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PFOs raise stroke risk from devices
LOS ANGELES – Patients with a patent foramen ovale and an implanted defibrillator or pacemaker may be good candidates for targeted closure, based on a review of more than 6,000 patients.
During an average follow-up of nearly 5 years, patients with a PFO who received an implantable cardioverter defibrillator (ICD) or a permanent pacemaker were more than fourfold more likely to develop stroke or transient ischemic attack (TIA) compared with implanted device recipients who did not have a PFO, Dr. Christopher V. DeSimone said at the annual scientific sessions of the American Heart Association.
"We think that this is a high-risk population that might benefit from PFO closure," said Dr. DeSimone, an internal medicine physician at the Mayo Clinic in Rochester, Minn. He acknowledged the poor efficacy of PFO closure for stroke prevention in several recent randomized trials, but noted that patients with a PFO who receive an ICD or permanent pacemaker may constitute a special subgroup that stands to benefit from PFO closure. "If a patient has a right atrial or ventricular lead and a clot forms and sits there next to the PFO, they would be at high risk" for a stroke or TIA, he said in an interview. In fact, trials that have assessed the efficacy of PFO closure explicitly excluded patients with permanent pacemakers as well as many ICD recipients because of their substantially impaired left ventricular function, such as in the CLOSURE I trial (N. Engl. J. Med. 2012;366:991-9). "This needs to be studied prospectively," he added, noting that his study was limited by being retrospective.
Dr. DeSimone and his associates reviewed 6,086 patients who received an ICD or permanent pacemaker at the Mayo Clinic during January 2000 to October 2010. The group included 375 patients with PFOs. Average age of the patients was 67 years; nearly two-thirds were men. About 15% had a history of stroke or TIA, about 44% had atrial fibrillation, and their average CHA2D2-VASc score was 3.1.
During an average follow-up of 4.7 years, the incidence of stroke or TIA was 11% in the PFO patients and 2% in the patients without a PFO. In a multivariate analysis that controlled for baseline demographic and clinical differences, including atrial fibrillation and aspirin and warfarin use, patients with a PFO were 4.6-fold more likely to have a stroke or TIA than were patients without a PFO, a statistically significant difference.
Additional analyses showed that the stroke and TIA rate remained significantly elevated in the PFO patients regardless of whether patients were on treatment with aspirin or on warfarin, and also regardless of whether or not they were older than age 65 or had a history of stroke or TIA, and regardless of whether they had a low or high CHA2D2-VASc score, Dr. DeSimone said. They saw no significant link between a PFO present and all-cause mortality.
The PFO-related difference in the incidence of stroke and TIA first became apparent about 1 year after device placement. The event curves continued to diverge more and more over time. Micro-emboli that originate on the device leads may pass through the PFO and into pulmonary circulation, causing increased pulmonary-artery pressures during the year after device placement. The increased right-sided pressure then favors a right-to-left shunt and increased embolization.
The stroke risk in this analysis may have underestimated the true risk because the methods used to find PFOs and stroke may not have been optimal.
Dr. DeSimone had no disclosures.
LOS ANGELES – Patients with a patent foramen ovale and an implanted defibrillator or pacemaker may be good candidates for targeted closure, based on a review of more than 6,000 patients.
During an average follow-up of nearly 5 years, patients with a PFO who received an implantable cardioverter defibrillator (ICD) or a permanent pacemaker were more than fourfold more likely to develop stroke or transient ischemic attack (TIA) compared with implanted device recipients who did not have a PFO, Dr. Christopher V. DeSimone said at the annual scientific sessions of the American Heart Association.
"We think that this is a high-risk population that might benefit from PFO closure," said Dr. DeSimone, an internal medicine physician at the Mayo Clinic in Rochester, Minn. He acknowledged the poor efficacy of PFO closure for stroke prevention in several recent randomized trials, but noted that patients with a PFO who receive an ICD or permanent pacemaker may constitute a special subgroup that stands to benefit from PFO closure. "If a patient has a right atrial or ventricular lead and a clot forms and sits there next to the PFO, they would be at high risk" for a stroke or TIA, he said in an interview. In fact, trials that have assessed the efficacy of PFO closure explicitly excluded patients with permanent pacemakers as well as many ICD recipients because of their substantially impaired left ventricular function, such as in the CLOSURE I trial (N. Engl. J. Med. 2012;366:991-9). "This needs to be studied prospectively," he added, noting that his study was limited by being retrospective.
Dr. DeSimone and his associates reviewed 6,086 patients who received an ICD or permanent pacemaker at the Mayo Clinic during January 2000 to October 2010. The group included 375 patients with PFOs. Average age of the patients was 67 years; nearly two-thirds were men. About 15% had a history of stroke or TIA, about 44% had atrial fibrillation, and their average CHA2D2-VASc score was 3.1.
During an average follow-up of 4.7 years, the incidence of stroke or TIA was 11% in the PFO patients and 2% in the patients without a PFO. In a multivariate analysis that controlled for baseline demographic and clinical differences, including atrial fibrillation and aspirin and warfarin use, patients with a PFO were 4.6-fold more likely to have a stroke or TIA than were patients without a PFO, a statistically significant difference.
Additional analyses showed that the stroke and TIA rate remained significantly elevated in the PFO patients regardless of whether patients were on treatment with aspirin or on warfarin, and also regardless of whether or not they were older than age 65 or had a history of stroke or TIA, and regardless of whether they had a low or high CHA2D2-VASc score, Dr. DeSimone said. They saw no significant link between a PFO present and all-cause mortality.
The PFO-related difference in the incidence of stroke and TIA first became apparent about 1 year after device placement. The event curves continued to diverge more and more over time. Micro-emboli that originate on the device leads may pass through the PFO and into pulmonary circulation, causing increased pulmonary-artery pressures during the year after device placement. The increased right-sided pressure then favors a right-to-left shunt and increased embolization.
The stroke risk in this analysis may have underestimated the true risk because the methods used to find PFOs and stroke may not have been optimal.
Dr. DeSimone had no disclosures.
LOS ANGELES – Patients with a patent foramen ovale and an implanted defibrillator or pacemaker may be good candidates for targeted closure, based on a review of more than 6,000 patients.
During an average follow-up of nearly 5 years, patients with a PFO who received an implantable cardioverter defibrillator (ICD) or a permanent pacemaker were more than fourfold more likely to develop stroke or transient ischemic attack (TIA) compared with implanted device recipients who did not have a PFO, Dr. Christopher V. DeSimone said at the annual scientific sessions of the American Heart Association.
"We think that this is a high-risk population that might benefit from PFO closure," said Dr. DeSimone, an internal medicine physician at the Mayo Clinic in Rochester, Minn. He acknowledged the poor efficacy of PFO closure for stroke prevention in several recent randomized trials, but noted that patients with a PFO who receive an ICD or permanent pacemaker may constitute a special subgroup that stands to benefit from PFO closure. "If a patient has a right atrial or ventricular lead and a clot forms and sits there next to the PFO, they would be at high risk" for a stroke or TIA, he said in an interview. In fact, trials that have assessed the efficacy of PFO closure explicitly excluded patients with permanent pacemakers as well as many ICD recipients because of their substantially impaired left ventricular function, such as in the CLOSURE I trial (N. Engl. J. Med. 2012;366:991-9). "This needs to be studied prospectively," he added, noting that his study was limited by being retrospective.
Dr. DeSimone and his associates reviewed 6,086 patients who received an ICD or permanent pacemaker at the Mayo Clinic during January 2000 to October 2010. The group included 375 patients with PFOs. Average age of the patients was 67 years; nearly two-thirds were men. About 15% had a history of stroke or TIA, about 44% had atrial fibrillation, and their average CHA2D2-VASc score was 3.1.
During an average follow-up of 4.7 years, the incidence of stroke or TIA was 11% in the PFO patients and 2% in the patients without a PFO. In a multivariate analysis that controlled for baseline demographic and clinical differences, including atrial fibrillation and aspirin and warfarin use, patients with a PFO were 4.6-fold more likely to have a stroke or TIA than were patients without a PFO, a statistically significant difference.
Additional analyses showed that the stroke and TIA rate remained significantly elevated in the PFO patients regardless of whether patients were on treatment with aspirin or on warfarin, and also regardless of whether or not they were older than age 65 or had a history of stroke or TIA, and regardless of whether they had a low or high CHA2D2-VASc score, Dr. DeSimone said. They saw no significant link between a PFO present and all-cause mortality.
The PFO-related difference in the incidence of stroke and TIA first became apparent about 1 year after device placement. The event curves continued to diverge more and more over time. Micro-emboli that originate on the device leads may pass through the PFO and into pulmonary circulation, causing increased pulmonary-artery pressures during the year after device placement. The increased right-sided pressure then favors a right-to-left shunt and increased embolization.
The stroke risk in this analysis may have underestimated the true risk because the methods used to find PFOs and stroke may not have been optimal.
Dr. DeSimone had no disclosures.
Major Finding: ICD or pacemaker recipients with a PFO had a 4.6-fold increased risk of stroke or TIA.
Data Source: A review of 6,086 patients at the Mayo Clinic.
Disclosures: Dr. DeSimone said that he had no disclosures.
Bacterial Contamination of Smart Phones
Mobile phones are now widely used. Healthcare workers, in particular, use them for rapid communication in many hospital settings. As mobile phones increase in popularity, a number of concerns have been raised, including noise and distraction in the clinical environment, confidentiality of patient information, and data security among others.[1]
Of the various concerns regarding mobile phone use in hospitals, one of the most important is that mobile phones may serve as vehicles for nosocomial transmission of micro‐organisms.[2, 3] One report showed that over 90% of healthcare workers' cell phones were contaminated with micro‐organisms, and 14.3% of cell phones were contaminated with bacteria that can cause nosocomial infection.[2]
Smart phones, which are rapidly flooding the mobile phone market, are useful in the hospital setting, as they could provide rapid access to medical information, quicker consultation and responding, feedback of results to the patient, and ongoing monitoring of chronic diseases (eg, asthma and diabetes).[4, 5, 6, 7, 8]
However, as most smart phones have wide, full, touch screens and are used more often by their owners than non‐smart phones are, bacterial contamination rates may be higher than those of non‐smart phones. The aim of this study was to compare the contamination rates by bacteria with pathogenic potential in smart phones versus non‐smart phones.
MATERIALS AND METHODS
Study Design and Participants
This cross‐sectional study was conducted from March 1, 2011 to June 30, 2011, in 3 teaching hospitals affiliated with Seoul National University School of Medicine, namely Seoul National University Hospital, Bundang Seoul National University Hospital, and Seoul National University Boramae Medical Center. Hospital staff working in general wards as well as in intensive care units of the 3 hospitals were invited to participate in this study. The study protocol was approved by the institutional review board of each of the 3 participating hospitals. Informed consent was obtained from all participants.
Questionnaire
We designed a questionnaire inquiring about demographics (age, gender, occupation) as well as behavior regarding cell phone use (type of cell phone, frequency and reasons for use, cleaning of cell phones).
Bacterial Culture, Identification, and Drug Susceptibility Testing
Both the anterior and posterior surfaces of each participant's mobile phone were touched onto blood agar plates. The sampled culture plates were subsequently incubated aerobically at 36C for 48 hours. To identify cultivated micro‐organisms and for the assessment of antibiotic susceptibility, VITEK2 (bioMrieux, Inc., Durham, NC) systems were used.
Classification of Isolated Micro‐organisms
We classified the micro‐organisms isolated from healthcare workers' mobile phones as bacteria with pathogenic potential (probable pathogens) or nonpathogens.[4, 9] Among probable pathogenic micro‐organisms, representative drug‐resistant strains such as methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant Enterococcus (VRE), and imipenem‐resistant Acinetobacter baumannii (IRAB) were categorized as drug‐resistant pathogens.
Classification of Smart Phones Versus Non‐Smart Phones
Mobile phones that ran complete mobile operating systems and software that provided a standardized interface and a platform for application developers, were classified as smart phones.[10] All others were classified as non‐smart phones.
Statistical Analysis
The participants' clinical variables were analyzed using descriptive statistics. The results are expressed as meanstandard deviation or median value with range. Variables were compared between the smart phone and non‐smart phone users. Categorical variables were compared by [2] analysis, and continuous variables were compared using Student t test or the Mann‐Whitney test. Variables with P<0.20 after univariate analysis or clinically significant variables were subjected to multiple logistic regression to determine the risk factors for contamination of cell phones with potentially pathogenic bacteria. For all analyses, P values <0.05 were considered significant. Homer‐Lemeshow goodness of fit (GOF) test was performed to confirm the fitness of the final model. The Statistical Package for the Social Sciences version 17.0 (IBM SPSS, Armonk, NY) was used for all statistical analysis.
RESULTS
Participants and Their Behaviors Regarding Cell Phone Use
In total, 203 healthcare workers participated in this study; 80 (39.4%) were physicians, 106 (52.2%) were nurses, and 17 (8.4%) were assistants. The median age of the participants was 29 years, 43 (21.2%) were males, 115 (56.7%) participants used smart phones, and 88 (43.3%) were non‐smart phone users (Table 1).
| Smart Phone Users (N=115) | Non‐Smart Phone Users (N=88) | P Valuea | |
|---|---|---|---|
| |||
| Age, median (range), y | 28 (2048) | 29 (1952) | 0.03 |
| Gender, female | 92 (80.0%) | 68 (77.3%) | 0.64 |
| ICU workers | 78 (67.8%) | 57 (64.8%) | 0.65 |
| Occupation | 0.93 | ||
| Physicians | 45 (39.1%) | 35 (39.8%) | |
| Nurses | 63 (54.8%) | 43 (48.9%) | |
| Others | 7 (6.1%) | 10 (11.4%) | |
| Direct contact with patients | 110 (95.7%) | 84 (95.5%) | 0.95 |
| Using phones during work hours | 53 (46.1%) | 45 (51.1%) | 0.48 |
| Frequency of using phones during working | 0.46 | ||
| 13 | 8 (7.0%) | 10 (11.4%) | |
| 46 | 11 (9.6%) | 6 (6.8%) | |
| 79 | 8 (7.0%) | 1 (1.1%) | |
| Over 10 times | 26 (22.6%) | 28 (31.8%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Reason of using phones | 0.04 | ||
| Calling | 30 (26.1%) | 42 (47.7%) | |
| Mail check or searching information | 3 (2.6%) | 0 | |
| Both reasons | 20 (17.4%) | 3 (3.4%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Routine cleaning of phones | 15 (13.2%) | 11 (12.8%) | 0.94 |
| Frequency of cleaning hands (times/day) | 0.21 | ||
| 03 | 1 (0.9%) | 4 (4.5%) | |
| 46 | 18 (15.7%) | 14 (15.9%) | |
| 710 | 13 (11.3%) | 13 (14.8%) | |
| Over 10 | 83 (72.2%) | 57 (64.8%) | |
| Methods of cleaning hands | 0.72 | ||
| Washing with soaps | 48 (41.7%) | 34 (38.6%) | |
| Disinfectant | 42 (36.5%) | 33 (37.5%) | |
| Both | 25 (21.8%) | 21 (23.8%) | |
Smart phone users were slightly younger than non‐smart phone users. The distribution of occupations did not differ between the two groups. The frequency of use, reasons for using cell phones, the proportion of participants who routinely cleaned their phone, and the frequency of hand washing were also similar (Table 1).
Bacteria Isolated From Cell Phones
Bacteria were isolated from all 203 mobile phones; 3 or more different types of bacteria were isolated from 155 (76.4%) phones, 2 types from 39 (19.2%) phones, and 1 type from 9 (4.4%) phones. The most commonly cultured micro‐organism was coagulase‐negative Staphylococcus, which was isolated from 194 (95.6%) cell phones. The isolation of Gram‐positive bacilli and Micrococcus species was also frequent.
Probable pathogenic bacteria were isolated from 58 (28.6%) mobile phones. Among probable pathogens, Staphylococcus aureus (S. aureus) was the most commonly isolated. Of the 50 mobile phones that were contaminated with S. aureus, 8 were contaminated with a methicillin‐resistant strain. Five (2.4%) phones yielded Acinetobacter baumannii (Table 2).
| Organisms | Total, N=203 | No. of Drug Resistant Strains |
|---|---|---|
| Probable pathogen | ||
| Gram‐positive bacteria | ||
| Staphylococcus aureus | 50 (24.6%) | 8 (16%) |
| Streptococcus agalactiae | 1 (0.5%) | 0 |
| Enterococcus faecium | 1 (0.5%) | 1 (100%) |
| Gram‐negative bacteria | ||
| Acinetobacter baumannii | 5 (2.4%) | 1 (20%) |
| Pseudomonas aeruginosa | 1 (0.5%) | 0 |
| Enterobacter cloacae | 2 (1.0%) | 0 |
Although all mobile phones were contaminated with bacteria, probable pathogens were isolated more often from smart phones (34.8% vs 20.5% of non‐smart phones, P=0.03). The total colony count of probable pathogens from smart phones was also higher (average, 5.5 vs 5.0 from non‐smart phones, P=0.01). The isolation rate of drug‐resistant pathogens appeared to be higher from smart phones (7.0% vs 2.3% from non‐smart phones), but this difference did not reach statistical significance (P=0.19).
Risk Factors for Contamination With Probable Pathogens
In the final model constructed to determine the risk factors for contamination with probable pathogenic bacteria, data regarding cell phone users' age, gender, occupation (ie, physician or not), duration of working in the same place, daily work hours, whether the phone was a smart phone, and frequency of cell phone use during working hours were included. Among these factors, only the phone's being a smart phone was found to be a risk factor for contamination by bacteria with pathogenic potential (adjusted odds ratio (OR), 4.02; 95% CI, 1.43‐11.31; P=0.01). The fitness of this model was confirmed with the Hosmer‐Lemeshow GOF test (P=0.94). Using the cell phone more than 10 times during working hours appeared to be associated with pathogen contamination; however, this correlation failed to reach statistical significance (OR, 2.9; 95% CI, 0.9‐9.3; P=0.07).
DISCUSSION
Our study showed that smart phones were more frequently contaminated with bacteria than were non‐smart phones. In addition, total colony count of probable pathogens from smart phones was also higher. The colony count as well as contamination rate of pathogens are clinically relevant, because both factors can attribute to increased transmission of pathogens.[11]
Previous studies have attempted to identify user risk factors associated with bacterial contamination of cell phones.[12, 13, 14] Many variables, including gender, frequency of use, type of phone, work time, and the medical specialty of the user were considered; however, none of these factors was associated with an increased risk of bacterial contamination.[2, 14, 15]
In our study, none of the above‐mentioned factors was associated with contamination of cell phones by potentially pathogenic bacteria. Smart phones were the sole predictor of contamination by such bacteria. The reason that smart phones were more frequently contaminated with bacteria with pathogenic potential than were non‐smart phones is not clear. We propose two hypotheses to explain this observation. First, smart phones generally have wide screens, whereas non‐smart phones have relatively small screens with keypads. Larger screens may afford more opportunity for contamination by micro‐organisms. The mean size of a monitor in the smart phone group was 6633.2 340.1 cm2 and 5729.4564.7 cm2 in the non‐smart phone group (P<0.01). However, in a multivariate model including size with other variables above, the smart phone remained a significant risk factor for the pathogen contamination (odds ratio [OR], 4.17; 95% CI, 1.06‐16.33; P=0.04). Cell phones are manufactured in a standardized form and the size cannot be changed or controlled. Therefore, we did not include the size in the final model of logistic regression in the main result. Our second explanation is in regard to the pattern of use of smart phones. Considering a single use, smart phones are used for longer periods and require a higher number of finger touches compared with non‐smart phones. The intensive use of phones with large screens could facilitate contamination of smart phones by pathogens from the healthcare workers' fingers or palms.
A recent study showed that cleaning cell phones on a daily basis decreased contamination rates. However, it did not decrease contamination by potentially pathogenic bacteria.[12] The role of the hospital environment as a reservoir of nosocomial pathogens and the effect of sanitization on decreasing clinical infection are still controversial.[16, 17, 18, 19] Thus, further studies are needed to recommend routine cell phone sanitizing and to declare that it is relevant in terms of reduction of hospital‐acquired infections potentially associated with the mobile phones of healthcare workers.
Our study is subject to limitation. Lack of association between hand washing and pathogen contamination might be a result of false reporting on hand washing behavior as well as the small number of participants. The bacterial contamination rate of the folding type of non‐smart phones may have been underestimated, as their keypads could not contact agar plates because they would not opened flatly (we touched the exterior surface of the folding type phones, which did not harbor the keypad, to the agar plate). However, given that folding phones are usually stored in their folded position, bacteria on the outside of the phones are likely more relevant than those within keypads insofar as transmission is concerned.
In summary, our data showed that over one‐fourth of the mobile phones examined in this study were found to harbor potentially pathogenic micro‐organisms. In particular, smart phones of healthcare workers were more frequently contaminated with potentially pathogenic bacteria than were non‐smart phones even after adjusting for the phone size. Preventive measures to minimize the possibility of bacterial transmission via cell phones should be devised.
Disclosure
This study was funded by grant 04‐2011‐1020 from the Seoul National University College of Medicine Research Fund (Seoul, South Korea). The sponsor of the study had no role in the tudy design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors declare that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
- , , , et al. Evidence‐based policy? The use of mobile phones in hospital. J Public Health (Oxf). 2006;28:299–303.
- , , , , . Is your phone bugged? The incidence of bacteria known to cause nosocomial infection on healthcare workers' mobile phones. J Hosp Infect. 2006;62:123–125.
- , , , , . Bacterial contamination of mobile communication devices in the operative environment. J Hosp Infect. 2007;66:397–398.
- , , , . Review of mobile communication devices as potential reservoirs of nosocomial pathogens. J Hosp Infect. 2009;71:295–300.
- , , . Use of SMS text messaging to improve outpatient attendance. Med J Aust. 2005;183:366–368.
- , , , et al. The use of text messaging to improve attendance in primary care: a randomized controlled trial. Fam Pract. 2006;23:699–705.
- , , , . Mobile phone text messaging in the management of diabetes. J Telemed Telecare. 2004;10:282–285.
- , , , , . Mobile phone text messaging can help young people manage asthma. BMJ. 2002;325:600.
- , , , et al. Use of cellular telephones and transmission of pathogens by medical staff in New York and Israel. Infect Control Hosp Epidemiol. 2007;28:500–503.
- Feature phone. Phone Scoop Web site. Available at: http://www.phonescoop.com/glossary/term.php?gid=310. Accessed June 22, 2011.
- , , . Comparison of two possible routes of pathogen contamination of spinach leaves in a hydroponic cultivation system. J Food Prot 2011;74:1536–1542.
- , , , et al. Use of mobile phones by medical staff at Queen Elizabeth Hospital, Barbados: evidence for both benefit and harm. J Hosp Infect. 2008;70:160–165.
- , , , . Pathogenic bacteria on personal pagers. Am J Infect Control. 2000;28:387–388.
- , , , , , . Bacterial contamination of health care workers' pagers and the efficacy of various disinfecting agents. Pediatr Infect Dis J. 2006;25: 1074–1075.
- , , . Preventing transmission of multidrug‐resistant bacteria in health care settings: a tale of 2 guidelines. Clin Infect Dis. 2006;42:828–835.
- . Environmental contamination makes an important contribution to hospital infection. J Hosp Infect. 2007;65(suppl 2):50–54.
- , , , . Widespread environmental contamination associated with patients with diarrhea and methicillin‐resistant Staphylococcus aureus colonization of the gastrointestinal tract. Infect Control Hosp Epidemiol. 2007;28:1142–1147.
- , , , , . Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control. 2000;28:465–471.
- , , , , , . Routine disinfection of patients' environmental surfaces. Myth or reality? J Hosp Infect. 1999;42:113–117.
Mobile phones are now widely used. Healthcare workers, in particular, use them for rapid communication in many hospital settings. As mobile phones increase in popularity, a number of concerns have been raised, including noise and distraction in the clinical environment, confidentiality of patient information, and data security among others.[1]
Of the various concerns regarding mobile phone use in hospitals, one of the most important is that mobile phones may serve as vehicles for nosocomial transmission of micro‐organisms.[2, 3] One report showed that over 90% of healthcare workers' cell phones were contaminated with micro‐organisms, and 14.3% of cell phones were contaminated with bacteria that can cause nosocomial infection.[2]
Smart phones, which are rapidly flooding the mobile phone market, are useful in the hospital setting, as they could provide rapid access to medical information, quicker consultation and responding, feedback of results to the patient, and ongoing monitoring of chronic diseases (eg, asthma and diabetes).[4, 5, 6, 7, 8]
However, as most smart phones have wide, full, touch screens and are used more often by their owners than non‐smart phones are, bacterial contamination rates may be higher than those of non‐smart phones. The aim of this study was to compare the contamination rates by bacteria with pathogenic potential in smart phones versus non‐smart phones.
MATERIALS AND METHODS
Study Design and Participants
This cross‐sectional study was conducted from March 1, 2011 to June 30, 2011, in 3 teaching hospitals affiliated with Seoul National University School of Medicine, namely Seoul National University Hospital, Bundang Seoul National University Hospital, and Seoul National University Boramae Medical Center. Hospital staff working in general wards as well as in intensive care units of the 3 hospitals were invited to participate in this study. The study protocol was approved by the institutional review board of each of the 3 participating hospitals. Informed consent was obtained from all participants.
Questionnaire
We designed a questionnaire inquiring about demographics (age, gender, occupation) as well as behavior regarding cell phone use (type of cell phone, frequency and reasons for use, cleaning of cell phones).
Bacterial Culture, Identification, and Drug Susceptibility Testing
Both the anterior and posterior surfaces of each participant's mobile phone were touched onto blood agar plates. The sampled culture plates were subsequently incubated aerobically at 36C for 48 hours. To identify cultivated micro‐organisms and for the assessment of antibiotic susceptibility, VITEK2 (bioMrieux, Inc., Durham, NC) systems were used.
Classification of Isolated Micro‐organisms
We classified the micro‐organisms isolated from healthcare workers' mobile phones as bacteria with pathogenic potential (probable pathogens) or nonpathogens.[4, 9] Among probable pathogenic micro‐organisms, representative drug‐resistant strains such as methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant Enterococcus (VRE), and imipenem‐resistant Acinetobacter baumannii (IRAB) were categorized as drug‐resistant pathogens.
Classification of Smart Phones Versus Non‐Smart Phones
Mobile phones that ran complete mobile operating systems and software that provided a standardized interface and a platform for application developers, were classified as smart phones.[10] All others were classified as non‐smart phones.
Statistical Analysis
The participants' clinical variables were analyzed using descriptive statistics. The results are expressed as meanstandard deviation or median value with range. Variables were compared between the smart phone and non‐smart phone users. Categorical variables were compared by [2] analysis, and continuous variables were compared using Student t test or the Mann‐Whitney test. Variables with P<0.20 after univariate analysis or clinically significant variables were subjected to multiple logistic regression to determine the risk factors for contamination of cell phones with potentially pathogenic bacteria. For all analyses, P values <0.05 were considered significant. Homer‐Lemeshow goodness of fit (GOF) test was performed to confirm the fitness of the final model. The Statistical Package for the Social Sciences version 17.0 (IBM SPSS, Armonk, NY) was used for all statistical analysis.
RESULTS
Participants and Their Behaviors Regarding Cell Phone Use
In total, 203 healthcare workers participated in this study; 80 (39.4%) were physicians, 106 (52.2%) were nurses, and 17 (8.4%) were assistants. The median age of the participants was 29 years, 43 (21.2%) were males, 115 (56.7%) participants used smart phones, and 88 (43.3%) were non‐smart phone users (Table 1).
| Smart Phone Users (N=115) | Non‐Smart Phone Users (N=88) | P Valuea | |
|---|---|---|---|
| |||
| Age, median (range), y | 28 (2048) | 29 (1952) | 0.03 |
| Gender, female | 92 (80.0%) | 68 (77.3%) | 0.64 |
| ICU workers | 78 (67.8%) | 57 (64.8%) | 0.65 |
| Occupation | 0.93 | ||
| Physicians | 45 (39.1%) | 35 (39.8%) | |
| Nurses | 63 (54.8%) | 43 (48.9%) | |
| Others | 7 (6.1%) | 10 (11.4%) | |
| Direct contact with patients | 110 (95.7%) | 84 (95.5%) | 0.95 |
| Using phones during work hours | 53 (46.1%) | 45 (51.1%) | 0.48 |
| Frequency of using phones during working | 0.46 | ||
| 13 | 8 (7.0%) | 10 (11.4%) | |
| 46 | 11 (9.6%) | 6 (6.8%) | |
| 79 | 8 (7.0%) | 1 (1.1%) | |
| Over 10 times | 26 (22.6%) | 28 (31.8%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Reason of using phones | 0.04 | ||
| Calling | 30 (26.1%) | 42 (47.7%) | |
| Mail check or searching information | 3 (2.6%) | 0 | |
| Both reasons | 20 (17.4%) | 3 (3.4%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Routine cleaning of phones | 15 (13.2%) | 11 (12.8%) | 0.94 |
| Frequency of cleaning hands (times/day) | 0.21 | ||
| 03 | 1 (0.9%) | 4 (4.5%) | |
| 46 | 18 (15.7%) | 14 (15.9%) | |
| 710 | 13 (11.3%) | 13 (14.8%) | |
| Over 10 | 83 (72.2%) | 57 (64.8%) | |
| Methods of cleaning hands | 0.72 | ||
| Washing with soaps | 48 (41.7%) | 34 (38.6%) | |
| Disinfectant | 42 (36.5%) | 33 (37.5%) | |
| Both | 25 (21.8%) | 21 (23.8%) | |
Smart phone users were slightly younger than non‐smart phone users. The distribution of occupations did not differ between the two groups. The frequency of use, reasons for using cell phones, the proportion of participants who routinely cleaned their phone, and the frequency of hand washing were also similar (Table 1).
Bacteria Isolated From Cell Phones
Bacteria were isolated from all 203 mobile phones; 3 or more different types of bacteria were isolated from 155 (76.4%) phones, 2 types from 39 (19.2%) phones, and 1 type from 9 (4.4%) phones. The most commonly cultured micro‐organism was coagulase‐negative Staphylococcus, which was isolated from 194 (95.6%) cell phones. The isolation of Gram‐positive bacilli and Micrococcus species was also frequent.
Probable pathogenic bacteria were isolated from 58 (28.6%) mobile phones. Among probable pathogens, Staphylococcus aureus (S. aureus) was the most commonly isolated. Of the 50 mobile phones that were contaminated with S. aureus, 8 were contaminated with a methicillin‐resistant strain. Five (2.4%) phones yielded Acinetobacter baumannii (Table 2).
| Organisms | Total, N=203 | No. of Drug Resistant Strains |
|---|---|---|
| Probable pathogen | ||
| Gram‐positive bacteria | ||
| Staphylococcus aureus | 50 (24.6%) | 8 (16%) |
| Streptococcus agalactiae | 1 (0.5%) | 0 |
| Enterococcus faecium | 1 (0.5%) | 1 (100%) |
| Gram‐negative bacteria | ||
| Acinetobacter baumannii | 5 (2.4%) | 1 (20%) |
| Pseudomonas aeruginosa | 1 (0.5%) | 0 |
| Enterobacter cloacae | 2 (1.0%) | 0 |
Although all mobile phones were contaminated with bacteria, probable pathogens were isolated more often from smart phones (34.8% vs 20.5% of non‐smart phones, P=0.03). The total colony count of probable pathogens from smart phones was also higher (average, 5.5 vs 5.0 from non‐smart phones, P=0.01). The isolation rate of drug‐resistant pathogens appeared to be higher from smart phones (7.0% vs 2.3% from non‐smart phones), but this difference did not reach statistical significance (P=0.19).
Risk Factors for Contamination With Probable Pathogens
In the final model constructed to determine the risk factors for contamination with probable pathogenic bacteria, data regarding cell phone users' age, gender, occupation (ie, physician or not), duration of working in the same place, daily work hours, whether the phone was a smart phone, and frequency of cell phone use during working hours were included. Among these factors, only the phone's being a smart phone was found to be a risk factor for contamination by bacteria with pathogenic potential (adjusted odds ratio (OR), 4.02; 95% CI, 1.43‐11.31; P=0.01). The fitness of this model was confirmed with the Hosmer‐Lemeshow GOF test (P=0.94). Using the cell phone more than 10 times during working hours appeared to be associated with pathogen contamination; however, this correlation failed to reach statistical significance (OR, 2.9; 95% CI, 0.9‐9.3; P=0.07).
DISCUSSION
Our study showed that smart phones were more frequently contaminated with bacteria than were non‐smart phones. In addition, total colony count of probable pathogens from smart phones was also higher. The colony count as well as contamination rate of pathogens are clinically relevant, because both factors can attribute to increased transmission of pathogens.[11]
Previous studies have attempted to identify user risk factors associated with bacterial contamination of cell phones.[12, 13, 14] Many variables, including gender, frequency of use, type of phone, work time, and the medical specialty of the user were considered; however, none of these factors was associated with an increased risk of bacterial contamination.[2, 14, 15]
In our study, none of the above‐mentioned factors was associated with contamination of cell phones by potentially pathogenic bacteria. Smart phones were the sole predictor of contamination by such bacteria. The reason that smart phones were more frequently contaminated with bacteria with pathogenic potential than were non‐smart phones is not clear. We propose two hypotheses to explain this observation. First, smart phones generally have wide screens, whereas non‐smart phones have relatively small screens with keypads. Larger screens may afford more opportunity for contamination by micro‐organisms. The mean size of a monitor in the smart phone group was 6633.2 340.1 cm2 and 5729.4564.7 cm2 in the non‐smart phone group (P<0.01). However, in a multivariate model including size with other variables above, the smart phone remained a significant risk factor for the pathogen contamination (odds ratio [OR], 4.17; 95% CI, 1.06‐16.33; P=0.04). Cell phones are manufactured in a standardized form and the size cannot be changed or controlled. Therefore, we did not include the size in the final model of logistic regression in the main result. Our second explanation is in regard to the pattern of use of smart phones. Considering a single use, smart phones are used for longer periods and require a higher number of finger touches compared with non‐smart phones. The intensive use of phones with large screens could facilitate contamination of smart phones by pathogens from the healthcare workers' fingers or palms.
A recent study showed that cleaning cell phones on a daily basis decreased contamination rates. However, it did not decrease contamination by potentially pathogenic bacteria.[12] The role of the hospital environment as a reservoir of nosocomial pathogens and the effect of sanitization on decreasing clinical infection are still controversial.[16, 17, 18, 19] Thus, further studies are needed to recommend routine cell phone sanitizing and to declare that it is relevant in terms of reduction of hospital‐acquired infections potentially associated with the mobile phones of healthcare workers.
Our study is subject to limitation. Lack of association between hand washing and pathogen contamination might be a result of false reporting on hand washing behavior as well as the small number of participants. The bacterial contamination rate of the folding type of non‐smart phones may have been underestimated, as their keypads could not contact agar plates because they would not opened flatly (we touched the exterior surface of the folding type phones, which did not harbor the keypad, to the agar plate). However, given that folding phones are usually stored in their folded position, bacteria on the outside of the phones are likely more relevant than those within keypads insofar as transmission is concerned.
In summary, our data showed that over one‐fourth of the mobile phones examined in this study were found to harbor potentially pathogenic micro‐organisms. In particular, smart phones of healthcare workers were more frequently contaminated with potentially pathogenic bacteria than were non‐smart phones even after adjusting for the phone size. Preventive measures to minimize the possibility of bacterial transmission via cell phones should be devised.
Disclosure
This study was funded by grant 04‐2011‐1020 from the Seoul National University College of Medicine Research Fund (Seoul, South Korea). The sponsor of the study had no role in the tudy design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors declare that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
Mobile phones are now widely used. Healthcare workers, in particular, use them for rapid communication in many hospital settings. As mobile phones increase in popularity, a number of concerns have been raised, including noise and distraction in the clinical environment, confidentiality of patient information, and data security among others.[1]
Of the various concerns regarding mobile phone use in hospitals, one of the most important is that mobile phones may serve as vehicles for nosocomial transmission of micro‐organisms.[2, 3] One report showed that over 90% of healthcare workers' cell phones were contaminated with micro‐organisms, and 14.3% of cell phones were contaminated with bacteria that can cause nosocomial infection.[2]
Smart phones, which are rapidly flooding the mobile phone market, are useful in the hospital setting, as they could provide rapid access to medical information, quicker consultation and responding, feedback of results to the patient, and ongoing monitoring of chronic diseases (eg, asthma and diabetes).[4, 5, 6, 7, 8]
However, as most smart phones have wide, full, touch screens and are used more often by their owners than non‐smart phones are, bacterial contamination rates may be higher than those of non‐smart phones. The aim of this study was to compare the contamination rates by bacteria with pathogenic potential in smart phones versus non‐smart phones.
MATERIALS AND METHODS
Study Design and Participants
This cross‐sectional study was conducted from March 1, 2011 to June 30, 2011, in 3 teaching hospitals affiliated with Seoul National University School of Medicine, namely Seoul National University Hospital, Bundang Seoul National University Hospital, and Seoul National University Boramae Medical Center. Hospital staff working in general wards as well as in intensive care units of the 3 hospitals were invited to participate in this study. The study protocol was approved by the institutional review board of each of the 3 participating hospitals. Informed consent was obtained from all participants.
Questionnaire
We designed a questionnaire inquiring about demographics (age, gender, occupation) as well as behavior regarding cell phone use (type of cell phone, frequency and reasons for use, cleaning of cell phones).
Bacterial Culture, Identification, and Drug Susceptibility Testing
Both the anterior and posterior surfaces of each participant's mobile phone were touched onto blood agar plates. The sampled culture plates were subsequently incubated aerobically at 36C for 48 hours. To identify cultivated micro‐organisms and for the assessment of antibiotic susceptibility, VITEK2 (bioMrieux, Inc., Durham, NC) systems were used.
Classification of Isolated Micro‐organisms
We classified the micro‐organisms isolated from healthcare workers' mobile phones as bacteria with pathogenic potential (probable pathogens) or nonpathogens.[4, 9] Among probable pathogenic micro‐organisms, representative drug‐resistant strains such as methicillin‐resistant Staphylococcus aureus (MRSA), vancomycin‐resistant Enterococcus (VRE), and imipenem‐resistant Acinetobacter baumannii (IRAB) were categorized as drug‐resistant pathogens.
Classification of Smart Phones Versus Non‐Smart Phones
Mobile phones that ran complete mobile operating systems and software that provided a standardized interface and a platform for application developers, were classified as smart phones.[10] All others were classified as non‐smart phones.
Statistical Analysis
The participants' clinical variables were analyzed using descriptive statistics. The results are expressed as meanstandard deviation or median value with range. Variables were compared between the smart phone and non‐smart phone users. Categorical variables were compared by [2] analysis, and continuous variables were compared using Student t test or the Mann‐Whitney test. Variables with P<0.20 after univariate analysis or clinically significant variables were subjected to multiple logistic regression to determine the risk factors for contamination of cell phones with potentially pathogenic bacteria. For all analyses, P values <0.05 were considered significant. Homer‐Lemeshow goodness of fit (GOF) test was performed to confirm the fitness of the final model. The Statistical Package for the Social Sciences version 17.0 (IBM SPSS, Armonk, NY) was used for all statistical analysis.
RESULTS
Participants and Their Behaviors Regarding Cell Phone Use
In total, 203 healthcare workers participated in this study; 80 (39.4%) were physicians, 106 (52.2%) were nurses, and 17 (8.4%) were assistants. The median age of the participants was 29 years, 43 (21.2%) were males, 115 (56.7%) participants used smart phones, and 88 (43.3%) were non‐smart phone users (Table 1).
| Smart Phone Users (N=115) | Non‐Smart Phone Users (N=88) | P Valuea | |
|---|---|---|---|
| |||
| Age, median (range), y | 28 (2048) | 29 (1952) | 0.03 |
| Gender, female | 92 (80.0%) | 68 (77.3%) | 0.64 |
| ICU workers | 78 (67.8%) | 57 (64.8%) | 0.65 |
| Occupation | 0.93 | ||
| Physicians | 45 (39.1%) | 35 (39.8%) | |
| Nurses | 63 (54.8%) | 43 (48.9%) | |
| Others | 7 (6.1%) | 10 (11.4%) | |
| Direct contact with patients | 110 (95.7%) | 84 (95.5%) | 0.95 |
| Using phones during work hours | 53 (46.1%) | 45 (51.1%) | 0.48 |
| Frequency of using phones during working | 0.46 | ||
| 13 | 8 (7.0%) | 10 (11.4%) | |
| 46 | 11 (9.6%) | 6 (6.8%) | |
| 79 | 8 (7.0%) | 1 (1.1%) | |
| Over 10 times | 26 (22.6%) | 28 (31.8%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Reason of using phones | 0.04 | ||
| Calling | 30 (26.1%) | 42 (47.7%) | |
| Mail check or searching information | 3 (2.6%) | 0 | |
| Both reasons | 20 (17.4%) | 3 (3.4%) | |
| None | 62 (53.9%) | 43 (48.9%) | |
| Routine cleaning of phones | 15 (13.2%) | 11 (12.8%) | 0.94 |
| Frequency of cleaning hands (times/day) | 0.21 | ||
| 03 | 1 (0.9%) | 4 (4.5%) | |
| 46 | 18 (15.7%) | 14 (15.9%) | |
| 710 | 13 (11.3%) | 13 (14.8%) | |
| Over 10 | 83 (72.2%) | 57 (64.8%) | |
| Methods of cleaning hands | 0.72 | ||
| Washing with soaps | 48 (41.7%) | 34 (38.6%) | |
| Disinfectant | 42 (36.5%) | 33 (37.5%) | |
| Both | 25 (21.8%) | 21 (23.8%) | |
Smart phone users were slightly younger than non‐smart phone users. The distribution of occupations did not differ between the two groups. The frequency of use, reasons for using cell phones, the proportion of participants who routinely cleaned their phone, and the frequency of hand washing were also similar (Table 1).
Bacteria Isolated From Cell Phones
Bacteria were isolated from all 203 mobile phones; 3 or more different types of bacteria were isolated from 155 (76.4%) phones, 2 types from 39 (19.2%) phones, and 1 type from 9 (4.4%) phones. The most commonly cultured micro‐organism was coagulase‐negative Staphylococcus, which was isolated from 194 (95.6%) cell phones. The isolation of Gram‐positive bacilli and Micrococcus species was also frequent.
Probable pathogenic bacteria were isolated from 58 (28.6%) mobile phones. Among probable pathogens, Staphylococcus aureus (S. aureus) was the most commonly isolated. Of the 50 mobile phones that were contaminated with S. aureus, 8 were contaminated with a methicillin‐resistant strain. Five (2.4%) phones yielded Acinetobacter baumannii (Table 2).
| Organisms | Total, N=203 | No. of Drug Resistant Strains |
|---|---|---|
| Probable pathogen | ||
| Gram‐positive bacteria | ||
| Staphylococcus aureus | 50 (24.6%) | 8 (16%) |
| Streptococcus agalactiae | 1 (0.5%) | 0 |
| Enterococcus faecium | 1 (0.5%) | 1 (100%) |
| Gram‐negative bacteria | ||
| Acinetobacter baumannii | 5 (2.4%) | 1 (20%) |
| Pseudomonas aeruginosa | 1 (0.5%) | 0 |
| Enterobacter cloacae | 2 (1.0%) | 0 |
Although all mobile phones were contaminated with bacteria, probable pathogens were isolated more often from smart phones (34.8% vs 20.5% of non‐smart phones, P=0.03). The total colony count of probable pathogens from smart phones was also higher (average, 5.5 vs 5.0 from non‐smart phones, P=0.01). The isolation rate of drug‐resistant pathogens appeared to be higher from smart phones (7.0% vs 2.3% from non‐smart phones), but this difference did not reach statistical significance (P=0.19).
Risk Factors for Contamination With Probable Pathogens
In the final model constructed to determine the risk factors for contamination with probable pathogenic bacteria, data regarding cell phone users' age, gender, occupation (ie, physician or not), duration of working in the same place, daily work hours, whether the phone was a smart phone, and frequency of cell phone use during working hours were included. Among these factors, only the phone's being a smart phone was found to be a risk factor for contamination by bacteria with pathogenic potential (adjusted odds ratio (OR), 4.02; 95% CI, 1.43‐11.31; P=0.01). The fitness of this model was confirmed with the Hosmer‐Lemeshow GOF test (P=0.94). Using the cell phone more than 10 times during working hours appeared to be associated with pathogen contamination; however, this correlation failed to reach statistical significance (OR, 2.9; 95% CI, 0.9‐9.3; P=0.07).
DISCUSSION
Our study showed that smart phones were more frequently contaminated with bacteria than were non‐smart phones. In addition, total colony count of probable pathogens from smart phones was also higher. The colony count as well as contamination rate of pathogens are clinically relevant, because both factors can attribute to increased transmission of pathogens.[11]
Previous studies have attempted to identify user risk factors associated with bacterial contamination of cell phones.[12, 13, 14] Many variables, including gender, frequency of use, type of phone, work time, and the medical specialty of the user were considered; however, none of these factors was associated with an increased risk of bacterial contamination.[2, 14, 15]
In our study, none of the above‐mentioned factors was associated with contamination of cell phones by potentially pathogenic bacteria. Smart phones were the sole predictor of contamination by such bacteria. The reason that smart phones were more frequently contaminated with bacteria with pathogenic potential than were non‐smart phones is not clear. We propose two hypotheses to explain this observation. First, smart phones generally have wide screens, whereas non‐smart phones have relatively small screens with keypads. Larger screens may afford more opportunity for contamination by micro‐organisms. The mean size of a monitor in the smart phone group was 6633.2 340.1 cm2 and 5729.4564.7 cm2 in the non‐smart phone group (P<0.01). However, in a multivariate model including size with other variables above, the smart phone remained a significant risk factor for the pathogen contamination (odds ratio [OR], 4.17; 95% CI, 1.06‐16.33; P=0.04). Cell phones are manufactured in a standardized form and the size cannot be changed or controlled. Therefore, we did not include the size in the final model of logistic regression in the main result. Our second explanation is in regard to the pattern of use of smart phones. Considering a single use, smart phones are used for longer periods and require a higher number of finger touches compared with non‐smart phones. The intensive use of phones with large screens could facilitate contamination of smart phones by pathogens from the healthcare workers' fingers or palms.
A recent study showed that cleaning cell phones on a daily basis decreased contamination rates. However, it did not decrease contamination by potentially pathogenic bacteria.[12] The role of the hospital environment as a reservoir of nosocomial pathogens and the effect of sanitization on decreasing clinical infection are still controversial.[16, 17, 18, 19] Thus, further studies are needed to recommend routine cell phone sanitizing and to declare that it is relevant in terms of reduction of hospital‐acquired infections potentially associated with the mobile phones of healthcare workers.
Our study is subject to limitation. Lack of association between hand washing and pathogen contamination might be a result of false reporting on hand washing behavior as well as the small number of participants. The bacterial contamination rate of the folding type of non‐smart phones may have been underestimated, as their keypads could not contact agar plates because they would not opened flatly (we touched the exterior surface of the folding type phones, which did not harbor the keypad, to the agar plate). However, given that folding phones are usually stored in their folded position, bacteria on the outside of the phones are likely more relevant than those within keypads insofar as transmission is concerned.
In summary, our data showed that over one‐fourth of the mobile phones examined in this study were found to harbor potentially pathogenic micro‐organisms. In particular, smart phones of healthcare workers were more frequently contaminated with potentially pathogenic bacteria than were non‐smart phones even after adjusting for the phone size. Preventive measures to minimize the possibility of bacterial transmission via cell phones should be devised.
Disclosure
This study was funded by grant 04‐2011‐1020 from the Seoul National University College of Medicine Research Fund (Seoul, South Korea). The sponsor of the study had no role in the tudy design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors declare that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
- , , , et al. Evidence‐based policy? The use of mobile phones in hospital. J Public Health (Oxf). 2006;28:299–303.
- , , , , . Is your phone bugged? The incidence of bacteria known to cause nosocomial infection on healthcare workers' mobile phones. J Hosp Infect. 2006;62:123–125.
- , , , , . Bacterial contamination of mobile communication devices in the operative environment. J Hosp Infect. 2007;66:397–398.
- , , , . Review of mobile communication devices as potential reservoirs of nosocomial pathogens. J Hosp Infect. 2009;71:295–300.
- , , . Use of SMS text messaging to improve outpatient attendance. Med J Aust. 2005;183:366–368.
- , , , et al. The use of text messaging to improve attendance in primary care: a randomized controlled trial. Fam Pract. 2006;23:699–705.
- , , , . Mobile phone text messaging in the management of diabetes. J Telemed Telecare. 2004;10:282–285.
- , , , , . Mobile phone text messaging can help young people manage asthma. BMJ. 2002;325:600.
- , , , et al. Use of cellular telephones and transmission of pathogens by medical staff in New York and Israel. Infect Control Hosp Epidemiol. 2007;28:500–503.
- Feature phone. Phone Scoop Web site. Available at: http://www.phonescoop.com/glossary/term.php?gid=310. Accessed June 22, 2011.
- , , . Comparison of two possible routes of pathogen contamination of spinach leaves in a hydroponic cultivation system. J Food Prot 2011;74:1536–1542.
- , , , et al. Use of mobile phones by medical staff at Queen Elizabeth Hospital, Barbados: evidence for both benefit and harm. J Hosp Infect. 2008;70:160–165.
- , , , . Pathogenic bacteria on personal pagers. Am J Infect Control. 2000;28:387–388.
- , , , , , . Bacterial contamination of health care workers' pagers and the efficacy of various disinfecting agents. Pediatr Infect Dis J. 2006;25: 1074–1075.
- , , . Preventing transmission of multidrug‐resistant bacteria in health care settings: a tale of 2 guidelines. Clin Infect Dis. 2006;42:828–835.
- . Environmental contamination makes an important contribution to hospital infection. J Hosp Infect. 2007;65(suppl 2):50–54.
- , , , . Widespread environmental contamination associated with patients with diarrhea and methicillin‐resistant Staphylococcus aureus colonization of the gastrointestinal tract. Infect Control Hosp Epidemiol. 2007;28:1142–1147.
- , , , , . Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control. 2000;28:465–471.
- , , , , , . Routine disinfection of patients' environmental surfaces. Myth or reality? J Hosp Infect. 1999;42:113–117.
- , , , et al. Evidence‐based policy? The use of mobile phones in hospital. J Public Health (Oxf). 2006;28:299–303.
- , , , , . Is your phone bugged? The incidence of bacteria known to cause nosocomial infection on healthcare workers' mobile phones. J Hosp Infect. 2006;62:123–125.
- , , , , . Bacterial contamination of mobile communication devices in the operative environment. J Hosp Infect. 2007;66:397–398.
- , , , . Review of mobile communication devices as potential reservoirs of nosocomial pathogens. J Hosp Infect. 2009;71:295–300.
- , , . Use of SMS text messaging to improve outpatient attendance. Med J Aust. 2005;183:366–368.
- , , , et al. The use of text messaging to improve attendance in primary care: a randomized controlled trial. Fam Pract. 2006;23:699–705.
- , , , . Mobile phone text messaging in the management of diabetes. J Telemed Telecare. 2004;10:282–285.
- , , , , . Mobile phone text messaging can help young people manage asthma. BMJ. 2002;325:600.
- , , , et al. Use of cellular telephones and transmission of pathogens by medical staff in New York and Israel. Infect Control Hosp Epidemiol. 2007;28:500–503.
- Feature phone. Phone Scoop Web site. Available at: http://www.phonescoop.com/glossary/term.php?gid=310. Accessed June 22, 2011.
- , , . Comparison of two possible routes of pathogen contamination of spinach leaves in a hydroponic cultivation system. J Food Prot 2011;74:1536–1542.
- , , , et al. Use of mobile phones by medical staff at Queen Elizabeth Hospital, Barbados: evidence for both benefit and harm. J Hosp Infect. 2008;70:160–165.
- , , , . Pathogenic bacteria on personal pagers. Am J Infect Control. 2000;28:387–388.
- , , , , , . Bacterial contamination of health care workers' pagers and the efficacy of various disinfecting agents. Pediatr Infect Dis J. 2006;25: 1074–1075.
- , , . Preventing transmission of multidrug‐resistant bacteria in health care settings: a tale of 2 guidelines. Clin Infect Dis. 2006;42:828–835.
- . Environmental contamination makes an important contribution to hospital infection. J Hosp Infect. 2007;65(suppl 2):50–54.
- , , , . Widespread environmental contamination associated with patients with diarrhea and methicillin‐resistant Staphylococcus aureus colonization of the gastrointestinal tract. Infect Control Hosp Epidemiol. 2007;28:1142–1147.
- , , , , . Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit. Am J Infect Control. 2000;28:465–471.
- , , , , , . Routine disinfection of patients' environmental surfaces. Myth or reality? J Hosp Infect. 1999;42:113–117.
Attendings' Perception of Housestaff
Clinical supervision in graduate medical education (GME) emphasizes patient safety while promoting development of clinical expertise by allowing trainees progressive independence.[1, 2, 3] The importance of the balance between supervision and autonomy has been recognized by accreditation organizations, namely the Institute of Medicine and the Accreditation Council for Graduate Medical Education (ACGME).[4, 5] However, little is known of best practices in supervision, and the model of progressive independence in clinical training lacks empirical support.[3] Limited evidence suggests that enhanced clinical supervision may have positive effects on patient and education‐related outcomes.[6, 7, 8, 9, 10, 11, 12, 13, 14, 15] However, a more nuanced understanding of potential effects of enhanced supervision on resident autonomy and decision making is still required, particularly as preliminary work on increased on‐site hospitalist supervision has yielded mixed results.[16, 17, 18, 19]
Understanding how trainees are entrusted with autonomy will be integral to the ACGME's Next Accreditation System.[20] Entrustable Professional Activities are benchmarks by which resident readiness to progress through training will be judged.[21] The extent to which trainees are entrusted with autonomy is largely determined by the subjective assessment of immediate supervisors, as autonomy is rarely measured or quantified.[3, 22, 23] This judgment of autonomy, most frequently performed by ward attendings, may be subject to significant variation and influenced by factors other than the resident's competence and clinical abilities.
To that end, it is worth considering what factors may affect attending perception of housestaff autonomy and decision making. Recent changes in the GME environment and policy implementation have altered the landscape of the attending workforce considerably. The growth of the hospitalist movement in teaching hospitals, in part due to duty hours, has led to more residents being supervised by hospitalists, who may perceive trainee autonomy differently than other attendings do.[24] This study aims to examine whether factors such as attending demographics and short‐term and long‐term secular trends influence attending perception of housestaff autonomy and participation in decision making.
METHODS
Study Design
From 2001 to 2008, attending physicians at a single academic institution were surveyed at the end of inpatient general medicine teaching rotations.[25] The University of Chicago general medicine service consists of ward teams of an attending physician (internists, hospitalists, or subspecialists), 1 senior resident, and 1 or 2 interns. Attendings serve for 2‐ or 4‐week rotations. Attendings were consented for participation and received a 40‐item, paper‐based survey at the rotation's end. The institutional review board approved this study.
Data Collection
From the 40 survey items, 2 statements were selected for analysis: The intern(s) were truly involved in decision making about their patients and My resident felt that s/he had sufficient autonomy this month. These items have been used in previous work studying attending‐resident dynamics.[19, 26] Attendings also reported demographic and professional information as well as self‐identified hospitalist status, ascertained by the question Do you consider yourself to be a hospitalist? Survey month and year were also recorded. We conducted a secondary data analysis of an inclusive sample of responses to the questions of interest.
Statistical Analysis
Descriptive statistics were used to summarize survey responses and demographics. Survey questions consisted of Likert‐type items. Because the distribution of responses was skewed toward strong agreement for both questions, we collapsed scores into 2 categories (Strongly Agree and Do Not Strongly Agree).[19] Perception of sufficient trainee autonomy was defined as a response of Strongly Agree. The Pearson 2 test was used to compare proportions, and t tests were used to compare mean years since completion of residency and weeks on service between different groups.
Multivariate logistic regression with stepwise forward regression was used to model the relationship between attending sex, institutional hospitalist designation, years of experience, implementation of duty‐hours restrictions, and academic season, and perception of trainee autonomy and decision making. Academic seasons were defined as summer (JulySeptember), fall (OctoberDecember), winter (JanuaryMarch) and spring (AprilJune).[26] Years of experience were divided into tertiles of years since residency: 04 years, 511 years, and >11 years. To account for the possibility that the effect of hospitalist specialty varied by experience, interaction terms were constructed. The interaction term hospitalist*early‐career was used as the reference group.
RESULTS
Seven hundred thirty‐eight surveys were distributed to attendings on inpatient general medicine teaching services from 2001 to 2008; 70% (n=514) were included in the analysis. Table 1 provides demographic characteristics of the respondents. Roughly half (47%) were female, and 23% were hospitalists. Experience ranged from 0 to 35 years, with a median of 7 years. Weeks on service per year ranged from 1 to 27, with a median of 6 weeks. Hospitalists represented a less‐experienced group of attendings, as their mean experience was 4.5 years (standard deviation [SD] 4.5) compared with 11.2 years (SD 7.7) for nonhospitalists (P<0.001). Hospitalists attended more frequently, with a mean 14.2 weeks on service (SD 6.5) compared with 5.8 weeks (SD 3.4) for nonhospitalists (P<0.001). Nineteen percent (n=98) of surveys were completed prior to the first ACGME duty‐hours restriction in 2003. Responses were distributed fairly equally across the academic year, with 29% completed in summer, 26% in fall, 24% in winter, and 21% in spring.
| Characteristics | Value |
|---|---|
| |
| Female, n (%) | 275 (47) |
| Hospitalist, n (%) | 125 (23) |
| Years since completion of residency | |
| Mean, median, SD | 9.3, 7, 7.6 |
| IQR | 314 |
| 04, n (%) | 167 (36) |
| 511, n (%) | 146 (32) |
| >11, n (%) | 149 (32) |
| Weeks on service per yearb | |
| Mean, median, SD | 8.1, 6, 5.8 |
| IQR | 412 |
Forty‐four percent (n=212) of attendings perceived adequate intern involvement in decision making, and 50% (n=238) perceived sufficient resident autonomy. The correlation coefficient between these 2 measures was 0.66.
Attending Factors Associated With Perception of Trainee Autonomy
In univariate analysis, hospitalists perceived sufficient trainee autonomy less frequently than nonhospitalists; 33% perceived adequate intern involvement in decision making compared with 48% of nonhospitalists (21=6.7, P=0.01), and 42% perceived sufficient resident autonomy compared with 54% of nonhospitalists (21=3.9, P=0.048) (Table 2).
| Attending Characteristics, n (%) | Agree With Intern Involvement in Decision Making | Agree With Sufficient Resident Autonomy |
|---|---|---|
| ||
| Designation | ||
| Hospitalist | 29 (33) | 37 (42) |
| Nonhospitalist | 163 (48) | 180 (54) |
| Years since completion of residency | ||
| 04 | 37 (27) | 49 (36) |
| 511 | 77 (53) | 88 (61) |
| >11 | 77 (53) | 81 (56) |
| Sex | ||
| F | 98 (46) | 100 (47) |
| M | 113 (43) | 138 (53) |
| Secular factors, n (%) | ||
| Pre‐2003 duty‐hours restrictions | 56 (57) | 62 (65) |
| Post‐2003 duty‐hours restrictions | 156 (41) | 176 (46) |
| Season of survey | ||
| Summer (JulySeptember) | 61 (45) | 69 (51) |
| Fall (OctoberDecember) | 53 (42) | 59 (48) |
| Winter (JanuaryMarch) | 42 (37) | 52 (46) |
| Spring (AprilJune) | 56 (54) | 58 (57) |
Perception of trainee autonomy increased with experience (Table 2). About 30% of early‐career attendings (04 years experience) perceived sufficient autonomy and involvement in decision making compared with >50% agreement in the later‐career tertiles (intern decision making: 22=25.1, P<0.001; resident autonomy: 22=18.9, P<0.001). Attendings perceiving more intern decision making involvement had a mean 11 years of experience (SD 7.1), whereas those perceiving less had a mean of 8.8 years (SD 7.8; P=0.003). Mean years of experience were similar for perception of resident autonomy (10.6 years [SD 7.2] vs 8.9 years [SD 7.8], P=0.021).
Sex was not associated with differences in perception of intern decision making (21=0.39, P=0.53) or resident autonomy (21=1.4, P=0.236) (Table 2).
Secular Factors Associated With Perception of Trainee Autonomy
The implementation of duty‐hour restrictions in 2003 was associated with decreased attending perception of autonomy. Only 41% of attendings perceived adequate intern involvement in decision making following the restrictions, compared with 57% before the restrictions were instituted (21=8.2, P=0.004). Similarly, 46% of attendings agreed with sufficient resident autonomy post‐duty hours, compared with 65% prior (21=10.1, P=0.001) (Table 2).
Academic season was also associated with differences in perception of autonomy (Table 2). In spring, 54% of attendings perceived adequate intern involvement in decision making, compared with 42% in the other seasons combined (21=5.34, P=0.021). Perception of resident autonomy was also higher in spring, though this was not statistically significant (57% in spring vs 48% in the other seasons; 21=2.37, P=0.123).
Multivariate Analyses
Variation in attending perception of housestaff autonomy by attending characteristics persisted in multivariate analysis. Table 3 shows ORs for perception of adequate intern involvement in decision making and sufficient resident autonomy. Sex was not a significant predictor of agreement with either statement. The odds that an attending would perceive adequate intern involvement in decision making were higher for later‐career attendings compared with early‐career attendings (ie, 04 years); attendings who completed residency 511 years ago were 2.16 more likely to perceive adequate involvement (OR: 2.16, 95% CI: 1.17‐3.97, P=0.013), and those >11 years from residency were 2.05 more likely (OR: 2.05, 95% CI: 1.16‐3.63, P=0.014). Later‐career attendings also had nonsignificant higher odds of perceiving sufficient resident autonomy compared with early‐career attendings (511 years, OR: 1.73, 95% CI: 0.963.14, P=0.07; >11 years, OR: 1.50, 95% CI: 0.862.62, P=0.154).
| Interns Involved With Decision Making | Resident Had Sufficient Autonomy | |||
|---|---|---|---|---|
| ||||
| Covariate | OR (95% CI) | P Value | OR (95% CI) | P Value |
| Attending characteristics | ||||
| 04 years of experience | ||||
| 511 years of experience | 2.16 (1.17‐3.97) | 0.013 | 1.73 (0.96‐3.14) | 0.07 |
| >11 years of experience | 2.05 (1.16‐3.63) | 0.014 | 1.50 (0.86‐2.62) | 0.154 |
| Hospitalist | 0.19 (0.06‐0.58) | 0.004 | 0.27 (0.11‐0.66) | 0.004 |
| Hospitalist 04 years of experiencea | ||||
| Hospitalist 511 years of experiencea | 7.36 (1.86‐29.1) | 0.004 | 5.85 (1.75‐19.6) | 0.004 |
| Hospitalist >11 years of experiencea | 21.2 (1.73‐260) | 0.017 | 14.4 (1.31‐159) | 0.029 |
| Female sex | 1.41 (0.92‐2.17) | 0.115 | 0.92 (0.60‐1.40) | 0.69 |
| Secular factors | ||||
| Post‐2003 duty hours | 0.51 (0.29‐0.87) | 0.014 | 0.49 (0.28‐0.86) | 0.012 |
| Spring academic season | 1.94 (1.18‐3.19) | 0.009 | 1.59 (0.97‐2.60) | 0.064 |
Hospitalists were associated with 81% lower odds of perceiving adequate intern involvement in decision making (OR: 0.19, 95% CI: 0.060.58, P=0.004) and 73% lower odds of perceiving sufficient resident autonomy compared with nonhospitalists (OR: 0.27, 95% CI: 0.110.66, P=0.004). However, there was a significant interaction between hospitalists and experience; compared with early‐career hospitalists, experienced hospitalists had higher odds of perceiving both adequate intern involvement in decision making (511 years, OR: 7.36, 95% CI: 1.8629.1, P=0.004; >11 years, OR: 21.2, 95% CI: 1.73260, P=0.017) and sufficient resident autonomy (511 years, OR: 5.85, 95% CI: 1.7519.6, P=0.004; >11 years, OR: 14.4, 95% CI: 1.3159, P=0.029) (Table 3).
Secular trends also remained associated with differences in perception of housestaff autonomy (Table 3). Attendings had 49% lower odds of perceiving adequate intern involvement in decision making in the years following duty‐hour limits compared with the years prior (OR: 0.51, 95% CI: 0.29‐0.87, P=0.014). Similarly, odds of perceiving sufficient resident autonomy were 51% lower post‐duty hours (OR: 0.49, 95% CI: 0.280.86, P=0.012). Spring season was associated with 94% higher odds of perceiving adequate intern involvement in decision making compared with other seasons (OR: 1.94, 95% 1.183.19, P=0.009). There were also nonsignificant higher odds of perception of sufficient resident autonomy in spring (OR: 1.59, 95% CI: 0.972.60, P=0.064). To address the possibility of associations due to secular trends resulting from repeated measures of attendings, models using attending fixed effects were also used. Clustering by attending, the associations between duty hours and perceiving sufficient resident autonomy and intern decision making both remained significant, but the association of spring season did not.
DISCUSSION
This study highlights that attendings' perception of housestaff autonomy varies by attending characteristics and secular trends. Specifically, early‐career attendings and hospitalists were less likely to perceive sufficient housestaff autonomy and involvement in decision making. However, there was a significant hospitalist‐experience interaction, such that more‐experienced hospitalists were associated with higher odds of perceiving sufficient autonomy than would be expected from the effect of experience alone. With respect to secular trends, attendings perceived more trainee autonomy in the last quarter of the academic year, and less autonomy after implementation of resident duty‐hour restrictions in 2003.
As Entrustable Professional Activities unveil a new emphasis on the notion of entrustment, it will be critical to ensure that attending assessment of resident performance is uniform and a valid judge of when to entrust autonomy.[27, 28] If, as suggested by these findings, perception of autonomy varies based on attending characteristics, all faculty may benefit from strategies to standardize assessment and evaluation skills to ensure trainees are appropriately progressing through various milestones to achieve competence. Our results suggest that faculty development may be particularly important for early‐career attendings and especially hospitalists.
Early‐career attendings may perceive less housestaff autonomy due to a reluctance to relinquish control over patient‐care duties and decision making when the attending is only a few years from residency. Hospitalists are relatively junior in most institutions and may be similar to early‐career attendings in that regard. It is noteworthy, however, that experienced hospitalists are associated with even greater perception of autonomy than would be predicted by years of experience alone. Hospitalists may gain experience at a rate faster than nonhospitalists, which could affect how they perceive autonomy and decision making in trainees and may make them more comfortable entrusting autonomy to housestaff. Early‐career hospitalists likely represent a heterogeneous group of physicians, in both 1‐year clinical hospitalists as well as academic‐career hospitalists, who may have different approaches to managing housestaff teams. Residents are less likely to fear hospitalists limiting their autonomy after exposure to working with hospitalists as teaching attendings, and our findings may suggest a corollary in that hospitalists may be more likely to perceive sufficient autonomy with more exposure to working with housestaff.[19]
Attendings perceived less housestaff autonomy following the 2003 duty‐hour limits. This may be due to attendings assuming more responsibilities that were traditionally performed by residents.[26, 29] This shifting of responsibility may lead to perception of less‐active housestaff decision making and less‐evident autonomy. These findings suggest autonomy may become even more restricted after implementation of the 2011 duty‐hour restrictions, which included 16‐hour shifts for interns.[5] Further studies are warranted in examining the effect of these new limits. Entrustment of autonomy and allowance for decision making is an essential part of any learning environment that allows residents to develop clinical reasoning skills, and it will be critical to adopt new strategies to encourage professional growth of housestaff in this new era.[30]
Attendings also perceived autonomy differently by academic season. Spring represents the season by which housestaff are most experienced and by which attendings may be most familiar with individual team members. Additionally, there may be a stronger emphasis on supervision and adherence to traditional hierarchy earlier in the academic year as interns and junior residents are learning their new roles.[30] These findings may have implications for system changes to support development of more functional educational dyads between attendings and trainees, especially early in the academic year.[31]
There are several limitations to our findings. This is a single‐institution study restricted to the general‐medicine service; thus generalizability is limited. Our outcome measures, the survey items of interest, question perception of housestaff autonomy but do not query the appropriateness of that autonomy, an important construct in entrustment. Additionally, self‐reported answers could be subject to recall bias. Although data were collected over 8 years, the most recent trends of residency training are not reflected. Although there was a significant interaction involving experienced hospitalists, wide confidence intervals and large standard errors likely reflect the relatively few individuals in this category. Though there was a large number of overall respondents, our interaction terms included few advanced‐career hospitalists, likely secondary to hospital medicine's relative youth as a specialty.
As this study focuses only on perception of autonomy, future work must investigate autonomy from a practical standpoint. It is conceivable that if factors such as attending characteristics and secular trends influence perception, they may also be associated with variation in how attendings entrust autonomy and provide supervision. To what extent perception and practice are linked remains to be studied, but it will be important to determine if variation due to these factors may also be associated with inconsistent and uneven supervisory practices that would adversely affect resident education and patient safety.
Finally, future work must include the viewpoint of the recipients of autonomy: the residents and interns. A significant limitation of the current study is the lack of the resident perspective, as our survey was only administered to attendings. Autonomy is clearly a 2‐way relationship, and attending perception must be corroborated by the resident's experience. It is possible attendings may perceive that their housestaff have sufficient autonomy, but residents may view this autonomy as inappropriate or unavoidable due an absentee attending who does not adequately supervise.[32] Future work must examine how resident and attending perceptions of autonomy correlate, and whether discordance or concordance in these perceptions influence satisfaction with attending‐resident relationships, education, and patient care.
In conclusion, significant variation existed among attending physicians with respect to perception of housestaff autonomy, an important aspect of entrustment and clinical supervision. This variation was present for hospitalists, among different levels of attending experience, and a significant interaction was found between these 2 factors. Additionally, secular trends were associated with differences in perception of autonomy. As entrustment of residents with progressive levels of autonomy becomes more integrated within the requirements for advancement in residency, a greater understanding of factors affecting entrustment will be critical in helping faculty develop skills to appropriately assess trainee professional growth and development.
Acknowledgments
The authors thank all members of the Multicenter Hospitalist Project for their assistance with this project.
Disclosures: The authors acknowledge funding from the AHRQ/CERT 5 U18 HS016967‐01. The funder had no role in the design of the study; the collection, analysis, and interpretation of the data; or the decision to approve publication of the finished manuscript. Prior presentations of the data include the 2012 Department of Medicine Research Day at the University of Chicago, the 2012 Society of Hospital Medicine Annual Meeting in San Diego, California, and the 2012 Midwest Society of General Medicine Meeting in Chicago, Illinois. All coauthors have seen and agree with the contents of the manuscript. The submission was not under review by any other publication. The authors report no conflicts of interest.
- , . Effective supervision in clinical practice settings: a literature review. Med Educ. 2000;34(10):827–840.
- . Deliberate practice and acquisition of expert performance: a general overview. Acad Emerg Med. 2008;15(11):988–994.
- , , , et al. Progressive independence in clinical training: a tradition worth defending? Acad Med. 2005;80(10 suppl):S106–S111.
- Committee on Optimizing Graduate Medical Trainee (Resident) Hours and Work Schedules to Improve Patient Safety, Institute of Medicine. Ulmer C, Wolman D, Johns M, eds. Resident Duty Hours: Enhancing Sleep, Supervision, and Safety. Washington, DC: National Academies Press; 2008.
- , , ; ACGME Duty Hour Task Force. The new recommendations on duty hours from the ACGME Task Force. N Engl J Med. 2010;363(2):e3.
- . Positive impact of pediatric critical care fellows on mortality: is it merely a function of resident supervision? Crit Care Med. 1997;25(10):1622–1623.
- , , , et al. The effect of supervision of residents on quality of care in five university‐affiliated emergency departments. Acad Med. 1998;73(7):776–782.
- , , , et al. Increased faculty presence on inpatient teaching services. Mayo Clin Proc. 2004;79(3):332–336.
- , , , et al. How medical residents perceive the quality of supervision provided by attending doctors in the clinical setting. Med Educ. 2005;39(7):696–703.
- , , . Resident supervision in the operating room: does this impact on outcome? J Trauma. 1993;35(4):556–560.
- , , , et al. Effects of supervision by attending anesthesiologists on complications of emergency tracheal intubation. Anesthesiology. 2008;109(6):973–937.
- , , , et al. Around‐the‐clock attending radiology coverage is essential to avoid mistakes in the care of trauma patients. Am Surg. 2001;67(12):1175–1177.
- , . Supervision in the outpatient clinic: effects on teaching and patient care. J Gen Int Med. 1993;8(7):378–380.
- , . How medical students and residents describe the roles and characteristics of their influential clinical teachers. Acad Med. 2000;75(8):843–845.
- , , , et al. A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428–442.
- , , , et al; for the SGIM Housestaff Oversight Subcommittee. Survey of overnight academic hospitalist supervision of trainees. J Hosp Med. 2012;7(7):521–523.
- , , , et al. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606–610.
- , , , et al. The effect of overnight in‐house attending coverage on perceptions of care and education on a general medical service. J Grad Med Educ. 2010;2(1):53–56.
- , , , et al. Resident satisfaction on an academic hospitalist service: time to teach. Am J Med. 2002;112(7):597–601.
- , , , et al. The next GME accreditation system—rationale and benefits. N Engl J Med. 2012;366(11):1051–1056.
- , . Competency‐based postgraduate training: can we bridge the gap between theory and clinical practice? Acad Med. 2007;82(6):542–547.
- . Trust, competence, and the supervisor's role in postgraduate training. BMJ. 2006;333(7571):748–751.
- , , , et al. Measuring progressive independence with the resident supervision index: empirical approach. J Grad Med Educ. 2010;2(1):17–30.
- , . The emerging role of “hospitalists” in the American health care system. N Engl J Med. 1996;335(7):514–517.
- , . Effect of ACGME duty hours on attending physician teaching and satisfaction. Arch Intern Med. 2008;168(11):1226–1227.
- , , , et al. Association of workload of on‐call interns with on‐call sleep duration, shift duration, and participation in educational activities. JAMA. 2008;300(10):1146–1153.
- . Entrustability of professional activities and competency‐based training. Med Educ. 2005;39:1176–1177.
- , , , et al. When do supervising physicians decide to entrust residents with unsupervised tasks? Acad Med. 2010;85(9):1399–1400.
- , , et al. Effect of residency duty‐hour limits. Arch Intern Med. 2007;167(14):1487–1492.
- , . Strategies for improving teaching practices: a comprehensive approach to faculty development. Acad Med. 1998;73:387–396.
- , , . A framework for effective training for supervisors. Med Teach. 2002;24:385–389.
- , , , et al. On‐call supervision and resident autonomy: from micromanager to absentee attending. Am J Med. 2009;122(8):784–788.
Clinical supervision in graduate medical education (GME) emphasizes patient safety while promoting development of clinical expertise by allowing trainees progressive independence.[1, 2, 3] The importance of the balance between supervision and autonomy has been recognized by accreditation organizations, namely the Institute of Medicine and the Accreditation Council for Graduate Medical Education (ACGME).[4, 5] However, little is known of best practices in supervision, and the model of progressive independence in clinical training lacks empirical support.[3] Limited evidence suggests that enhanced clinical supervision may have positive effects on patient and education‐related outcomes.[6, 7, 8, 9, 10, 11, 12, 13, 14, 15] However, a more nuanced understanding of potential effects of enhanced supervision on resident autonomy and decision making is still required, particularly as preliminary work on increased on‐site hospitalist supervision has yielded mixed results.[16, 17, 18, 19]
Understanding how trainees are entrusted with autonomy will be integral to the ACGME's Next Accreditation System.[20] Entrustable Professional Activities are benchmarks by which resident readiness to progress through training will be judged.[21] The extent to which trainees are entrusted with autonomy is largely determined by the subjective assessment of immediate supervisors, as autonomy is rarely measured or quantified.[3, 22, 23] This judgment of autonomy, most frequently performed by ward attendings, may be subject to significant variation and influenced by factors other than the resident's competence and clinical abilities.
To that end, it is worth considering what factors may affect attending perception of housestaff autonomy and decision making. Recent changes in the GME environment and policy implementation have altered the landscape of the attending workforce considerably. The growth of the hospitalist movement in teaching hospitals, in part due to duty hours, has led to more residents being supervised by hospitalists, who may perceive trainee autonomy differently than other attendings do.[24] This study aims to examine whether factors such as attending demographics and short‐term and long‐term secular trends influence attending perception of housestaff autonomy and participation in decision making.
METHODS
Study Design
From 2001 to 2008, attending physicians at a single academic institution were surveyed at the end of inpatient general medicine teaching rotations.[25] The University of Chicago general medicine service consists of ward teams of an attending physician (internists, hospitalists, or subspecialists), 1 senior resident, and 1 or 2 interns. Attendings serve for 2‐ or 4‐week rotations. Attendings were consented for participation and received a 40‐item, paper‐based survey at the rotation's end. The institutional review board approved this study.
Data Collection
From the 40 survey items, 2 statements were selected for analysis: The intern(s) were truly involved in decision making about their patients and My resident felt that s/he had sufficient autonomy this month. These items have been used in previous work studying attending‐resident dynamics.[19, 26] Attendings also reported demographic and professional information as well as self‐identified hospitalist status, ascertained by the question Do you consider yourself to be a hospitalist? Survey month and year were also recorded. We conducted a secondary data analysis of an inclusive sample of responses to the questions of interest.
Statistical Analysis
Descriptive statistics were used to summarize survey responses and demographics. Survey questions consisted of Likert‐type items. Because the distribution of responses was skewed toward strong agreement for both questions, we collapsed scores into 2 categories (Strongly Agree and Do Not Strongly Agree).[19] Perception of sufficient trainee autonomy was defined as a response of Strongly Agree. The Pearson 2 test was used to compare proportions, and t tests were used to compare mean years since completion of residency and weeks on service between different groups.
Multivariate logistic regression with stepwise forward regression was used to model the relationship between attending sex, institutional hospitalist designation, years of experience, implementation of duty‐hours restrictions, and academic season, and perception of trainee autonomy and decision making. Academic seasons were defined as summer (JulySeptember), fall (OctoberDecember), winter (JanuaryMarch) and spring (AprilJune).[26] Years of experience were divided into tertiles of years since residency: 04 years, 511 years, and >11 years. To account for the possibility that the effect of hospitalist specialty varied by experience, interaction terms were constructed. The interaction term hospitalist*early‐career was used as the reference group.
RESULTS
Seven hundred thirty‐eight surveys were distributed to attendings on inpatient general medicine teaching services from 2001 to 2008; 70% (n=514) were included in the analysis. Table 1 provides demographic characteristics of the respondents. Roughly half (47%) were female, and 23% were hospitalists. Experience ranged from 0 to 35 years, with a median of 7 years. Weeks on service per year ranged from 1 to 27, with a median of 6 weeks. Hospitalists represented a less‐experienced group of attendings, as their mean experience was 4.5 years (standard deviation [SD] 4.5) compared with 11.2 years (SD 7.7) for nonhospitalists (P<0.001). Hospitalists attended more frequently, with a mean 14.2 weeks on service (SD 6.5) compared with 5.8 weeks (SD 3.4) for nonhospitalists (P<0.001). Nineteen percent (n=98) of surveys were completed prior to the first ACGME duty‐hours restriction in 2003. Responses were distributed fairly equally across the academic year, with 29% completed in summer, 26% in fall, 24% in winter, and 21% in spring.
| Characteristics | Value |
|---|---|
| |
| Female, n (%) | 275 (47) |
| Hospitalist, n (%) | 125 (23) |
| Years since completion of residency | |
| Mean, median, SD | 9.3, 7, 7.6 |
| IQR | 314 |
| 04, n (%) | 167 (36) |
| 511, n (%) | 146 (32) |
| >11, n (%) | 149 (32) |
| Weeks on service per yearb | |
| Mean, median, SD | 8.1, 6, 5.8 |
| IQR | 412 |
Forty‐four percent (n=212) of attendings perceived adequate intern involvement in decision making, and 50% (n=238) perceived sufficient resident autonomy. The correlation coefficient between these 2 measures was 0.66.
Attending Factors Associated With Perception of Trainee Autonomy
In univariate analysis, hospitalists perceived sufficient trainee autonomy less frequently than nonhospitalists; 33% perceived adequate intern involvement in decision making compared with 48% of nonhospitalists (21=6.7, P=0.01), and 42% perceived sufficient resident autonomy compared with 54% of nonhospitalists (21=3.9, P=0.048) (Table 2).
| Attending Characteristics, n (%) | Agree With Intern Involvement in Decision Making | Agree With Sufficient Resident Autonomy |
|---|---|---|
| ||
| Designation | ||
| Hospitalist | 29 (33) | 37 (42) |
| Nonhospitalist | 163 (48) | 180 (54) |
| Years since completion of residency | ||
| 04 | 37 (27) | 49 (36) |
| 511 | 77 (53) | 88 (61) |
| >11 | 77 (53) | 81 (56) |
| Sex | ||
| F | 98 (46) | 100 (47) |
| M | 113 (43) | 138 (53) |
| Secular factors, n (%) | ||
| Pre‐2003 duty‐hours restrictions | 56 (57) | 62 (65) |
| Post‐2003 duty‐hours restrictions | 156 (41) | 176 (46) |
| Season of survey | ||
| Summer (JulySeptember) | 61 (45) | 69 (51) |
| Fall (OctoberDecember) | 53 (42) | 59 (48) |
| Winter (JanuaryMarch) | 42 (37) | 52 (46) |
| Spring (AprilJune) | 56 (54) | 58 (57) |
Perception of trainee autonomy increased with experience (Table 2). About 30% of early‐career attendings (04 years experience) perceived sufficient autonomy and involvement in decision making compared with >50% agreement in the later‐career tertiles (intern decision making: 22=25.1, P<0.001; resident autonomy: 22=18.9, P<0.001). Attendings perceiving more intern decision making involvement had a mean 11 years of experience (SD 7.1), whereas those perceiving less had a mean of 8.8 years (SD 7.8; P=0.003). Mean years of experience were similar for perception of resident autonomy (10.6 years [SD 7.2] vs 8.9 years [SD 7.8], P=0.021).
Sex was not associated with differences in perception of intern decision making (21=0.39, P=0.53) or resident autonomy (21=1.4, P=0.236) (Table 2).
Secular Factors Associated With Perception of Trainee Autonomy
The implementation of duty‐hour restrictions in 2003 was associated with decreased attending perception of autonomy. Only 41% of attendings perceived adequate intern involvement in decision making following the restrictions, compared with 57% before the restrictions were instituted (21=8.2, P=0.004). Similarly, 46% of attendings agreed with sufficient resident autonomy post‐duty hours, compared with 65% prior (21=10.1, P=0.001) (Table 2).
Academic season was also associated with differences in perception of autonomy (Table 2). In spring, 54% of attendings perceived adequate intern involvement in decision making, compared with 42% in the other seasons combined (21=5.34, P=0.021). Perception of resident autonomy was also higher in spring, though this was not statistically significant (57% in spring vs 48% in the other seasons; 21=2.37, P=0.123).
Multivariate Analyses
Variation in attending perception of housestaff autonomy by attending characteristics persisted in multivariate analysis. Table 3 shows ORs for perception of adequate intern involvement in decision making and sufficient resident autonomy. Sex was not a significant predictor of agreement with either statement. The odds that an attending would perceive adequate intern involvement in decision making were higher for later‐career attendings compared with early‐career attendings (ie, 04 years); attendings who completed residency 511 years ago were 2.16 more likely to perceive adequate involvement (OR: 2.16, 95% CI: 1.17‐3.97, P=0.013), and those >11 years from residency were 2.05 more likely (OR: 2.05, 95% CI: 1.16‐3.63, P=0.014). Later‐career attendings also had nonsignificant higher odds of perceiving sufficient resident autonomy compared with early‐career attendings (511 years, OR: 1.73, 95% CI: 0.963.14, P=0.07; >11 years, OR: 1.50, 95% CI: 0.862.62, P=0.154).
| Interns Involved With Decision Making | Resident Had Sufficient Autonomy | |||
|---|---|---|---|---|
| ||||
| Covariate | OR (95% CI) | P Value | OR (95% CI) | P Value |
| Attending characteristics | ||||
| 04 years of experience | ||||
| 511 years of experience | 2.16 (1.17‐3.97) | 0.013 | 1.73 (0.96‐3.14) | 0.07 |
| >11 years of experience | 2.05 (1.16‐3.63) | 0.014 | 1.50 (0.86‐2.62) | 0.154 |
| Hospitalist | 0.19 (0.06‐0.58) | 0.004 | 0.27 (0.11‐0.66) | 0.004 |
| Hospitalist 04 years of experiencea | ||||
| Hospitalist 511 years of experiencea | 7.36 (1.86‐29.1) | 0.004 | 5.85 (1.75‐19.6) | 0.004 |
| Hospitalist >11 years of experiencea | 21.2 (1.73‐260) | 0.017 | 14.4 (1.31‐159) | 0.029 |
| Female sex | 1.41 (0.92‐2.17) | 0.115 | 0.92 (0.60‐1.40) | 0.69 |
| Secular factors | ||||
| Post‐2003 duty hours | 0.51 (0.29‐0.87) | 0.014 | 0.49 (0.28‐0.86) | 0.012 |
| Spring academic season | 1.94 (1.18‐3.19) | 0.009 | 1.59 (0.97‐2.60) | 0.064 |
Hospitalists were associated with 81% lower odds of perceiving adequate intern involvement in decision making (OR: 0.19, 95% CI: 0.060.58, P=0.004) and 73% lower odds of perceiving sufficient resident autonomy compared with nonhospitalists (OR: 0.27, 95% CI: 0.110.66, P=0.004). However, there was a significant interaction between hospitalists and experience; compared with early‐career hospitalists, experienced hospitalists had higher odds of perceiving both adequate intern involvement in decision making (511 years, OR: 7.36, 95% CI: 1.8629.1, P=0.004; >11 years, OR: 21.2, 95% CI: 1.73260, P=0.017) and sufficient resident autonomy (511 years, OR: 5.85, 95% CI: 1.7519.6, P=0.004; >11 years, OR: 14.4, 95% CI: 1.3159, P=0.029) (Table 3).
Secular trends also remained associated with differences in perception of housestaff autonomy (Table 3). Attendings had 49% lower odds of perceiving adequate intern involvement in decision making in the years following duty‐hour limits compared with the years prior (OR: 0.51, 95% CI: 0.29‐0.87, P=0.014). Similarly, odds of perceiving sufficient resident autonomy were 51% lower post‐duty hours (OR: 0.49, 95% CI: 0.280.86, P=0.012). Spring season was associated with 94% higher odds of perceiving adequate intern involvement in decision making compared with other seasons (OR: 1.94, 95% 1.183.19, P=0.009). There were also nonsignificant higher odds of perception of sufficient resident autonomy in spring (OR: 1.59, 95% CI: 0.972.60, P=0.064). To address the possibility of associations due to secular trends resulting from repeated measures of attendings, models using attending fixed effects were also used. Clustering by attending, the associations between duty hours and perceiving sufficient resident autonomy and intern decision making both remained significant, but the association of spring season did not.
DISCUSSION
This study highlights that attendings' perception of housestaff autonomy varies by attending characteristics and secular trends. Specifically, early‐career attendings and hospitalists were less likely to perceive sufficient housestaff autonomy and involvement in decision making. However, there was a significant hospitalist‐experience interaction, such that more‐experienced hospitalists were associated with higher odds of perceiving sufficient autonomy than would be expected from the effect of experience alone. With respect to secular trends, attendings perceived more trainee autonomy in the last quarter of the academic year, and less autonomy after implementation of resident duty‐hour restrictions in 2003.
As Entrustable Professional Activities unveil a new emphasis on the notion of entrustment, it will be critical to ensure that attending assessment of resident performance is uniform and a valid judge of when to entrust autonomy.[27, 28] If, as suggested by these findings, perception of autonomy varies based on attending characteristics, all faculty may benefit from strategies to standardize assessment and evaluation skills to ensure trainees are appropriately progressing through various milestones to achieve competence. Our results suggest that faculty development may be particularly important for early‐career attendings and especially hospitalists.
Early‐career attendings may perceive less housestaff autonomy due to a reluctance to relinquish control over patient‐care duties and decision making when the attending is only a few years from residency. Hospitalists are relatively junior in most institutions and may be similar to early‐career attendings in that regard. It is noteworthy, however, that experienced hospitalists are associated with even greater perception of autonomy than would be predicted by years of experience alone. Hospitalists may gain experience at a rate faster than nonhospitalists, which could affect how they perceive autonomy and decision making in trainees and may make them more comfortable entrusting autonomy to housestaff. Early‐career hospitalists likely represent a heterogeneous group of physicians, in both 1‐year clinical hospitalists as well as academic‐career hospitalists, who may have different approaches to managing housestaff teams. Residents are less likely to fear hospitalists limiting their autonomy after exposure to working with hospitalists as teaching attendings, and our findings may suggest a corollary in that hospitalists may be more likely to perceive sufficient autonomy with more exposure to working with housestaff.[19]
Attendings perceived less housestaff autonomy following the 2003 duty‐hour limits. This may be due to attendings assuming more responsibilities that were traditionally performed by residents.[26, 29] This shifting of responsibility may lead to perception of less‐active housestaff decision making and less‐evident autonomy. These findings suggest autonomy may become even more restricted after implementation of the 2011 duty‐hour restrictions, which included 16‐hour shifts for interns.[5] Further studies are warranted in examining the effect of these new limits. Entrustment of autonomy and allowance for decision making is an essential part of any learning environment that allows residents to develop clinical reasoning skills, and it will be critical to adopt new strategies to encourage professional growth of housestaff in this new era.[30]
Attendings also perceived autonomy differently by academic season. Spring represents the season by which housestaff are most experienced and by which attendings may be most familiar with individual team members. Additionally, there may be a stronger emphasis on supervision and adherence to traditional hierarchy earlier in the academic year as interns and junior residents are learning their new roles.[30] These findings may have implications for system changes to support development of more functional educational dyads between attendings and trainees, especially early in the academic year.[31]
There are several limitations to our findings. This is a single‐institution study restricted to the general‐medicine service; thus generalizability is limited. Our outcome measures, the survey items of interest, question perception of housestaff autonomy but do not query the appropriateness of that autonomy, an important construct in entrustment. Additionally, self‐reported answers could be subject to recall bias. Although data were collected over 8 years, the most recent trends of residency training are not reflected. Although there was a significant interaction involving experienced hospitalists, wide confidence intervals and large standard errors likely reflect the relatively few individuals in this category. Though there was a large number of overall respondents, our interaction terms included few advanced‐career hospitalists, likely secondary to hospital medicine's relative youth as a specialty.
As this study focuses only on perception of autonomy, future work must investigate autonomy from a practical standpoint. It is conceivable that if factors such as attending characteristics and secular trends influence perception, they may also be associated with variation in how attendings entrust autonomy and provide supervision. To what extent perception and practice are linked remains to be studied, but it will be important to determine if variation due to these factors may also be associated with inconsistent and uneven supervisory practices that would adversely affect resident education and patient safety.
Finally, future work must include the viewpoint of the recipients of autonomy: the residents and interns. A significant limitation of the current study is the lack of the resident perspective, as our survey was only administered to attendings. Autonomy is clearly a 2‐way relationship, and attending perception must be corroborated by the resident's experience. It is possible attendings may perceive that their housestaff have sufficient autonomy, but residents may view this autonomy as inappropriate or unavoidable due an absentee attending who does not adequately supervise.[32] Future work must examine how resident and attending perceptions of autonomy correlate, and whether discordance or concordance in these perceptions influence satisfaction with attending‐resident relationships, education, and patient care.
In conclusion, significant variation existed among attending physicians with respect to perception of housestaff autonomy, an important aspect of entrustment and clinical supervision. This variation was present for hospitalists, among different levels of attending experience, and a significant interaction was found between these 2 factors. Additionally, secular trends were associated with differences in perception of autonomy. As entrustment of residents with progressive levels of autonomy becomes more integrated within the requirements for advancement in residency, a greater understanding of factors affecting entrustment will be critical in helping faculty develop skills to appropriately assess trainee professional growth and development.
Acknowledgments
The authors thank all members of the Multicenter Hospitalist Project for their assistance with this project.
Disclosures: The authors acknowledge funding from the AHRQ/CERT 5 U18 HS016967‐01. The funder had no role in the design of the study; the collection, analysis, and interpretation of the data; or the decision to approve publication of the finished manuscript. Prior presentations of the data include the 2012 Department of Medicine Research Day at the University of Chicago, the 2012 Society of Hospital Medicine Annual Meeting in San Diego, California, and the 2012 Midwest Society of General Medicine Meeting in Chicago, Illinois. All coauthors have seen and agree with the contents of the manuscript. The submission was not under review by any other publication. The authors report no conflicts of interest.
Clinical supervision in graduate medical education (GME) emphasizes patient safety while promoting development of clinical expertise by allowing trainees progressive independence.[1, 2, 3] The importance of the balance between supervision and autonomy has been recognized by accreditation organizations, namely the Institute of Medicine and the Accreditation Council for Graduate Medical Education (ACGME).[4, 5] However, little is known of best practices in supervision, and the model of progressive independence in clinical training lacks empirical support.[3] Limited evidence suggests that enhanced clinical supervision may have positive effects on patient and education‐related outcomes.[6, 7, 8, 9, 10, 11, 12, 13, 14, 15] However, a more nuanced understanding of potential effects of enhanced supervision on resident autonomy and decision making is still required, particularly as preliminary work on increased on‐site hospitalist supervision has yielded mixed results.[16, 17, 18, 19]
Understanding how trainees are entrusted with autonomy will be integral to the ACGME's Next Accreditation System.[20] Entrustable Professional Activities are benchmarks by which resident readiness to progress through training will be judged.[21] The extent to which trainees are entrusted with autonomy is largely determined by the subjective assessment of immediate supervisors, as autonomy is rarely measured or quantified.[3, 22, 23] This judgment of autonomy, most frequently performed by ward attendings, may be subject to significant variation and influenced by factors other than the resident's competence and clinical abilities.
To that end, it is worth considering what factors may affect attending perception of housestaff autonomy and decision making. Recent changes in the GME environment and policy implementation have altered the landscape of the attending workforce considerably. The growth of the hospitalist movement in teaching hospitals, in part due to duty hours, has led to more residents being supervised by hospitalists, who may perceive trainee autonomy differently than other attendings do.[24] This study aims to examine whether factors such as attending demographics and short‐term and long‐term secular trends influence attending perception of housestaff autonomy and participation in decision making.
METHODS
Study Design
From 2001 to 2008, attending physicians at a single academic institution were surveyed at the end of inpatient general medicine teaching rotations.[25] The University of Chicago general medicine service consists of ward teams of an attending physician (internists, hospitalists, or subspecialists), 1 senior resident, and 1 or 2 interns. Attendings serve for 2‐ or 4‐week rotations. Attendings were consented for participation and received a 40‐item, paper‐based survey at the rotation's end. The institutional review board approved this study.
Data Collection
From the 40 survey items, 2 statements were selected for analysis: The intern(s) were truly involved in decision making about their patients and My resident felt that s/he had sufficient autonomy this month. These items have been used in previous work studying attending‐resident dynamics.[19, 26] Attendings also reported demographic and professional information as well as self‐identified hospitalist status, ascertained by the question Do you consider yourself to be a hospitalist? Survey month and year were also recorded. We conducted a secondary data analysis of an inclusive sample of responses to the questions of interest.
Statistical Analysis
Descriptive statistics were used to summarize survey responses and demographics. Survey questions consisted of Likert‐type items. Because the distribution of responses was skewed toward strong agreement for both questions, we collapsed scores into 2 categories (Strongly Agree and Do Not Strongly Agree).[19] Perception of sufficient trainee autonomy was defined as a response of Strongly Agree. The Pearson 2 test was used to compare proportions, and t tests were used to compare mean years since completion of residency and weeks on service between different groups.
Multivariate logistic regression with stepwise forward regression was used to model the relationship between attending sex, institutional hospitalist designation, years of experience, implementation of duty‐hours restrictions, and academic season, and perception of trainee autonomy and decision making. Academic seasons were defined as summer (JulySeptember), fall (OctoberDecember), winter (JanuaryMarch) and spring (AprilJune).[26] Years of experience were divided into tertiles of years since residency: 04 years, 511 years, and >11 years. To account for the possibility that the effect of hospitalist specialty varied by experience, interaction terms were constructed. The interaction term hospitalist*early‐career was used as the reference group.
RESULTS
Seven hundred thirty‐eight surveys were distributed to attendings on inpatient general medicine teaching services from 2001 to 2008; 70% (n=514) were included in the analysis. Table 1 provides demographic characteristics of the respondents. Roughly half (47%) were female, and 23% were hospitalists. Experience ranged from 0 to 35 years, with a median of 7 years. Weeks on service per year ranged from 1 to 27, with a median of 6 weeks. Hospitalists represented a less‐experienced group of attendings, as their mean experience was 4.5 years (standard deviation [SD] 4.5) compared with 11.2 years (SD 7.7) for nonhospitalists (P<0.001). Hospitalists attended more frequently, with a mean 14.2 weeks on service (SD 6.5) compared with 5.8 weeks (SD 3.4) for nonhospitalists (P<0.001). Nineteen percent (n=98) of surveys were completed prior to the first ACGME duty‐hours restriction in 2003. Responses were distributed fairly equally across the academic year, with 29% completed in summer, 26% in fall, 24% in winter, and 21% in spring.
| Characteristics | Value |
|---|---|
| |
| Female, n (%) | 275 (47) |
| Hospitalist, n (%) | 125 (23) |
| Years since completion of residency | |
| Mean, median, SD | 9.3, 7, 7.6 |
| IQR | 314 |
| 04, n (%) | 167 (36) |
| 511, n (%) | 146 (32) |
| >11, n (%) | 149 (32) |
| Weeks on service per yearb | |
| Mean, median, SD | 8.1, 6, 5.8 |
| IQR | 412 |
Forty‐four percent (n=212) of attendings perceived adequate intern involvement in decision making, and 50% (n=238) perceived sufficient resident autonomy. The correlation coefficient between these 2 measures was 0.66.
Attending Factors Associated With Perception of Trainee Autonomy
In univariate analysis, hospitalists perceived sufficient trainee autonomy less frequently than nonhospitalists; 33% perceived adequate intern involvement in decision making compared with 48% of nonhospitalists (21=6.7, P=0.01), and 42% perceived sufficient resident autonomy compared with 54% of nonhospitalists (21=3.9, P=0.048) (Table 2).
| Attending Characteristics, n (%) | Agree With Intern Involvement in Decision Making | Agree With Sufficient Resident Autonomy |
|---|---|---|
| ||
| Designation | ||
| Hospitalist | 29 (33) | 37 (42) |
| Nonhospitalist | 163 (48) | 180 (54) |
| Years since completion of residency | ||
| 04 | 37 (27) | 49 (36) |
| 511 | 77 (53) | 88 (61) |
| >11 | 77 (53) | 81 (56) |
| Sex | ||
| F | 98 (46) | 100 (47) |
| M | 113 (43) | 138 (53) |
| Secular factors, n (%) | ||
| Pre‐2003 duty‐hours restrictions | 56 (57) | 62 (65) |
| Post‐2003 duty‐hours restrictions | 156 (41) | 176 (46) |
| Season of survey | ||
| Summer (JulySeptember) | 61 (45) | 69 (51) |
| Fall (OctoberDecember) | 53 (42) | 59 (48) |
| Winter (JanuaryMarch) | 42 (37) | 52 (46) |
| Spring (AprilJune) | 56 (54) | 58 (57) |
Perception of trainee autonomy increased with experience (Table 2). About 30% of early‐career attendings (04 years experience) perceived sufficient autonomy and involvement in decision making compared with >50% agreement in the later‐career tertiles (intern decision making: 22=25.1, P<0.001; resident autonomy: 22=18.9, P<0.001). Attendings perceiving more intern decision making involvement had a mean 11 years of experience (SD 7.1), whereas those perceiving less had a mean of 8.8 years (SD 7.8; P=0.003). Mean years of experience were similar for perception of resident autonomy (10.6 years [SD 7.2] vs 8.9 years [SD 7.8], P=0.021).
Sex was not associated with differences in perception of intern decision making (21=0.39, P=0.53) or resident autonomy (21=1.4, P=0.236) (Table 2).
Secular Factors Associated With Perception of Trainee Autonomy
The implementation of duty‐hour restrictions in 2003 was associated with decreased attending perception of autonomy. Only 41% of attendings perceived adequate intern involvement in decision making following the restrictions, compared with 57% before the restrictions were instituted (21=8.2, P=0.004). Similarly, 46% of attendings agreed with sufficient resident autonomy post‐duty hours, compared with 65% prior (21=10.1, P=0.001) (Table 2).
Academic season was also associated with differences in perception of autonomy (Table 2). In spring, 54% of attendings perceived adequate intern involvement in decision making, compared with 42% in the other seasons combined (21=5.34, P=0.021). Perception of resident autonomy was also higher in spring, though this was not statistically significant (57% in spring vs 48% in the other seasons; 21=2.37, P=0.123).
Multivariate Analyses
Variation in attending perception of housestaff autonomy by attending characteristics persisted in multivariate analysis. Table 3 shows ORs for perception of adequate intern involvement in decision making and sufficient resident autonomy. Sex was not a significant predictor of agreement with either statement. The odds that an attending would perceive adequate intern involvement in decision making were higher for later‐career attendings compared with early‐career attendings (ie, 04 years); attendings who completed residency 511 years ago were 2.16 more likely to perceive adequate involvement (OR: 2.16, 95% CI: 1.17‐3.97, P=0.013), and those >11 years from residency were 2.05 more likely (OR: 2.05, 95% CI: 1.16‐3.63, P=0.014). Later‐career attendings also had nonsignificant higher odds of perceiving sufficient resident autonomy compared with early‐career attendings (511 years, OR: 1.73, 95% CI: 0.963.14, P=0.07; >11 years, OR: 1.50, 95% CI: 0.862.62, P=0.154).
| Interns Involved With Decision Making | Resident Had Sufficient Autonomy | |||
|---|---|---|---|---|
| ||||
| Covariate | OR (95% CI) | P Value | OR (95% CI) | P Value |
| Attending characteristics | ||||
| 04 years of experience | ||||
| 511 years of experience | 2.16 (1.17‐3.97) | 0.013 | 1.73 (0.96‐3.14) | 0.07 |
| >11 years of experience | 2.05 (1.16‐3.63) | 0.014 | 1.50 (0.86‐2.62) | 0.154 |
| Hospitalist | 0.19 (0.06‐0.58) | 0.004 | 0.27 (0.11‐0.66) | 0.004 |
| Hospitalist 04 years of experiencea | ||||
| Hospitalist 511 years of experiencea | 7.36 (1.86‐29.1) | 0.004 | 5.85 (1.75‐19.6) | 0.004 |
| Hospitalist >11 years of experiencea | 21.2 (1.73‐260) | 0.017 | 14.4 (1.31‐159) | 0.029 |
| Female sex | 1.41 (0.92‐2.17) | 0.115 | 0.92 (0.60‐1.40) | 0.69 |
| Secular factors | ||||
| Post‐2003 duty hours | 0.51 (0.29‐0.87) | 0.014 | 0.49 (0.28‐0.86) | 0.012 |
| Spring academic season | 1.94 (1.18‐3.19) | 0.009 | 1.59 (0.97‐2.60) | 0.064 |
Hospitalists were associated with 81% lower odds of perceiving adequate intern involvement in decision making (OR: 0.19, 95% CI: 0.060.58, P=0.004) and 73% lower odds of perceiving sufficient resident autonomy compared with nonhospitalists (OR: 0.27, 95% CI: 0.110.66, P=0.004). However, there was a significant interaction between hospitalists and experience; compared with early‐career hospitalists, experienced hospitalists had higher odds of perceiving both adequate intern involvement in decision making (511 years, OR: 7.36, 95% CI: 1.8629.1, P=0.004; >11 years, OR: 21.2, 95% CI: 1.73260, P=0.017) and sufficient resident autonomy (511 years, OR: 5.85, 95% CI: 1.7519.6, P=0.004; >11 years, OR: 14.4, 95% CI: 1.3159, P=0.029) (Table 3).
Secular trends also remained associated with differences in perception of housestaff autonomy (Table 3). Attendings had 49% lower odds of perceiving adequate intern involvement in decision making in the years following duty‐hour limits compared with the years prior (OR: 0.51, 95% CI: 0.29‐0.87, P=0.014). Similarly, odds of perceiving sufficient resident autonomy were 51% lower post‐duty hours (OR: 0.49, 95% CI: 0.280.86, P=0.012). Spring season was associated with 94% higher odds of perceiving adequate intern involvement in decision making compared with other seasons (OR: 1.94, 95% 1.183.19, P=0.009). There were also nonsignificant higher odds of perception of sufficient resident autonomy in spring (OR: 1.59, 95% CI: 0.972.60, P=0.064). To address the possibility of associations due to secular trends resulting from repeated measures of attendings, models using attending fixed effects were also used. Clustering by attending, the associations between duty hours and perceiving sufficient resident autonomy and intern decision making both remained significant, but the association of spring season did not.
DISCUSSION
This study highlights that attendings' perception of housestaff autonomy varies by attending characteristics and secular trends. Specifically, early‐career attendings and hospitalists were less likely to perceive sufficient housestaff autonomy and involvement in decision making. However, there was a significant hospitalist‐experience interaction, such that more‐experienced hospitalists were associated with higher odds of perceiving sufficient autonomy than would be expected from the effect of experience alone. With respect to secular trends, attendings perceived more trainee autonomy in the last quarter of the academic year, and less autonomy after implementation of resident duty‐hour restrictions in 2003.
As Entrustable Professional Activities unveil a new emphasis on the notion of entrustment, it will be critical to ensure that attending assessment of resident performance is uniform and a valid judge of when to entrust autonomy.[27, 28] If, as suggested by these findings, perception of autonomy varies based on attending characteristics, all faculty may benefit from strategies to standardize assessment and evaluation skills to ensure trainees are appropriately progressing through various milestones to achieve competence. Our results suggest that faculty development may be particularly important for early‐career attendings and especially hospitalists.
Early‐career attendings may perceive less housestaff autonomy due to a reluctance to relinquish control over patient‐care duties and decision making when the attending is only a few years from residency. Hospitalists are relatively junior in most institutions and may be similar to early‐career attendings in that regard. It is noteworthy, however, that experienced hospitalists are associated with even greater perception of autonomy than would be predicted by years of experience alone. Hospitalists may gain experience at a rate faster than nonhospitalists, which could affect how they perceive autonomy and decision making in trainees and may make them more comfortable entrusting autonomy to housestaff. Early‐career hospitalists likely represent a heterogeneous group of physicians, in both 1‐year clinical hospitalists as well as academic‐career hospitalists, who may have different approaches to managing housestaff teams. Residents are less likely to fear hospitalists limiting their autonomy after exposure to working with hospitalists as teaching attendings, and our findings may suggest a corollary in that hospitalists may be more likely to perceive sufficient autonomy with more exposure to working with housestaff.[19]
Attendings perceived less housestaff autonomy following the 2003 duty‐hour limits. This may be due to attendings assuming more responsibilities that were traditionally performed by residents.[26, 29] This shifting of responsibility may lead to perception of less‐active housestaff decision making and less‐evident autonomy. These findings suggest autonomy may become even more restricted after implementation of the 2011 duty‐hour restrictions, which included 16‐hour shifts for interns.[5] Further studies are warranted in examining the effect of these new limits. Entrustment of autonomy and allowance for decision making is an essential part of any learning environment that allows residents to develop clinical reasoning skills, and it will be critical to adopt new strategies to encourage professional growth of housestaff in this new era.[30]
Attendings also perceived autonomy differently by academic season. Spring represents the season by which housestaff are most experienced and by which attendings may be most familiar with individual team members. Additionally, there may be a stronger emphasis on supervision and adherence to traditional hierarchy earlier in the academic year as interns and junior residents are learning their new roles.[30] These findings may have implications for system changes to support development of more functional educational dyads between attendings and trainees, especially early in the academic year.[31]
There are several limitations to our findings. This is a single‐institution study restricted to the general‐medicine service; thus generalizability is limited. Our outcome measures, the survey items of interest, question perception of housestaff autonomy but do not query the appropriateness of that autonomy, an important construct in entrustment. Additionally, self‐reported answers could be subject to recall bias. Although data were collected over 8 years, the most recent trends of residency training are not reflected. Although there was a significant interaction involving experienced hospitalists, wide confidence intervals and large standard errors likely reflect the relatively few individuals in this category. Though there was a large number of overall respondents, our interaction terms included few advanced‐career hospitalists, likely secondary to hospital medicine's relative youth as a specialty.
As this study focuses only on perception of autonomy, future work must investigate autonomy from a practical standpoint. It is conceivable that if factors such as attending characteristics and secular trends influence perception, they may also be associated with variation in how attendings entrust autonomy and provide supervision. To what extent perception and practice are linked remains to be studied, but it will be important to determine if variation due to these factors may also be associated with inconsistent and uneven supervisory practices that would adversely affect resident education and patient safety.
Finally, future work must include the viewpoint of the recipients of autonomy: the residents and interns. A significant limitation of the current study is the lack of the resident perspective, as our survey was only administered to attendings. Autonomy is clearly a 2‐way relationship, and attending perception must be corroborated by the resident's experience. It is possible attendings may perceive that their housestaff have sufficient autonomy, but residents may view this autonomy as inappropriate or unavoidable due an absentee attending who does not adequately supervise.[32] Future work must examine how resident and attending perceptions of autonomy correlate, and whether discordance or concordance in these perceptions influence satisfaction with attending‐resident relationships, education, and patient care.
In conclusion, significant variation existed among attending physicians with respect to perception of housestaff autonomy, an important aspect of entrustment and clinical supervision. This variation was present for hospitalists, among different levels of attending experience, and a significant interaction was found between these 2 factors. Additionally, secular trends were associated with differences in perception of autonomy. As entrustment of residents with progressive levels of autonomy becomes more integrated within the requirements for advancement in residency, a greater understanding of factors affecting entrustment will be critical in helping faculty develop skills to appropriately assess trainee professional growth and development.
Acknowledgments
The authors thank all members of the Multicenter Hospitalist Project for their assistance with this project.
Disclosures: The authors acknowledge funding from the AHRQ/CERT 5 U18 HS016967‐01. The funder had no role in the design of the study; the collection, analysis, and interpretation of the data; or the decision to approve publication of the finished manuscript. Prior presentations of the data include the 2012 Department of Medicine Research Day at the University of Chicago, the 2012 Society of Hospital Medicine Annual Meeting in San Diego, California, and the 2012 Midwest Society of General Medicine Meeting in Chicago, Illinois. All coauthors have seen and agree with the contents of the manuscript. The submission was not under review by any other publication. The authors report no conflicts of interest.
- , . Effective supervision in clinical practice settings: a literature review. Med Educ. 2000;34(10):827–840.
- . Deliberate practice and acquisition of expert performance: a general overview. Acad Emerg Med. 2008;15(11):988–994.
- , , , et al. Progressive independence in clinical training: a tradition worth defending? Acad Med. 2005;80(10 suppl):S106–S111.
- Committee on Optimizing Graduate Medical Trainee (Resident) Hours and Work Schedules to Improve Patient Safety, Institute of Medicine. Ulmer C, Wolman D, Johns M, eds. Resident Duty Hours: Enhancing Sleep, Supervision, and Safety. Washington, DC: National Academies Press; 2008.
- , , ; ACGME Duty Hour Task Force. The new recommendations on duty hours from the ACGME Task Force. N Engl J Med. 2010;363(2):e3.
- . Positive impact of pediatric critical care fellows on mortality: is it merely a function of resident supervision? Crit Care Med. 1997;25(10):1622–1623.
- , , , et al. The effect of supervision of residents on quality of care in five university‐affiliated emergency departments. Acad Med. 1998;73(7):776–782.
- , , , et al. Increased faculty presence on inpatient teaching services. Mayo Clin Proc. 2004;79(3):332–336.
- , , , et al. How medical residents perceive the quality of supervision provided by attending doctors in the clinical setting. Med Educ. 2005;39(7):696–703.
- , , . Resident supervision in the operating room: does this impact on outcome? J Trauma. 1993;35(4):556–560.
- , , , et al. Effects of supervision by attending anesthesiologists on complications of emergency tracheal intubation. Anesthesiology. 2008;109(6):973–937.
- , , , et al. Around‐the‐clock attending radiology coverage is essential to avoid mistakes in the care of trauma patients. Am Surg. 2001;67(12):1175–1177.
- , . Supervision in the outpatient clinic: effects on teaching and patient care. J Gen Int Med. 1993;8(7):378–380.
- , . How medical students and residents describe the roles and characteristics of their influential clinical teachers. Acad Med. 2000;75(8):843–845.
- , , , et al. A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428–442.
- , , , et al; for the SGIM Housestaff Oversight Subcommittee. Survey of overnight academic hospitalist supervision of trainees. J Hosp Med. 2012;7(7):521–523.
- , , , et al. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606–610.
- , , , et al. The effect of overnight in‐house attending coverage on perceptions of care and education on a general medical service. J Grad Med Educ. 2010;2(1):53–56.
- , , , et al. Resident satisfaction on an academic hospitalist service: time to teach. Am J Med. 2002;112(7):597–601.
- , , , et al. The next GME accreditation system—rationale and benefits. N Engl J Med. 2012;366(11):1051–1056.
- , . Competency‐based postgraduate training: can we bridge the gap between theory and clinical practice? Acad Med. 2007;82(6):542–547.
- . Trust, competence, and the supervisor's role in postgraduate training. BMJ. 2006;333(7571):748–751.
- , , , et al. Measuring progressive independence with the resident supervision index: empirical approach. J Grad Med Educ. 2010;2(1):17–30.
- , . The emerging role of “hospitalists” in the American health care system. N Engl J Med. 1996;335(7):514–517.
- , . Effect of ACGME duty hours on attending physician teaching and satisfaction. Arch Intern Med. 2008;168(11):1226–1227.
- , , , et al. Association of workload of on‐call interns with on‐call sleep duration, shift duration, and participation in educational activities. JAMA. 2008;300(10):1146–1153.
- . Entrustability of professional activities and competency‐based training. Med Educ. 2005;39:1176–1177.
- , , , et al. When do supervising physicians decide to entrust residents with unsupervised tasks? Acad Med. 2010;85(9):1399–1400.
- , , et al. Effect of residency duty‐hour limits. Arch Intern Med. 2007;167(14):1487–1492.
- , . Strategies for improving teaching practices: a comprehensive approach to faculty development. Acad Med. 1998;73:387–396.
- , , . A framework for effective training for supervisors. Med Teach. 2002;24:385–389.
- , , , et al. On‐call supervision and resident autonomy: from micromanager to absentee attending. Am J Med. 2009;122(8):784–788.
- , . Effective supervision in clinical practice settings: a literature review. Med Educ. 2000;34(10):827–840.
- . Deliberate practice and acquisition of expert performance: a general overview. Acad Emerg Med. 2008;15(11):988–994.
- , , , et al. Progressive independence in clinical training: a tradition worth defending? Acad Med. 2005;80(10 suppl):S106–S111.
- Committee on Optimizing Graduate Medical Trainee (Resident) Hours and Work Schedules to Improve Patient Safety, Institute of Medicine. Ulmer C, Wolman D, Johns M, eds. Resident Duty Hours: Enhancing Sleep, Supervision, and Safety. Washington, DC: National Academies Press; 2008.
- , , ; ACGME Duty Hour Task Force. The new recommendations on duty hours from the ACGME Task Force. N Engl J Med. 2010;363(2):e3.
- . Positive impact of pediatric critical care fellows on mortality: is it merely a function of resident supervision? Crit Care Med. 1997;25(10):1622–1623.
- , , , et al. The effect of supervision of residents on quality of care in five university‐affiliated emergency departments. Acad Med. 1998;73(7):776–782.
- , , , et al. Increased faculty presence on inpatient teaching services. Mayo Clin Proc. 2004;79(3):332–336.
- , , , et al. How medical residents perceive the quality of supervision provided by attending doctors in the clinical setting. Med Educ. 2005;39(7):696–703.
- , , . Resident supervision in the operating room: does this impact on outcome? J Trauma. 1993;35(4):556–560.
- , , , et al. Effects of supervision by attending anesthesiologists on complications of emergency tracheal intubation. Anesthesiology. 2008;109(6):973–937.
- , , , et al. Around‐the‐clock attending radiology coverage is essential to avoid mistakes in the care of trauma patients. Am Surg. 2001;67(12):1175–1177.
- , . Supervision in the outpatient clinic: effects on teaching and patient care. J Gen Int Med. 1993;8(7):378–380.
- , . How medical students and residents describe the roles and characteristics of their influential clinical teachers. Acad Med. 2000;75(8):843–845.
- , , , et al. A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428–442.
- , , , et al; for the SGIM Housestaff Oversight Subcommittee. Survey of overnight academic hospitalist supervision of trainees. J Hosp Med. 2012;7(7):521–523.
- , , , et al. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606–610.
- , , , et al. The effect of overnight in‐house attending coverage on perceptions of care and education on a general medical service. J Grad Med Educ. 2010;2(1):53–56.
- , , , et al. Resident satisfaction on an academic hospitalist service: time to teach. Am J Med. 2002;112(7):597–601.
- , , , et al. The next GME accreditation system—rationale and benefits. N Engl J Med. 2012;366(11):1051–1056.
- , . Competency‐based postgraduate training: can we bridge the gap between theory and clinical practice? Acad Med. 2007;82(6):542–547.
- . Trust, competence, and the supervisor's role in postgraduate training. BMJ. 2006;333(7571):748–751.
- , , , et al. Measuring progressive independence with the resident supervision index: empirical approach. J Grad Med Educ. 2010;2(1):17–30.
- , . The emerging role of “hospitalists” in the American health care system. N Engl J Med. 1996;335(7):514–517.
- , . Effect of ACGME duty hours on attending physician teaching and satisfaction. Arch Intern Med. 2008;168(11):1226–1227.
- , , , et al. Association of workload of on‐call interns with on‐call sleep duration, shift duration, and participation in educational activities. JAMA. 2008;300(10):1146–1153.
- . Entrustability of professional activities and competency‐based training. Med Educ. 2005;39:1176–1177.
- , , , et al. When do supervising physicians decide to entrust residents with unsupervised tasks? Acad Med. 2010;85(9):1399–1400.
- , , et al. Effect of residency duty‐hour limits. Arch Intern Med. 2007;167(14):1487–1492.
- , . Strategies for improving teaching practices: a comprehensive approach to faculty development. Acad Med. 1998;73:387–396.
- , , . A framework for effective training for supervisors. Med Teach. 2002;24:385–389.
- , , , et al. On‐call supervision and resident autonomy: from micromanager to absentee attending. Am J Med. 2009;122(8):784–788.
Copyright © 2013 Society of Hospital Medicine
Probiotics prevent C. diff-associated diarrhea in patients taking antibiotics
Clinical question
Does the use of probiotics prevent Clostridium difficile-associated diarrhea in patients taking antibiotics?
Bottom line
Moderate-quality evidence suggests that probiotic administration reduces the incidence of C. difficile-associated diarrhea (CDAD) in patients who are taking antibiotics. LOE = 1a-
Reference
Study Design
Meta-analysis (other)
Funding Source
None
Setting
Various (meta-analysis)
Synopsis
These investigators searched multiple databases, including the Cochrane Register, MEDLINE, EMBASE, as well as reviewed bibliographies of relevant articles and spoke to experts in the field, to find randomized controlled trials that compared probiotics with placebo in reducing the incidence of CDAD in patients taking antibiotics. Two reviewers independently selected the articles, extracted data, and assessed study quality. Half of the 20 studies selected had either an unclear or high risk of bias; 7 studies had an overall low risk of bias. Patients included in the individual studies (N = 3818) varied in age and baseline risk of CDAD. Meta-analysis of the data showed that probiotics, as compared with placebo, reduced the incidence of CDAD in patients taking antibiotics (relative risk = 0.34; 95% CI, 0.24-0.49). Subgroup analyses showed similar results in adults and children, with lower and higher doses of probiotics, and with different probiotic species. There was no evidence of an increased risk of adverse events in the probiotics group. The majority of the studies excluded immunocompromised patients, thus limiting the generalizability of the results. Addtionally, the authors downrated the level of evidence to moderate quality because the overall sample size was smaller than what would be required for an optimally powered single study, which decreases the precision of the results.
Clinical question
Does the use of probiotics prevent Clostridium difficile-associated diarrhea in patients taking antibiotics?
Bottom line
Moderate-quality evidence suggests that probiotic administration reduces the incidence of C. difficile-associated diarrhea (CDAD) in patients who are taking antibiotics. LOE = 1a-
Reference
Study Design
Meta-analysis (other)
Funding Source
None
Setting
Various (meta-analysis)
Synopsis
These investigators searched multiple databases, including the Cochrane Register, MEDLINE, EMBASE, as well as reviewed bibliographies of relevant articles and spoke to experts in the field, to find randomized controlled trials that compared probiotics with placebo in reducing the incidence of CDAD in patients taking antibiotics. Two reviewers independently selected the articles, extracted data, and assessed study quality. Half of the 20 studies selected had either an unclear or high risk of bias; 7 studies had an overall low risk of bias. Patients included in the individual studies (N = 3818) varied in age and baseline risk of CDAD. Meta-analysis of the data showed that probiotics, as compared with placebo, reduced the incidence of CDAD in patients taking antibiotics (relative risk = 0.34; 95% CI, 0.24-0.49). Subgroup analyses showed similar results in adults and children, with lower and higher doses of probiotics, and with different probiotic species. There was no evidence of an increased risk of adverse events in the probiotics group. The majority of the studies excluded immunocompromised patients, thus limiting the generalizability of the results. Addtionally, the authors downrated the level of evidence to moderate quality because the overall sample size was smaller than what would be required for an optimally powered single study, which decreases the precision of the results.
Clinical question
Does the use of probiotics prevent Clostridium difficile-associated diarrhea in patients taking antibiotics?
Bottom line
Moderate-quality evidence suggests that probiotic administration reduces the incidence of C. difficile-associated diarrhea (CDAD) in patients who are taking antibiotics. LOE = 1a-
Reference
Study Design
Meta-analysis (other)
Funding Source
None
Setting
Various (meta-analysis)
Synopsis
These investigators searched multiple databases, including the Cochrane Register, MEDLINE, EMBASE, as well as reviewed bibliographies of relevant articles and spoke to experts in the field, to find randomized controlled trials that compared probiotics with placebo in reducing the incidence of CDAD in patients taking antibiotics. Two reviewers independently selected the articles, extracted data, and assessed study quality. Half of the 20 studies selected had either an unclear or high risk of bias; 7 studies had an overall low risk of bias. Patients included in the individual studies (N = 3818) varied in age and baseline risk of CDAD. Meta-analysis of the data showed that probiotics, as compared with placebo, reduced the incidence of CDAD in patients taking antibiotics (relative risk = 0.34; 95% CI, 0.24-0.49). Subgroup analyses showed similar results in adults and children, with lower and higher doses of probiotics, and with different probiotic species. There was no evidence of an increased risk of adverse events in the probiotics group. The majority of the studies excluded immunocompromised patients, thus limiting the generalizability of the results. Addtionally, the authors downrated the level of evidence to moderate quality because the overall sample size was smaller than what would be required for an optimally powered single study, which decreases the precision of the results.
No benefit to ultrafiltration for treatment of acute cardiorenal syndrome (CARRESS-HF)
Clinical question
Does ultrafiltration therapy result in improved diuresis in hospitalized patients with decompensated heart failure and worsening renal function?
Bottom line
For hospitalized patients with acute decompensated heart failure and worsening renal function, intravenous diuretic therapy is superior to ultrafiltration for preserving renal function while providing similar weight reduction. Moreover, ultrafiltration is a costly and invasive therapy that is associated with more adverse events. LOE = 1b
Reference
Study Design
Randomized controlled trial (nonblinded)
Funding Source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
In hospitalized patients with acute cardiorenal syndrome (acute heart failure exacerbation and worsening renal function), ultrafiltration is an alternative strategy for fluid removal. These investigators used concealed allocation to randomize 188 of these patients to receive either ultrafiltration therapy or pharmacologic therapy with intravenous diuretics for fluid removal. Patients with severe renal impairment were excluded (creatinine >3.5 mg/dL [> 309.4 umol/L]). In the pharmacologic therapy group, diuretic doses were adjusted as needed to achieve a urine output of 3 liters to 5 liters per day. In the ultrafiltration group, fluid removal was performed at a rate of 200 mL per hour. Both therapies were continued until symptoms and signs of congestion were optimally reduced. Participants had a median age of 68 years and a median ejection fraction of 33%. More than 75% had been hospitalized for heart failure within the previous year. Analysis was by intention to treat. The primary endpoint was change in weight and change in serum creatinine level at 96 hours postrandomization. Although there was no significant difference in weight loss between the 2 groups at 96 hours, there was a significant increase in serum creatinine level in the ultrafiltration group (an increase of 0.23 mg/dL [20.3 umol/L] in ultrafiltration group vs a decrease in creatinine of 0.04 mg/dL [3.5 umol/L] in diuretic group; P = .003). Despite the worsened renal function in the short-term, there were no differences in long-term outcomes between the 2 groups, including mortality and rehospitalization within 60 days. Finally, ultrafiltration patients were more likely to experience serious adverse events (72% vs 57%; P = .03) during the 60-day follow-up period, mainly due to kidney failure and intravenous catheter-related complications. Although the outcomes assessed were objective, the nonmasked methodology of this study may have introduced a bias on the part of the investigators as to how aggressively they pursued the 2 therapies.
Clinical question
Does ultrafiltration therapy result in improved diuresis in hospitalized patients with decompensated heart failure and worsening renal function?
Bottom line
For hospitalized patients with acute decompensated heart failure and worsening renal function, intravenous diuretic therapy is superior to ultrafiltration for preserving renal function while providing similar weight reduction. Moreover, ultrafiltration is a costly and invasive therapy that is associated with more adverse events. LOE = 1b
Reference
Study Design
Randomized controlled trial (nonblinded)
Funding Source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
In hospitalized patients with acute cardiorenal syndrome (acute heart failure exacerbation and worsening renal function), ultrafiltration is an alternative strategy for fluid removal. These investigators used concealed allocation to randomize 188 of these patients to receive either ultrafiltration therapy or pharmacologic therapy with intravenous diuretics for fluid removal. Patients with severe renal impairment were excluded (creatinine >3.5 mg/dL [> 309.4 umol/L]). In the pharmacologic therapy group, diuretic doses were adjusted as needed to achieve a urine output of 3 liters to 5 liters per day. In the ultrafiltration group, fluid removal was performed at a rate of 200 mL per hour. Both therapies were continued until symptoms and signs of congestion were optimally reduced. Participants had a median age of 68 years and a median ejection fraction of 33%. More than 75% had been hospitalized for heart failure within the previous year. Analysis was by intention to treat. The primary endpoint was change in weight and change in serum creatinine level at 96 hours postrandomization. Although there was no significant difference in weight loss between the 2 groups at 96 hours, there was a significant increase in serum creatinine level in the ultrafiltration group (an increase of 0.23 mg/dL [20.3 umol/L] in ultrafiltration group vs a decrease in creatinine of 0.04 mg/dL [3.5 umol/L] in diuretic group; P = .003). Despite the worsened renal function in the short-term, there were no differences in long-term outcomes between the 2 groups, including mortality and rehospitalization within 60 days. Finally, ultrafiltration patients were more likely to experience serious adverse events (72% vs 57%; P = .03) during the 60-day follow-up period, mainly due to kidney failure and intravenous catheter-related complications. Although the outcomes assessed were objective, the nonmasked methodology of this study may have introduced a bias on the part of the investigators as to how aggressively they pursued the 2 therapies.
Clinical question
Does ultrafiltration therapy result in improved diuresis in hospitalized patients with decompensated heart failure and worsening renal function?
Bottom line
For hospitalized patients with acute decompensated heart failure and worsening renal function, intravenous diuretic therapy is superior to ultrafiltration for preserving renal function while providing similar weight reduction. Moreover, ultrafiltration is a costly and invasive therapy that is associated with more adverse events. LOE = 1b
Reference
Study Design
Randomized controlled trial (nonblinded)
Funding Source
Government
Allocation
Concealed
Setting
Inpatient (any location)
Synopsis
In hospitalized patients with acute cardiorenal syndrome (acute heart failure exacerbation and worsening renal function), ultrafiltration is an alternative strategy for fluid removal. These investigators used concealed allocation to randomize 188 of these patients to receive either ultrafiltration therapy or pharmacologic therapy with intravenous diuretics for fluid removal. Patients with severe renal impairment were excluded (creatinine >3.5 mg/dL [> 309.4 umol/L]). In the pharmacologic therapy group, diuretic doses were adjusted as needed to achieve a urine output of 3 liters to 5 liters per day. In the ultrafiltration group, fluid removal was performed at a rate of 200 mL per hour. Both therapies were continued until symptoms and signs of congestion were optimally reduced. Participants had a median age of 68 years and a median ejection fraction of 33%. More than 75% had been hospitalized for heart failure within the previous year. Analysis was by intention to treat. The primary endpoint was change in weight and change in serum creatinine level at 96 hours postrandomization. Although there was no significant difference in weight loss between the 2 groups at 96 hours, there was a significant increase in serum creatinine level in the ultrafiltration group (an increase of 0.23 mg/dL [20.3 umol/L] in ultrafiltration group vs a decrease in creatinine of 0.04 mg/dL [3.5 umol/L] in diuretic group; P = .003). Despite the worsened renal function in the short-term, there were no differences in long-term outcomes between the 2 groups, including mortality and rehospitalization within 60 days. Finally, ultrafiltration patients were more likely to experience serious adverse events (72% vs 57%; P = .03) during the 60-day follow-up period, mainly due to kidney failure and intravenous catheter-related complications. Although the outcomes assessed were objective, the nonmasked methodology of this study may have introduced a bias on the part of the investigators as to how aggressively they pursued the 2 therapies.
Beware of subgroup analyses in trial results
Studies often include subgroup analyses outlining how a specific treatment is more or less effective in one group of patients compared with another. But clinicians, beware: Subgroup analyses too often are not clinically meaningful and should be interpreted cautiously, Dr. Sarah R. Barton and her associates reported in a poster presentation at the American Society for Clinical Oncology’s Gastrointestinal Cancers Symposium.
The investigators reviewed 145 randomized, controlled phase III trials published in peer-reviewed journals from January 2003 to January 2012 that tested an investigational therapy in GI cancer and that involved at least 150 patients. Subgroup analyses appeared in 100 studies (69%), more often in larger ones.
Here’s the shocking part: Only 25% of trials that claimed the treatment worked in a subgroup of patients had the statistical measures to back that up, reported Dr. Barton of Royal Marsden Hospital, Sutton, England. That proportion was the same for industry-sponsored and nonindustry trials.
The study, which won a Merit Award at the meeting, conducted some interesting subgroup analyses of its own. Trials sponsored by for-profit companies included a significantly higher number of subgroup analyses compared with nonindustry trials – a median of six versus two, respectively.
Trials of targeted therapies were more than three times as likely to report subgroup analyses compared with studies of cytotoxic therapies and included significantly more subgroup analyses (a median of six vs. two, respectively). Studies that reported a positive effect in the primary outcome also included a significantly higher median number of subgroup analyses compared with negative trials (again, six versus two).
Industry-sponsored trials that reported a positive effect in the primary outcome of the study were the most likely to report subgroup analyses (23 of 25 studies, or 95%) and to include the highest median number of subgroup analyses (eight) compared with industry-funded trials with a negative primary outcome or nonindustry trials, positive or negative.
Dr. Barton gave some clues that, in general, should cause physicians to look closely at efficacy claims. These include subgroup analyses conducted post hoc, when multiple tests are applied, when multiple endpoints are used, and if there’s no statistically significant test of interaction.
This is not just a problem in oncology. A previous study of 469 randomized, controlled trials published in 118 journals reported that industry-funded trials were less likely to define subgroups before starting the trial, less likely to use the interaction test for analyses of subgroup effects, and more likely to report on subgroups if the primary outcome in the study did not show a positive result (BMJ 2011;342:d1569)
The New England Journal of Medicine provides similar cautions in its guidelines for investigators reporting on subgroup analyses (N. Engl. J. Med. 2007;357:2189-2194).
Dr. Barton reported having no financial disclosures.
– Sherry Boschert
On Twitter @sherryboschert
Studies often include subgroup analyses outlining how a specific treatment is more or less effective in one group of patients compared with another. But clinicians, beware: Subgroup analyses too often are not clinically meaningful and should be interpreted cautiously, Dr. Sarah R. Barton and her associates reported in a poster presentation at the American Society for Clinical Oncology’s Gastrointestinal Cancers Symposium.
The investigators reviewed 145 randomized, controlled phase III trials published in peer-reviewed journals from January 2003 to January 2012 that tested an investigational therapy in GI cancer and that involved at least 150 patients. Subgroup analyses appeared in 100 studies (69%), more often in larger ones.
Here’s the shocking part: Only 25% of trials that claimed the treatment worked in a subgroup of patients had the statistical measures to back that up, reported Dr. Barton of Royal Marsden Hospital, Sutton, England. That proportion was the same for industry-sponsored and nonindustry trials.
The study, which won a Merit Award at the meeting, conducted some interesting subgroup analyses of its own. Trials sponsored by for-profit companies included a significantly higher number of subgroup analyses compared with nonindustry trials – a median of six versus two, respectively.
Trials of targeted therapies were more than three times as likely to report subgroup analyses compared with studies of cytotoxic therapies and included significantly more subgroup analyses (a median of six vs. two, respectively). Studies that reported a positive effect in the primary outcome also included a significantly higher median number of subgroup analyses compared with negative trials (again, six versus two).
Industry-sponsored trials that reported a positive effect in the primary outcome of the study were the most likely to report subgroup analyses (23 of 25 studies, or 95%) and to include the highest median number of subgroup analyses (eight) compared with industry-funded trials with a negative primary outcome or nonindustry trials, positive or negative.
Dr. Barton gave some clues that, in general, should cause physicians to look closely at efficacy claims. These include subgroup analyses conducted post hoc, when multiple tests are applied, when multiple endpoints are used, and if there’s no statistically significant test of interaction.
This is not just a problem in oncology. A previous study of 469 randomized, controlled trials published in 118 journals reported that industry-funded trials were less likely to define subgroups before starting the trial, less likely to use the interaction test for analyses of subgroup effects, and more likely to report on subgroups if the primary outcome in the study did not show a positive result (BMJ 2011;342:d1569)
The New England Journal of Medicine provides similar cautions in its guidelines for investigators reporting on subgroup analyses (N. Engl. J. Med. 2007;357:2189-2194).
Dr. Barton reported having no financial disclosures.
– Sherry Boschert
On Twitter @sherryboschert
Studies often include subgroup analyses outlining how a specific treatment is more or less effective in one group of patients compared with another. But clinicians, beware: Subgroup analyses too often are not clinically meaningful and should be interpreted cautiously, Dr. Sarah R. Barton and her associates reported in a poster presentation at the American Society for Clinical Oncology’s Gastrointestinal Cancers Symposium.
The investigators reviewed 145 randomized, controlled phase III trials published in peer-reviewed journals from January 2003 to January 2012 that tested an investigational therapy in GI cancer and that involved at least 150 patients. Subgroup analyses appeared in 100 studies (69%), more often in larger ones.
Here’s the shocking part: Only 25% of trials that claimed the treatment worked in a subgroup of patients had the statistical measures to back that up, reported Dr. Barton of Royal Marsden Hospital, Sutton, England. That proportion was the same for industry-sponsored and nonindustry trials.
The study, which won a Merit Award at the meeting, conducted some interesting subgroup analyses of its own. Trials sponsored by for-profit companies included a significantly higher number of subgroup analyses compared with nonindustry trials – a median of six versus two, respectively.
Trials of targeted therapies were more than three times as likely to report subgroup analyses compared with studies of cytotoxic therapies and included significantly more subgroup analyses (a median of six vs. two, respectively). Studies that reported a positive effect in the primary outcome also included a significantly higher median number of subgroup analyses compared with negative trials (again, six versus two).
Industry-sponsored trials that reported a positive effect in the primary outcome of the study were the most likely to report subgroup analyses (23 of 25 studies, or 95%) and to include the highest median number of subgroup analyses (eight) compared with industry-funded trials with a negative primary outcome or nonindustry trials, positive or negative.
Dr. Barton gave some clues that, in general, should cause physicians to look closely at efficacy claims. These include subgroup analyses conducted post hoc, when multiple tests are applied, when multiple endpoints are used, and if there’s no statistically significant test of interaction.
This is not just a problem in oncology. A previous study of 469 randomized, controlled trials published in 118 journals reported that industry-funded trials were less likely to define subgroups before starting the trial, less likely to use the interaction test for analyses of subgroup effects, and more likely to report on subgroups if the primary outcome in the study did not show a positive result (BMJ 2011;342:d1569)
The New England Journal of Medicine provides similar cautions in its guidelines for investigators reporting on subgroup analyses (N. Engl. J. Med. 2007;357:2189-2194).
Dr. Barton reported having no financial disclosures.
– Sherry Boschert
On Twitter @sherryboschert
Heavy Workloads Burden Hospitalists, Raise Concerns about Patient Safety
A recent study in which 36% of hospitalists reported that their workload exceeds safe patient census levels at least once a week could spur serious discussions on productivity and quality of care, according to one of its authors.
Daniel Brotman, MD, FACP, FHM, director of the hospitalist program at Johns Hopkins Hospital in Baltimore and one of the study's authors, says the results highlight the delicate balance between pushing hospitalists to generate revenue and maintaining patient safety.
"It's certainly not in the best interest of our patients or our healthcare system to fix financial stress by expecting more clinical productivity of doctors year over year,” he says. "At some point, and it's self-evident—at least in my mind—quality starts to suffer when workload gets excessive."
The report, "Impact of Attending Physician Workload on Patient Care: A Survey of Hospitalists," details findings of the first study to assess perception of unsafe workloads by directly questioning physicians, according to its authors. They electronically queried 506 hospitalists enrolled in the physicians' online network and information site QuantiaMD.com.
As many as 40% of physicians reported their typical inpatient census exceeded safe levels at least once monthly, the report noted, and physicians pegged 15 as the optimal number of patients to see on a shift dedicated to clinical work.
John Nelson, MD, MHM, a principal in Nelson Flores Hospital Medicine Consultants in La Quinta, Calif., says staffing shortages are likely the most common cause of heavy workloads, and that the high number of physicians reporting overloaded censuses is evidence that hospitalists are concerned their job performance is adversely affected.
"I suspect that as belt-tightening continues to occur," Dr. Brotman adds, "we're going to see the importance of [research] like this increasing, because we're going to see more and more stressed-out, overextended doctors who are having trouble delivering the care that they know they can deliver if they had more time."
Visit our website for more information on hospital medicine workloads.
A recent study in which 36% of hospitalists reported that their workload exceeds safe patient census levels at least once a week could spur serious discussions on productivity and quality of care, according to one of its authors.
Daniel Brotman, MD, FACP, FHM, director of the hospitalist program at Johns Hopkins Hospital in Baltimore and one of the study's authors, says the results highlight the delicate balance between pushing hospitalists to generate revenue and maintaining patient safety.
"It's certainly not in the best interest of our patients or our healthcare system to fix financial stress by expecting more clinical productivity of doctors year over year,” he says. "At some point, and it's self-evident—at least in my mind—quality starts to suffer when workload gets excessive."
The report, "Impact of Attending Physician Workload on Patient Care: A Survey of Hospitalists," details findings of the first study to assess perception of unsafe workloads by directly questioning physicians, according to its authors. They electronically queried 506 hospitalists enrolled in the physicians' online network and information site QuantiaMD.com.
As many as 40% of physicians reported their typical inpatient census exceeded safe levels at least once monthly, the report noted, and physicians pegged 15 as the optimal number of patients to see on a shift dedicated to clinical work.
John Nelson, MD, MHM, a principal in Nelson Flores Hospital Medicine Consultants in La Quinta, Calif., says staffing shortages are likely the most common cause of heavy workloads, and that the high number of physicians reporting overloaded censuses is evidence that hospitalists are concerned their job performance is adversely affected.
"I suspect that as belt-tightening continues to occur," Dr. Brotman adds, "we're going to see the importance of [research] like this increasing, because we're going to see more and more stressed-out, overextended doctors who are having trouble delivering the care that they know they can deliver if they had more time."
Visit our website for more information on hospital medicine workloads.
A recent study in which 36% of hospitalists reported that their workload exceeds safe patient census levels at least once a week could spur serious discussions on productivity and quality of care, according to one of its authors.
Daniel Brotman, MD, FACP, FHM, director of the hospitalist program at Johns Hopkins Hospital in Baltimore and one of the study's authors, says the results highlight the delicate balance between pushing hospitalists to generate revenue and maintaining patient safety.
"It's certainly not in the best interest of our patients or our healthcare system to fix financial stress by expecting more clinical productivity of doctors year over year,” he says. "At some point, and it's self-evident—at least in my mind—quality starts to suffer when workload gets excessive."
The report, "Impact of Attending Physician Workload on Patient Care: A Survey of Hospitalists," details findings of the first study to assess perception of unsafe workloads by directly questioning physicians, according to its authors. They electronically queried 506 hospitalists enrolled in the physicians' online network and information site QuantiaMD.com.
As many as 40% of physicians reported their typical inpatient census exceeded safe levels at least once monthly, the report noted, and physicians pegged 15 as the optimal number of patients to see on a shift dedicated to clinical work.
John Nelson, MD, MHM, a principal in Nelson Flores Hospital Medicine Consultants in La Quinta, Calif., says staffing shortages are likely the most common cause of heavy workloads, and that the high number of physicians reporting overloaded censuses is evidence that hospitalists are concerned their job performance is adversely affected.
"I suspect that as belt-tightening continues to occur," Dr. Brotman adds, "we're going to see the importance of [research] like this increasing, because we're going to see more and more stressed-out, overextended doctors who are having trouble delivering the care that they know they can deliver if they had more time."
Visit our website for more information on hospital medicine workloads.
Former SHM President Lands South Carolina Hospital’s Top Post
Patrick Cawley, MD, MBA, MHM, a past president of SHM and a recipient of its prestigious Master of Hospital Medicine award, has been named vice president for clinical operations and executive director of the Medical University Hospital Authority at the Medical University of South Carolina (MUSC) in Charleston.
"What distinguished Dr. Cawley from the rest of the field is his intimate knowledge of MUSC, his medical expertise combined with graduate education in management, and his track record of improving our performance in quality and patient safety," says Raymond S. Greenberg, MD, PhD, and president of MUSC. "Given his familiarity with the issues here, Dr. Cawley can step in quickly to assume his new responsibilities. He's already demonstrating steady and thoughtful leadership."
Dr. Cawley took his first leadership course 15 years ago. That led to other courses on such topics as marketing and finance, and that led to his earning a master’s degree in business administration from the University of Massachusetts at Amherst. "Just like medicine, you never stop learning in business or trying to do things better," he says.
Dr. Cawley says hospitalists have a leg up on other physicians when it comes to moving into hospital administration. "Being a hospitalist allowed me to get into every nook and cranny of this hospital," he says. He advises other hospitalists interested in this path to seek out progressive leadership roles. “Show what you can do,” he says, “and get that management degree.”
As Dr. Cawley's administrative responsibilities continue to expand, the time he spends in clinical practice continues to decrease. Although he plans to give up clinical work for the crucial first six months in his new position, he says he hopes to return to hospitalist practice at least 10% of the time after that.
"Any CEO worth his or her salt goes out to the front lines to see what is happening," Dr. Cawley notes. "As a physician, it is easier to get to those front lines. Once there, you get a feel for how the hospital really runs."
Visit our website for more information about executive leadership positions in hospitals.
Patrick Cawley, MD, MBA, MHM, a past president of SHM and a recipient of its prestigious Master of Hospital Medicine award, has been named vice president for clinical operations and executive director of the Medical University Hospital Authority at the Medical University of South Carolina (MUSC) in Charleston.
"What distinguished Dr. Cawley from the rest of the field is his intimate knowledge of MUSC, his medical expertise combined with graduate education in management, and his track record of improving our performance in quality and patient safety," says Raymond S. Greenberg, MD, PhD, and president of MUSC. "Given his familiarity with the issues here, Dr. Cawley can step in quickly to assume his new responsibilities. He's already demonstrating steady and thoughtful leadership."
Dr. Cawley took his first leadership course 15 years ago. That led to other courses on such topics as marketing and finance, and that led to his earning a master’s degree in business administration from the University of Massachusetts at Amherst. "Just like medicine, you never stop learning in business or trying to do things better," he says.
Dr. Cawley says hospitalists have a leg up on other physicians when it comes to moving into hospital administration. "Being a hospitalist allowed me to get into every nook and cranny of this hospital," he says. He advises other hospitalists interested in this path to seek out progressive leadership roles. “Show what you can do,” he says, “and get that management degree.”
As Dr. Cawley's administrative responsibilities continue to expand, the time he spends in clinical practice continues to decrease. Although he plans to give up clinical work for the crucial first six months in his new position, he says he hopes to return to hospitalist practice at least 10% of the time after that.
"Any CEO worth his or her salt goes out to the front lines to see what is happening," Dr. Cawley notes. "As a physician, it is easier to get to those front lines. Once there, you get a feel for how the hospital really runs."
Visit our website for more information about executive leadership positions in hospitals.
Patrick Cawley, MD, MBA, MHM, a past president of SHM and a recipient of its prestigious Master of Hospital Medicine award, has been named vice president for clinical operations and executive director of the Medical University Hospital Authority at the Medical University of South Carolina (MUSC) in Charleston.
"What distinguished Dr. Cawley from the rest of the field is his intimate knowledge of MUSC, his medical expertise combined with graduate education in management, and his track record of improving our performance in quality and patient safety," says Raymond S. Greenberg, MD, PhD, and president of MUSC. "Given his familiarity with the issues here, Dr. Cawley can step in quickly to assume his new responsibilities. He's already demonstrating steady and thoughtful leadership."
Dr. Cawley took his first leadership course 15 years ago. That led to other courses on such topics as marketing and finance, and that led to his earning a master’s degree in business administration from the University of Massachusetts at Amherst. "Just like medicine, you never stop learning in business or trying to do things better," he says.
Dr. Cawley says hospitalists have a leg up on other physicians when it comes to moving into hospital administration. "Being a hospitalist allowed me to get into every nook and cranny of this hospital," he says. He advises other hospitalists interested in this path to seek out progressive leadership roles. “Show what you can do,” he says, “and get that management degree.”
As Dr. Cawley's administrative responsibilities continue to expand, the time he spends in clinical practice continues to decrease. Although he plans to give up clinical work for the crucial first six months in his new position, he says he hopes to return to hospitalist practice at least 10% of the time after that.
"Any CEO worth his or her salt goes out to the front lines to see what is happening," Dr. Cawley notes. "As a physician, it is easier to get to those front lines. Once there, you get a feel for how the hospital really runs."
Visit our website for more information about executive leadership positions in hospitals.
FDA approves pomalidomide for MM
Credit: Steven Harbour
The US Food and Drug Administration (FDA) has granted accelerated approval for the immunomodulatory agent pomalidomide (Pomalyst) to treat patients with advanced multiple myeloma (MM).
Continued FDA approval for the drug may be contingent upon verification and description of clinical benefit in confirmatory trials.
Pomalidomide is intended for use in combination with dexamethasone to treat MM patients who have received at least 2 prior
therapies (including lenalidomide and a proteasome inhibitor) and who experienced progression within 60 days of their last treatment.
Pomalidomide has demonstrated some efficacy in this patient population in a number of studies.
In a study published in Blood last year (PG Richardson et al.), pomalidomide elicited responses in MM patients who were refractory to lenalidomide, bortezomib, or both drugs.
In a study presented at ASH 2011 (abstract 634), pomalidomide did not fare as well when given alone to patients with refractory MM. However, combining the drug with low-dose dexamethasone significantly improved responses.
A study presented at ASH 2012 (LBA-6) built upon those findings, showing that pomalidomide plus low-dose dexamethasone was superior to high-dose dexamethasone in MM patients who were refractory to lenalidomide and bortezomib.
Common side effects observed with pomalidomide include neutropenia, anemia, thrombocytopenia, fatigue, weakness, constipation, diarrhea, upper respiratory tract infections, back pain, and fever.
In addition, pomalidomide has been shown to cause venous thromboembolism, as well as severe, life-threatening birth defects in pregnant women. The drug carries a boxed warning alerting patients and healthcare professionals to both of these risks.
Because of the embryo-fetal risk, pomalidomide is available only through the Pomalyst Risk Evaluation and Mitigation Strategy (REMS) Program. Prescribers must be certified with the program by enrolling and complying with the REMS requirements.
Patients must sign a patient-physician agreement form and comply with the REMS requirements. In particular, female patients who are not pregnant but can become pregnant must comply with the pregnancy testing and contraception requirements, and males must comply with contraception requirements.
Pharmacies must be certified with the Pomalyst REMS Program, must only dispense the drug to patients who are authorized to receive it, and must comply with REMS requirements. Both lenalidomide and thalidomide have similar REMS.
Pomalidomide is marketed by Celgene, which is based in Summit, New Jersey. 
Credit: Steven Harbour
The US Food and Drug Administration (FDA) has granted accelerated approval for the immunomodulatory agent pomalidomide (Pomalyst) to treat patients with advanced multiple myeloma (MM).
Continued FDA approval for the drug may be contingent upon verification and description of clinical benefit in confirmatory trials.
Pomalidomide is intended for use in combination with dexamethasone to treat MM patients who have received at least 2 prior
therapies (including lenalidomide and a proteasome inhibitor) and who experienced progression within 60 days of their last treatment.
Pomalidomide has demonstrated some efficacy in this patient population in a number of studies.
In a study published in Blood last year (PG Richardson et al.), pomalidomide elicited responses in MM patients who were refractory to lenalidomide, bortezomib, or both drugs.
In a study presented at ASH 2011 (abstract 634), pomalidomide did not fare as well when given alone to patients with refractory MM. However, combining the drug with low-dose dexamethasone significantly improved responses.
A study presented at ASH 2012 (LBA-6) built upon those findings, showing that pomalidomide plus low-dose dexamethasone was superior to high-dose dexamethasone in MM patients who were refractory to lenalidomide and bortezomib.
Common side effects observed with pomalidomide include neutropenia, anemia, thrombocytopenia, fatigue, weakness, constipation, diarrhea, upper respiratory tract infections, back pain, and fever.
In addition, pomalidomide has been shown to cause venous thromboembolism, as well as severe, life-threatening birth defects in pregnant women. The drug carries a boxed warning alerting patients and healthcare professionals to both of these risks.
Because of the embryo-fetal risk, pomalidomide is available only through the Pomalyst Risk Evaluation and Mitigation Strategy (REMS) Program. Prescribers must be certified with the program by enrolling and complying with the REMS requirements.
Patients must sign a patient-physician agreement form and comply with the REMS requirements. In particular, female patients who are not pregnant but can become pregnant must comply with the pregnancy testing and contraception requirements, and males must comply with contraception requirements.
Pharmacies must be certified with the Pomalyst REMS Program, must only dispense the drug to patients who are authorized to receive it, and must comply with REMS requirements. Both lenalidomide and thalidomide have similar REMS.
Pomalidomide is marketed by Celgene, which is based in Summit, New Jersey.
Credit: Steven Harbour
The US Food and Drug Administration (FDA) has granted accelerated approval for the immunomodulatory agent pomalidomide (Pomalyst) to treat patients with advanced multiple myeloma (MM).
Continued FDA approval for the drug may be contingent upon verification and description of clinical benefit in confirmatory trials.
Pomalidomide is intended for use in combination with dexamethasone to treat MM patients who have received at least 2 prior
therapies (including lenalidomide and a proteasome inhibitor) and who experienced progression within 60 days of their last treatment.
Pomalidomide has demonstrated some efficacy in this patient population in a number of studies.
In a study published in Blood last year (PG Richardson et al.), pomalidomide elicited responses in MM patients who were refractory to lenalidomide, bortezomib, or both drugs.
In a study presented at ASH 2011 (abstract 634), pomalidomide did not fare as well when given alone to patients with refractory MM. However, combining the drug with low-dose dexamethasone significantly improved responses.
A study presented at ASH 2012 (LBA-6) built upon those findings, showing that pomalidomide plus low-dose dexamethasone was superior to high-dose dexamethasone in MM patients who were refractory to lenalidomide and bortezomib.
Common side effects observed with pomalidomide include neutropenia, anemia, thrombocytopenia, fatigue, weakness, constipation, diarrhea, upper respiratory tract infections, back pain, and fever.
In addition, pomalidomide has been shown to cause venous thromboembolism, as well as severe, life-threatening birth defects in pregnant women. The drug carries a boxed warning alerting patients and healthcare professionals to both of these risks.
Because of the embryo-fetal risk, pomalidomide is available only through the Pomalyst Risk Evaluation and Mitigation Strategy (REMS) Program. Prescribers must be certified with the program by enrolling and complying with the REMS requirements.
Patients must sign a patient-physician agreement form and comply with the REMS requirements. In particular, female patients who are not pregnant but can become pregnant must comply with the pregnancy testing and contraception requirements, and males must comply with contraception requirements.
Pharmacies must be certified with the Pomalyst REMS Program, must only dispense the drug to patients who are authorized to receive it, and must comply with REMS requirements. Both lenalidomide and thalidomide have similar REMS.
Pomalidomide is marketed by Celgene, which is based in Summit, New Jersey.
Report: Hospitals Show Improvement on Infection Rates, but Progress Slows on CAUTIs
U.S. hospitals in 2011 showed improvements in their rates of central line-associated bloodstream infections (CLABSI) and in some surgical-site infections, compared with 2010, but the rate essentially hit a plateau for catheter-associated urinary tract infections (CAUTI), according to a new CDC report.
“Reductions in some of the deadliest healthcare-associated infections are encouraging, especially when you consider the costs to both patients and the health care system,” CDC director Thomas R. Frieden, MD, MPH, says. “However, the slower progress in reducing catheter-associated urinary tract infections is a call to action for hospitals to redouble their efforts to track these infections and implement control strategies we know that work.”
The report showed a 41% reduction in 2011 central-line infections compared with 2008, the baseline year for the report. In 2010, the reduction was 32% over the 2008 baseline. The improvement was seen across ICUs, general wards, and neonatal ICUs.
—Scott Flanders, MD, SFHM, professor of medicine, director of hospital medicine, University of Michigan Health System, Ann Arbor, former SHM president
The CDC also reported a 17% drop in surgical-site infections since 2008, better than the 7% reduction in 2010. The biggest reductions were seen in coronary artery bypass graft surgery and cardiac surgery; little improvement was seen in infections from hip arthroplasty and vaginal hysterectomy procedures.
The rate of infections from CAUTIs was 7%, nearly the same as the 6% rate in 2010 data. The infection rate in ICUs actually went up—a 1% drop in 2011 compared with a 3% drop from baseline in 2010.
SHM is a partner in two initiatives that aim to reduce CAUTI infections: the University HealthSystems Consortium’s Partnership for Patients project and On the CUSP: STOP CAUTI, an American Hospital Association HRET effort that’s funded by the Agency for Healthcare Research and Quality-funded project.
Gregory Maynard, MD, SFHM, director of hospital medicine at the University of San Diego Medical Center and senior vice president of SHM’s Center for Healthcare Improvement and Innovation is encouraged by the CLABSI and SSI figures. The report highlights the need for more effort on CAUTI.
“I think all the tools and information are available for improvement teams,” he says. “The CDC, the HRET On the CUSP group, and others all have great toolkits.”
He also says it was telling that the CAUTI numbers were worse in the ICU than in general wards.
“The more complex the environment, the easier it is for those things to get lost,” he says. “It just will probably take more attention to it and making it more of a priority.
“The more complex the environment, the easier it is for those things to get lost. It just will probably take more attention to it and making it more of a priority…. We’re supposed to reduce these adverse events by a very significant amount and obviously we’re not getting there based on this report. We have to do a better job. Reducing CAUTI by 40% is one of goals for the $500 million Partnerships for Patients effort. With that much money involved, it should increase the pressure to get this done.”
Click here to hear more of Dr. Maynard's interview with The Hospitalist
Scott Flanders, MD, SFHM, a former SHM president and SHM’s physician leader for STOP CAUTI, says the report shows that CAUTIs may be more difficult to prevent. In part, that is because catheters are used more broadly throughout a hospital than, say, central lines, which are most common in ICUs.
It takes a multi-disciplinary team implementing a variety of tools: critieria for putting catheters in, managing them appropriately once they are in, and developing protocols for removing them as quickly as possible, he adds.
“Having all those elements in place are critical to preventing CAUTI and I think many hospitals around the country have not implemented all of those strategies to reduce CAUTI,” says Dr. Flanders, professor of medicine and director of hospital medicine at the University of Michigan Health System in Ann Arbor. “No single strategy used in isolation is going to be effective.”
Efforts to reduce CAUTIs have been launched more recently than efforts to reduce other infection types, he says.
“There’s been less of a drive for CAUTI,” he says. “It’s a tougher problem to tackle than some of these other issues, which is a contributing factor in the lower rate of improvement.” TH
Tom Collins is a freelance writer in South Florida.
U.S. hospitals in 2011 showed improvements in their rates of central line-associated bloodstream infections (CLABSI) and in some surgical-site infections, compared with 2010, but the rate essentially hit a plateau for catheter-associated urinary tract infections (CAUTI), according to a new CDC report.
“Reductions in some of the deadliest healthcare-associated infections are encouraging, especially when you consider the costs to both patients and the health care system,” CDC director Thomas R. Frieden, MD, MPH, says. “However, the slower progress in reducing catheter-associated urinary tract infections is a call to action for hospitals to redouble their efforts to track these infections and implement control strategies we know that work.”
The report showed a 41% reduction in 2011 central-line infections compared with 2008, the baseline year for the report. In 2010, the reduction was 32% over the 2008 baseline. The improvement was seen across ICUs, general wards, and neonatal ICUs.
—Scott Flanders, MD, SFHM, professor of medicine, director of hospital medicine, University of Michigan Health System, Ann Arbor, former SHM president
The CDC also reported a 17% drop in surgical-site infections since 2008, better than the 7% reduction in 2010. The biggest reductions were seen in coronary artery bypass graft surgery and cardiac surgery; little improvement was seen in infections from hip arthroplasty and vaginal hysterectomy procedures.
The rate of infections from CAUTIs was 7%, nearly the same as the 6% rate in 2010 data. The infection rate in ICUs actually went up—a 1% drop in 2011 compared with a 3% drop from baseline in 2010.
SHM is a partner in two initiatives that aim to reduce CAUTI infections: the University HealthSystems Consortium’s Partnership for Patients project and On the CUSP: STOP CAUTI, an American Hospital Association HRET effort that’s funded by the Agency for Healthcare Research and Quality-funded project.
Gregory Maynard, MD, SFHM, director of hospital medicine at the University of San Diego Medical Center and senior vice president of SHM’s Center for Healthcare Improvement and Innovation is encouraged by the CLABSI and SSI figures. The report highlights the need for more effort on CAUTI.
“I think all the tools and information are available for improvement teams,” he says. “The CDC, the HRET On the CUSP group, and others all have great toolkits.”
He also says it was telling that the CAUTI numbers were worse in the ICU than in general wards.
“The more complex the environment, the easier it is for those things to get lost,” he says. “It just will probably take more attention to it and making it more of a priority.
“The more complex the environment, the easier it is for those things to get lost. It just will probably take more attention to it and making it more of a priority…. We’re supposed to reduce these adverse events by a very significant amount and obviously we’re not getting there based on this report. We have to do a better job. Reducing CAUTI by 40% is one of goals for the $500 million Partnerships for Patients effort. With that much money involved, it should increase the pressure to get this done.”
Click here to hear more of Dr. Maynard's interview with The Hospitalist
Scott Flanders, MD, SFHM, a former SHM president and SHM’s physician leader for STOP CAUTI, says the report shows that CAUTIs may be more difficult to prevent. In part, that is because catheters are used more broadly throughout a hospital than, say, central lines, which are most common in ICUs.
It takes a multi-disciplinary team implementing a variety of tools: critieria for putting catheters in, managing them appropriately once they are in, and developing protocols for removing them as quickly as possible, he adds.
“Having all those elements in place are critical to preventing CAUTI and I think many hospitals around the country have not implemented all of those strategies to reduce CAUTI,” says Dr. Flanders, professor of medicine and director of hospital medicine at the University of Michigan Health System in Ann Arbor. “No single strategy used in isolation is going to be effective.”
Efforts to reduce CAUTIs have been launched more recently than efforts to reduce other infection types, he says.
“There’s been less of a drive for CAUTI,” he says. “It’s a tougher problem to tackle than some of these other issues, which is a contributing factor in the lower rate of improvement.” TH
Tom Collins is a freelance writer in South Florida.
U.S. hospitals in 2011 showed improvements in their rates of central line-associated bloodstream infections (CLABSI) and in some surgical-site infections, compared with 2010, but the rate essentially hit a plateau for catheter-associated urinary tract infections (CAUTI), according to a new CDC report.
“Reductions in some of the deadliest healthcare-associated infections are encouraging, especially when you consider the costs to both patients and the health care system,” CDC director Thomas R. Frieden, MD, MPH, says. “However, the slower progress in reducing catheter-associated urinary tract infections is a call to action for hospitals to redouble their efforts to track these infections and implement control strategies we know that work.”
The report showed a 41% reduction in 2011 central-line infections compared with 2008, the baseline year for the report. In 2010, the reduction was 32% over the 2008 baseline. The improvement was seen across ICUs, general wards, and neonatal ICUs.
—Scott Flanders, MD, SFHM, professor of medicine, director of hospital medicine, University of Michigan Health System, Ann Arbor, former SHM president
The CDC also reported a 17% drop in surgical-site infections since 2008, better than the 7% reduction in 2010. The biggest reductions were seen in coronary artery bypass graft surgery and cardiac surgery; little improvement was seen in infections from hip arthroplasty and vaginal hysterectomy procedures.
The rate of infections from CAUTIs was 7%, nearly the same as the 6% rate in 2010 data. The infection rate in ICUs actually went up—a 1% drop in 2011 compared with a 3% drop from baseline in 2010.
SHM is a partner in two initiatives that aim to reduce CAUTI infections: the University HealthSystems Consortium’s Partnership for Patients project and On the CUSP: STOP CAUTI, an American Hospital Association HRET effort that’s funded by the Agency for Healthcare Research and Quality-funded project.
Gregory Maynard, MD, SFHM, director of hospital medicine at the University of San Diego Medical Center and senior vice president of SHM’s Center for Healthcare Improvement and Innovation is encouraged by the CLABSI and SSI figures. The report highlights the need for more effort on CAUTI.
“I think all the tools and information are available for improvement teams,” he says. “The CDC, the HRET On the CUSP group, and others all have great toolkits.”
He also says it was telling that the CAUTI numbers were worse in the ICU than in general wards.
“The more complex the environment, the easier it is for those things to get lost,” he says. “It just will probably take more attention to it and making it more of a priority.
“The more complex the environment, the easier it is for those things to get lost. It just will probably take more attention to it and making it more of a priority…. We’re supposed to reduce these adverse events by a very significant amount and obviously we’re not getting there based on this report. We have to do a better job. Reducing CAUTI by 40% is one of goals for the $500 million Partnerships for Patients effort. With that much money involved, it should increase the pressure to get this done.”
Click here to hear more of Dr. Maynard's interview with The Hospitalist
Scott Flanders, MD, SFHM, a former SHM president and SHM’s physician leader for STOP CAUTI, says the report shows that CAUTIs may be more difficult to prevent. In part, that is because catheters are used more broadly throughout a hospital than, say, central lines, which are most common in ICUs.
It takes a multi-disciplinary team implementing a variety of tools: critieria for putting catheters in, managing them appropriately once they are in, and developing protocols for removing them as quickly as possible, he adds.
“Having all those elements in place are critical to preventing CAUTI and I think many hospitals around the country have not implemented all of those strategies to reduce CAUTI,” says Dr. Flanders, professor of medicine and director of hospital medicine at the University of Michigan Health System in Ann Arbor. “No single strategy used in isolation is going to be effective.”
Efforts to reduce CAUTIs have been launched more recently than efforts to reduce other infection types, he says.
“There’s been less of a drive for CAUTI,” he says. “It’s a tougher problem to tackle than some of these other issues, which is a contributing factor in the lower rate of improvement.” TH
Tom Collins is a freelance writer in South Florida.