative. Repeat blood work was unremarkable, and the ACE level was 2 g/L.

A chest radiograph (Fig. 4a) and CT chest (Fig. 4b) showed marked deterioration, with increased diffuse airspace opacities, interstitial nodularity, and small apical bullae. His PFTs showed some deterioration, with FEV1 2.52 L (73%), FVC 3.29 L (73%), FEV1/FVC 76%, TLC 70% predicted, DLCO 72% predicted. However, he still had no respiratory symptoms.

Figure 4
(a) Plain chest radiograph showing worsening bilateral upper lobe reticulonodular infiltrates; (b) CT of thorax showing worsening bilateral upper lobe reticulonodular infiltrates.

The changes on lumbar puncture are nonspecific. The ACE level is now very low, making sarcoidosis unlikely but not impossible. The chest imaging shows features, specifically interstitial nodularity, consistent with ongoing or relapsing sarcoidosis, but the extensive apical bullae are not characteristic. My best guess is that this patient's illness is not simply relapsing sarcoid but represents superimposed opportunistic infectious disease. I would not reintroduce steroids without pursuing a definitive diagnosis with tissue pathology.

He was placed on prednisone 60 mg po qd and started on trimethoprim‐sulfamethoxazole for Pneumocystis pneumonia (PCP) prophylaxis. He showed modest improvement in his neurological status. A repeat bronchoscopy was not performed. Four months later he was seen by his pulmonologist. He remained without respiratory symptoms and was neurologically unchanged, and a chest radiograph showed no change. He was continued on prednisone 60 mg po qd.

Three weeks later, he was admitted to the hospital with a 2‐week history of anorexia, fatigue, night sweats, right‐sided pleuritic chest pain with productive cough, increasing dyspnea, and no hemoptysis. On admission he was hypoxic with evidence of respiratory distress, and his chest radiograph showed evidence of new right‐sided airspace disease with an associated large right pleural effusion. Initial labs demonstrated a leukocytosis.

I am now very suspicious that this illness is not relapsed sarcoidosis based on his prior clinical response to high‐dose prednisone and that he currently is showing no neurological improvement. His recent clinical deterioration on this very high dose of prednisone makes me think that opportunistic lung infection or disseminated disease is definitely the cause, although the differential is broad. In addition to the typical viral and bacterial causes of community‐acquired pneumonia, this could be caused by unusual bacterial pathogens, tuberculosis, nontuberculous mycobacteria, or fungal diseases including Candida, Aspergillus and dimorphic fungi. I would begin empiric therapy with antibiotics, obtain pleural fluid for examination and culture, and blood cultures.

The patient was treated with a respiratory fluoroquinolone, and blood and sputum cultures were performed. A right thoracentesis removed 300 cc of yellow exudate, with negative gram stain and initial culture. Over the next 24 hours, the patient deteriorated rapidly, with progressive hypoxia and clinical and radiological (Fig. 5) evidence of acute respiratory distress syndrome (ARDS). He required endotracheal intubation with mechanical ventilation.

Figure 5
Plain chest radiograph showing ARDS and right pleural effusion..

He has a progressive illness not responsive to broad‐spectrum antibiotics, and he has deteriorated. At this point it is imperative that he undergo bronchoscopy and transbronchial biopsy.

Bronchoscopy demonstrated secretions from the right lower lobe. Gram stain from a bronchoalveolar lavage from the right lower lobe was negative, and cultures showed no growth after 24 hours. Immediately after bronchoscopy a third‐generation cephalosporin was empirically added. The next day the patient developed hypotension and was started on norepinephrine. Over the subsequent 48 hours, he developed progressive multiorgan failure. Despite multiple vasopressors, high‐frequency oscillator ventilation, broad‐spectrum antimicrobials, and activated protein C, he died in the intensive care unit. At the time of death, all blood cultures were negative, abdominal CT scans showed no intraabdominal infections, and the BAL performed on admission demonstrated negative gram stain, fungal stain, AFB stain, and PCP and no growth from fungal or bacterial cultures.

I think it is an unavoidable conclusion that this man's progressive systemic inflammatory response syndrome and ultimate multiorgan failure was caused by an opportunistic pathogen that was not antibiotic responsive and not identified from the extensive range of infectious disease studies performed. Despite all the negative studies, there still might be either mycobacterial illness or fungal illness. With negative cultures, Candida or Aspergillus infection is unlikely. Other opportunistic fungi like Blastomyces, Histoplasma, and Cryptococcus are certainly in the differential because these organisms can be notoriously difficult to detect on routine surveying such as bronchoalveolar lavage or lumbar puncture. Blastomyces and Histoplasma are both endemic in the area of Canada where the patient resided. I would also keep the zygomycoses in the differential.

Five days after death, fungal culture was reported demonstrating Blastomyces dermatitidis. Postmortem demonstrated disseminated blastomycosis causing severe bilateral pneumonia (Fig. 6a), empyema of right lung, and involvement of the thyroid, heart, liver, spleen, and kidneys. There was also evidence of active CNS blastomycosis involving the meninges and cerebral cortex and diencephalon (Fig. 6b). As well as active blastomycosis, the leptomeninges demonstrated fibrosis and old granulomas that did not contain an organism.

Figure 6
(a) Lung Gomori‐methanamine‐silver (GMS) stain 100× showing multiple yeast forms with broad‐based budding consistent with blastomycosis; (b) Brain GMS stain 40× showing CNS blastomycosis with involvement of the leptomeninges and cortex.

COMMENTARY

This case describes a 45‐year‐old man who presented with chronic cognitive symptoms associated with hydrocephalus. The first step in establishing the diagnosis was made by realizing that a communicating hydrocephalus with no parenchymal CNS disease was highly suggestive of a leptomeningeal process. This narrowed the differential diagnosis to an infiltrative disease affecting the leptomeninges. The next step involved the discovery of an upper‐lobe interstitial lung process, establishing sarcoidosis as the most likely unifying diagnosis. This was confirmed with transbronchial biopsies showing noncaseating granulomas and by the sustained response to treatment with corticosteroids. Unfortunately, after a 2‐year remission, he developed a recurrence of both the neurological and respiratory findings. When his symptoms progressed despite higher doses of corticosteroids, it became apparent that the etiology of his clinical deterioration was not recurrent disease. Instead, the deterioration was caused by disseminated blastomycosis, an opportunistic infection that developed as a result of the immunosuppressants used to treat the sarcoidosis.

With the final diagnosis of blastomycosis, one question about this case becomes: Could it have been blastomycosis and not sarcoid that was responsible for his original neurological presentation? Blastomyces dermatitidis is a thermally dimorphic fungus that causes disease from inhalation of airborne spores found in soil. Areas of North America in which it is endemic include regions bordering the Mississipi and Ohio rivers, as well as the areas bordering the Great Lakes.1 The patient in this case lived in metropolitan Toronto, on Lake Ontario, where blastomycosis is an important yet underreported disease.24 He likely was exposed to blastomyces in Toronto, which in immunocompromised patients may be followed after weeks to months by dissemination to other body sites including the dermis, bones, joints, urogenital system, and, rarely, the central nervous system (CNS) and liver.5 Like sarcoidosis, infection with blastomycosis can produce pathologic evidence of noncaseating granulomatous inflammation. However, as the discussant astutely pointed out, it would be unusual for this patient to have clinically inapparent blastomycosis for almost 2 years while on high‐dose prednisone. The initial diagnosis of sarcoid likely was correct.

CNS disease caused by Blastomyces dermatitidis is quite rare, with only 22 reported cases of meningoencephalitis in the literature.6 As this case demonstrates, CNS blastomycosis is very difficult to diagnose because of the absence of sensitive serologic markers and the difficulty of isolating the organism from blood and cerebrospinal fluid. CSF sampling from lumbar puncture led to its diagnosis in only 2 of the 22 reported cases.7 Furthermore, reliable CSF cultures are usually only obtained via ventricular sampling or tissue biopsy, which itself is limited by the organism's predilection for deep structures of the cerebrum, midbrain, and basal meninges.6 Blastomyces involving the CNS rarely occurs in isolation. In the patient's case, during his neurological deterioration, there was clear radiological evidence of progressive pulmonary pathology despite his being asymptomatic, and as the discussant suggests, pulmonary investigations were warranted.

Pulmonary manifestations of blastomycosis are variable. Acute infections most commonly resemble pneumonia, whereas chronic disease may show reticulonodular changes indistinguishable from sarcoidosis. Severe cases have been shown to progress to respiratory failure with acute respiratory distress syndrome (ARDS).1 The diagnosis is usually established through culture of noninvasive (sensitivity 86%) or bronchoalveolar lavage (sensitivity 92%) specimens.8 However, blastomyces will take between 5 and 30 days to grow in culture.1 In cases where the diagnosis needs to be established quickly, a KOH smear can be done looking for broad‐based budding yeast. Although the yield of this test is lower (0%‐50%), the results can be available within 24 hours.9 As these tests are not always routinely performed, direct communication with the pathologist is recommended if a rapid diagnosis is needed.

The major challenge of this case lay in distinguishing between the recurrence of an old disease and the complications of its treatment. In this case the discussant addresses strategies that might be useful in differentiating recurrent sarcoidosis from an opportunistic infection like blastomycosis. The first issue is the steroid therapy. The exact dose of steroids required to compromise the immune system enough to yield infections is not known. However, in a meta‐analysis of 71 controlled clinical trials performed with steroids, Stuck et. al. were able to show that the occurrence of opportunistic infections depended on both the amount of daily steroid and the cumulative dose.10 Opportunistic infections were unlikely to occur in patients given a mean daily dose of less than 10 mg/day or a cumulative dose of less than 700 mg of prednisone. Although the patient in the present case was only on 10 mg/day of prednisone, his mean daily dose was more than 10 mg/day, and his cumulative dose far exceeded 700 mg. Therefore, an opportunistic infection should have been strongly considered.

The other item used to help distinguish between the 2 diseases was serum angiotensin‐converting enzyme (ACE) level. ACE is an enzyme produced by the epithelial cells of the granulomas in sarcoidosis. ACE alone is inadequate for diagnosis, with a reported sensitivity of 40%‐90%, depending on the population studied and on the definition of normal.1114 Even an ACE level more than twice the normal is not diagnostic for sarcoidosis, with elevated levels found in histoplasmosis, silicosis, tuberculosis, Gaucher's disease, and other disorders.15 Rather than as a diagnostic test, ACE level instead is used to follow disease activity in sarcoidosis, as ACE level often reflects the granuloma burden.1618 The low levels at the initial recurrence suggests the symptoms were not a result of active sarcoid, especially considering that if ACE levels are originally elevated with sarcoidosis, they are almost always elevated again when the disease recurs.14 Normal levels of ACE in sarcoid patients with previously elevated ACE levels should therefore prompt a search for an alternate diagnosis.

This case is an example of the therapy causing a complication that mimics the disease it was intended to cure. When any patient deteriorates while on steroids, the clinician must ask the age‐old question: should more steroids be prescribed or less? As in this case, the answer is not always apparent. Safe decisions in these situations demand awareness of the opportunistic infections endemic to the area and a willingness to perform early invasive procedures (in this case bronchoscopy) to obtain samples to make a definitive diagnosis. By doing so, the devastating chain of events that occurred here hopefully can be avoided.

Acknowledgements

The authors would like to acknowledge Dr. Eleanor Latta and Dr. Serge Jothy, Department of Pathology, St. Michael's Hospital, University of Toronto, for contributing the pathological images.

References
  1. Bradsher RW,Chapman SW,Pappas PG.Blastomycosis.Infect Dis Clin North Am.2003;17(1):21,40, vii.
  2. Lester RS,DeKoven JG,Kane J,Simor AE,Krajden S,Summerbell RC.Novel cases of blastomycosis acquired in Toronto, Ontario.CMAJ.2000;163:13091312.
  3. Bernstein S,Brunner HI,Summerbell R,Allen U,Babyn P,Richardson SE.Blastomycosis acquired by three children in Toronto.Can J Infect Dis Med Micro.2002;13(4):259263.
  4. Morris SK,Brophy J,Richardson SE, et al.Blastomycosis in Ontario, 1994‐2003.Emerg Infect Dis.2006;12(2):274279.
  5. Crampton TL,Light RB,Berg GM, et al.Epidemiology and clinical spectrum of blastomycosis diagnosed at Manitoba hospitals.Clin Infect Dis.2002;34:13101316.
  6. Friedman JA,Wijdicks EF,Fulgham JR,Wright AJ.Meningoencephalitis due to Blastomyces dermatitidis: case report and literature review.Mayo Clin Proc.2000;75:403408.
  7. Kravitz GR,Davies SF,Eckman MR,Sarosi GA.Chronic blastomycotic meningitis.Am J Med.1981;71:501505.
  8. Martynowicz MA,Prakash UB.Pulmonary blastomycosis: an appraisal of diagnostic techniques.Chest.2002;121:768773.
  9. Thompson CA,McEachern R,Norman JR.Blastomycosis as an etiology of acute lung injury.South Med J.1998;91:861863.
  10. Stuck AE,Minder CE,Frey FJ.Risk of infectious complications in patients taking glucocorticosteroids.Rev Infect Dis.1989;11:954963.
  11. Lieberman J.Elevation of serum angiotensin‐converting‐enzyme (ACE) level in sarcoidosis.Am J Med.1975;59:365372.
  12. Fanburg BL,Schoenberger MD,Bachus B,Snider GL.Elevated serum angiotensin I converting enzyme in sarcoidosis.Am Rev Respir Dis.1976;114:525528.
  13. Studdy P,Bird R,James DG.Serum angiotensin‐converting enzyme (SACE) in sarcoidosis and other granulomatous disorders.Lancet.1978;2:13311334.
  14. Ainslie GM,Benatar SR.Serum angiotensin converting enzyme in sarcoidosis: sensitivity and specificity in diagnosis: correlations with disease activity, duration, extra‐thoracic involvement, radiographic type and therapy.Q J Med.1985;55(218):253270.
  15. Statement on sarcoidosis.Joint Statement of the American Thoracic Society (ATS), theEuropean Respiratory Society (ERS) and theWorld Association of Sarcoidosis and Other Granulomatous Disorders (WASOG) adopted by the ATS Board of Directors and by the ERS Executive Committee, February 1999.Am J Respir Crit Care Med.1999;160:736755.
  16. Rohatgi PK,Ryan JW,Lindeman P.Value of serial measurement of serum angiotensin converting enzyme in the management of sarcoidosis.Am J Med.1981;70(1):4450.
  17. Muthuswamy PP,Lopez‐Majano V,Ranginwala M,Trainor WD.Serum angiotensin‐converting enzyme (SACE) activity as an indicator of total body granuloma load and prognosis in sarcoidosis.Sarcoidosis.1987;4(2):142148.
  18. Silverstein E,Friedland J,Lyons HA.Serum angiotensin converting enzyme in sarcoidosis: clinical significance.Isr J Med Sci.1977;13:10011006.
References
  1. Bradsher RW,Chapman SW,Pappas PG.Blastomycosis.Infect Dis Clin North Am.2003;17(1):21,40, vii.
  2. Lester RS,DeKoven JG,Kane J,Simor AE,Krajden S,Summerbell RC.Novel cases of blastomycosis acquired in Toronto, Ontario.CMAJ.2000;163:13091312.
  3. Bernstein S,Brunner HI,Summerbell R,Allen U,Babyn P,Richardson SE.Blastomycosis acquired by three children in Toronto.Can J Infect Dis Med Micro.2002;13(4):259263.
  4. Morris SK,Brophy J,Richardson SE, et al.Blastomycosis in Ontario, 1994‐2003.Emerg Infect Dis.2006;12(2):274279.
  5. Crampton TL,Light RB,Berg GM, et al.Epidemiology and clinical spectrum of blastomycosis diagnosed at Manitoba hospitals.Clin Infect Dis.2002;34:13101316.
  6. Friedman JA,Wijdicks EF,Fulgham JR,Wright AJ.Meningoencephalitis due to Blastomyces dermatitidis: case report and literature review.Mayo Clin Proc.2000;75:403408.
  7. Kravitz GR,Davies SF,Eckman MR,Sarosi GA.Chronic blastomycotic meningitis.Am J Med.1981;71:501505.
  8. Martynowicz MA,Prakash UB.Pulmonary blastomycosis: an appraisal of diagnostic techniques.Chest.2002;121:768773.
  9. Thompson CA,McEachern R,Norman JR.Blastomycosis as an etiology of acute lung injury.South Med J.1998;91:861863.
  10. Stuck AE,Minder CE,Frey FJ.Risk of infectious complications in patients taking glucocorticosteroids.Rev Infect Dis.1989;11:954963.
  11. Lieberman J.Elevation of serum angiotensin‐converting‐enzyme (ACE) level in sarcoidosis.Am J Med.1975;59:365372.
  12. Fanburg BL,Schoenberger MD,Bachus B,Snider GL.Elevated serum angiotensin I converting enzyme in sarcoidosis.Am Rev Respir Dis.1976;114:525528.
  13. Studdy P,Bird R,James DG.Serum angiotensin‐converting enzyme (SACE) in sarcoidosis and other granulomatous disorders.Lancet.1978;2:13311334.
  14. Ainslie GM,Benatar SR.Serum angiotensin converting enzyme in sarcoidosis: sensitivity and specificity in diagnosis: correlations with disease activity, duration, extra‐thoracic involvement, radiographic type and therapy.Q J Med.1985;55(218):253270.
  15. Statement on sarcoidosis.Joint Statement of the American Thoracic Society (ATS), theEuropean Respiratory Society (ERS) and theWorld Association of Sarcoidosis and Other Granulomatous Disorders (WASOG) adopted by the ATS Board of Directors and by the ERS Executive Committee, February 1999.Am J Respir Crit Care Med.1999;160:736755.
  16. Rohatgi PK,Ryan JW,Lindeman P.Value of serial measurement of serum angiotensin converting enzyme in the management of sarcoidosis.Am J Med.1981;70(1):4450.
  17. Muthuswamy PP,Lopez‐Majano V,Ranginwala M,Trainor WD.Serum angiotensin‐converting enzyme (SACE) activity as an indicator of total body granuloma load and prognosis in sarcoidosis.Sarcoidosis.1987;4(2):142148.
  18. Silverstein E,Friedland J,Lyons HA.Serum angiotensin converting enzyme in sarcoidosis: clinical significance.Isr J Med Sci.1977;13:10011006.
Issue
Journal of Hospital Medicine - 1(4)
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Journal of Hospital Medicine - 1(4)
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241-247
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241-247
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More steroids or less? That is the question!
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More steroids or less? That is the question!
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A tasty stew: A tale that changed my practice

I was a newly appointed head of a department of medicine. Supervising the care of 44 patients and instructing interns and residents was a new and thrilling experience. Some patients presented complex problems, which satisfied my detective instincts and provided a stimulating intellectual challenge. Many others were less intellectually demanding, but I loved the personal interaction, the ability to change things for the better, and the endless variability.

It amazes me to reflect on how uncritical I was at the time, adopting and following common clinical practices with little questioning. It never really crossed my mind that medicine could be practiced in a different and better way. When I managed after some months to set aside one day a week to continue basic research, I was overjoyed. On that day, I became a scientist, putting each assumption to rigorous testing. At the hospital however, I was much more self‐assured and complacent. It was during a break between experiments at the research institute that I slumped wearily into an armchair in the library and picked up a shabby copy of the Green Journal. Being too tired for anything serious, I started reading what looked like a fairy tale. It was titled In a stew, by Michael LaCombe, whom I knew to be a gifted medical writer.1 Soon I found myself immersed in the story. The princess is seriously sick, and all the court doctors are baffled. She already has had 4 CT scans, 3 MRIs, and dozens of other tests. All the tests were fine, but the princess remains very sick, and the king is terribly worried. Then, somebody remembers an old, forgotten clinician who has been relegated to a small dusty den somewhere in the basement. For his services to be rendered, all he demands is that someone find him his stethoscope and that he be allowed to have a pupil. Using observation, knowledge, and wisdom (but no further tests), he elegantly elicits the relevant history and makes the correct diagnosis, which has eluded all the sophisticated court doctors armed with their batteries of high‐tech tests but with little regard for old‐fashioned clinical methods.

This was good fun, but though I enjoyed it very much, I had no idea that it would remain in my mind and shape my thinking, my practice, and my teaching. Nevertheless, I gradually found myself during rounds reflecting on this story with the patient who had had 2 CT scans done before anyone bothered to listen to him or examine him and with the patient who had been studied for months before a simple fact that should have been noted at once was finally revealed, which led to a single test that was diagnostic and to the patient's recovery.2 Then there was the patient who underwent a procedure, which looked innocent enough, but resulted in an adverse event that cascaded into months of life‐threatening illness.3 Was the procedure really necessary?

One night, a couple of years later, I woke up and instead of going back to sleep, sat in the silent living room, suddenly thinking of our departmental routine and realizing somehow that many things we physicians do may be seriously flawed: taking a superficial history and performing a perfunctory exam; having a light finger on the trigger of test ordering even if imaging and tests may mean little out of the clinical context and often beget more unnecessary testing; skipping significant information only because it is not immediately available but has to be found at another hospital or clinic or by calling the primary physician; disregarding the ubiquitous and influential emotional aspect or the patient's perspective and health literacy, which are essential for shared decisions; and the repeated underuse4 of highly effective medications and especially of proven preventive measures that are not pharmacological and hence not vigorously promoted by the large pharmaceutical companies.

The seed for this heresy was sown by the fable, and it colored my clinical life with a vein of skepticism and self‐criticism. Slowly it also grew into a long‐term commitment to teaching about and research on avoidable pitfalls in patient care.5

Thus, Lacombe's little piece often comes back to me, teaching me that a fairy tale can sometimes be more powerful than a randomized controlled study of 10,000 patients.

References
  1. LaCombe M.In a stew.Am J Med.1991;91:276278.
  2. Schattner A,Zimhony O,Avidor B,Giladi M.Asking the right question.Lancet.2003;361:1786.
  3. Schattner A.Down the cascade.Br Med J.2004;329:678.
  4. Woolf SH.The need for perspective in evidence‐based medicine.JAMA.1999;282:23582365.
  5. Schattner A,Fletcher RH.Pearls and pitfalls in patient care: the need to revive traditional clinical values.Am J Med Sci.2004;327:7985.
Article PDF
Issue
Journal of Hospital Medicine - 1(4)
Page Number
267-268
Sections
Article PDF
Article PDF

I was a newly appointed head of a department of medicine. Supervising the care of 44 patients and instructing interns and residents was a new and thrilling experience. Some patients presented complex problems, which satisfied my detective instincts and provided a stimulating intellectual challenge. Many others were less intellectually demanding, but I loved the personal interaction, the ability to change things for the better, and the endless variability.

It amazes me to reflect on how uncritical I was at the time, adopting and following common clinical practices with little questioning. It never really crossed my mind that medicine could be practiced in a different and better way. When I managed after some months to set aside one day a week to continue basic research, I was overjoyed. On that day, I became a scientist, putting each assumption to rigorous testing. At the hospital however, I was much more self‐assured and complacent. It was during a break between experiments at the research institute that I slumped wearily into an armchair in the library and picked up a shabby copy of the Green Journal. Being too tired for anything serious, I started reading what looked like a fairy tale. It was titled In a stew, by Michael LaCombe, whom I knew to be a gifted medical writer.1 Soon I found myself immersed in the story. The princess is seriously sick, and all the court doctors are baffled. She already has had 4 CT scans, 3 MRIs, and dozens of other tests. All the tests were fine, but the princess remains very sick, and the king is terribly worried. Then, somebody remembers an old, forgotten clinician who has been relegated to a small dusty den somewhere in the basement. For his services to be rendered, all he demands is that someone find him his stethoscope and that he be allowed to have a pupil. Using observation, knowledge, and wisdom (but no further tests), he elegantly elicits the relevant history and makes the correct diagnosis, which has eluded all the sophisticated court doctors armed with their batteries of high‐tech tests but with little regard for old‐fashioned clinical methods.

This was good fun, but though I enjoyed it very much, I had no idea that it would remain in my mind and shape my thinking, my practice, and my teaching. Nevertheless, I gradually found myself during rounds reflecting on this story with the patient who had had 2 CT scans done before anyone bothered to listen to him or examine him and with the patient who had been studied for months before a simple fact that should have been noted at once was finally revealed, which led to a single test that was diagnostic and to the patient's recovery.2 Then there was the patient who underwent a procedure, which looked innocent enough, but resulted in an adverse event that cascaded into months of life‐threatening illness.3 Was the procedure really necessary?

One night, a couple of years later, I woke up and instead of going back to sleep, sat in the silent living room, suddenly thinking of our departmental routine and realizing somehow that many things we physicians do may be seriously flawed: taking a superficial history and performing a perfunctory exam; having a light finger on the trigger of test ordering even if imaging and tests may mean little out of the clinical context and often beget more unnecessary testing; skipping significant information only because it is not immediately available but has to be found at another hospital or clinic or by calling the primary physician; disregarding the ubiquitous and influential emotional aspect or the patient's perspective and health literacy, which are essential for shared decisions; and the repeated underuse4 of highly effective medications and especially of proven preventive measures that are not pharmacological and hence not vigorously promoted by the large pharmaceutical companies.

The seed for this heresy was sown by the fable, and it colored my clinical life with a vein of skepticism and self‐criticism. Slowly it also grew into a long‐term commitment to teaching about and research on avoidable pitfalls in patient care.5

Thus, Lacombe's little piece often comes back to me, teaching me that a fairy tale can sometimes be more powerful than a randomized controlled study of 10,000 patients.

I was a newly appointed head of a department of medicine. Supervising the care of 44 patients and instructing interns and residents was a new and thrilling experience. Some patients presented complex problems, which satisfied my detective instincts and provided a stimulating intellectual challenge. Many others were less intellectually demanding, but I loved the personal interaction, the ability to change things for the better, and the endless variability.

It amazes me to reflect on how uncritical I was at the time, adopting and following common clinical practices with little questioning. It never really crossed my mind that medicine could be practiced in a different and better way. When I managed after some months to set aside one day a week to continue basic research, I was overjoyed. On that day, I became a scientist, putting each assumption to rigorous testing. At the hospital however, I was much more self‐assured and complacent. It was during a break between experiments at the research institute that I slumped wearily into an armchair in the library and picked up a shabby copy of the Green Journal. Being too tired for anything serious, I started reading what looked like a fairy tale. It was titled In a stew, by Michael LaCombe, whom I knew to be a gifted medical writer.1 Soon I found myself immersed in the story. The princess is seriously sick, and all the court doctors are baffled. She already has had 4 CT scans, 3 MRIs, and dozens of other tests. All the tests were fine, but the princess remains very sick, and the king is terribly worried. Then, somebody remembers an old, forgotten clinician who has been relegated to a small dusty den somewhere in the basement. For his services to be rendered, all he demands is that someone find him his stethoscope and that he be allowed to have a pupil. Using observation, knowledge, and wisdom (but no further tests), he elegantly elicits the relevant history and makes the correct diagnosis, which has eluded all the sophisticated court doctors armed with their batteries of high‐tech tests but with little regard for old‐fashioned clinical methods.

This was good fun, but though I enjoyed it very much, I had no idea that it would remain in my mind and shape my thinking, my practice, and my teaching. Nevertheless, I gradually found myself during rounds reflecting on this story with the patient who had had 2 CT scans done before anyone bothered to listen to him or examine him and with the patient who had been studied for months before a simple fact that should have been noted at once was finally revealed, which led to a single test that was diagnostic and to the patient's recovery.2 Then there was the patient who underwent a procedure, which looked innocent enough, but resulted in an adverse event that cascaded into months of life‐threatening illness.3 Was the procedure really necessary?

One night, a couple of years later, I woke up and instead of going back to sleep, sat in the silent living room, suddenly thinking of our departmental routine and realizing somehow that many things we physicians do may be seriously flawed: taking a superficial history and performing a perfunctory exam; having a light finger on the trigger of test ordering even if imaging and tests may mean little out of the clinical context and often beget more unnecessary testing; skipping significant information only because it is not immediately available but has to be found at another hospital or clinic or by calling the primary physician; disregarding the ubiquitous and influential emotional aspect or the patient's perspective and health literacy, which are essential for shared decisions; and the repeated underuse4 of highly effective medications and especially of proven preventive measures that are not pharmacological and hence not vigorously promoted by the large pharmaceutical companies.

The seed for this heresy was sown by the fable, and it colored my clinical life with a vein of skepticism and self‐criticism. Slowly it also grew into a long‐term commitment to teaching about and research on avoidable pitfalls in patient care.5

Thus, Lacombe's little piece often comes back to me, teaching me that a fairy tale can sometimes be more powerful than a randomized controlled study of 10,000 patients.

References
  1. LaCombe M.In a stew.Am J Med.1991;91:276278.
  2. Schattner A,Zimhony O,Avidor B,Giladi M.Asking the right question.Lancet.2003;361:1786.
  3. Schattner A.Down the cascade.Br Med J.2004;329:678.
  4. Woolf SH.The need for perspective in evidence‐based medicine.JAMA.1999;282:23582365.
  5. Schattner A,Fletcher RH.Pearls and pitfalls in patient care: the need to revive traditional clinical values.Am J Med Sci.2004;327:7985.
References
  1. LaCombe M.In a stew.Am J Med.1991;91:276278.
  2. Schattner A,Zimhony O,Avidor B,Giladi M.Asking the right question.Lancet.2003;361:1786.
  3. Schattner A.Down the cascade.Br Med J.2004;329:678.
  4. Woolf SH.The need for perspective in evidence‐based medicine.JAMA.1999;282:23582365.
  5. Schattner A,Fletcher RH.Pearls and pitfalls in patient care: the need to revive traditional clinical values.Am J Med Sci.2004;327:7985.
Issue
Journal of Hospital Medicine - 1(4)
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Journal of Hospital Medicine - 1(4)
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267-268
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A tasty stew: A tale that changed my practice
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Physician Attitudes and Use of Computerized Order Entry

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Physician characteristics, attitudes, and use of computerized order entry

It is widely acknowledged that the U.S. health care system is plagued by error and inefficiency and that these factors contribute to as many as 44,000‐98,000 deaths each year in U.S. hospitals. In To Err Is Human: Building a Safer Health System, the Institute of Medicine1 outlined the critical role that information technology can play in improving patient safety and highlighted computerized physician order entry (CPOE) systems for their potential to reduce the frequency of medication errors and to improve the quality of medical care.

Computerized physician order entry systems are specialized software applications that allow physicians to place orders directly into a computer. This process has a number of potential advantages over traditional handwritten ordering, including the ability to structure the ordering process to ensure the completeness of individual orders, to provide clinical decision support through diagnosis‐based order sets, and to automatically check orders for potential drugallergy, drugdrug, and drugfood interactions.2 Finally, entering orders directly into a computer eliminates the problem of transcription‐related errors that stem from the difficulty of interpreting handwriting. In clinical trials, the introduction of CPOE has been shown to reduce the frequency of medication errors, to improve the use of preventive services, and to reduce costs.36 Recognition of the benefits of these systems has not been confined to the medical community. The Leapfrog Organization, a coalition of large businesses in the United States, has chosen CPOE as one of its 3 initial safety leaps and has established a threshold that 70% of medication orders should be entered directly by physicians.7

Although the benefits of CPOE systems are widely recognized, few hospitals have implemented these systems successfully.8, 9 Those that have, have often developed the applications internally, and many have relied on house staff to do most or all of the actual ordering.10 However, most hospitals do not have the expertise for internal development and instead rely on commercially available products. Moreover, most patients hospitalized in the United States are cared for by attending physicians working without the assistance of house staff.11 In light of the importance of successfully implementing CPOE systems in such settings, we assessed the adoption of CPOE by attending physicians at 2 community hospitals where its use was voluntary and examined the characteristics and attitudes associated with use of the system to place orders.

METHODS

Setting and Participants

Baystate Medical Center is a 600‐bed teaching hospital in Springfield, Massachusetts, where approximately 50% of patients are cared for with the assistance of house staff. Franklin Medical Center is a 125‐bed community hospital in rural Greenfield, Massachusetts, and is not a house staff training site. Medical staff membership at the 2 hospitals is largely voluntary. Both institutions share a vendor‐supplied computerized order entry system that was implemented in the early 1990s (E7000, Eclipsys Corporation, Boca Raton, FL). The system provides a structured format for the creation of medication, laboratory, and radiology orders and contains thousands of preconstructed medication order sentences and hundreds of order sets designed to standardize ordering for common diagnoses and procedures. Pharmacists are alerted of potential drugallergy and drugdrug interactions and use clinical judgment about whether to communicate this information to the physician. Although the house staff at Baystate Medical Center is mandated to place orders in the system, attending physicians have no such requirement at either institution. Access to the system is provided though the many fixed workstations located on nursing units, in operating rooms, and in the health sciences library. On a typical medical‐surgical patient care unit most computers are behind the nurses' station, though some are distributed along hallways and in physician charting rooms. No computers are in patient rooms. Although the number varies slightly across units, the average ratio of computers to patient beds is roughly 1 to 1.

Survey

In June 2003 we mailed a 20‐item survey to attending physicians who had been responsible for a minimum of 25 orders during the preceding month at either Baystate or Franklin Medical Center. Orders counted toward this minimum if they had been written, given verbally in person or by phone, or entered directly into the computer by the physician. The survey consisted of 20 questions focused on the topic of computerized order entry. In addition to collecting information about sex and specialty, we asked respondents to describe their use of CPOE during training, their use of computers at home, and, where applicable, their use of computers in their outpatient practices. The survey included questions about how often respondents used the order entry system when caring for hospitalized patients and which features of the system they used. To assess physician attitudes about the order entry process, we asked respondents to consider whether it was faster to place orders directly into the system than it was by handwriting them, whether orders placed in the system were carried out more rapidly, whether placing orders in the system led to fewer medication and other errors, whether order sets were important for the efficient use of the system, whether order sets helped to ensure that important aspects of care did not slip through the cracks, whether the system's user interface supported their work flow, and whether the encouragement of nurses was an important factor in their use of the system. Questions that assessed physician attitudes were presented on a 5‐point Likert scale. Nonrespondents were sent reminder letters along with duplicate surveys twice, approximately 1 and 2 months after the initial mailing. No financial incentive was offered for participation. The study protocol was approved by the Institutional Review Board of Baystate Health System.

Order Entry Rates

Regardless of whether an order is placed directly by a physician into a computer, given verbally, or handwritten, all orders are ultimately entered into the CPOE system. Working with our hospitals' Departments of Information Services, we developed a report that provided physician‐specific information about order entry patterns. For each physician in the study, we determined the total number of orders generated during the month preceding the initial June mailing, as well as the absolute number and percentage of orders of each of the following categories: directly entered, telephone, verbal, and written. Because verbal and telephone orders are required during urgent situations and when physicians give orders from outside the hospital, we calculated and report an adjusted order entry rate as the total number of orders placed directly into the system divided by the sum of the orders entered directly and the number of written orders.

Analysis

Summary statistics for the overall sample were constructed using simple frequencies and proportions for categorical variables and medians and interquartile ranges for continuous variables. We compared characteristics of respondents from the 2 hospitals using chi‐square tests of association for categorical factors and Wilcoxon rank‐sum tests for continuous scale data. We compared the total number of orders placed during the study month and the order entry rates of responders and nonresponders using the Wilcoxon rank‐sum test. We categorized physicians as low (20%), intermediate (21%‐79%), and high (80%) users of the system based on their calculated order entry rate. Responses to each of the attitude questions in the survey were tabulated, and the responses strongly agree and agree were combined for analyses comparing responses. Demographic variables and physician attitudes were tested for associations with order entry rate categories via the Pearson chi‐square for categorical factors, the Mantel‐Haenszel chi‐square for ordered factors, and Kruskal‐Wallis analysis of variance for continuous variables. Initial analyses were stratified by hospital; where no differences in association were found across strata, the data were combined. Statistical tests were performed using SAS version 9.1 (SAS Institute, Cary, NC)

RESULTS

During the study period the target group of physicians placed a total of 135,692 orders, of which 69,654 (51%) were placed directly into the CPOE system, 38,878 (29%) were made using pen and paper, 7,208 (5%) were made verbally, and 19,952 (15%) were placed by telephone. Three hundred and fifty‐six (71%) of the 502 surveys sent out to physicians at the 2 hospitals were returned. Thirteen surveys were excluded from analysis because the respondent was not a physician, and 2 because we were unable to match the survey to system usage data, leaving a total of 341 surveys for analysis. Order entry rates were not computed for an additional 3 physicians who only placed verbal and telephone orders during the study period. Response rates did not differ by clinician specialty (P = .53); compared to those of nonresponders, respondents had a similar median total number of orders (111 vs. 101, P = .67) and a higher median order entry rate (66% vs. 48%, P = .03).

Characteristics of Respondents

Seventy‐two percent of physicians who completed the survey were men; half had graduated from medical school at least 20 years ago, and the median duration of practice at the study institution was 11 years (Table 1). Forty percent practiced internal medicine, 18% were surgeons, and 16% were pediatricians. Thirty‐five percent completed training at an institution that had computerized physician order entry, and 86% cared for patients primarily at Baystate Medical Center. More than half reported they used the system many times each day for patient care, and the features they used most commonly were retrieval of results (95%), placing of orders (78%), and viewing and printing of patient lists (75%). Among those with outpatient practices, 81% used computers in their outpatient practice, and more than half used computers for personal activities at home at least once a day. On average, respondents from Franklin Medical Center had graduated from medical school farther in the past and reported less reliance on the system to carry out all activities other than viewing results.

Characteristics of Physicians Participating in the Study (N = 341)
 Overall n (%)Baystate n (%) 293 (85.9)Franklin n (%) 48 (14.1)Chi square P value
  • From survey responses.

  • CPOE rate = (orders directly entered)/(orders directly entered + orders placed in writing).

  • Data of actual use during month preceding survey mailing.

Sex   .64
Male244 (71.6)211 (72.0)33 (68.8) 
Specialty   .24
Anesthesia23 (6.7)23 (7.9)0 (0.0) 
Internal medicine135 (39.6)112 (38.2)23 (47.9) 
Medicine/pediatrics13 (3.8)6 (2.0)7 (14.6) 
OB/GYN36 (10.6)30 (10.2)6 (12.5) 
Pediatrics54 (15.8)51 (17.4)3 (6.3) 
Surgery61 (17.9)55 (18.8)6 (12.5) 
Other19 (5.6)16 (5.5)3 (6.3) 
Use of CPOE systema   .09
Many times a day176 (52.2)160 (55.0)16 (34.8) 
At least once a day77 (22.9)61 (21.0)16 (34.8) 
A few times a week55 (16.3)45 (15.5)10 (21.7) 
Once a week or less29 (8.6)25 (8.6)4 (8.7) 
Features useda    
Viewing and printing patient lists254 (75.2)212 (72.6)42 (91.3).01
Looking up results320 (94.7)277 (94.9)43 (93.5).70
Viewing current medications218 (64.5)204 (69.9)14 (30.4)< .01
Placing orders263 (77.8)244 (83.6)19 (41.3)< .01
Entering discharge summaries72 (21.3)70 (24.0)2 (4.4)< .01
Use of order setsa    
Rarely or never98 (29.0)74 (25.3)24 (52.2)< .01
Minority of patients92 (27.2)78 (26.7)14 (30.4) 
Majority of patients104 (30.8)97 (33.2)7 (15.2) 
For all or nearly all patients44 (13.0)43 (14.7)1 (2.2) 
Percentage of orders placed using order setsa   < .01
None46 (13.7)26 (9.0)20 (44.4) 
1%‐25%62 (18.5)50 (17.2)12 (26.7) 
26%‐50%29 (8.7)23 (7.9)6 (13.3) 
51%‐75%45 (13.4)43 (14.9)2 (4.4) 
76%‐99%103 (30.8)98 (33.8)5 (11.1) 
All50 (14.9)50 (17.2)0 (0.0) 
Use of computer in outpatient practiceab243 (81.3)206 (80.8)37 (84.1).60
Personal computer usea   .47
At least once a day209 (61.7)185 (63.4)24 (51.1) 
Several times a week84 (24.8)67 (23.0)17 (36.2) 
A few times a month21 (6.2)18 (6.2)3 (6.4) 
Rarely25 (7.4)22 (7.5)3 (6.4) 
Training at an institution that had CPOE117 (34.7)105 (36.1)12 (26.1)0.19
Use of system to enter orders should be mandatorya    
Yes113 (35.2)106 (38.4)7 (15.6)<.01
 Median (IQR)Median (IQR)Median (IQR)WilcoxonPvalue
Years since medical school graduationa20 (13, 26)20 (13, 26)24 (17, 28).02
Years in practice at study institutiona11 (5, 18)11 (5, 18)13 (7, 19).39
Orders directly enteredc23 (2, 99)27 (5, 108)1 (0, 27)< .01
Orders placed by telephonec14 (5, 49)12 (3, 38)49.5 (16, 123.5)< .01
Orders placed verballyc2 (0, 11)3 (0, 13)1 (0,3)< .01
Orders placed in writingc21 (4, 73)14 (3, 45)220 (106.5, 391)< .01
CPOE ratebc66% (3%, 94%)76% (19%, 96%)0.25% (0%, 17%)< .01

Attitudes Toward Computerized Physician Order Entry

Physicians who completed the survey offered diverse opinions about the impact of computerized order entry on work flow, patient safety, and quality of care. Only 22% believed the system's user interface supported their work flow (Q7), 34% believed it was faster to enter orders directly into the system than to handwrite them (Q1), and 41% believed orders placed into the system were carried out more rapidly (Q2) (Table 2). On the other hand, 63% of respondents believed that placing orders directly into the system led to fewer medication errors (Q3), and 51% stated the system generally reduced medical errors (Q4). Sixty‐nine percent stated order sets were important for efficient use of the system (Q5), and 71% believed order sets served an important decision support role (Q6). Twenty‐six percent stated that the encouragement of nurses was an important factor in their use of the system (Q8). Finally, 35% of attending physicians believed use of the system to place orders should be mandatory.

Attitudes of Respondents (N = 341) to Computerized Physician Order Entry

Characteristics and Attitudes of High, Intermediate, and Low Users

The median order entry rate of respondents was 66%. One hundred and forty‐one (42%) placed at least 80% of their orders directly into the system, whereas 109 (32%) placed no more than 20% of their orders directly in the system (Fig. 1). There was not a significant difference between the low, intermediate, and high use groups in the total number of orders that each physician placed during the study period (Table 3). Sex, years since graduation from medical school, years in practice at the study institution, and use of computers in the outpatient setting were not meaningfully different between the 3 categories of users (Table 3). On the other hand, medical specialty was strongly associated with use of the system, with anesthesiologists, pediatricians, and surgeons the specialties with the largest proportion of high users. Furthermore, physicians who were trained in a CPOE environment and those who reported daily use of computers for personal activities showed the highest levels of adoption. Physicians at Franklin Medical Center showed lower levels of order entry than their counterparts at Baystate.

Figure 1
Distribution of direct order entry rate among clinicians responding to survey.
Characteristics of Survey Respondents (n=338) with Written and/or Direct Entry Orders in Month Preceding Survey according to Low, Intermediate, and High Usage of a CPOE System
 Low (20%) n (row %)Intermediate (20%‐79%) n (row %)High (80%) n (row %)P value
  • Among n = 299 with outpatient practice.

  • Because of missing survey responses, category values may not add up to total.

  • Pearson chi‐square P value.

  • Mantel‐Haenszel chi‐square P value.

  • Kruskal‐Wallis P value

 n = 109n = 88n = 141 
Hospital   < .01c
Baystate73 (25)79 (27)138 (48) 
Franklin36 (75)9 (19)3 (6) 
Sex   .69c
Female28 (29)24 (25)43 (45) 
Male81 (33)64 (26)98 (40) 
Specialty   .0001c
Anesthesia8 (35)3 (13)12 (52) 
Internal medicine45 (33)37 (27)53 (39) 
Medicine/pediatrics6 (46)5 (38)2 (15) 
OB/GYN20 (56)12 (33)4 (11) 
Pediatrics13 (24)9 (17)32 (59) 
Surgery14 (23)21 (34)26 (43) 
Other3 (19)1 (6)12 (75) 
Do you use a computer in your outpatient practice?a
Yes75 (31)61 (25)105 (44).22c
No20 (36)18 (33)17 (31) 
Level of personal computer useb   .045d
Rarely11 (44)8 (32)6 (24) 
A few times a month7 (33)4 (19)10 (48) 
Several times a week28 (35)25 (31)28 (35) 
At least once a day62 (30)50 (24)97 (46) 
Training at an institution that had CPOE   .037c
Yes30 (26)40 (34)46 (40) 
No76 (35)48 (22)94 (43) 
 Median (IQR)Median (IQR)Median (IQR) 
Years since graduation from medical school21 (16, 28)18 (14, 25)19 (12, 25).06e
Years in practice at study institution12 (5, 19)12 (6, 19)12 (6, 17).84e
Total number of orders placed112 (45, 306)105 (56, 254)113 (44, 382).92e

Use of the system was highly associated with physician attitudes toward CPOE, with the views of intermediate and high users consistently different than those of low users (Fig. 2). The associations found held true regardless of hospital: low, intermediate, and high users from Franklin had similar responses to those from Baystate (P > .05 for all questions), and the data from the 2 hospitals therefore were combined for presentation. Although few physicians believed that the user interface of the system supported their work flow, high and intermediate users were 3 times as likely to share this view than were low users (Q7; Fig. 2). Similarly, 19% of low users, 31% of intermediate users, and 45% of high users believed that entering orders into the system was faster than writing orders (Q1). High and intermediate users of the system were more likely than low users to believe that orders entered into the system were carried out more rapidly (Q2) and led to fewer medication (Q3) and nonmedication (Q4) errors. Regardless of their utilization pattern, most physicians believed that order sets played an important role in promoting efficiency and quality.

Figure 2
Attitudes of low‐, intermediate‐, and high‐use users of a computerized physician order entry system.

DISCUSSION

In this study of the clinical computing practices of physicians at 2 community hospitals, we observed wide variation in the adoption of CPOE by individual attendings. Although roughly one‐third rarely placed orders directly into the system, 42% had an order entry rate of at least 80%. Contrary to our initial expectation, we found little association between a physician's order entry rate with years in practice, duration of exposure to CPOE, or use of computers in the outpatient setting. On the other hand, we observed marked differences in use of the CPOE system across specialty lines and found that physicians who were exposed to CPOE during training and those who were regular users of computers for personal activities were more likely to embrace this technology. Further, we observed important differences between physicians who used the system to place some or most of their orders and those who did so only rarely in their beliefs and attitudes about the impact and benefits of CPOE. Physicians with higher order entry rates were more likely than their colleagues to believe that placing orders electronically was faster than handwriting and that use of the system led to fewer medical errors. These findings should be encouraging to hospitals hoping to implement CPOE because they suggest that successful adoption of CPOE is not limited to physicians who have just completed their residencies or to hospitals with the capability of designing and building their own systems. On the contrary, we documented that women, older physicians, and those with limited CPOE experience were as likely to be frequent users, especially if they perceived CPOE to be safer than handwriting and if they believed the user interface supported the efficient entering of orders.

On the basis of these results we recommend that in addition to purchasing systems that meet physician work‐flow needs and support the efficient entry of orders, hospital leaders should emphasize the quality and safety benefits of CPOE as part of a comprehensive change management strategy. The differences we observed in order entry rates across specialties may have resulted from several factors, including inherent differences in personality type associated with choice of specialty and in the level of customization of a system reflected in which and how many order sets are included. Such findings suggest that when it comes to CPOE, one size does not fit all, and implementation planning should be carried out at the specialty level. Finally, our observation that physicians who had exposure to CPOE during training were more likely to use the system to place orders suggests that the nation's training institutions will play an important role in fostering universal adoption of this technology.

Several earlier studies have reported on physician experiences with CPOE systems. Murff and Kannry12 surveyed 94 internal medicine house staff to compare experiences with 2 CPOE systems: the Department of Veterans Affairs Computerized Patient Record System (CPRS) and a commercially available product. They found striking differences in user satisfaction with numerous aspects of the systems, however they did not address attitudes toward safety or quality, and because house staff were required to place orders electronically they were unable to correlate responses with actual usage patterns. Weiner et al.13 compared the opinions of internal medicine house staff, attendings, fellows, and nurses about the benefits and challenges of using a computerized provider order entry system. In contrast to the findings from our study, Weiner et al. reported that more than half of physicians believed that provider order entry led to a greater number of errors, and only a minority believed the system increased quality of care overall. Finally, Lee et al.14 surveyed medical and surgical house officers and nurses at a large academic medical center about their satisfaction with a locally developed order entry system. They found that attitudes about the impact of the system on productivity and ease of use were more strongly associated with overall satisfaction than having undergone training or experience with personal computers. These findings are congruous with our own observation that beliefs about the speed with which orders are placed are closely associated with actual use of the system. They reported, as have we, that physicians placed a high value on order sets.

Our study had a number of strengths. First, we were able to offer insight into the attitudes and behaviors of a previously neglected, but critically important groupattending physicians who care for patients at community hospitals without the assistance of house staff. Second, whereas previous studies primarily assessed physician satisfaction with CPOE, we explored how physician attitudes about the impact of CPOE on work flow and on safety were associated with actual ordering habits. Information about ordering was obtained directly from the order entry system and not through self‐report. We conducted the study at 2 hospitals, a large urban community teaching hospital and a smaller rural hospital, and focused on a CPOE system that is in use at many institutions throughout the country, thereby increasing the generalizability of our findings. Although adoption of the system by physicians at the 2 hospitals differed, factors that associated with the use of CPOE to place orders were similar. Finally, we surveyed a large number of physicians, had a high response rate, and found only small differences in the utilization patterns of responders and nonresponders, suggesting that our portrayal of the attitudes of physicians was representative of the views of physicians practicing in our community.

The study had a number of weaknesses. First, we cannot be sure whether preexisting beliefs about the benefits of CPOE directly influenced physicians' use of the system or, conversely, if these attitudes developed in response to experience as users. Nevertheless, it seems practical to suggest that hospitals focus on purchasing systems that support the efficient entering of orders while simultaneously adopting a communication and change management strategy that emphasizes the safety and quality benefits of CPOE more broadly. Second, we did not attempt to validate the opinions expressed by physicians about the usability or safety benefits of the system. That said, the purpose of the study was to determine whether physician attitudes toward these issues was associated with the use of the system to place orders. Whether or not this particular CPOE system actually prevented medication errors, most physicians believed it did, a belief strongly associated with the observed order entry rates. Third, we studied a single CPOE system implemented approximately 10 years ago that does not reflect state‐of‐the‐art user interface design or functionality. Nevertheless, our observation about the importance of the user experience is probably no less relevant today. Fourth, we were unable to ascertain every order given by physicians, as some so‐called MD to RN orders may never have made it into the system. Finally, there is a small risk that some written, telephone, and verbal orders may have been randomly or systematically assigned to incorrect physicians, which would have led us to calculate inaccurate utilization rates.

CONCLUSIONS

In a voluntary community hospital environment the adoption of CPOE by attending physicians varies widely. While placing a premium on the purchase of systems that meet the work‐flow needs of physicians and support the efficient entry of orders, hospital leaders can enhance physician adoption of this technology by communicating the role of CPOE in improving quality and safety.

Acknowledgements

The authors thank Gilad Kuperman, MD, PhD, for his thoughtful comments on an earlier version of the manuscript.

References
  1. Kohn LT,Corrigan JM,Donaldson MS, eds.To Err Is Human: Building a Safer Health System.Washington, DC:National Academy Press,2000.
  2. Kuperman GJ,Gibson RF.Computer physician order entry: benefits, costs, and issues.Ann Intern Med.2003;139:3139.
  3. Bates DW,Leape LL,Cullen DJ, et al.Effect of computerized physician order entry and a team intervention on prevention of serious medication errors.JAMA.1998;280:13111316.
  4. Dexter PR,Perkins S,Overhage JM,Maharry K,Kohler RB,McDonald CJ.A computerized reminder system to increase the use of preventive care for hospitalized patients.N Engl J Med.2001;345:965970.
  5. Overhage JM,Tierney WM,Zhou XH,McDonald CJ.A randomized trial of “corollary orders” to prevent errors of omission.J Am Med Inform Assoc.1997;4:364375.
  6. Evans RS,Pestotnik SL,Classen DC, et al.A computer‐assisted management program for antibiotics and other antiinfective agents.N Engl J Med.1998;338:232238.
  7. The Leapfrog Group. Patient Safety Fact Sheet. Available at: http://www.leapfroggroup.org/FactSheets/LF_FactSheet.pdf. Accessed October 6,2004.
  8. Ash JS,Gorman PN,Seshadri V,Hersh WR.Computerized physician order entry in U.S. hospitals: results of a 2002 survey.J Am Med Inform Assoc.2004;11:9599.
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Article PDF
Issue
Journal of Hospital Medicine - 1(4)
Page Number
221-230
Legacy Keywords
CPOE, computers in medicine, patient safety, errors in medicine
Sections
Article PDF
Article PDF

It is widely acknowledged that the U.S. health care system is plagued by error and inefficiency and that these factors contribute to as many as 44,000‐98,000 deaths each year in U.S. hospitals. In To Err Is Human: Building a Safer Health System, the Institute of Medicine1 outlined the critical role that information technology can play in improving patient safety and highlighted computerized physician order entry (CPOE) systems for their potential to reduce the frequency of medication errors and to improve the quality of medical care.

Computerized physician order entry systems are specialized software applications that allow physicians to place orders directly into a computer. This process has a number of potential advantages over traditional handwritten ordering, including the ability to structure the ordering process to ensure the completeness of individual orders, to provide clinical decision support through diagnosis‐based order sets, and to automatically check orders for potential drugallergy, drugdrug, and drugfood interactions.2 Finally, entering orders directly into a computer eliminates the problem of transcription‐related errors that stem from the difficulty of interpreting handwriting. In clinical trials, the introduction of CPOE has been shown to reduce the frequency of medication errors, to improve the use of preventive services, and to reduce costs.36 Recognition of the benefits of these systems has not been confined to the medical community. The Leapfrog Organization, a coalition of large businesses in the United States, has chosen CPOE as one of its 3 initial safety leaps and has established a threshold that 70% of medication orders should be entered directly by physicians.7

Although the benefits of CPOE systems are widely recognized, few hospitals have implemented these systems successfully.8, 9 Those that have, have often developed the applications internally, and many have relied on house staff to do most or all of the actual ordering.10 However, most hospitals do not have the expertise for internal development and instead rely on commercially available products. Moreover, most patients hospitalized in the United States are cared for by attending physicians working without the assistance of house staff.11 In light of the importance of successfully implementing CPOE systems in such settings, we assessed the adoption of CPOE by attending physicians at 2 community hospitals where its use was voluntary and examined the characteristics and attitudes associated with use of the system to place orders.

METHODS

Setting and Participants

Baystate Medical Center is a 600‐bed teaching hospital in Springfield, Massachusetts, where approximately 50% of patients are cared for with the assistance of house staff. Franklin Medical Center is a 125‐bed community hospital in rural Greenfield, Massachusetts, and is not a house staff training site. Medical staff membership at the 2 hospitals is largely voluntary. Both institutions share a vendor‐supplied computerized order entry system that was implemented in the early 1990s (E7000, Eclipsys Corporation, Boca Raton, FL). The system provides a structured format for the creation of medication, laboratory, and radiology orders and contains thousands of preconstructed medication order sentences and hundreds of order sets designed to standardize ordering for common diagnoses and procedures. Pharmacists are alerted of potential drugallergy and drugdrug interactions and use clinical judgment about whether to communicate this information to the physician. Although the house staff at Baystate Medical Center is mandated to place orders in the system, attending physicians have no such requirement at either institution. Access to the system is provided though the many fixed workstations located on nursing units, in operating rooms, and in the health sciences library. On a typical medical‐surgical patient care unit most computers are behind the nurses' station, though some are distributed along hallways and in physician charting rooms. No computers are in patient rooms. Although the number varies slightly across units, the average ratio of computers to patient beds is roughly 1 to 1.

Survey

In June 2003 we mailed a 20‐item survey to attending physicians who had been responsible for a minimum of 25 orders during the preceding month at either Baystate or Franklin Medical Center. Orders counted toward this minimum if they had been written, given verbally in person or by phone, or entered directly into the computer by the physician. The survey consisted of 20 questions focused on the topic of computerized order entry. In addition to collecting information about sex and specialty, we asked respondents to describe their use of CPOE during training, their use of computers at home, and, where applicable, their use of computers in their outpatient practices. The survey included questions about how often respondents used the order entry system when caring for hospitalized patients and which features of the system they used. To assess physician attitudes about the order entry process, we asked respondents to consider whether it was faster to place orders directly into the system than it was by handwriting them, whether orders placed in the system were carried out more rapidly, whether placing orders in the system led to fewer medication and other errors, whether order sets were important for the efficient use of the system, whether order sets helped to ensure that important aspects of care did not slip through the cracks, whether the system's user interface supported their work flow, and whether the encouragement of nurses was an important factor in their use of the system. Questions that assessed physician attitudes were presented on a 5‐point Likert scale. Nonrespondents were sent reminder letters along with duplicate surveys twice, approximately 1 and 2 months after the initial mailing. No financial incentive was offered for participation. The study protocol was approved by the Institutional Review Board of Baystate Health System.

Order Entry Rates

Regardless of whether an order is placed directly by a physician into a computer, given verbally, or handwritten, all orders are ultimately entered into the CPOE system. Working with our hospitals' Departments of Information Services, we developed a report that provided physician‐specific information about order entry patterns. For each physician in the study, we determined the total number of orders generated during the month preceding the initial June mailing, as well as the absolute number and percentage of orders of each of the following categories: directly entered, telephone, verbal, and written. Because verbal and telephone orders are required during urgent situations and when physicians give orders from outside the hospital, we calculated and report an adjusted order entry rate as the total number of orders placed directly into the system divided by the sum of the orders entered directly and the number of written orders.

Analysis

Summary statistics for the overall sample were constructed using simple frequencies and proportions for categorical variables and medians and interquartile ranges for continuous variables. We compared characteristics of respondents from the 2 hospitals using chi‐square tests of association for categorical factors and Wilcoxon rank‐sum tests for continuous scale data. We compared the total number of orders placed during the study month and the order entry rates of responders and nonresponders using the Wilcoxon rank‐sum test. We categorized physicians as low (20%), intermediate (21%‐79%), and high (80%) users of the system based on their calculated order entry rate. Responses to each of the attitude questions in the survey were tabulated, and the responses strongly agree and agree were combined for analyses comparing responses. Demographic variables and physician attitudes were tested for associations with order entry rate categories via the Pearson chi‐square for categorical factors, the Mantel‐Haenszel chi‐square for ordered factors, and Kruskal‐Wallis analysis of variance for continuous variables. Initial analyses were stratified by hospital; where no differences in association were found across strata, the data were combined. Statistical tests were performed using SAS version 9.1 (SAS Institute, Cary, NC)

RESULTS

During the study period the target group of physicians placed a total of 135,692 orders, of which 69,654 (51%) were placed directly into the CPOE system, 38,878 (29%) were made using pen and paper, 7,208 (5%) were made verbally, and 19,952 (15%) were placed by telephone. Three hundred and fifty‐six (71%) of the 502 surveys sent out to physicians at the 2 hospitals were returned. Thirteen surveys were excluded from analysis because the respondent was not a physician, and 2 because we were unable to match the survey to system usage data, leaving a total of 341 surveys for analysis. Order entry rates were not computed for an additional 3 physicians who only placed verbal and telephone orders during the study period. Response rates did not differ by clinician specialty (P = .53); compared to those of nonresponders, respondents had a similar median total number of orders (111 vs. 101, P = .67) and a higher median order entry rate (66% vs. 48%, P = .03).

Characteristics of Respondents

Seventy‐two percent of physicians who completed the survey were men; half had graduated from medical school at least 20 years ago, and the median duration of practice at the study institution was 11 years (Table 1). Forty percent practiced internal medicine, 18% were surgeons, and 16% were pediatricians. Thirty‐five percent completed training at an institution that had computerized physician order entry, and 86% cared for patients primarily at Baystate Medical Center. More than half reported they used the system many times each day for patient care, and the features they used most commonly were retrieval of results (95%), placing of orders (78%), and viewing and printing of patient lists (75%). Among those with outpatient practices, 81% used computers in their outpatient practice, and more than half used computers for personal activities at home at least once a day. On average, respondents from Franklin Medical Center had graduated from medical school farther in the past and reported less reliance on the system to carry out all activities other than viewing results.

Characteristics of Physicians Participating in the Study (N = 341)
 Overall n (%)Baystate n (%) 293 (85.9)Franklin n (%) 48 (14.1)Chi square P value
  • From survey responses.

  • CPOE rate = (orders directly entered)/(orders directly entered + orders placed in writing).

  • Data of actual use during month preceding survey mailing.

Sex   .64
Male244 (71.6)211 (72.0)33 (68.8) 
Specialty   .24
Anesthesia23 (6.7)23 (7.9)0 (0.0) 
Internal medicine135 (39.6)112 (38.2)23 (47.9) 
Medicine/pediatrics13 (3.8)6 (2.0)7 (14.6) 
OB/GYN36 (10.6)30 (10.2)6 (12.5) 
Pediatrics54 (15.8)51 (17.4)3 (6.3) 
Surgery61 (17.9)55 (18.8)6 (12.5) 
Other19 (5.6)16 (5.5)3 (6.3) 
Use of CPOE systema   .09
Many times a day176 (52.2)160 (55.0)16 (34.8) 
At least once a day77 (22.9)61 (21.0)16 (34.8) 
A few times a week55 (16.3)45 (15.5)10 (21.7) 
Once a week or less29 (8.6)25 (8.6)4 (8.7) 
Features useda    
Viewing and printing patient lists254 (75.2)212 (72.6)42 (91.3).01
Looking up results320 (94.7)277 (94.9)43 (93.5).70
Viewing current medications218 (64.5)204 (69.9)14 (30.4)< .01
Placing orders263 (77.8)244 (83.6)19 (41.3)< .01
Entering discharge summaries72 (21.3)70 (24.0)2 (4.4)< .01
Use of order setsa    
Rarely or never98 (29.0)74 (25.3)24 (52.2)< .01
Minority of patients92 (27.2)78 (26.7)14 (30.4) 
Majority of patients104 (30.8)97 (33.2)7 (15.2) 
For all or nearly all patients44 (13.0)43 (14.7)1 (2.2) 
Percentage of orders placed using order setsa   < .01
None46 (13.7)26 (9.0)20 (44.4) 
1%‐25%62 (18.5)50 (17.2)12 (26.7) 
26%‐50%29 (8.7)23 (7.9)6 (13.3) 
51%‐75%45 (13.4)43 (14.9)2 (4.4) 
76%‐99%103 (30.8)98 (33.8)5 (11.1) 
All50 (14.9)50 (17.2)0 (0.0) 
Use of computer in outpatient practiceab243 (81.3)206 (80.8)37 (84.1).60
Personal computer usea   .47
At least once a day209 (61.7)185 (63.4)24 (51.1) 
Several times a week84 (24.8)67 (23.0)17 (36.2) 
A few times a month21 (6.2)18 (6.2)3 (6.4) 
Rarely25 (7.4)22 (7.5)3 (6.4) 
Training at an institution that had CPOE117 (34.7)105 (36.1)12 (26.1)0.19
Use of system to enter orders should be mandatorya    
Yes113 (35.2)106 (38.4)7 (15.6)<.01
 Median (IQR)Median (IQR)Median (IQR)WilcoxonPvalue
Years since medical school graduationa20 (13, 26)20 (13, 26)24 (17, 28).02
Years in practice at study institutiona11 (5, 18)11 (5, 18)13 (7, 19).39
Orders directly enteredc23 (2, 99)27 (5, 108)1 (0, 27)< .01
Orders placed by telephonec14 (5, 49)12 (3, 38)49.5 (16, 123.5)< .01
Orders placed verballyc2 (0, 11)3 (0, 13)1 (0,3)< .01
Orders placed in writingc21 (4, 73)14 (3, 45)220 (106.5, 391)< .01
CPOE ratebc66% (3%, 94%)76% (19%, 96%)0.25% (0%, 17%)< .01

Attitudes Toward Computerized Physician Order Entry

Physicians who completed the survey offered diverse opinions about the impact of computerized order entry on work flow, patient safety, and quality of care. Only 22% believed the system's user interface supported their work flow (Q7), 34% believed it was faster to enter orders directly into the system than to handwrite them (Q1), and 41% believed orders placed into the system were carried out more rapidly (Q2) (Table 2). On the other hand, 63% of respondents believed that placing orders directly into the system led to fewer medication errors (Q3), and 51% stated the system generally reduced medical errors (Q4). Sixty‐nine percent stated order sets were important for efficient use of the system (Q5), and 71% believed order sets served an important decision support role (Q6). Twenty‐six percent stated that the encouragement of nurses was an important factor in their use of the system (Q8). Finally, 35% of attending physicians believed use of the system to place orders should be mandatory.

Attitudes of Respondents (N = 341) to Computerized Physician Order Entry

Characteristics and Attitudes of High, Intermediate, and Low Users

The median order entry rate of respondents was 66%. One hundred and forty‐one (42%) placed at least 80% of their orders directly into the system, whereas 109 (32%) placed no more than 20% of their orders directly in the system (Fig. 1). There was not a significant difference between the low, intermediate, and high use groups in the total number of orders that each physician placed during the study period (Table 3). Sex, years since graduation from medical school, years in practice at the study institution, and use of computers in the outpatient setting were not meaningfully different between the 3 categories of users (Table 3). On the other hand, medical specialty was strongly associated with use of the system, with anesthesiologists, pediatricians, and surgeons the specialties with the largest proportion of high users. Furthermore, physicians who were trained in a CPOE environment and those who reported daily use of computers for personal activities showed the highest levels of adoption. Physicians at Franklin Medical Center showed lower levels of order entry than their counterparts at Baystate.

Figure 1
Distribution of direct order entry rate among clinicians responding to survey.
Characteristics of Survey Respondents (n=338) with Written and/or Direct Entry Orders in Month Preceding Survey according to Low, Intermediate, and High Usage of a CPOE System
 Low (20%) n (row %)Intermediate (20%‐79%) n (row %)High (80%) n (row %)P value
  • Among n = 299 with outpatient practice.

  • Because of missing survey responses, category values may not add up to total.

  • Pearson chi‐square P value.

  • Mantel‐Haenszel chi‐square P value.

  • Kruskal‐Wallis P value

 n = 109n = 88n = 141 
Hospital   < .01c
Baystate73 (25)79 (27)138 (48) 
Franklin36 (75)9 (19)3 (6) 
Sex   .69c
Female28 (29)24 (25)43 (45) 
Male81 (33)64 (26)98 (40) 
Specialty   .0001c
Anesthesia8 (35)3 (13)12 (52) 
Internal medicine45 (33)37 (27)53 (39) 
Medicine/pediatrics6 (46)5 (38)2 (15) 
OB/GYN20 (56)12 (33)4 (11) 
Pediatrics13 (24)9 (17)32 (59) 
Surgery14 (23)21 (34)26 (43) 
Other3 (19)1 (6)12 (75) 
Do you use a computer in your outpatient practice?a
Yes75 (31)61 (25)105 (44).22c
No20 (36)18 (33)17 (31) 
Level of personal computer useb   .045d
Rarely11 (44)8 (32)6 (24) 
A few times a month7 (33)4 (19)10 (48) 
Several times a week28 (35)25 (31)28 (35) 
At least once a day62 (30)50 (24)97 (46) 
Training at an institution that had CPOE   .037c
Yes30 (26)40 (34)46 (40) 
No76 (35)48 (22)94 (43) 
 Median (IQR)Median (IQR)Median (IQR) 
Years since graduation from medical school21 (16, 28)18 (14, 25)19 (12, 25).06e
Years in practice at study institution12 (5, 19)12 (6, 19)12 (6, 17).84e
Total number of orders placed112 (45, 306)105 (56, 254)113 (44, 382).92e

Use of the system was highly associated with physician attitudes toward CPOE, with the views of intermediate and high users consistently different than those of low users (Fig. 2). The associations found held true regardless of hospital: low, intermediate, and high users from Franklin had similar responses to those from Baystate (P > .05 for all questions), and the data from the 2 hospitals therefore were combined for presentation. Although few physicians believed that the user interface of the system supported their work flow, high and intermediate users were 3 times as likely to share this view than were low users (Q7; Fig. 2). Similarly, 19% of low users, 31% of intermediate users, and 45% of high users believed that entering orders into the system was faster than writing orders (Q1). High and intermediate users of the system were more likely than low users to believe that orders entered into the system were carried out more rapidly (Q2) and led to fewer medication (Q3) and nonmedication (Q4) errors. Regardless of their utilization pattern, most physicians believed that order sets played an important role in promoting efficiency and quality.

Figure 2
Attitudes of low‐, intermediate‐, and high‐use users of a computerized physician order entry system.

DISCUSSION

In this study of the clinical computing practices of physicians at 2 community hospitals, we observed wide variation in the adoption of CPOE by individual attendings. Although roughly one‐third rarely placed orders directly into the system, 42% had an order entry rate of at least 80%. Contrary to our initial expectation, we found little association between a physician's order entry rate with years in practice, duration of exposure to CPOE, or use of computers in the outpatient setting. On the other hand, we observed marked differences in use of the CPOE system across specialty lines and found that physicians who were exposed to CPOE during training and those who were regular users of computers for personal activities were more likely to embrace this technology. Further, we observed important differences between physicians who used the system to place some or most of their orders and those who did so only rarely in their beliefs and attitudes about the impact and benefits of CPOE. Physicians with higher order entry rates were more likely than their colleagues to believe that placing orders electronically was faster than handwriting and that use of the system led to fewer medical errors. These findings should be encouraging to hospitals hoping to implement CPOE because they suggest that successful adoption of CPOE is not limited to physicians who have just completed their residencies or to hospitals with the capability of designing and building their own systems. On the contrary, we documented that women, older physicians, and those with limited CPOE experience were as likely to be frequent users, especially if they perceived CPOE to be safer than handwriting and if they believed the user interface supported the efficient entering of orders.

On the basis of these results we recommend that in addition to purchasing systems that meet physician work‐flow needs and support the efficient entry of orders, hospital leaders should emphasize the quality and safety benefits of CPOE as part of a comprehensive change management strategy. The differences we observed in order entry rates across specialties may have resulted from several factors, including inherent differences in personality type associated with choice of specialty and in the level of customization of a system reflected in which and how many order sets are included. Such findings suggest that when it comes to CPOE, one size does not fit all, and implementation planning should be carried out at the specialty level. Finally, our observation that physicians who had exposure to CPOE during training were more likely to use the system to place orders suggests that the nation's training institutions will play an important role in fostering universal adoption of this technology.

Several earlier studies have reported on physician experiences with CPOE systems. Murff and Kannry12 surveyed 94 internal medicine house staff to compare experiences with 2 CPOE systems: the Department of Veterans Affairs Computerized Patient Record System (CPRS) and a commercially available product. They found striking differences in user satisfaction with numerous aspects of the systems, however they did not address attitudes toward safety or quality, and because house staff were required to place orders electronically they were unable to correlate responses with actual usage patterns. Weiner et al.13 compared the opinions of internal medicine house staff, attendings, fellows, and nurses about the benefits and challenges of using a computerized provider order entry system. In contrast to the findings from our study, Weiner et al. reported that more than half of physicians believed that provider order entry led to a greater number of errors, and only a minority believed the system increased quality of care overall. Finally, Lee et al.14 surveyed medical and surgical house officers and nurses at a large academic medical center about their satisfaction with a locally developed order entry system. They found that attitudes about the impact of the system on productivity and ease of use were more strongly associated with overall satisfaction than having undergone training or experience with personal computers. These findings are congruous with our own observation that beliefs about the speed with which orders are placed are closely associated with actual use of the system. They reported, as have we, that physicians placed a high value on order sets.

Our study had a number of strengths. First, we were able to offer insight into the attitudes and behaviors of a previously neglected, but critically important groupattending physicians who care for patients at community hospitals without the assistance of house staff. Second, whereas previous studies primarily assessed physician satisfaction with CPOE, we explored how physician attitudes about the impact of CPOE on work flow and on safety were associated with actual ordering habits. Information about ordering was obtained directly from the order entry system and not through self‐report. We conducted the study at 2 hospitals, a large urban community teaching hospital and a smaller rural hospital, and focused on a CPOE system that is in use at many institutions throughout the country, thereby increasing the generalizability of our findings. Although adoption of the system by physicians at the 2 hospitals differed, factors that associated with the use of CPOE to place orders were similar. Finally, we surveyed a large number of physicians, had a high response rate, and found only small differences in the utilization patterns of responders and nonresponders, suggesting that our portrayal of the attitudes of physicians was representative of the views of physicians practicing in our community.

The study had a number of weaknesses. First, we cannot be sure whether preexisting beliefs about the benefits of CPOE directly influenced physicians' use of the system or, conversely, if these attitudes developed in response to experience as users. Nevertheless, it seems practical to suggest that hospitals focus on purchasing systems that support the efficient entering of orders while simultaneously adopting a communication and change management strategy that emphasizes the safety and quality benefits of CPOE more broadly. Second, we did not attempt to validate the opinions expressed by physicians about the usability or safety benefits of the system. That said, the purpose of the study was to determine whether physician attitudes toward these issues was associated with the use of the system to place orders. Whether or not this particular CPOE system actually prevented medication errors, most physicians believed it did, a belief strongly associated with the observed order entry rates. Third, we studied a single CPOE system implemented approximately 10 years ago that does not reflect state‐of‐the‐art user interface design or functionality. Nevertheless, our observation about the importance of the user experience is probably no less relevant today. Fourth, we were unable to ascertain every order given by physicians, as some so‐called MD to RN orders may never have made it into the system. Finally, there is a small risk that some written, telephone, and verbal orders may have been randomly or systematically assigned to incorrect physicians, which would have led us to calculate inaccurate utilization rates.

CONCLUSIONS

In a voluntary community hospital environment the adoption of CPOE by attending physicians varies widely. While placing a premium on the purchase of systems that meet the work‐flow needs of physicians and support the efficient entry of orders, hospital leaders can enhance physician adoption of this technology by communicating the role of CPOE in improving quality and safety.

Acknowledgements

The authors thank Gilad Kuperman, MD, PhD, for his thoughtful comments on an earlier version of the manuscript.

It is widely acknowledged that the U.S. health care system is plagued by error and inefficiency and that these factors contribute to as many as 44,000‐98,000 deaths each year in U.S. hospitals. In To Err Is Human: Building a Safer Health System, the Institute of Medicine1 outlined the critical role that information technology can play in improving patient safety and highlighted computerized physician order entry (CPOE) systems for their potential to reduce the frequency of medication errors and to improve the quality of medical care.

Computerized physician order entry systems are specialized software applications that allow physicians to place orders directly into a computer. This process has a number of potential advantages over traditional handwritten ordering, including the ability to structure the ordering process to ensure the completeness of individual orders, to provide clinical decision support through diagnosis‐based order sets, and to automatically check orders for potential drugallergy, drugdrug, and drugfood interactions.2 Finally, entering orders directly into a computer eliminates the problem of transcription‐related errors that stem from the difficulty of interpreting handwriting. In clinical trials, the introduction of CPOE has been shown to reduce the frequency of medication errors, to improve the use of preventive services, and to reduce costs.36 Recognition of the benefits of these systems has not been confined to the medical community. The Leapfrog Organization, a coalition of large businesses in the United States, has chosen CPOE as one of its 3 initial safety leaps and has established a threshold that 70% of medication orders should be entered directly by physicians.7

Although the benefits of CPOE systems are widely recognized, few hospitals have implemented these systems successfully.8, 9 Those that have, have often developed the applications internally, and many have relied on house staff to do most or all of the actual ordering.10 However, most hospitals do not have the expertise for internal development and instead rely on commercially available products. Moreover, most patients hospitalized in the United States are cared for by attending physicians working without the assistance of house staff.11 In light of the importance of successfully implementing CPOE systems in such settings, we assessed the adoption of CPOE by attending physicians at 2 community hospitals where its use was voluntary and examined the characteristics and attitudes associated with use of the system to place orders.

METHODS

Setting and Participants

Baystate Medical Center is a 600‐bed teaching hospital in Springfield, Massachusetts, where approximately 50% of patients are cared for with the assistance of house staff. Franklin Medical Center is a 125‐bed community hospital in rural Greenfield, Massachusetts, and is not a house staff training site. Medical staff membership at the 2 hospitals is largely voluntary. Both institutions share a vendor‐supplied computerized order entry system that was implemented in the early 1990s (E7000, Eclipsys Corporation, Boca Raton, FL). The system provides a structured format for the creation of medication, laboratory, and radiology orders and contains thousands of preconstructed medication order sentences and hundreds of order sets designed to standardize ordering for common diagnoses and procedures. Pharmacists are alerted of potential drugallergy and drugdrug interactions and use clinical judgment about whether to communicate this information to the physician. Although the house staff at Baystate Medical Center is mandated to place orders in the system, attending physicians have no such requirement at either institution. Access to the system is provided though the many fixed workstations located on nursing units, in operating rooms, and in the health sciences library. On a typical medical‐surgical patient care unit most computers are behind the nurses' station, though some are distributed along hallways and in physician charting rooms. No computers are in patient rooms. Although the number varies slightly across units, the average ratio of computers to patient beds is roughly 1 to 1.

Survey

In June 2003 we mailed a 20‐item survey to attending physicians who had been responsible for a minimum of 25 orders during the preceding month at either Baystate or Franklin Medical Center. Orders counted toward this minimum if they had been written, given verbally in person or by phone, or entered directly into the computer by the physician. The survey consisted of 20 questions focused on the topic of computerized order entry. In addition to collecting information about sex and specialty, we asked respondents to describe their use of CPOE during training, their use of computers at home, and, where applicable, their use of computers in their outpatient practices. The survey included questions about how often respondents used the order entry system when caring for hospitalized patients and which features of the system they used. To assess physician attitudes about the order entry process, we asked respondents to consider whether it was faster to place orders directly into the system than it was by handwriting them, whether orders placed in the system were carried out more rapidly, whether placing orders in the system led to fewer medication and other errors, whether order sets were important for the efficient use of the system, whether order sets helped to ensure that important aspects of care did not slip through the cracks, whether the system's user interface supported their work flow, and whether the encouragement of nurses was an important factor in their use of the system. Questions that assessed physician attitudes were presented on a 5‐point Likert scale. Nonrespondents were sent reminder letters along with duplicate surveys twice, approximately 1 and 2 months after the initial mailing. No financial incentive was offered for participation. The study protocol was approved by the Institutional Review Board of Baystate Health System.

Order Entry Rates

Regardless of whether an order is placed directly by a physician into a computer, given verbally, or handwritten, all orders are ultimately entered into the CPOE system. Working with our hospitals' Departments of Information Services, we developed a report that provided physician‐specific information about order entry patterns. For each physician in the study, we determined the total number of orders generated during the month preceding the initial June mailing, as well as the absolute number and percentage of orders of each of the following categories: directly entered, telephone, verbal, and written. Because verbal and telephone orders are required during urgent situations and when physicians give orders from outside the hospital, we calculated and report an adjusted order entry rate as the total number of orders placed directly into the system divided by the sum of the orders entered directly and the number of written orders.

Analysis

Summary statistics for the overall sample were constructed using simple frequencies and proportions for categorical variables and medians and interquartile ranges for continuous variables. We compared characteristics of respondents from the 2 hospitals using chi‐square tests of association for categorical factors and Wilcoxon rank‐sum tests for continuous scale data. We compared the total number of orders placed during the study month and the order entry rates of responders and nonresponders using the Wilcoxon rank‐sum test. We categorized physicians as low (20%), intermediate (21%‐79%), and high (80%) users of the system based on their calculated order entry rate. Responses to each of the attitude questions in the survey were tabulated, and the responses strongly agree and agree were combined for analyses comparing responses. Demographic variables and physician attitudes were tested for associations with order entry rate categories via the Pearson chi‐square for categorical factors, the Mantel‐Haenszel chi‐square for ordered factors, and Kruskal‐Wallis analysis of variance for continuous variables. Initial analyses were stratified by hospital; where no differences in association were found across strata, the data were combined. Statistical tests were performed using SAS version 9.1 (SAS Institute, Cary, NC)

RESULTS

During the study period the target group of physicians placed a total of 135,692 orders, of which 69,654 (51%) were placed directly into the CPOE system, 38,878 (29%) were made using pen and paper, 7,208 (5%) were made verbally, and 19,952 (15%) were placed by telephone. Three hundred and fifty‐six (71%) of the 502 surveys sent out to physicians at the 2 hospitals were returned. Thirteen surveys were excluded from analysis because the respondent was not a physician, and 2 because we were unable to match the survey to system usage data, leaving a total of 341 surveys for analysis. Order entry rates were not computed for an additional 3 physicians who only placed verbal and telephone orders during the study period. Response rates did not differ by clinician specialty (P = .53); compared to those of nonresponders, respondents had a similar median total number of orders (111 vs. 101, P = .67) and a higher median order entry rate (66% vs. 48%, P = .03).

Characteristics of Respondents

Seventy‐two percent of physicians who completed the survey were men; half had graduated from medical school at least 20 years ago, and the median duration of practice at the study institution was 11 years (Table 1). Forty percent practiced internal medicine, 18% were surgeons, and 16% were pediatricians. Thirty‐five percent completed training at an institution that had computerized physician order entry, and 86% cared for patients primarily at Baystate Medical Center. More than half reported they used the system many times each day for patient care, and the features they used most commonly were retrieval of results (95%), placing of orders (78%), and viewing and printing of patient lists (75%). Among those with outpatient practices, 81% used computers in their outpatient practice, and more than half used computers for personal activities at home at least once a day. On average, respondents from Franklin Medical Center had graduated from medical school farther in the past and reported less reliance on the system to carry out all activities other than viewing results.

Characteristics of Physicians Participating in the Study (N = 341)
 Overall n (%)Baystate n (%) 293 (85.9)Franklin n (%) 48 (14.1)Chi square P value
  • From survey responses.

  • CPOE rate = (orders directly entered)/(orders directly entered + orders placed in writing).

  • Data of actual use during month preceding survey mailing.

Sex   .64
Male244 (71.6)211 (72.0)33 (68.8) 
Specialty   .24
Anesthesia23 (6.7)23 (7.9)0 (0.0) 
Internal medicine135 (39.6)112 (38.2)23 (47.9) 
Medicine/pediatrics13 (3.8)6 (2.0)7 (14.6) 
OB/GYN36 (10.6)30 (10.2)6 (12.5) 
Pediatrics54 (15.8)51 (17.4)3 (6.3) 
Surgery61 (17.9)55 (18.8)6 (12.5) 
Other19 (5.6)16 (5.5)3 (6.3) 
Use of CPOE systema   .09
Many times a day176 (52.2)160 (55.0)16 (34.8) 
At least once a day77 (22.9)61 (21.0)16 (34.8) 
A few times a week55 (16.3)45 (15.5)10 (21.7) 
Once a week or less29 (8.6)25 (8.6)4 (8.7) 
Features useda    
Viewing and printing patient lists254 (75.2)212 (72.6)42 (91.3).01
Looking up results320 (94.7)277 (94.9)43 (93.5).70
Viewing current medications218 (64.5)204 (69.9)14 (30.4)< .01
Placing orders263 (77.8)244 (83.6)19 (41.3)< .01
Entering discharge summaries72 (21.3)70 (24.0)2 (4.4)< .01
Use of order setsa    
Rarely or never98 (29.0)74 (25.3)24 (52.2)< .01
Minority of patients92 (27.2)78 (26.7)14 (30.4) 
Majority of patients104 (30.8)97 (33.2)7 (15.2) 
For all or nearly all patients44 (13.0)43 (14.7)1 (2.2) 
Percentage of orders placed using order setsa   < .01
None46 (13.7)26 (9.0)20 (44.4) 
1%‐25%62 (18.5)50 (17.2)12 (26.7) 
26%‐50%29 (8.7)23 (7.9)6 (13.3) 
51%‐75%45 (13.4)43 (14.9)2 (4.4) 
76%‐99%103 (30.8)98 (33.8)5 (11.1) 
All50 (14.9)50 (17.2)0 (0.0) 
Use of computer in outpatient practiceab243 (81.3)206 (80.8)37 (84.1).60
Personal computer usea   .47
At least once a day209 (61.7)185 (63.4)24 (51.1) 
Several times a week84 (24.8)67 (23.0)17 (36.2) 
A few times a month21 (6.2)18 (6.2)3 (6.4) 
Rarely25 (7.4)22 (7.5)3 (6.4) 
Training at an institution that had CPOE117 (34.7)105 (36.1)12 (26.1)0.19
Use of system to enter orders should be mandatorya    
Yes113 (35.2)106 (38.4)7 (15.6)<.01
 Median (IQR)Median (IQR)Median (IQR)WilcoxonPvalue
Years since medical school graduationa20 (13, 26)20 (13, 26)24 (17, 28).02
Years in practice at study institutiona11 (5, 18)11 (5, 18)13 (7, 19).39
Orders directly enteredc23 (2, 99)27 (5, 108)1 (0, 27)< .01
Orders placed by telephonec14 (5, 49)12 (3, 38)49.5 (16, 123.5)< .01
Orders placed verballyc2 (0, 11)3 (0, 13)1 (0,3)< .01
Orders placed in writingc21 (4, 73)14 (3, 45)220 (106.5, 391)< .01
CPOE ratebc66% (3%, 94%)76% (19%, 96%)0.25% (0%, 17%)< .01

Attitudes Toward Computerized Physician Order Entry

Physicians who completed the survey offered diverse opinions about the impact of computerized order entry on work flow, patient safety, and quality of care. Only 22% believed the system's user interface supported their work flow (Q7), 34% believed it was faster to enter orders directly into the system than to handwrite them (Q1), and 41% believed orders placed into the system were carried out more rapidly (Q2) (Table 2). On the other hand, 63% of respondents believed that placing orders directly into the system led to fewer medication errors (Q3), and 51% stated the system generally reduced medical errors (Q4). Sixty‐nine percent stated order sets were important for efficient use of the system (Q5), and 71% believed order sets served an important decision support role (Q6). Twenty‐six percent stated that the encouragement of nurses was an important factor in their use of the system (Q8). Finally, 35% of attending physicians believed use of the system to place orders should be mandatory.

Attitudes of Respondents (N = 341) to Computerized Physician Order Entry

Characteristics and Attitudes of High, Intermediate, and Low Users

The median order entry rate of respondents was 66%. One hundred and forty‐one (42%) placed at least 80% of their orders directly into the system, whereas 109 (32%) placed no more than 20% of their orders directly in the system (Fig. 1). There was not a significant difference between the low, intermediate, and high use groups in the total number of orders that each physician placed during the study period (Table 3). Sex, years since graduation from medical school, years in practice at the study institution, and use of computers in the outpatient setting were not meaningfully different between the 3 categories of users (Table 3). On the other hand, medical specialty was strongly associated with use of the system, with anesthesiologists, pediatricians, and surgeons the specialties with the largest proportion of high users. Furthermore, physicians who were trained in a CPOE environment and those who reported daily use of computers for personal activities showed the highest levels of adoption. Physicians at Franklin Medical Center showed lower levels of order entry than their counterparts at Baystate.

Figure 1
Distribution of direct order entry rate among clinicians responding to survey.
Characteristics of Survey Respondents (n=338) with Written and/or Direct Entry Orders in Month Preceding Survey according to Low, Intermediate, and High Usage of a CPOE System
 Low (20%) n (row %)Intermediate (20%‐79%) n (row %)High (80%) n (row %)P value
  • Among n = 299 with outpatient practice.

  • Because of missing survey responses, category values may not add up to total.

  • Pearson chi‐square P value.

  • Mantel‐Haenszel chi‐square P value.

  • Kruskal‐Wallis P value

 n = 109n = 88n = 141 
Hospital   < .01c
Baystate73 (25)79 (27)138 (48) 
Franklin36 (75)9 (19)3 (6) 
Sex   .69c
Female28 (29)24 (25)43 (45) 
Male81 (33)64 (26)98 (40) 
Specialty   .0001c
Anesthesia8 (35)3 (13)12 (52) 
Internal medicine45 (33)37 (27)53 (39) 
Medicine/pediatrics6 (46)5 (38)2 (15) 
OB/GYN20 (56)12 (33)4 (11) 
Pediatrics13 (24)9 (17)32 (59) 
Surgery14 (23)21 (34)26 (43) 
Other3 (19)1 (6)12 (75) 
Do you use a computer in your outpatient practice?a
Yes75 (31)61 (25)105 (44).22c
No20 (36)18 (33)17 (31) 
Level of personal computer useb   .045d
Rarely11 (44)8 (32)6 (24) 
A few times a month7 (33)4 (19)10 (48) 
Several times a week28 (35)25 (31)28 (35) 
At least once a day62 (30)50 (24)97 (46) 
Training at an institution that had CPOE   .037c
Yes30 (26)40 (34)46 (40) 
No76 (35)48 (22)94 (43) 
 Median (IQR)Median (IQR)Median (IQR) 
Years since graduation from medical school21 (16, 28)18 (14, 25)19 (12, 25).06e
Years in practice at study institution12 (5, 19)12 (6, 19)12 (6, 17).84e
Total number of orders placed112 (45, 306)105 (56, 254)113 (44, 382).92e

Use of the system was highly associated with physician attitudes toward CPOE, with the views of intermediate and high users consistently different than those of low users (Fig. 2). The associations found held true regardless of hospital: low, intermediate, and high users from Franklin had similar responses to those from Baystate (P > .05 for all questions), and the data from the 2 hospitals therefore were combined for presentation. Although few physicians believed that the user interface of the system supported their work flow, high and intermediate users were 3 times as likely to share this view than were low users (Q7; Fig. 2). Similarly, 19% of low users, 31% of intermediate users, and 45% of high users believed that entering orders into the system was faster than writing orders (Q1). High and intermediate users of the system were more likely than low users to believe that orders entered into the system were carried out more rapidly (Q2) and led to fewer medication (Q3) and nonmedication (Q4) errors. Regardless of their utilization pattern, most physicians believed that order sets played an important role in promoting efficiency and quality.

Figure 2
Attitudes of low‐, intermediate‐, and high‐use users of a computerized physician order entry system.

DISCUSSION

In this study of the clinical computing practices of physicians at 2 community hospitals, we observed wide variation in the adoption of CPOE by individual attendings. Although roughly one‐third rarely placed orders directly into the system, 42% had an order entry rate of at least 80%. Contrary to our initial expectation, we found little association between a physician's order entry rate with years in practice, duration of exposure to CPOE, or use of computers in the outpatient setting. On the other hand, we observed marked differences in use of the CPOE system across specialty lines and found that physicians who were exposed to CPOE during training and those who were regular users of computers for personal activities were more likely to embrace this technology. Further, we observed important differences between physicians who used the system to place some or most of their orders and those who did so only rarely in their beliefs and attitudes about the impact and benefits of CPOE. Physicians with higher order entry rates were more likely than their colleagues to believe that placing orders electronically was faster than handwriting and that use of the system led to fewer medical errors. These findings should be encouraging to hospitals hoping to implement CPOE because they suggest that successful adoption of CPOE is not limited to physicians who have just completed their residencies or to hospitals with the capability of designing and building their own systems. On the contrary, we documented that women, older physicians, and those with limited CPOE experience were as likely to be frequent users, especially if they perceived CPOE to be safer than handwriting and if they believed the user interface supported the efficient entering of orders.

On the basis of these results we recommend that in addition to purchasing systems that meet physician work‐flow needs and support the efficient entry of orders, hospital leaders should emphasize the quality and safety benefits of CPOE as part of a comprehensive change management strategy. The differences we observed in order entry rates across specialties may have resulted from several factors, including inherent differences in personality type associated with choice of specialty and in the level of customization of a system reflected in which and how many order sets are included. Such findings suggest that when it comes to CPOE, one size does not fit all, and implementation planning should be carried out at the specialty level. Finally, our observation that physicians who had exposure to CPOE during training were more likely to use the system to place orders suggests that the nation's training institutions will play an important role in fostering universal adoption of this technology.

Several earlier studies have reported on physician experiences with CPOE systems. Murff and Kannry12 surveyed 94 internal medicine house staff to compare experiences with 2 CPOE systems: the Department of Veterans Affairs Computerized Patient Record System (CPRS) and a commercially available product. They found striking differences in user satisfaction with numerous aspects of the systems, however they did not address attitudes toward safety or quality, and because house staff were required to place orders electronically they were unable to correlate responses with actual usage patterns. Weiner et al.13 compared the opinions of internal medicine house staff, attendings, fellows, and nurses about the benefits and challenges of using a computerized provider order entry system. In contrast to the findings from our study, Weiner et al. reported that more than half of physicians believed that provider order entry led to a greater number of errors, and only a minority believed the system increased quality of care overall. Finally, Lee et al.14 surveyed medical and surgical house officers and nurses at a large academic medical center about their satisfaction with a locally developed order entry system. They found that attitudes about the impact of the system on productivity and ease of use were more strongly associated with overall satisfaction than having undergone training or experience with personal computers. These findings are congruous with our own observation that beliefs about the speed with which orders are placed are closely associated with actual use of the system. They reported, as have we, that physicians placed a high value on order sets.

Our study had a number of strengths. First, we were able to offer insight into the attitudes and behaviors of a previously neglected, but critically important groupattending physicians who care for patients at community hospitals without the assistance of house staff. Second, whereas previous studies primarily assessed physician satisfaction with CPOE, we explored how physician attitudes about the impact of CPOE on work flow and on safety were associated with actual ordering habits. Information about ordering was obtained directly from the order entry system and not through self‐report. We conducted the study at 2 hospitals, a large urban community teaching hospital and a smaller rural hospital, and focused on a CPOE system that is in use at many institutions throughout the country, thereby increasing the generalizability of our findings. Although adoption of the system by physicians at the 2 hospitals differed, factors that associated with the use of CPOE to place orders were similar. Finally, we surveyed a large number of physicians, had a high response rate, and found only small differences in the utilization patterns of responders and nonresponders, suggesting that our portrayal of the attitudes of physicians was representative of the views of physicians practicing in our community.

The study had a number of weaknesses. First, we cannot be sure whether preexisting beliefs about the benefits of CPOE directly influenced physicians' use of the system or, conversely, if these attitudes developed in response to experience as users. Nevertheless, it seems practical to suggest that hospitals focus on purchasing systems that support the efficient entering of orders while simultaneously adopting a communication and change management strategy that emphasizes the safety and quality benefits of CPOE more broadly. Second, we did not attempt to validate the opinions expressed by physicians about the usability or safety benefits of the system. That said, the purpose of the study was to determine whether physician attitudes toward these issues was associated with the use of the system to place orders. Whether or not this particular CPOE system actually prevented medication errors, most physicians believed it did, a belief strongly associated with the observed order entry rates. Third, we studied a single CPOE system implemented approximately 10 years ago that does not reflect state‐of‐the‐art user interface design or functionality. Nevertheless, our observation about the importance of the user experience is probably no less relevant today. Fourth, we were unable to ascertain every order given by physicians, as some so‐called MD to RN orders may never have made it into the system. Finally, there is a small risk that some written, telephone, and verbal orders may have been randomly or systematically assigned to incorrect physicians, which would have led us to calculate inaccurate utilization rates.

CONCLUSIONS

In a voluntary community hospital environment the adoption of CPOE by attending physicians varies widely. While placing a premium on the purchase of systems that meet the work‐flow needs of physicians and support the efficient entry of orders, hospital leaders can enhance physician adoption of this technology by communicating the role of CPOE in improving quality and safety.

Acknowledgements

The authors thank Gilad Kuperman, MD, PhD, for his thoughtful comments on an earlier version of the manuscript.

References
  1. Kohn LT,Corrigan JM,Donaldson MS, eds.To Err Is Human: Building a Safer Health System.Washington, DC:National Academy Press,2000.
  2. Kuperman GJ,Gibson RF.Computer physician order entry: benefits, costs, and issues.Ann Intern Med.2003;139:3139.
  3. Bates DW,Leape LL,Cullen DJ, et al.Effect of computerized physician order entry and a team intervention on prevention of serious medication errors.JAMA.1998;280:13111316.
  4. Dexter PR,Perkins S,Overhage JM,Maharry K,Kohler RB,McDonald CJ.A computerized reminder system to increase the use of preventive care for hospitalized patients.N Engl J Med.2001;345:965970.
  5. Overhage JM,Tierney WM,Zhou XH,McDonald CJ.A randomized trial of “corollary orders” to prevent errors of omission.J Am Med Inform Assoc.1997;4:364375.
  6. Evans RS,Pestotnik SL,Classen DC, et al.A computer‐assisted management program for antibiotics and other antiinfective agents.N Engl J Med.1998;338:232238.
  7. The Leapfrog Group. Patient Safety Fact Sheet. Available at: http://www.leapfroggroup.org/FactSheets/LF_FactSheet.pdf. Accessed October 6,2004.
  8. Ash JS,Gorman PN,Seshadri V,Hersh WR.Computerized physician order entry in U.S. hospitals: results of a 2002 survey.J Am Med Inform Assoc.2004;11:9599.
  9. Cutler DM,Feldman NE,Horwitz JR.U.S. adoption of computerized physician order entry systems.Health Aff.2005;24:16541663.
  10. Kaushal R,Shojania KG,Bates DW.Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review.Arch Intern Med.2003;163:14091416.
  11. HCUPnet, Healthcare Cost and Utilization Project. Agency for Healthcare Research and Quality, Rockville, MD. Available at: http://www.ahrq.gov/data/hcup/hcupnet.htm. Accessed October 6,2004.
  12. Murff HJ,Kannry J.Physician satisfaction with two order entry systems.J Am Med Inform Assoc.2001;8:499509.
  13. Weiner M,Gress T,Thiemann DR, et al.Contrasting views of physicians and nurses about an inpatient computer‐based provider order‐entry system.J Am Med Inform Assoc.1999;6:234244.
  14. Lee F,Teich JM,Spurr CD,Bates DW.Implementation of physician order entry: user satisfaction and self‐reported usage patterns.J Am Med Inform Assoc.1996;3:4255.
References
  1. Kohn LT,Corrigan JM,Donaldson MS, eds.To Err Is Human: Building a Safer Health System.Washington, DC:National Academy Press,2000.
  2. Kuperman GJ,Gibson RF.Computer physician order entry: benefits, costs, and issues.Ann Intern Med.2003;139:3139.
  3. Bates DW,Leape LL,Cullen DJ, et al.Effect of computerized physician order entry and a team intervention on prevention of serious medication errors.JAMA.1998;280:13111316.
  4. Dexter PR,Perkins S,Overhage JM,Maharry K,Kohler RB,McDonald CJ.A computerized reminder system to increase the use of preventive care for hospitalized patients.N Engl J Med.2001;345:965970.
  5. Overhage JM,Tierney WM,Zhou XH,McDonald CJ.A randomized trial of “corollary orders” to prevent errors of omission.J Am Med Inform Assoc.1997;4:364375.
  6. Evans RS,Pestotnik SL,Classen DC, et al.A computer‐assisted management program for antibiotics and other antiinfective agents.N Engl J Med.1998;338:232238.
  7. The Leapfrog Group. Patient Safety Fact Sheet. Available at: http://www.leapfroggroup.org/FactSheets/LF_FactSheet.pdf. Accessed October 6,2004.
  8. Ash JS,Gorman PN,Seshadri V,Hersh WR.Computerized physician order entry in U.S. hospitals: results of a 2002 survey.J Am Med Inform Assoc.2004;11:9599.
  9. Cutler DM,Feldman NE,Horwitz JR.U.S. adoption of computerized physician order entry systems.Health Aff.2005;24:16541663.
  10. Kaushal R,Shojania KG,Bates DW.Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review.Arch Intern Med.2003;163:14091416.
  11. HCUPnet, Healthcare Cost and Utilization Project. Agency for Healthcare Research and Quality, Rockville, MD. Available at: http://www.ahrq.gov/data/hcup/hcupnet.htm. Accessed October 6,2004.
  12. Murff HJ,Kannry J.Physician satisfaction with two order entry systems.J Am Med Inform Assoc.2001;8:499509.
  13. Weiner M,Gress T,Thiemann DR, et al.Contrasting views of physicians and nurses about an inpatient computer‐based provider order‐entry system.J Am Med Inform Assoc.1999;6:234244.
  14. Lee F,Teich JM,Spurr CD,Bates DW.Implementation of physician order entry: user satisfaction and self‐reported usage patterns.J Am Med Inform Assoc.1996;3:4255.
Issue
Journal of Hospital Medicine - 1(4)
Issue
Journal of Hospital Medicine - 1(4)
Page Number
221-230
Page Number
221-230
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Physician characteristics, attitudes, and use of computerized order entry
Display Headline
Physician characteristics, attitudes, and use of computerized order entry
Legacy Keywords
CPOE, computers in medicine, patient safety, errors in medicine
Legacy Keywords
CPOE, computers in medicine, patient safety, errors in medicine
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