Recognition that healthcare carries considerable risks of patient injury has focused efforts on identifying problems before they occur, and understanding the root causes of those problems that do occur to prevent them from happening again.1 To further these efforts, a Joint Commission (JC) standard requires hospitals to review sentinel events (SE).2 Reviews must develop a timely, thorough, and credible root cause analysis (RCA), implement action plans to reduce risk, and monitor the effectiveness of implemented improvements.3

Ideally, hospitals would summarize their experiences with SE reviews, identify high‐risk activities and patients, institute system changes to prevent SE recurrences, and share their findings with other healthcare organizations to help them avoid similar patient injuries.1 In support of this last goal, the JC maintains a voluntary database system that allows hospitals to report their SE analyses for other facilities to review and institute preventative actions.

Unfortunately, the reality of SE reviews does not match their ideals for improving patient safety.4 Healthcare organizations often describe their review process as less than credible and note a need for ongoing oversight to maintain the reviews' effectiveness.5 The JC voluntary reporting system captures less than 1% of the SEs that occur nationally,2 because hospitals perceive barriers to external reporting.1 If healthcare organizations decide against reporting externally, they can create their own internal systems to aggregate and summarize SEs, but few such systems exist. A major impediment to designing internal systems is the absence of universally endorsed nomenclature for safety‐related events.6, 7 Poorly aligned terminology and subjective conceptualizations for safety incidents impede the aggregation of SEs, comparisons between facilities, and trend analyses for tracking SE patterns.

In 2005, the World Health Organization (WHO) World Alliance for Patient Safety, in collaboration with the JC, began developing an International Classification for Patient Safety (ICPS) to provide healthcare organizations a consistent conceptual model for safety incidents and promote their classification by a standardized taxonomy.810 Although this system has promise for allowing standardization, data aggregation, analysis, and learning between institutions,11 integration of the ICPS conceptual model into an SE decision support tool with summarizing and reporting features has not been reported.

This report describes our development of an intranet‐based SE reporting system, called Incident Tracker (I‐Tracker), based on the ICPS model. For our SE review groups from the 4 Providence Health Systems (PHS) Portland Service Area (PSA) hospitals, the I‐Tracker system offers a tool to guide efforts in developing RCAs and action plans in alignment with the ICPS framework. The system includes scripts that automatically generate and distribute standardized reports of individual and aggregated SEs. The objectives of this project were to report our experience with developing a flexible and accessible intranet‐based system that assists RCA participants in conforming to the ICPS framework and oversight safety staff in summarizing and reporting root cause analyses.

METHODS

The 4 PSA hospitals have 1083 licensed beds and perform SE reviews with a centralized process that reports results to a Community Governing Board. An ad hoc team for each SE performs the RCAs. The SE groups report RCAs and action plans in an unstructured format that varies for each event. A paper file is maintained for each SE report, but a system for aggregating reports to track trends, disseminating SE trends, or monitoring the completion or effectiveness of action plans is not available.

We designed a system to achieve the following objectives:

• 1

  Apply the ICPS framework (Figure 1) and taxonomy of terms to SE analyses;

• 2

  Provide a computer‐based tool to assist review groups and quality staff to perform their SE reviews and data collection in alignment with the ICPS framework;

• 3

  Create an intranet‐based database that captures elements of the reviews, RCAs, and action plans with the use of drop‐down lists, help windows, windows with live access to Internet educational resources and tools, decision support tools, default entries, and audio prompts to streamline data entry;

• 4

  Generate a suite of standardized reports customized for different audiences that can be accessed online and printed from the database with automated scripts;

• 5

  Produce intranet‐based summaries of aggregated events to identify common causes and disseminate observed patterns and action plans to other PSA hospitals.

Figure 1

We selected FileMaker Pro 11 Advanced (FMP11) for authoring and maintaining the decision support tool and database, and FileMaker Pro Server 11 Advanced (FMPS11) (Filemaker, Inc, Santa Clara, CA) for hosting the system, because it provides intranet access and tools for updating the system by personnel with minimal programming experience. End users can view and enter data through layouts that display only the information allowed by the user's login password and access privileges, with external authentication by Active Directory and Open Directory technology. Staff who author and manage the database do so through client FMP11 software loaded on a computer that provides remote server access.

The I‐Tracker system was authored using the ICPS definitions for the 48 preferred terms for safety incidents and the ICPS conceptual framework.8 The conceptual framework consists of 10 major incident domains, that include incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors and hazards, organizational outcomes, detection, mitigating factors, ameliorating actions, and actions taken to reduce risk (Figure 1).11 The framework is applicable to all hospital safety incidents, but we limited I‐Tracker to SEs because our hospitals had completed comprehensive reviews and action plans only for these more serious events. The literature on the ICPS framework812 was carefully reviewed to identify the specific data fields that were recommended by ICPS developers to be included under each of the 10 major classification domains. In most instances, data fields existed only in the body of these reports. Article texts, however, provided sufficient descriptions of these data fields to allow their translation into data entry fields in I‐Tracker with accompanying help windows and explanations to guide I‐Tracker users. Sixty ICPS data fields were programmed into I‐Tracker, with another 120 fields that allowed entry of descriptions and explanations of the ICPS data field entries. For instance, an entry of Yes into an ICPS data field that queried Was there a systems problem of an external organization other than a Providence entity opens a Describe field that allows a brief description of the problem, and an additional Details field that allows a longer explanation of the problem if necessary. The brief Describe field contents populate an automatically generated fishbone diagram.

The authors and quality staff translated the most recent 15 SE reviews into ICPS terms and classifications, and entered the results into I‐Tracker as it was being developed, to assist system design and programming of the system. The authors noted during data entry which of the 10 ICPS major domains had not been analyzed by the previous 15 reviews. Because existing reports were unstructured with considerable variation in style and usage of terms, the authors and quality staff made group decisions regarding how to cross‐walk existing information into the standardized ICPS data fields.

RESULTS

In developing I‐Tracker, the authors and quality staff observed that the ICPS framework and recommended data fields were logical and straightforward to learn. Although it was difficult to find the definitions of specific ICPS data fields within the 10 major domains in the text of retrieved articles, these fields could be readily cross‐walked into I‐Tracker data entry fields. Translating existing SE reports into I‐Tracker classifications, however, presented considerable challenges because of the unstructured, discursive, and variable nature of our SE review and reports. The authors and staff spent 1 to 2 hours conferring over each report to make judgments as to which elements of the review would be entered into which I‐Tracker data fields. Once the authors and staff translated existing reports into ICPS terms, actual data entry into I‐Tracker took typically less than 30 minutes for each review. We found that none of our 15 SE reviews included information on the following ICPS major domains: detection, mitigating factors, and ameliorating actions. We also observed that many ICPS data fields were not assessed, such as patient contributions to errors and external organization's contributions to a safety incident.

The latest version of I‐Tracker receives and displays information at the individual patient level. Records are shown onscreen with different screen layouts depending on the viewer's login security clearance. Hospital safety staff have full access to view and enter data on the initial layout, which displays patient demographic information and folder tabs that navigate when clicked to other database fields (Figure 2). Viewers with lower security clearance either view the same opening screen, but have limited access to other screens, or view a different opening screen designed to meet their specific needs. All screens provide definitions of terms and information to assist data entry, buttons that navigate to help pages, pop‐up windows that provide tips, and buttons that trigger brief audio explanations. Most fields use drop‐down lists to standardize data entry around the ICPS definitions, with default values entered into many fields to streamline data entry. A list view allows review of all patients and quick access to an individual patient's record. All fields and combinations of fields with Boolean rules are searchable within the database.

Figure 2

I‐Tracker has features that support SE review groups in beginning an SE review by providing them a paper form or electronic interface by way of a portable computer or tablet device, that guides their discussions and analyses toward providing conclusions that can be entered into the database fields, thereby aligning their deliberations with the ICPS conceptual framework. The same resource is available within the database online for those groups who would prefer to use computer prompts and enter data directly into the database as they proceed through their analyses. Some layouts contain windows that port live views from external Web sites (eg, JC RCA resources) that provide participants of RCA groups with tools to assist their work. FMP11 allows users to access the database by portable computers or handheld tablet devices using the hospitals' WiFi network.

A report screen allows automatic generation of different printouts of individual or aggregate summary reports. A Comprehensive Report includes all of the data fields included in the ICPS conceptual framework. Other reports present subsets of data depending on the user's needs and access privileges. The FMPS11 database allows printing the reports to paper or Portable Document Format (pdf), exporting data into an Excel spreadsheet, or e‐mailing reports to recipients from within I‐Tracker.

Additionally, I‐Tracker functionality facilitates follow‐up and monitoring of action items developed during the RCA process in a manner that conforms to the ICPS framework. We are now developing educational resources for RCA team members to investigate the implementation of I‐Tracker into future RCAs.

DISCUSSION

I‐Tracker provides an intranet‐based tool that met the objectives of the present project. The process of entering 15 existing SE reviews and action plans from our healthcare system into I‐Tracker allowed an incremental development of the database and identified gaps in our existing RCA process. For instance, none of the previous RCAs critically appraised detection, mitigating factors, or ameliorating actions; defined the specific nature or quantified severity of patient injuries using standardized terms; distinguished between human errors and negligence; or comprehensively reported the full spectrum of underlying causes of Tracker's use of standardized terms based on the ICPS conceptual framework provided a potential resource for focusing SE reviews and producing more comprehensive RCAs and action plans in the future. I‐Tracker has additional potential to facilitate dissemination of RCAs to other facilities, both as individual incident reports and aggregated summaries as recommended by experts in patient safety.13

The deficiencies in our existing RCA analyses, identified during data entry into I‐Tracker, represent common shortcomings experienced by other healthcare organizations and summarized in a report by the Agency for Healthcare Research and Quality.4 Considerable hindsight bias and prevailing concerns of the day taint the RCA process, which is time‐consuming and labor intensive, and thereby hinders comprehensive reviews. Also, our SE reviews, like others reviewed in the literature,14 focused on biologic injury to patients and omitted assessment of psychologic, organizational, social, and economic injury domains. Although SE review teams benefit from involvement of quality improvement staff who are trained in techniques and goals of RCA,15 many hospitals like ours have limited resources for fully staffing all SE reviews with trained facilitators. These SE reviews generate both quantitative and qualitative data, the latter of which hinders standardized data entry in the absence of a conceptual framework. A structured database with formative tools to guide RCAs in conformance with the ICPS framework in organizations without sufficient numbers of trained facilitators offers opportunities to produce more comprehensive, standardized, and actionable reports. To date, our quality staff and leadership have responded positively to presentations of the functional features of I‐Tracker (Table 1).

Limitations of our report include its focus solely on the development and programming phase of I‐Tracker and the absence of information on its actual implementation. We believe, however, the development phase is important to report because it demonstrates that the ICPS framework and specific ICPS data fields are amenable to incorporation into a decision support and reporting tool, which to our knowledge has not been previously reported. We begin implementation of I‐Tracker within our organization this year and will have observations on its feasibility, acceptability, and staff training needs. As an additional limitation, we emphasize that we do not propose I‐Tracker as a solution for other organizations, because we have no plans for its commercial or public domain development. This report is intended to demonstrate, however, that commercially available software, such as FileMaker, can readily support the ICPS Framework and thereby has potential to assist RCAs and SE reporting. Other organizations may develop similar systems on other database platforms that incorporate the ICPS system into their reviews.

To implement I‐Tracker, we are now working with nursing and pharmacy leadership focus groups to develop formative tools, data collection forms, and other resources to assist their RCA efforts and data entry into the database. We also plan to apply the database tool to our residency training program to promote resident involvement in SE reviews by providing standardized, reproducible, and structured processes.16 Our 5‐state healthcare system has funded an evaluation of the implementation phase of I‐Tracker to other Providence facilities. Because the ICPS framework applies to all safety incidents beyond SEs (Table 2), a successful implementation of I‐Tracker for SEs will allow its eventual application to other types of critical incidents.

The strength of this project derives from its innovative development of an intranet‐based tool that allows groups to conform their RCAs to the ICPS framework. Because the absence of a standardized classification for patient safety concepts has hindered advances in patient safety,11 we believe I‐Tracker, or decision support tools like it that use the ICPS framework, can standardize RCAs and promote dissemination and adoption of action plans.

Recognition that healthcare carries considerable risks of patient injury has focused efforts on identifying problems before they occur, and understanding the root causes of those problems that do occur to prevent them from happening again.1 To further these efforts, a Joint Commission (JC) standard requires hospitals to review sentinel events (SE).2 Reviews must develop a timely, thorough, and credible root cause analysis (RCA), implement action plans to reduce risk, and monitor the effectiveness of implemented improvements.3

Ideally, hospitals would summarize their experiences with SE reviews, identify high‐risk activities and patients, institute system changes to prevent SE recurrences, and share their findings with other healthcare organizations to help them avoid similar patient injuries.1 In support of this last goal, the JC maintains a voluntary database system that allows hospitals to report their SE analyses for other facilities to review and institute preventative actions.

Unfortunately, the reality of SE reviews does not match their ideals for improving patient safety.4 Healthcare organizations often describe their review process as less than credible and note a need for ongoing oversight to maintain the reviews' effectiveness.5 The JC voluntary reporting system captures less than 1% of the SEs that occur nationally,2 because hospitals perceive barriers to external reporting.1 If healthcare organizations decide against reporting externally, they can create their own internal systems to aggregate and summarize SEs, but few such systems exist. A major impediment to designing internal systems is the absence of universally endorsed nomenclature for safety‐related events.6, 7 Poorly aligned terminology and subjective conceptualizations for safety incidents impede the aggregation of SEs, comparisons between facilities, and trend analyses for tracking SE patterns.

In 2005, the World Health Organization (WHO) World Alliance for Patient Safety, in collaboration with the JC, began developing an International Classification for Patient Safety (ICPS) to provide healthcare organizations a consistent conceptual model for safety incidents and promote their classification by a standardized taxonomy.810 Although this system has promise for allowing standardization, data aggregation, analysis, and learning between institutions,11 integration of the ICPS conceptual model into an SE decision support tool with summarizing and reporting features has not been reported.

This report describes our development of an intranet‐based SE reporting system, called Incident Tracker (I‐Tracker), based on the ICPS model. For our SE review groups from the 4 Providence Health Systems (PHS) Portland Service Area (PSA) hospitals, the I‐Tracker system offers a tool to guide efforts in developing RCAs and action plans in alignment with the ICPS framework. The system includes scripts that automatically generate and distribute standardized reports of individual and aggregated SEs. The objectives of this project were to report our experience with developing a flexible and accessible intranet‐based system that assists RCA participants in conforming to the ICPS framework and oversight safety staff in summarizing and reporting root cause analyses.

METHODS

The 4 PSA hospitals have 1083 licensed beds and perform SE reviews with a centralized process that reports results to a Community Governing Board. An ad hoc team for each SE performs the RCAs. The SE groups report RCAs and action plans in an unstructured format that varies for each event. A paper file is maintained for each SE report, but a system for aggregating reports to track trends, disseminating SE trends, or monitoring the completion or effectiveness of action plans is not available.

We designed a system to achieve the following objectives:

• 1

  Apply the ICPS framework (Figure 1) and taxonomy of terms to SE analyses;

• 2

  Provide a computer‐based tool to assist review groups and quality staff to perform their SE reviews and data collection in alignment with the ICPS framework;

• 3

  Create an intranet‐based database that captures elements of the reviews, RCAs, and action plans with the use of drop‐down lists, help windows, windows with live access to Internet educational resources and tools, decision support tools, default entries, and audio prompts to streamline data entry;

• 4

  Generate a suite of standardized reports customized for different audiences that can be accessed online and printed from the database with automated scripts;

• 5

  Produce intranet‐based summaries of aggregated events to identify common causes and disseminate observed patterns and action plans to other PSA hospitals.

Figure 1

We selected FileMaker Pro 11 Advanced (FMP11) for authoring and maintaining the decision support tool and database, and FileMaker Pro Server 11 Advanced (FMPS11) (Filemaker, Inc, Santa Clara, CA) for hosting the system, because it provides intranet access and tools for updating the system by personnel with minimal programming experience. End users can view and enter data through layouts that display only the information allowed by the user's login password and access privileges, with external authentication by Active Directory and Open Directory technology. Staff who author and manage the database do so through client FMP11 software loaded on a computer that provides remote server access.

The I‐Tracker system was authored using the ICPS definitions for the 48 preferred terms for safety incidents and the ICPS conceptual framework.8 The conceptual framework consists of 10 major incident domains, that include incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors and hazards, organizational outcomes, detection, mitigating factors, ameliorating actions, and actions taken to reduce risk (Figure 1).11 The framework is applicable to all hospital safety incidents, but we limited I‐Tracker to SEs because our hospitals had completed comprehensive reviews and action plans only for these more serious events. The literature on the ICPS framework812 was carefully reviewed to identify the specific data fields that were recommended by ICPS developers to be included under each of the 10 major classification domains. In most instances, data fields existed only in the body of these reports. Article texts, however, provided sufficient descriptions of these data fields to allow their translation into data entry fields in I‐Tracker with accompanying help windows and explanations to guide I‐Tracker users. Sixty ICPS data fields were programmed into I‐Tracker, with another 120 fields that allowed entry of descriptions and explanations of the ICPS data field entries. For instance, an entry of Yes into an ICPS data field that queried Was there a systems problem of an external organization other than a Providence entity opens a Describe field that allows a brief description of the problem, and an additional Details field that allows a longer explanation of the problem if necessary. The brief Describe field contents populate an automatically generated fishbone diagram.

The authors and quality staff translated the most recent 15 SE reviews into ICPS terms and classifications, and entered the results into I‐Tracker as it was being developed, to assist system design and programming of the system. The authors noted during data entry which of the 10 ICPS major domains had not been analyzed by the previous 15 reviews. Because existing reports were unstructured with considerable variation in style and usage of terms, the authors and quality staff made group decisions regarding how to cross‐walk existing information into the standardized ICPS data fields.

RESULTS

In developing I‐Tracker, the authors and quality staff observed that the ICPS framework and recommended data fields were logical and straightforward to learn. Although it was difficult to find the definitions of specific ICPS data fields within the 10 major domains in the text of retrieved articles, these fields could be readily cross‐walked into I‐Tracker data entry fields. Translating existing SE reports into I‐Tracker classifications, however, presented considerable challenges because of the unstructured, discursive, and variable nature of our SE review and reports. The authors and staff spent 1 to 2 hours conferring over each report to make judgments as to which elements of the review would be entered into which I‐Tracker data fields. Once the authors and staff translated existing reports into ICPS terms, actual data entry into I‐Tracker took typically less than 30 minutes for each review. We found that none of our 15 SE reviews included information on the following ICPS major domains: detection, mitigating factors, and ameliorating actions. We also observed that many ICPS data fields were not assessed, such as patient contributions to errors and external organization's contributions to a safety incident.

The latest version of I‐Tracker receives and displays information at the individual patient level. Records are shown onscreen with different screen layouts depending on the viewer's login security clearance. Hospital safety staff have full access to view and enter data on the initial layout, which displays patient demographic information and folder tabs that navigate when clicked to other database fields (Figure 2). Viewers with lower security clearance either view the same opening screen, but have limited access to other screens, or view a different opening screen designed to meet their specific needs. All screens provide definitions of terms and information to assist data entry, buttons that navigate to help pages, pop‐up windows that provide tips, and buttons that trigger brief audio explanations. Most fields use drop‐down lists to standardize data entry around the ICPS definitions, with default values entered into many fields to streamline data entry. A list view allows review of all patients and quick access to an individual patient's record. All fields and combinations of fields with Boolean rules are searchable within the database.

Figure 2

I‐Tracker has features that support SE review groups in beginning an SE review by providing them a paper form or electronic interface by way of a portable computer or tablet device, that guides their discussions and analyses toward providing conclusions that can be entered into the database fields, thereby aligning their deliberations with the ICPS conceptual framework. The same resource is available within the database online for those groups who would prefer to use computer prompts and enter data directly into the database as they proceed through their analyses. Some layouts contain windows that port live views from external Web sites (eg, JC RCA resources) that provide participants of RCA groups with tools to assist their work. FMP11 allows users to access the database by portable computers or handheld tablet devices using the hospitals' WiFi network.

A report screen allows automatic generation of different printouts of individual or aggregate summary reports. A Comprehensive Report includes all of the data fields included in the ICPS conceptual framework. Other reports present subsets of data depending on the user's needs and access privileges. The FMPS11 database allows printing the reports to paper or Portable Document Format (pdf), exporting data into an Excel spreadsheet, or e‐mailing reports to recipients from within I‐Tracker.

Additionally, I‐Tracker functionality facilitates follow‐up and monitoring of action items developed during the RCA process in a manner that conforms to the ICPS framework. We are now developing educational resources for RCA team members to investigate the implementation of I‐Tracker into future RCAs.

DISCUSSION

I‐Tracker provides an intranet‐based tool that met the objectives of the present project. The process of entering 15 existing SE reviews and action plans from our healthcare system into I‐Tracker allowed an incremental development of the database and identified gaps in our existing RCA process. For instance, none of the previous RCAs critically appraised detection, mitigating factors, or ameliorating actions; defined the specific nature or quantified severity of patient injuries using standardized terms; distinguished between human errors and negligence; or comprehensively reported the full spectrum of underlying causes of Tracker's use of standardized terms based on the ICPS conceptual framework provided a potential resource for focusing SE reviews and producing more comprehensive RCAs and action plans in the future. I‐Tracker has additional potential to facilitate dissemination of RCAs to other facilities, both as individual incident reports and aggregated summaries as recommended by experts in patient safety.13

The deficiencies in our existing RCA analyses, identified during data entry into I‐Tracker, represent common shortcomings experienced by other healthcare organizations and summarized in a report by the Agency for Healthcare Research and Quality.4 Considerable hindsight bias and prevailing concerns of the day taint the RCA process, which is time‐consuming and labor intensive, and thereby hinders comprehensive reviews. Also, our SE reviews, like others reviewed in the literature,14 focused on biologic injury to patients and omitted assessment of psychologic, organizational, social, and economic injury domains. Although SE review teams benefit from involvement of quality improvement staff who are trained in techniques and goals of RCA,15 many hospitals like ours have limited resources for fully staffing all SE reviews with trained facilitators. These SE reviews generate both quantitative and qualitative data, the latter of which hinders standardized data entry in the absence of a conceptual framework. A structured database with formative tools to guide RCAs in conformance with the ICPS framework in organizations without sufficient numbers of trained facilitators offers opportunities to produce more comprehensive, standardized, and actionable reports. To date, our quality staff and leadership have responded positively to presentations of the functional features of I‐Tracker (Table 1).

Limitations of our report include its focus solely on the development and programming phase of I‐Tracker and the absence of information on its actual implementation. We believe, however, the development phase is important to report because it demonstrates that the ICPS framework and specific ICPS data fields are amenable to incorporation into a decision support and reporting tool, which to our knowledge has not been previously reported. We begin implementation of I‐Tracker within our organization this year and will have observations on its feasibility, acceptability, and staff training needs. As an additional limitation, we emphasize that we do not propose I‐Tracker as a solution for other organizations, because we have no plans for its commercial or public domain development. This report is intended to demonstrate, however, that commercially available software, such as FileMaker, can readily support the ICPS Framework and thereby has potential to assist RCAs and SE reporting. Other organizations may develop similar systems on other database platforms that incorporate the ICPS system into their reviews.

To implement I‐Tracker, we are now working with nursing and pharmacy leadership focus groups to develop formative tools, data collection forms, and other resources to assist their RCA efforts and data entry into the database. We also plan to apply the database tool to our residency training program to promote resident involvement in SE reviews by providing standardized, reproducible, and structured processes.16 Our 5‐state healthcare system has funded an evaluation of the implementation phase of I‐Tracker to other Providence facilities. Because the ICPS framework applies to all safety incidents beyond SEs (Table 2), a successful implementation of I‐Tracker for SEs will allow its eventual application to other types of critical incidents.

The strength of this project derives from its innovative development of an intranet‐based tool that allows groups to conform their RCAs to the ICPS framework. Because the absence of a standardized classification for patient safety concepts has hindered advances in patient safety,11 we believe I‐Tracker, or decision support tools like it that use the ICPS framework, can standardize RCAs and promote dissemination and adoption of action plans.

Recognition that healthcare carries considerable risks of patient injury has focused efforts on identifying problems before they occur, and understanding the root causes of those problems that do occur to prevent them from happening again.1 To further these efforts, a Joint Commission (JC) standard requires hospitals to review sentinel events (SE).2 Reviews must develop a timely, thorough, and credible root cause analysis (RCA), implement action plans to reduce risk, and monitor the effectiveness of implemented improvements.3

Ideally, hospitals would summarize their experiences with SE reviews, identify high‐risk activities and patients, institute system changes to prevent SE recurrences, and share their findings with other healthcare organizations to help them avoid similar patient injuries.1 In support of this last goal, the JC maintains a voluntary database system that allows hospitals to report their SE analyses for other facilities to review and institute preventative actions.

Unfortunately, the reality of SE reviews does not match their ideals for improving patient safety.4 Healthcare organizations often describe their review process as less than credible and note a need for ongoing oversight to maintain the reviews' effectiveness.5 The JC voluntary reporting system captures less than 1% of the SEs that occur nationally,2 because hospitals perceive barriers to external reporting.1 If healthcare organizations decide against reporting externally, they can create their own internal systems to aggregate and summarize SEs, but few such systems exist. A major impediment to designing internal systems is the absence of universally endorsed nomenclature for safety‐related events.6, 7 Poorly aligned terminology and subjective conceptualizations for safety incidents impede the aggregation of SEs, comparisons between facilities, and trend analyses for tracking SE patterns.

In 2005, the World Health Organization (WHO) World Alliance for Patient Safety, in collaboration with the JC, began developing an International Classification for Patient Safety (ICPS) to provide healthcare organizations a consistent conceptual model for safety incidents and promote their classification by a standardized taxonomy.810 Although this system has promise for allowing standardization, data aggregation, analysis, and learning between institutions,11 integration of the ICPS conceptual model into an SE decision support tool with summarizing and reporting features has not been reported.

This report describes our development of an intranet‐based SE reporting system, called Incident Tracker (I‐Tracker), based on the ICPS model. For our SE review groups from the 4 Providence Health Systems (PHS) Portland Service Area (PSA) hospitals, the I‐Tracker system offers a tool to guide efforts in developing RCAs and action plans in alignment with the ICPS framework. The system includes scripts that automatically generate and distribute standardized reports of individual and aggregated SEs. The objectives of this project were to report our experience with developing a flexible and accessible intranet‐based system that assists RCA participants in conforming to the ICPS framework and oversight safety staff in summarizing and reporting root cause analyses.

METHODS

The 4 PSA hospitals have 1083 licensed beds and perform SE reviews with a centralized process that reports results to a Community Governing Board. An ad hoc team for each SE performs the RCAs. The SE groups report RCAs and action plans in an unstructured format that varies for each event. A paper file is maintained for each SE report, but a system for aggregating reports to track trends, disseminating SE trends, or monitoring the completion or effectiveness of action plans is not available.

We designed a system to achieve the following objectives:

• 1

  Apply the ICPS framework (Figure 1) and taxonomy of terms to SE analyses;

• 2

  Provide a computer‐based tool to assist review groups and quality staff to perform their SE reviews and data collection in alignment with the ICPS framework;

• 3

  Create an intranet‐based database that captures elements of the reviews, RCAs, and action plans with the use of drop‐down lists, help windows, windows with live access to Internet educational resources and tools, decision support tools, default entries, and audio prompts to streamline data entry;

• 4

  Generate a suite of standardized reports customized for different audiences that can be accessed online and printed from the database with automated scripts;

• 5

  Produce intranet‐based summaries of aggregated events to identify common causes and disseminate observed patterns and action plans to other PSA hospitals.

Figure 1

We selected FileMaker Pro 11 Advanced (FMP11) for authoring and maintaining the decision support tool and database, and FileMaker Pro Server 11 Advanced (FMPS11) (Filemaker, Inc, Santa Clara, CA) for hosting the system, because it provides intranet access and tools for updating the system by personnel with minimal programming experience. End users can view and enter data through layouts that display only the information allowed by the user's login password and access privileges, with external authentication by Active Directory and Open Directory technology. Staff who author and manage the database do so through client FMP11 software loaded on a computer that provides remote server access.

The I‐Tracker system was authored using the ICPS definitions for the 48 preferred terms for safety incidents and the ICPS conceptual framework.8 The conceptual framework consists of 10 major incident domains, that include incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors and hazards, organizational outcomes, detection, mitigating factors, ameliorating actions, and actions taken to reduce risk (Figure 1).11 The framework is applicable to all hospital safety incidents, but we limited I‐Tracker to SEs because our hospitals had completed comprehensive reviews and action plans only for these more serious events. The literature on the ICPS framework812 was carefully reviewed to identify the specific data fields that were recommended by ICPS developers to be included under each of the 10 major classification domains. In most instances, data fields existed only in the body of these reports. Article texts, however, provided sufficient descriptions of these data fields to allow their translation into data entry fields in I‐Tracker with accompanying help windows and explanations to guide I‐Tracker users. Sixty ICPS data fields were programmed into I‐Tracker, with another 120 fields that allowed entry of descriptions and explanations of the ICPS data field entries. For instance, an entry of Yes into an ICPS data field that queried Was there a systems problem of an external organization other than a Providence entity opens a Describe field that allows a brief description of the problem, and an additional Details field that allows a longer explanation of the problem if necessary. The brief Describe field contents populate an automatically generated fishbone diagram.

The authors and quality staff translated the most recent 15 SE reviews into ICPS terms and classifications, and entered the results into I‐Tracker as it was being developed, to assist system design and programming of the system. The authors noted during data entry which of the 10 ICPS major domains had not been analyzed by the previous 15 reviews. Because existing reports were unstructured with considerable variation in style and usage of terms, the authors and quality staff made group decisions regarding how to cross‐walk existing information into the standardized ICPS data fields.

RESULTS

In developing I‐Tracker, the authors and quality staff observed that the ICPS framework and recommended data fields were logical and straightforward to learn. Although it was difficult to find the definitions of specific ICPS data fields within the 10 major domains in the text of retrieved articles, these fields could be readily cross‐walked into I‐Tracker data entry fields. Translating existing SE reports into I‐Tracker classifications, however, presented considerable challenges because of the unstructured, discursive, and variable nature of our SE review and reports. The authors and staff spent 1 to 2 hours conferring over each report to make judgments as to which elements of the review would be entered into which I‐Tracker data fields. Once the authors and staff translated existing reports into ICPS terms, actual data entry into I‐Tracker took typically less than 30 minutes for each review. We found that none of our 15 SE reviews included information on the following ICPS major domains: detection, mitigating factors, and ameliorating actions. We also observed that many ICPS data fields were not assessed, such as patient contributions to errors and external organization's contributions to a safety incident.

The latest version of I‐Tracker receives and displays information at the individual patient level. Records are shown onscreen with different screen layouts depending on the viewer's login security clearance. Hospital safety staff have full access to view and enter data on the initial layout, which displays patient demographic information and folder tabs that navigate when clicked to other database fields (Figure 2). Viewers with lower security clearance either view the same opening screen, but have limited access to other screens, or view a different opening screen designed to meet their specific needs. All screens provide definitions of terms and information to assist data entry, buttons that navigate to help pages, pop‐up windows that provide tips, and buttons that trigger brief audio explanations. Most fields use drop‐down lists to standardize data entry around the ICPS definitions, with default values entered into many fields to streamline data entry. A list view allows review of all patients and quick access to an individual patient's record. All fields and combinations of fields with Boolean rules are searchable within the database.

Figure 2

I‐Tracker has features that support SE review groups in beginning an SE review by providing them a paper form or electronic interface by way of a portable computer or tablet device, that guides their discussions and analyses toward providing conclusions that can be entered into the database fields, thereby aligning their deliberations with the ICPS conceptual framework. The same resource is available within the database online for those groups who would prefer to use computer prompts and enter data directly into the database as they proceed through their analyses. Some layouts contain windows that port live views from external Web sites (eg, JC RCA resources) that provide participants of RCA groups with tools to assist their work. FMP11 allows users to access the database by portable computers or handheld tablet devices using the hospitals' WiFi network.

A report screen allows automatic generation of different printouts of individual or aggregate summary reports. A Comprehensive Report includes all of the data fields included in the ICPS conceptual framework. Other reports present subsets of data depending on the user's needs and access privileges. The FMPS11 database allows printing the reports to paper or Portable Document Format (pdf), exporting data into an Excel spreadsheet, or e‐mailing reports to recipients from within I‐Tracker.

Additionally, I‐Tracker functionality facilitates follow‐up and monitoring of action items developed during the RCA process in a manner that conforms to the ICPS framework. We are now developing educational resources for RCA team members to investigate the implementation of I‐Tracker into future RCAs.

DISCUSSION

I‐Tracker provides an intranet‐based tool that met the objectives of the present project. The process of entering 15 existing SE reviews and action plans from our healthcare system into I‐Tracker allowed an incremental development of the database and identified gaps in our existing RCA process. For instance, none of the previous RCAs critically appraised detection, mitigating factors, or ameliorating actions; defined the specific nature or quantified severity of patient injuries using standardized terms; distinguished between human errors and negligence; or comprehensively reported the full spectrum of underlying causes of Tracker's use of standardized terms based on the ICPS conceptual framework provided a potential resource for focusing SE reviews and producing more comprehensive RCAs and action plans in the future. I‐Tracker has additional potential to facilitate dissemination of RCAs to other facilities, both as individual incident reports and aggregated summaries as recommended by experts in patient safety.13

The deficiencies in our existing RCA analyses, identified during data entry into I‐Tracker, represent common shortcomings experienced by other healthcare organizations and summarized in a report by the Agency for Healthcare Research and Quality.4 Considerable hindsight bias and prevailing concerns of the day taint the RCA process, which is time‐consuming and labor intensive, and thereby hinders comprehensive reviews. Also, our SE reviews, like others reviewed in the literature,14 focused on biologic injury to patients and omitted assessment of psychologic, organizational, social, and economic injury domains. Although SE review teams benefit from involvement of quality improvement staff who are trained in techniques and goals of RCA,15 many hospitals like ours have limited resources for fully staffing all SE reviews with trained facilitators. These SE reviews generate both quantitative and qualitative data, the latter of which hinders standardized data entry in the absence of a conceptual framework. A structured database with formative tools to guide RCAs in conformance with the ICPS framework in organizations without sufficient numbers of trained facilitators offers opportunities to produce more comprehensive, standardized, and actionable reports. To date, our quality staff and leadership have responded positively to presentations of the functional features of I‐Tracker (Table 1).

Limitations of our report include its focus solely on the development and programming phase of I‐Tracker and the absence of information on its actual implementation. We believe, however, the development phase is important to report because it demonstrates that the ICPS framework and specific ICPS data fields are amenable to incorporation into a decision support and reporting tool, which to our knowledge has not been previously reported. We begin implementation of I‐Tracker within our organization this year and will have observations on its feasibility, acceptability, and staff training needs. As an additional limitation, we emphasize that we do not propose I‐Tracker as a solution for other organizations, because we have no plans for its commercial or public domain development. This report is intended to demonstrate, however, that commercially available software, such as FileMaker, can readily support the ICPS Framework and thereby has potential to assist RCAs and SE reporting. Other organizations may develop similar systems on other database platforms that incorporate the ICPS system into their reviews.

To implement I‐Tracker, we are now working with nursing and pharmacy leadership focus groups to develop formative tools, data collection forms, and other resources to assist their RCA efforts and data entry into the database. We also plan to apply the database tool to our residency training program to promote resident involvement in SE reviews by providing standardized, reproducible, and structured processes.16 Our 5‐state healthcare system has funded an evaluation of the implementation phase of I‐Tracker to other Providence facilities. Because the ICPS framework applies to all safety incidents beyond SEs (Table 2), a successful implementation of I‐Tracker for SEs will allow its eventual application to other types of critical incidents.

The strength of this project derives from its innovative development of an intranet‐based tool that allows groups to conform their RCAs to the ICPS framework. Because the absence of a standardized classification for patient safety concepts has hindered advances in patient safety,11 we believe I‐Tracker, or decision support tools like it that use the ICPS framework, can standardize RCAs and promote dissemination and adoption of action plans.

In‐hospital cardiopulmonary arrests are often preceded by signs of clinical instability, such as changes in vital signs or mental status.1 Nearly 85% of patients who suffer from cardiopulmonary arrests have documented observations of deterioration in the 8 hours before arrest.2 A Medical Emergency Team (MET), sometimes known as Rapid Response Team (RRT), can rapidly assess and manage unstable patients, with the goal that early intervention will prevent adverse outcomes. In 2004, the Institute for Healthcare Improvement (IHI), as part of its 100,000 Lives Campaign, called for hospitals to implement rapid response systems as 1 of 6 strategies to reduce deaths in hospital.3 Since this recommendation, hundreds of hospitals in the United States have invested substantial financial and personnel resources to implement some form of a rapid response system, which is comprised of a varying array of healthcare providers who bring critical care expertise to the patient's bedside.4, 5

Despite the intuitive appeal of the approach, and early observational data which suggested that METs could reduce both codes and unexpected in‐hospital mortality,2, 6 the largest randomized controlled trial found that METs failed to reduce unplanned intensive care unit (ICU) admissions, cardiac arrests, or unexpected deaths.7 More recently, in a prospective observational cohort study at 1 US hospital, Chan et al. found that a nurse‐led RRT did not impact hospital‐wide code rates or mortality.4

The study of rapid response systems is further complicated by a lack of standard definition, and the many types of hospitals in which they may be implemented. In 2006, a consensus conference suggested that MET be used to refer to teams led by physicians (usually intensivists), and RRT be used for teams led by nurses.8 Many studies have been conducted at non‐US institutions, and follow‐up periods have generally been 1 year or less. We report on almost 4 years of experience with a hospitalist‐led MET implemented in a major US academic medical center, and examine the subsequent changes in code calls, cardiac arrests, deaths following cardiopulmonary resuscitation, and overall hospital mortality. Because the MET did not operate in the critical care units, and because cardiac arrest may occur without prior signs of deterioration, we hypothesized that implementation of the MET would correspond to a small drop in total code calls, no change in codes called inside of critical care units, no change in cardiac arrest outside of critical care, and a marked drop in other medical crises (mostly respiratory distress) outside critical care. We also hypothesized that there would be no change in the rate of fatal codes, because most deaths occur in patients who were found to be pulseless on arrival of the code team.

METHODS

RESULTS

Implementation of the MET

The MET was introduced in the first and second quarters of 2006, with 2717 calls logged through the end of 2009 (out of 154,382 admissions). The rate of MET calls increased during the first 6 months of implementation from 5.95 per 1000 admissions in the first quarter of the intervention, to 15.8 calls per 1000 admissions in the second quarter. Call rates peaked in the first half of 2009, at 20.9 calls per 1000 admissions, leveling off to 17.9 calls per 1000 admissions in the last half of 2009 (Figure 1). Of calls with time recorded, 40% occurred on the day shift, 35% on the evening shift, and 25% on the night shift. The most common reason to call the MET was respiratory distress (33%), followed by cardiovascular instability (25%), and neurological abnormality (20%). In 15% of cases, concern about a patient's condition prompted the nurse to call. Calls came primarily from medical floors (75%) and surgical units (20%). The median response time was 4 minutes (interquartile range [IQR], 2.8 to 5.2 minutes) with no meaningful trend during the study period. The median call duration was 50 minutes (IQR, 38 to 72 minutes). Again, there was no trend over time. The most common interventions were arterial blood gas, fluid resuscitation, and electrocardiogram (see Supporting Web Appendix Table 1 in the online version of this article). A physician was present at 52% of the calls in the first year, which rose to 93% of calls in the final year. Approximately 25% of calls resulted in the patient being transferred to a critical care unit. Staff evaluations were overwhelmingly positive. Nurses rated the teams on the following points: whether the critical care nurse and respiratory therapist were efficient and respectful (mean rating 98%, SD 5.6%); promptness (98%, SD 5.6%); whether the patient's needs were addressed appropriately (mean 98%, SD 4.2%); whether the nurse felt supported by the MET (99.5%, SD 1.7%); and whether they would call the MET again (99.7%, SD 1.4%).

Figure 1

Effect of MET on Code Calls and Mortality

Between January 2004 and December of 2009, the hospital case mix index remained constant, and there were a total of 1202 codes called. The majority (62%) took place outside of critical care units. Linear contrasts of pre‐piecewise and post‐piecewise intercepts revealed that overall code calls declined significantly between pre‐implementation and post‐implementation of the MET from 7.30 (95% CI 5.81, 9.16) codes called per 1000 admissions to 4.21 (95% CI 3.42, 5.18) calls per 1000 admissions (Figure 1; also see Supporting Web Appendix Table 2 in the online version of this article). Outside of critical care, code calls declined from 4.70 (95% CI 3.92, 5.63) before the MET was implemented to 3.11 (95% CI 2.44, 3.97) afterwards (Figure 2); this was due primarily to a decrease in medical crises, which averaged 3.29 events per 1000 admissions (95% CI 2.70, 4.02) before implementation and decreased to 1.72 (95% CI 1.28, 2.31) afterwards, whereas cardiac arrests did not change significantly (Figure 3). Following implementation, code calls within critical care also declined significantly, from 2.59 events per 1000 admissions (95% CI 1.82, 3.69) before to 1.24 events per 1000 admissions (95% CI 0.94, 1.63) afterwards. The change in codes called within critical care was smaller, however, and included reductions in both cardiac arrests ( 0.84 events, P = 0.01) and medical crises ( 0.55, P = 0.08). There was no significant change in the rate of fatal codes per 1000 admissions ( +0.06, P = 0.65) (Figure 4). Overall hospital mortality remained steady at 22.0 deaths per 1000 admissions throughout the study period.

Figure 2

Figure 3

Figure 4

DISCUSSION

In this report, we detail the implementation of a novel hospitalist‐led medical emergency team at a large academic medical center over a period of 4 years. The team, which consisted of the patient's physician, a critical care nurse, a respiratory therapist, and an intravenous therapist, achieved full implementation within 6 months, was well received by the nursing staff, and was associated with a 42% decrease in code calls hospital‐wide. Most of the overall reduction was due to a reduction in codes called for medical crises outside of critical care, accompanied by a lesser reduction in codes called for cardiac arrests and medical crises within critical care units. There was no significant effect on the rate of cardiac arrest outside critical care. More importantly, there was no change in the rate of fatal codes or overall hospital mortality.

The idea of early intervention to prevent deterioration among hospitalized patients appeals to the concept that an ounce of prevention is worth a pound of cure. Like many other preventive interventions, rapid response systems have not always delivered on this promise. Since several early reports from Australia2 suggested that medical emergency teams could reduce not only cardiopulmonary arrests, but overall hospital mortality, there has been a rapid proliferation in their implementation, spurred on by the IHI's 100,000 Lives Campaign, which incorporated rapid response systems as one of 6 hospital‐wide interventions aimed at reducing harm and mortality.13 Subsequent randomized trials have both reproduced and refuted the early observational results. A ward‐randomized trial within 1 British hospital found a 50% reduction in hospital mortality for wards assigned to have an RRT,14 while a cluster randomized trial conducted at 23 Australian hospitals found no difference in rates of cardiac arrest or mortality between hospitals implementing METs and those continuing with usual care.7 Interestingly, in the Australian trial, the rates of cardiac arrest and mortality declined for both groups compared to historical controls, an important limitation to observational trials. Reports from single‐institution observational trials are also divided between those that found a reduction in mortality following implementation and those that did not. A recent meta‐analysis reported that there was too much heterogeneity among these trials to reach a conclusion about the benefits of rapid response systems.15

Our study adds to this literature in several ways. First, our MET design, which included the patient's physician (as opposed to an intensive care physician), was different from those previously studied. Including the patient's physician increases the team's knowledge of the patient and disease, and may improve physician acceptance of METs. In addition, our study provides 4 full years of follow‐up. Second, our rate of MET activation (18 calls/1000 admissions) was 2 to 3 times higher than that seen in most other studies,16 thus, the lack of mortality benefit was not likely the result of underuse. Third, our hospital employs a large number of hospitalists whose continuous presence might be expected to attenuate the benefits of an MET. Indeed, our initial rate of codes (7.5/1000 admissions) was similar to the post‐intervention rate in other studies.4 Nevertheless, the decrease in the overall rate of code calls following implementation of our MET was similar to that observed by others.17 Finally, our stratification of code calls inside critical care (where the MET was not deployed) and outside critical care, as well as the division of codes into cardiac arrest (where intervention is often unsuccessful) and other medical crises (primarily respiratory distress), gives further insight into how METs might work. As expected, we found that outside critical care only, codes called for medical crises declined, implying that the main effect of the MET was to provide early interventions for patients who were not likely to die anyway (eg, respiratory care for patients with respiratory distress or intravenous fluids for hypotensive patients). Instead of intervening to prevent death, MET may avoid emergent intubation by providing respiratory therapy and/or urgent intubation. In addition, it represents a less‐intense option for responding to nonlife‐threatening emergencies, such as seizures or syncope. As codes were no longer called for these types of crises, the rate of code calls necessarily fell. The reason that code calls declined inside critical care is less clear. It could be that patients transferred to critical care by the MET were less likely to code than those transferred before implementation, or the decline might be due to other factors that were not evaluated. Regardless, it is clear that the MET did not simply relocate codes to critical care units.

Our study has a number of limitations. First, it is an observational study and cannot account for other confounders relating to temporal trends in the hospital. However, our long time window allowed us to examine trends over several years. For 2 years prior to implementation of the MET, there was no decline at all in the rate of code calls, followed by an immediate and sustained drop after implementation. Other interventions, including ventilator‐associated pneumonia bundles, sepsis bundles, and advanced cardiac life support simulation training were also implemented at different times during the study period. However, the stark demarcation in code call rates coinciding with MET implementation makes it less likely that these other interventions were responsible for the observed decline. Second, our study was limited to a single institution and a single type of MET. Our findings may not apply to other types of institutions with different staffing arrangements or a different hospital culture, nor would they necessarily apply to different types of MET. Third, our nurse surveys were not collected anonymously, and this may have affected the nurses' responses. Finally, we did not collect physiological parameters on our patients, so we cannot state with certainty what the MET intervention accomplished.

Since initial studies suggested that METs could reduce hospital mortality rates, the Joint Commission has effectively mandated implementation of rapid response systems in all hospitals. Newer evidence, however, has been less convincing of mortality or other benefit. Our study adds to the literature in that we also did not find a mortality benefit. However, there were 2 clear benefits that we did identify. Our MET did appear to substantially reduce total numbers of code calls, particularly codes called for medical crises. Also, our nurses had a very positive response to the MET, which empowered them to get help for a patient when the patient's physician was unavailable or did not take their concerns seriously. Clearly, additional study is needed to better understand the effects of METs on mortality, codes, and other indicators of patient outcomes. However, in the current regulatory environment, such studies will be difficult to perform. Instead, additional studies can clarify which models deliver best outcomes and optimal use of our limited resources.

In‐hospital cardiopulmonary arrests are often preceded by signs of clinical instability, such as changes in vital signs or mental status.1 Nearly 85% of patients who suffer from cardiopulmonary arrests have documented observations of deterioration in the 8 hours before arrest.2 A Medical Emergency Team (MET), sometimes known as Rapid Response Team (RRT), can rapidly assess and manage unstable patients, with the goal that early intervention will prevent adverse outcomes. In 2004, the Institute for Healthcare Improvement (IHI), as part of its 100,000 Lives Campaign, called for hospitals to implement rapid response systems as 1 of 6 strategies to reduce deaths in hospital.3 Since this recommendation, hundreds of hospitals in the United States have invested substantial financial and personnel resources to implement some form of a rapid response system, which is comprised of a varying array of healthcare providers who bring critical care expertise to the patient's bedside.4, 5

Despite the intuitive appeal of the approach, and early observational data which suggested that METs could reduce both codes and unexpected in‐hospital mortality,2, 6 the largest randomized controlled trial found that METs failed to reduce unplanned intensive care unit (ICU) admissions, cardiac arrests, or unexpected deaths.7 More recently, in a prospective observational cohort study at 1 US hospital, Chan et al. found that a nurse‐led RRT did not impact hospital‐wide code rates or mortality.4

The study of rapid response systems is further complicated by a lack of standard definition, and the many types of hospitals in which they may be implemented. In 2006, a consensus conference suggested that MET be used to refer to teams led by physicians (usually intensivists), and RRT be used for teams led by nurses.8 Many studies have been conducted at non‐US institutions, and follow‐up periods have generally been 1 year or less. We report on almost 4 years of experience with a hospitalist‐led MET implemented in a major US academic medical center, and examine the subsequent changes in code calls, cardiac arrests, deaths following cardiopulmonary resuscitation, and overall hospital mortality. Because the MET did not operate in the critical care units, and because cardiac arrest may occur without prior signs of deterioration, we hypothesized that implementation of the MET would correspond to a small drop in total code calls, no change in codes called inside of critical care units, no change in cardiac arrest outside of critical care, and a marked drop in other medical crises (mostly respiratory distress) outside critical care. We also hypothesized that there would be no change in the rate of fatal codes, because most deaths occur in patients who were found to be pulseless on arrival of the code team.

METHODS

RESULTS

Implementation of the MET

The MET was introduced in the first and second quarters of 2006, with 2717 calls logged through the end of 2009 (out of 154,382 admissions). The rate of MET calls increased during the first 6 months of implementation from 5.95 per 1000 admissions in the first quarter of the intervention, to 15.8 calls per 1000 admissions in the second quarter. Call rates peaked in the first half of 2009, at 20.9 calls per 1000 admissions, leveling off to 17.9 calls per 1000 admissions in the last half of 2009 (Figure 1). Of calls with time recorded, 40% occurred on the day shift, 35% on the evening shift, and 25% on the night shift. The most common reason to call the MET was respiratory distress (33%), followed by cardiovascular instability (25%), and neurological abnormality (20%). In 15% of cases, concern about a patient's condition prompted the nurse to call. Calls came primarily from medical floors (75%) and surgical units (20%). The median response time was 4 minutes (interquartile range [IQR], 2.8 to 5.2 minutes) with no meaningful trend during the study period. The median call duration was 50 minutes (IQR, 38 to 72 minutes). Again, there was no trend over time. The most common interventions were arterial blood gas, fluid resuscitation, and electrocardiogram (see Supporting Web Appendix Table 1 in the online version of this article). A physician was present at 52% of the calls in the first year, which rose to 93% of calls in the final year. Approximately 25% of calls resulted in the patient being transferred to a critical care unit. Staff evaluations were overwhelmingly positive. Nurses rated the teams on the following points: whether the critical care nurse and respiratory therapist were efficient and respectful (mean rating 98%, SD 5.6%); promptness (98%, SD 5.6%); whether the patient's needs were addressed appropriately (mean 98%, SD 4.2%); whether the nurse felt supported by the MET (99.5%, SD 1.7%); and whether they would call the MET again (99.7%, SD 1.4%).

Figure 1

Effect of MET on Code Calls and Mortality

Between January 2004 and December of 2009, the hospital case mix index remained constant, and there were a total of 1202 codes called. The majority (62%) took place outside of critical care units. Linear contrasts of pre‐piecewise and post‐piecewise intercepts revealed that overall code calls declined significantly between pre‐implementation and post‐implementation of the MET from 7.30 (95% CI 5.81, 9.16) codes called per 1000 admissions to 4.21 (95% CI 3.42, 5.18) calls per 1000 admissions (Figure 1; also see Supporting Web Appendix Table 2 in the online version of this article). Outside of critical care, code calls declined from 4.70 (95% CI 3.92, 5.63) before the MET was implemented to 3.11 (95% CI 2.44, 3.97) afterwards (Figure 2); this was due primarily to a decrease in medical crises, which averaged 3.29 events per 1000 admissions (95% CI 2.70, 4.02) before implementation and decreased to 1.72 (95% CI 1.28, 2.31) afterwards, whereas cardiac arrests did not change significantly (Figure 3). Following implementation, code calls within critical care also declined significantly, from 2.59 events per 1000 admissions (95% CI 1.82, 3.69) before to 1.24 events per 1000 admissions (95% CI 0.94, 1.63) afterwards. The change in codes called within critical care was smaller, however, and included reductions in both cardiac arrests ( 0.84 events, P = 0.01) and medical crises ( 0.55, P = 0.08). There was no significant change in the rate of fatal codes per 1000 admissions ( +0.06, P = 0.65) (Figure 4). Overall hospital mortality remained steady at 22.0 deaths per 1000 admissions throughout the study period.

Figure 2

Figure 3

Figure 4

DISCUSSION

In this report, we detail the implementation of a novel hospitalist‐led medical emergency team at a large academic medical center over a period of 4 years. The team, which consisted of the patient's physician, a critical care nurse, a respiratory therapist, and an intravenous therapist, achieved full implementation within 6 months, was well received by the nursing staff, and was associated with a 42% decrease in code calls hospital‐wide. Most of the overall reduction was due to a reduction in codes called for medical crises outside of critical care, accompanied by a lesser reduction in codes called for cardiac arrests and medical crises within critical care units. There was no significant effect on the rate of cardiac arrest outside critical care. More importantly, there was no change in the rate of fatal codes or overall hospital mortality.

The idea of early intervention to prevent deterioration among hospitalized patients appeals to the concept that an ounce of prevention is worth a pound of cure. Like many other preventive interventions, rapid response systems have not always delivered on this promise. Since several early reports from Australia2 suggested that medical emergency teams could reduce not only cardiopulmonary arrests, but overall hospital mortality, there has been a rapid proliferation in their implementation, spurred on by the IHI's 100,000 Lives Campaign, which incorporated rapid response systems as one of 6 hospital‐wide interventions aimed at reducing harm and mortality.13 Subsequent randomized trials have both reproduced and refuted the early observational results. A ward‐randomized trial within 1 British hospital found a 50% reduction in hospital mortality for wards assigned to have an RRT,14 while a cluster randomized trial conducted at 23 Australian hospitals found no difference in rates of cardiac arrest or mortality between hospitals implementing METs and those continuing with usual care.7 Interestingly, in the Australian trial, the rates of cardiac arrest and mortality declined for both groups compared to historical controls, an important limitation to observational trials. Reports from single‐institution observational trials are also divided between those that found a reduction in mortality following implementation and those that did not. A recent meta‐analysis reported that there was too much heterogeneity among these trials to reach a conclusion about the benefits of rapid response systems.15

Our study adds to this literature in several ways. First, our MET design, which included the patient's physician (as opposed to an intensive care physician), was different from those previously studied. Including the patient's physician increases the team's knowledge of the patient and disease, and may improve physician acceptance of METs. In addition, our study provides 4 full years of follow‐up. Second, our rate of MET activation (18 calls/1000 admissions) was 2 to 3 times higher than that seen in most other studies,16 thus, the lack of mortality benefit was not likely the result of underuse. Third, our hospital employs a large number of hospitalists whose continuous presence might be expected to attenuate the benefits of an MET. Indeed, our initial rate of codes (7.5/1000 admissions) was similar to the post‐intervention rate in other studies.4 Nevertheless, the decrease in the overall rate of code calls following implementation of our MET was similar to that observed by others.17 Finally, our stratification of code calls inside critical care (where the MET was not deployed) and outside critical care, as well as the division of codes into cardiac arrest (where intervention is often unsuccessful) and other medical crises (primarily respiratory distress), gives further insight into how METs might work. As expected, we found that outside critical care only, codes called for medical crises declined, implying that the main effect of the MET was to provide early interventions for patients who were not likely to die anyway (eg, respiratory care for patients with respiratory distress or intravenous fluids for hypotensive patients). Instead of intervening to prevent death, MET may avoid emergent intubation by providing respiratory therapy and/or urgent intubation. In addition, it represents a less‐intense option for responding to nonlife‐threatening emergencies, such as seizures or syncope. As codes were no longer called for these types of crises, the rate of code calls necessarily fell. The reason that code calls declined inside critical care is less clear. It could be that patients transferred to critical care by the MET were less likely to code than those transferred before implementation, or the decline might be due to other factors that were not evaluated. Regardless, it is clear that the MET did not simply relocate codes to critical care units.

Our study has a number of limitations. First, it is an observational study and cannot account for other confounders relating to temporal trends in the hospital. However, our long time window allowed us to examine trends over several years. For 2 years prior to implementation of the MET, there was no decline at all in the rate of code calls, followed by an immediate and sustained drop after implementation. Other interventions, including ventilator‐associated pneumonia bundles, sepsis bundles, and advanced cardiac life support simulation training were also implemented at different times during the study period. However, the stark demarcation in code call rates coinciding with MET implementation makes it less likely that these other interventions were responsible for the observed decline. Second, our study was limited to a single institution and a single type of MET. Our findings may not apply to other types of institutions with different staffing arrangements or a different hospital culture, nor would they necessarily apply to different types of MET. Third, our nurse surveys were not collected anonymously, and this may have affected the nurses' responses. Finally, we did not collect physiological parameters on our patients, so we cannot state with certainty what the MET intervention accomplished.

Since initial studies suggested that METs could reduce hospital mortality rates, the Joint Commission has effectively mandated implementation of rapid response systems in all hospitals. Newer evidence, however, has been less convincing of mortality or other benefit. Our study adds to the literature in that we also did not find a mortality benefit. However, there were 2 clear benefits that we did identify. Our MET did appear to substantially reduce total numbers of code calls, particularly codes called for medical crises. Also, our nurses had a very positive response to the MET, which empowered them to get help for a patient when the patient's physician was unavailable or did not take their concerns seriously. Clearly, additional study is needed to better understand the effects of METs on mortality, codes, and other indicators of patient outcomes. However, in the current regulatory environment, such studies will be difficult to perform. Instead, additional studies can clarify which models deliver best outcomes and optimal use of our limited resources.

In‐hospital cardiopulmonary arrests are often preceded by signs of clinical instability, such as changes in vital signs or mental status.1 Nearly 85% of patients who suffer from cardiopulmonary arrests have documented observations of deterioration in the 8 hours before arrest.2 A Medical Emergency Team (MET), sometimes known as Rapid Response Team (RRT), can rapidly assess and manage unstable patients, with the goal that early intervention will prevent adverse outcomes. In 2004, the Institute for Healthcare Improvement (IHI), as part of its 100,000 Lives Campaign, called for hospitals to implement rapid response systems as 1 of 6 strategies to reduce deaths in hospital.3 Since this recommendation, hundreds of hospitals in the United States have invested substantial financial and personnel resources to implement some form of a rapid response system, which is comprised of a varying array of healthcare providers who bring critical care expertise to the patient's bedside.4, 5

Despite the intuitive appeal of the approach, and early observational data which suggested that METs could reduce both codes and unexpected in‐hospital mortality,2, 6 the largest randomized controlled trial found that METs failed to reduce unplanned intensive care unit (ICU) admissions, cardiac arrests, or unexpected deaths.7 More recently, in a prospective observational cohort study at 1 US hospital, Chan et al. found that a nurse‐led RRT did not impact hospital‐wide code rates or mortality.4

The study of rapid response systems is further complicated by a lack of standard definition, and the many types of hospitals in which they may be implemented. In 2006, a consensus conference suggested that MET be used to refer to teams led by physicians (usually intensivists), and RRT be used for teams led by nurses.8 Many studies have been conducted at non‐US institutions, and follow‐up periods have generally been 1 year or less. We report on almost 4 years of experience with a hospitalist‐led MET implemented in a major US academic medical center, and examine the subsequent changes in code calls, cardiac arrests, deaths following cardiopulmonary resuscitation, and overall hospital mortality. Because the MET did not operate in the critical care units, and because cardiac arrest may occur without prior signs of deterioration, we hypothesized that implementation of the MET would correspond to a small drop in total code calls, no change in codes called inside of critical care units, no change in cardiac arrest outside of critical care, and a marked drop in other medical crises (mostly respiratory distress) outside critical care. We also hypothesized that there would be no change in the rate of fatal codes, because most deaths occur in patients who were found to be pulseless on arrival of the code team.

METHODS

RESULTS

Implementation of the MET

The MET was introduced in the first and second quarters of 2006, with 2717 calls logged through the end of 2009 (out of 154,382 admissions). The rate of MET calls increased during the first 6 months of implementation from 5.95 per 1000 admissions in the first quarter of the intervention, to 15.8 calls per 1000 admissions in the second quarter. Call rates peaked in the first half of 2009, at 20.9 calls per 1000 admissions, leveling off to 17.9 calls per 1000 admissions in the last half of 2009 (Figure 1). Of calls with time recorded, 40% occurred on the day shift, 35% on the evening shift, and 25% on the night shift. The most common reason to call the MET was respiratory distress (33%), followed by cardiovascular instability (25%), and neurological abnormality (20%). In 15% of cases, concern about a patient's condition prompted the nurse to call. Calls came primarily from medical floors (75%) and surgical units (20%). The median response time was 4 minutes (interquartile range [IQR], 2.8 to 5.2 minutes) with no meaningful trend during the study period. The median call duration was 50 minutes (IQR, 38 to 72 minutes). Again, there was no trend over time. The most common interventions were arterial blood gas, fluid resuscitation, and electrocardiogram (see Supporting Web Appendix Table 1 in the online version of this article). A physician was present at 52% of the calls in the first year, which rose to 93% of calls in the final year. Approximately 25% of calls resulted in the patient being transferred to a critical care unit. Staff evaluations were overwhelmingly positive. Nurses rated the teams on the following points: whether the critical care nurse and respiratory therapist were efficient and respectful (mean rating 98%, SD 5.6%); promptness (98%, SD 5.6%); whether the patient's needs were addressed appropriately (mean 98%, SD 4.2%); whether the nurse felt supported by the MET (99.5%, SD 1.7%); and whether they would call the MET again (99.7%, SD 1.4%).

Figure 1

Effect of MET on Code Calls and Mortality

Between January 2004 and December of 2009, the hospital case mix index remained constant, and there were a total of 1202 codes called. The majority (62%) took place outside of critical care units. Linear contrasts of pre‐piecewise and post‐piecewise intercepts revealed that overall code calls declined significantly between pre‐implementation and post‐implementation of the MET from 7.30 (95% CI 5.81, 9.16) codes called per 1000 admissions to 4.21 (95% CI 3.42, 5.18) calls per 1000 admissions (Figure 1; also see Supporting Web Appendix Table 2 in the online version of this article). Outside of critical care, code calls declined from 4.70 (95% CI 3.92, 5.63) before the MET was implemented to 3.11 (95% CI 2.44, 3.97) afterwards (Figure 2); this was due primarily to a decrease in medical crises, which averaged 3.29 events per 1000 admissions (95% CI 2.70, 4.02) before implementation and decreased to 1.72 (95% CI 1.28, 2.31) afterwards, whereas cardiac arrests did not change significantly (Figure 3). Following implementation, code calls within critical care also declined significantly, from 2.59 events per 1000 admissions (95% CI 1.82, 3.69) before to 1.24 events per 1000 admissions (95% CI 0.94, 1.63) afterwards. The change in codes called within critical care was smaller, however, and included reductions in both cardiac arrests ( 0.84 events, P = 0.01) and medical crises ( 0.55, P = 0.08). There was no significant change in the rate of fatal codes per 1000 admissions ( +0.06, P = 0.65) (Figure 4). Overall hospital mortality remained steady at 22.0 deaths per 1000 admissions throughout the study period.

Figure 2

Figure 3

Figure 4

DISCUSSION

In this report, we detail the implementation of a novel hospitalist‐led medical emergency team at a large academic medical center over a period of 4 years. The team, which consisted of the patient's physician, a critical care nurse, a respiratory therapist, and an intravenous therapist, achieved full implementation within 6 months, was well received by the nursing staff, and was associated with a 42% decrease in code calls hospital‐wide. Most of the overall reduction was due to a reduction in codes called for medical crises outside of critical care, accompanied by a lesser reduction in codes called for cardiac arrests and medical crises within critical care units. There was no significant effect on the rate of cardiac arrest outside critical care. More importantly, there was no change in the rate of fatal codes or overall hospital mortality.

The idea of early intervention to prevent deterioration among hospitalized patients appeals to the concept that an ounce of prevention is worth a pound of cure. Like many other preventive interventions, rapid response systems have not always delivered on this promise. Since several early reports from Australia2 suggested that medical emergency teams could reduce not only cardiopulmonary arrests, but overall hospital mortality, there has been a rapid proliferation in their implementation, spurred on by the IHI's 100,000 Lives Campaign, which incorporated rapid response systems as one of 6 hospital‐wide interventions aimed at reducing harm and mortality.13 Subsequent randomized trials have both reproduced and refuted the early observational results. A ward‐randomized trial within 1 British hospital found a 50% reduction in hospital mortality for wards assigned to have an RRT,14 while a cluster randomized trial conducted at 23 Australian hospitals found no difference in rates of cardiac arrest or mortality between hospitals implementing METs and those continuing with usual care.7 Interestingly, in the Australian trial, the rates of cardiac arrest and mortality declined for both groups compared to historical controls, an important limitation to observational trials. Reports from single‐institution observational trials are also divided between those that found a reduction in mortality following implementation and those that did not. A recent meta‐analysis reported that there was too much heterogeneity among these trials to reach a conclusion about the benefits of rapid response systems.15

Our study adds to this literature in several ways. First, our MET design, which included the patient's physician (as opposed to an intensive care physician), was different from those previously studied. Including the patient's physician increases the team's knowledge of the patient and disease, and may improve physician acceptance of METs. In addition, our study provides 4 full years of follow‐up. Second, our rate of MET activation (18 calls/1000 admissions) was 2 to 3 times higher than that seen in most other studies,16 thus, the lack of mortality benefit was not likely the result of underuse. Third, our hospital employs a large number of hospitalists whose continuous presence might be expected to attenuate the benefits of an MET. Indeed, our initial rate of codes (7.5/1000 admissions) was similar to the post‐intervention rate in other studies.4 Nevertheless, the decrease in the overall rate of code calls following implementation of our MET was similar to that observed by others.17 Finally, our stratification of code calls inside critical care (where the MET was not deployed) and outside critical care, as well as the division of codes into cardiac arrest (where intervention is often unsuccessful) and other medical crises (primarily respiratory distress), gives further insight into how METs might work. As expected, we found that outside critical care only, codes called for medical crises declined, implying that the main effect of the MET was to provide early interventions for patients who were not likely to die anyway (eg, respiratory care for patients with respiratory distress or intravenous fluids for hypotensive patients). Instead of intervening to prevent death, MET may avoid emergent intubation by providing respiratory therapy and/or urgent intubation. In addition, it represents a less‐intense option for responding to nonlife‐threatening emergencies, such as seizures or syncope. As codes were no longer called for these types of crises, the rate of code calls necessarily fell. The reason that code calls declined inside critical care is less clear. It could be that patients transferred to critical care by the MET were less likely to code than those transferred before implementation, or the decline might be due to other factors that were not evaluated. Regardless, it is clear that the MET did not simply relocate codes to critical care units.

Our study has a number of limitations. First, it is an observational study and cannot account for other confounders relating to temporal trends in the hospital. However, our long time window allowed us to examine trends over several years. For 2 years prior to implementation of the MET, there was no decline at all in the rate of code calls, followed by an immediate and sustained drop after implementation. Other interventions, including ventilator‐associated pneumonia bundles, sepsis bundles, and advanced cardiac life support simulation training were also implemented at different times during the study period. However, the stark demarcation in code call rates coinciding with MET implementation makes it less likely that these other interventions were responsible for the observed decline. Second, our study was limited to a single institution and a single type of MET. Our findings may not apply to other types of institutions with different staffing arrangements or a different hospital culture, nor would they necessarily apply to different types of MET. Third, our nurse surveys were not collected anonymously, and this may have affected the nurses' responses. Finally, we did not collect physiological parameters on our patients, so we cannot state with certainty what the MET intervention accomplished.

Since initial studies suggested that METs could reduce hospital mortality rates, the Joint Commission has effectively mandated implementation of rapid response systems in all hospitals. Newer evidence, however, has been less convincing of mortality or other benefit. Our study adds to the literature in that we also did not find a mortality benefit. However, there were 2 clear benefits that we did identify. Our MET did appear to substantially reduce total numbers of code calls, particularly codes called for medical crises. Also, our nurses had a very positive response to the MET, which empowered them to get help for a patient when the patient's physician was unavailable or did not take their concerns seriously. Clearly, additional study is needed to better understand the effects of METs on mortality, codes, and other indicators of patient outcomes. However, in the current regulatory environment, such studies will be difficult to perform. Instead, additional studies can clarify which models deliver best outcomes and optimal use of our limited resources.

The number of pediatric hospitalists (PH) in the United States is increasing rapidly. The membership of the American Academy of Pediatrics (AAP) Section on Hospital Medicine has grown to 880 (7/10, AAP Section on Hospital Medicine), and there over 10,000 members of the Society of Hospital Medicine of which an estimated 5% care for children (7/10, Society of Hospital Medicine). Little is known about the educational contributions of pediatric hospitalists, residents' perceptions of hospitalists' roles, or how hospitalists may influence residents' eventual career plans even though 89% of pediatric hospitalists report they serve as teaching attendings.1 Teaching by hospitalists is well received and valued by residents, but, to date, all such data are from single institution studies of individual hospitalist programs.27 Less is known regarding what residents perceive about the differences in patient care provided by hospitalists as compared with traditional pediatric teaching attendings. There is a paucity of information about the level of interest of current pediatric residents in becoming hospitalists, including how many plan such a career, reasons why residents might prefer to become hospitalists, and their perceptions of Pediatric Hospital Medicine (PHM) careers as either long or short term. In addition, the effects of new residency graduates going into Hospital Medicine on the overall pediatric workforce, and how the availability of Hospital Medicine careers affects the choice of practice in Primary Care Pediatrics have not been examined.

We surveyed a national, randomly selected representative sample of pediatric residents to determine their level of exposure to hospitalist attending physicians during training. We asked the resident cohort about their educational experiences with hospitalists, patient care provided by hospitalists on their team, and career plans regarding becoming a hospitalist, including perceived needs for different or additional training. We obtained further information about reasons why hospitalist positions were appealing and about the current relationship between careers in Pediatric Hospital Medicine and Primary Care. To our knowledge, this is the first national study of how pediatric hospitalists might influence residents in the domains of education, patient care, and career planning.

METHODS

We conducted a survey of randomly selected pediatric residents from the AAP membership database. The selection was done by random generation by the AAP Department of Research from the membership database, in the same way members are selected for the annual Survey of Fellows and the annual pediatric level 3 (PL3) survey. Permission was obtained from the American Academy of Pediatrics Section on Residents (AAP SORe) to survey a selection of US pediatric residents in June 2007. The full sample of US pediatric residents included 9569 residents. The AAP SORe had 7694 e‐mail addresses from which the AAP Department of Research generated a random sample of 300 for our use, including Medicine‐Pediatric, Pediatric, and Pediatric Chief residents. One of the researchers (A.H.) sent an e‐mail with the title $200 AAP Career Raffle Survey containing a link to a SurveyMonkey survey (see Supporting Appendix AQuestionnaire in the online version of this article) and offering incentivized participation with a raffle. The need for informed consent was waived, as consent was implied by participation in the survey. The survey was taken anonymously by connecting through the link, and when it was completed, residents were asked to separately e‐mail a Section on Hospital Medicine address if they wished to participate in the raffle. Their raffle request was not linked to their survey results in any way. The $200 was supplied by the AAP Section on Hospital Medicine. The survey was sent 3 times. We analyzed responses with descriptive statistics. Institutional Review Board approval was obtained from Concord Hospital in Concord, New Hampshire.

RESULTS

The respondents are described in Figure 1 and Table 1. For their exposure to PHM, 54% (73 of 111) reported PH attendings in medical school; 90% (75 of 83) did have or will have PH attendings during residency, with no significant variation by program size (small, medium, large, or extra large). The degree of exposure was not asked. To learn about PHM, 47% (46 of 97 respondents) asked a PH in their program, while 28% (27 of 99) visited the AAP web site. Sixty‐eight percent (73 of 108) felt familiar or very familiar with PHM.

Figure 1

Table 2 summarizes the respondents' perception of PHM. They report a positive opinion of the field and overwhelmingly feel that PHM is a growing/developing field. Almost none feel PHM will not survive. A small percentage (10%, 28 of 99) felt there was no difference between PH and residents, with 25% (25 of 99) feeling some ambiguity about whether the PH role differs from that of a resident. Many (35 of 99) did not disagree that there is little difference between PH and resident positions, although most did. Sixty percent (59 of 99) agreed or strongly agreed that a PH position would be a good job for the short‐term. Forty‐seven percent (46 of 99) agreed in some form that PHM gives you something to do while you are waiting for another position. Given the choice of PHM as a long‐term opportunity, short‐term opportunity, either or not sure: 21% (21 of 98) saw PHM as a short‐term option only; 26% (25 of 98) saw PHM as a long‐term career only; 49% (48 of 98) saw it as either a short‐term option or long‐term career. Most (65%, 64 of 99) believed PH were better than primary care providers at caring for complex inpatients, but only 28% (28 of 99) thought PH provided better care for routine admissions. Most (82%, 81 of 99) agreed in some form that working with pediatric hospitalists enhances a resident's education.

On a 5‐point scale ranging from would definitely not include to might or might not include to would definitely include, the majority of respondents felt a PHM job would definitely include Pediatric Wards (86%, 84 of 98) and Inpatient Consultant for Specialists (54%, 52 of 97). Only 47% (46/97) felt the responsibilities would probably or definitely include Medical Student and Resident Education (47%, 46 of 97). The respondents were less certain (might or might not response) if PHM should include Normal Newborn Nursery (37%, 36 of 98), Delivery Room (42%, 41 of 98), Intensive Care Nursery (35%, 34 of 98), ED/Urgent Care (34%, 33 of 98), or Research (50%, 49 of 98). A majority of respondents felt PHM unlikely to include, or felt the job might not or might include: Outpatient Clinics (77%, 75 of 98), Outpatient Consults (81%, 79 of 98), and Pediatric Intensive Care Unit work (70%, 68 of 98).

Of categorical pediatric trainees answering the question, 35% (28 of 80) are considering a PHM career. Immediately post‐residency, 30% (24 of 80) of categorical trainees plan to enter Primary Care (PC), 4% (3 of 80) plan on PHM, and 3% (2 of 80) plan to pursue PH fellowship.

Of all respondents given the choice of whether a factor plays no role, limited role, or strong role in considering a career in PHM: flexible hours (96%, 94 of 98), opportunities to participate in education (97%, 95 of 98), and better salary than PC (94%, 91 of 97) would influence their decision to choose PHM. For 49% (48 of 98), ability to do the job without fellowship would play a strong role in choosing a career in PHM.

Forty‐five percent (44 of 97) support training in addition to residency; 16.5% (16 of 97) are against it; the remaining 38% (37 of 97) are unsure. Three percent (3 of 98) thought 3‐year fellowship best, while 28% (27 of 98) preferred 2‐year fellowship; 29% (28 of 98) would like a hospitalist‐track residency; 28% (27 of 98) believe standard residency sufficient; and 4% (4 of 98) felt a chief year adequate. If they were to pursue PHM, 31% (30 of 98) would enter PH fellowship, 34% (33 of 98) would not, and 36% (35 of 98) were unsure.

On a 5‐point scale, respondents were asked about barriers identified to choosing a career in PHM: 28% (27 of 96) agreed or strongly agreed that not feeling well‐enough trained was a barrier to entering the field; 42% (40 of 96) were agreed in some form that they were unsure of what training they needed; 39% (37 of 95) were unsure about where positions are available. Seven percent (7 of 98) of respondents were less likely to choose to practice Primary Care (PC) pediatrics because of hospitalists. Of respondents choosing PC, 59% (34 of 58) prefer or must have PH to work within their future practices, while 12% (7 of 58) prefer not to, or definitely do not want to, work with PH.

DISCUSSION

In 2006, the American Board of Pediatrics (ABP) General Pediatrics Career Survey found that 1% of first‐time applicants were taking a hospitalist position.8 In 2007, this number grew to 3% choosing a position in Pediatric Hospital Medicine.9, 10 The 2009‐2010 survey data found that 7.6% of first‐time applicants would be taking a job as hospitalist as of July 1.11 Our data suggest this number will continue to grow over the next few years. The growth of PHM has prompted an in‐depth look at the field by the ABP.1, 12, 13 PHM programs appear to have become part of the fabric of pediatric care, with the majority of hospitals with PHM programs planning to continue the programs despite the need to pay for value‐added by hospitalists beyond revenue received for their direct clinical service.13 Looking forward, when the Institute of Medicine recommendations to further restrict resident work hours to 16 hour shifts are implemented, many programs plan on increasing their PHM programs.14, 15 Therefore, residents' views of a career in PHM are important, as they give perspective on attitudes of those who might be, or interact with, hospitalists in the future, and should impact training programs for residents regardless of their interest in a career in PHM.

Our national data support local, large institution studies that hospitalists are positively impacting education.27 However, this study suggests that this is not only a local or large academic center phenomenon, but a national trend towards providing a different and positive education experience for pediatric residents. This mirrors the opinion of the majority of residency and clerkship directors who feel that hospitalists are more accessible to trainees than traditional attendings.12 Training programs should consider this impact when selecting attending hospitalists and supporting their roles as mentors and educators.

As residents finish their training and seek positions as pediatric hospitalists, programs need to be aware that a significant percentage of residents in our survey see PHM as a short‐term career option and/or fail to see a difference between a PH job and their own. Program Directors also need to be aware of the breadth of PHM practice which can include areas our respondents felt were less likely to be part of PHM, such as other inpatient areas and the expectation of research.

While 1 option to address some of these issues is fellowship training, this is not a simple decision. PHM needs to determine if fellowship is truly the best option for future hospitalists and, if so, what the fellowship should look like in terms of duration and scope. While the needs of optimal training should be paramount, resident preferences to not commit to an additional 3 years of training must be considered. Many residents fail to see a difference between the role of PH and their own role during training, and feel that the current format of residency training is all the preparation needed to step into a career as a PH. This demonstrates a clear gap between resident perceptions of PHM and the accepted definition of a hospitalist,16 which reaches far beyond direct inpatient care. While The Core Competencies for Pediatric Hospital Medicine17 address a number of these areas, neither trainees nor hospitalists themselves have fully integrated these into their practice. PH must recognize and prepare for their position as mentors and role models to residents. This responsibility should differentiate PH role from that of a resident, demonstrating roles PH play in policy making, patient safety and quality initiatives, in administration, and in providing advanced thinking in direct patient care. Finally, PH and their employers must work to build programs that present PHM as a long‐term career option for residents.

There is a significant impact on the field if those who enter it see it only as something to do while waiting for a position elsewhere. While some of these new‐careerists may stay with the field once they have tried it and become significant contributors, inherent in these answers are the issues of turnover and lack of senior experience many Hospital Medicine programs currently face. Additionally, and outside the scope of this survey, it is unclear what those next positions are and how a brief experience as a hospitalist might impact their future practice.

It is a significant change that residents entering a Primary Care career expect to work with pediatric hospitalists and, in general, see this as a benefit and necessity. The 2007 American Board of Pediatrics' survey found that 27% of respondents planned a career in General Pediatrics with little or no inpatient care.10 Hospitalists of the near future will likely face a dichotomy of needs between primary care providers who trained before, and those who trained after, the existence of hospitalists. Hospitalists will need to understand and address the ongoing needs of both of these groups in order to adequately serve them and their patient‐bases.

Limitations of our study include our small sample size, with a response rate of 43% at best (individual question response rate varied). Though the group was nationally representative, it was skewed towards first year respondents, likely due to the time of year in which it was distributed. There is likely some bias due to the low response rate, in that those more interested in careers as hospitalists might be more likely to respond. This might potentially inflate the percentages of those who state they are interested in being a hospitalist. In addition, given that the last round of the survey went out at the very end of the academic year, graduating residents had a lower response rate.

We were unable to compare opinions across unexposed and exposed residents because only 6.5% reported knowing nothing about the field, and only 2 respondents had not had any exposure to pediatric hospitalists to date. Given that most residencies have PHM services,12 this distinction is unlikely to be significant. In looking at training desires, we did not compare them to residents considering entering other fields of medicine. It may be true that residents considering other fellowships do not desire to do 3 years of fellowship training. That being said, it in no way diminishes the implication that 3‐year fellowships for PHM may not be the right answer for future training.

Strengths of the study include that it is, to our knowledge, the first national study of a group of residents regarding exposure to, and career plans as related to, PH. In addition, the group is gender‐balanced, and represents residents from a range of training sites (urban, suburban, rural) and program sizes. This study offers important information that must be considered in the further development of the field of Pediatric Hospital Medicine.

CONCLUSION

This was the first national study of residents regarding Pediatric Hospital Medicine. Almost all residents are exposed to PH during their training, though a gap of no exposure still exists. More work needs to be done to improve the perception of PHM as a viable long‐term career. Nevertheless, PHM has become a career consideration for trainees. Nearly half agreed that some type of specialized training would be helpful. This information should impact on the development of PHM training programs.

The number of pediatric hospitalists (PH) in the United States is increasing rapidly. The membership of the American Academy of Pediatrics (AAP) Section on Hospital Medicine has grown to 880 (7/10, AAP Section on Hospital Medicine), and there over 10,000 members of the Society of Hospital Medicine of which an estimated 5% care for children (7/10, Society of Hospital Medicine). Little is known about the educational contributions of pediatric hospitalists, residents' perceptions of hospitalists' roles, or how hospitalists may influence residents' eventual career plans even though 89% of pediatric hospitalists report they serve as teaching attendings.1 Teaching by hospitalists is well received and valued by residents, but, to date, all such data are from single institution studies of individual hospitalist programs.27 Less is known regarding what residents perceive about the differences in patient care provided by hospitalists as compared with traditional pediatric teaching attendings. There is a paucity of information about the level of interest of current pediatric residents in becoming hospitalists, including how many plan such a career, reasons why residents might prefer to become hospitalists, and their perceptions of Pediatric Hospital Medicine (PHM) careers as either long or short term. In addition, the effects of new residency graduates going into Hospital Medicine on the overall pediatric workforce, and how the availability of Hospital Medicine careers affects the choice of practice in Primary Care Pediatrics have not been examined.

We surveyed a national, randomly selected representative sample of pediatric residents to determine their level of exposure to hospitalist attending physicians during training. We asked the resident cohort about their educational experiences with hospitalists, patient care provided by hospitalists on their team, and career plans regarding becoming a hospitalist, including perceived needs for different or additional training. We obtained further information about reasons why hospitalist positions were appealing and about the current relationship between careers in Pediatric Hospital Medicine and Primary Care. To our knowledge, this is the first national study of how pediatric hospitalists might influence residents in the domains of education, patient care, and career planning.

METHODS

We conducted a survey of randomly selected pediatric residents from the AAP membership database. The selection was done by random generation by the AAP Department of Research from the membership database, in the same way members are selected for the annual Survey of Fellows and the annual pediatric level 3 (PL3) survey. Permission was obtained from the American Academy of Pediatrics Section on Residents (AAP SORe) to survey a selection of US pediatric residents in June 2007. The full sample of US pediatric residents included 9569 residents. The AAP SORe had 7694 e‐mail addresses from which the AAP Department of Research generated a random sample of 300 for our use, including Medicine‐Pediatric, Pediatric, and Pediatric Chief residents. One of the researchers (A.H.) sent an e‐mail with the title $200 AAP Career Raffle Survey containing a link to a SurveyMonkey survey (see Supporting Appendix AQuestionnaire in the online version of this article) and offering incentivized participation with a raffle. The need for informed consent was waived, as consent was implied by participation in the survey. The survey was taken anonymously by connecting through the link, and when it was completed, residents were asked to separately e‐mail a Section on Hospital Medicine address if they wished to participate in the raffle. Their raffle request was not linked to their survey results in any way. The $200 was supplied by the AAP Section on Hospital Medicine. The survey was sent 3 times. We analyzed responses with descriptive statistics. Institutional Review Board approval was obtained from Concord Hospital in Concord, New Hampshire.

RESULTS

The respondents are described in Figure 1 and Table 1. For their exposure to PHM, 54% (73 of 111) reported PH attendings in medical school; 90% (75 of 83) did have or will have PH attendings during residency, with no significant variation by program size (small, medium, large, or extra large). The degree of exposure was not asked. To learn about PHM, 47% (46 of 97 respondents) asked a PH in their program, while 28% (27 of 99) visited the AAP web site. Sixty‐eight percent (73 of 108) felt familiar or very familiar with PHM.

Figure 1

Table 2 summarizes the respondents' perception of PHM. They report a positive opinion of the field and overwhelmingly feel that PHM is a growing/developing field. Almost none feel PHM will not survive. A small percentage (10%, 28 of 99) felt there was no difference between PH and residents, with 25% (25 of 99) feeling some ambiguity about whether the PH role differs from that of a resident. Many (35 of 99) did not disagree that there is little difference between PH and resident positions, although most did. Sixty percent (59 of 99) agreed or strongly agreed that a PH position would be a good job for the short‐term. Forty‐seven percent (46 of 99) agreed in some form that PHM gives you something to do while you are waiting for another position. Given the choice of PHM as a long‐term opportunity, short‐term opportunity, either or not sure: 21% (21 of 98) saw PHM as a short‐term option only; 26% (25 of 98) saw PHM as a long‐term career only; 49% (48 of 98) saw it as either a short‐term option or long‐term career. Most (65%, 64 of 99) believed PH were better than primary care providers at caring for complex inpatients, but only 28% (28 of 99) thought PH provided better care for routine admissions. Most (82%, 81 of 99) agreed in some form that working with pediatric hospitalists enhances a resident's education.

On a 5‐point scale ranging from would definitely not include to might or might not include to would definitely include, the majority of respondents felt a PHM job would definitely include Pediatric Wards (86%, 84 of 98) and Inpatient Consultant for Specialists (54%, 52 of 97). Only 47% (46/97) felt the responsibilities would probably or definitely include Medical Student and Resident Education (47%, 46 of 97). The respondents were less certain (might or might not response) if PHM should include Normal Newborn Nursery (37%, 36 of 98), Delivery Room (42%, 41 of 98), Intensive Care Nursery (35%, 34 of 98), ED/Urgent Care (34%, 33 of 98), or Research (50%, 49 of 98). A majority of respondents felt PHM unlikely to include, or felt the job might not or might include: Outpatient Clinics (77%, 75 of 98), Outpatient Consults (81%, 79 of 98), and Pediatric Intensive Care Unit work (70%, 68 of 98).

Of categorical pediatric trainees answering the question, 35% (28 of 80) are considering a PHM career. Immediately post‐residency, 30% (24 of 80) of categorical trainees plan to enter Primary Care (PC), 4% (3 of 80) plan on PHM, and 3% (2 of 80) plan to pursue PH fellowship.

Of all respondents given the choice of whether a factor plays no role, limited role, or strong role in considering a career in PHM: flexible hours (96%, 94 of 98), opportunities to participate in education (97%, 95 of 98), and better salary than PC (94%, 91 of 97) would influence their decision to choose PHM. For 49% (48 of 98), ability to do the job without fellowship would play a strong role in choosing a career in PHM.

Forty‐five percent (44 of 97) support training in addition to residency; 16.5% (16 of 97) are against it; the remaining 38% (37 of 97) are unsure. Three percent (3 of 98) thought 3‐year fellowship best, while 28% (27 of 98) preferred 2‐year fellowship; 29% (28 of 98) would like a hospitalist‐track residency; 28% (27 of 98) believe standard residency sufficient; and 4% (4 of 98) felt a chief year adequate. If they were to pursue PHM, 31% (30 of 98) would enter PH fellowship, 34% (33 of 98) would not, and 36% (35 of 98) were unsure.

On a 5‐point scale, respondents were asked about barriers identified to choosing a career in PHM: 28% (27 of 96) agreed or strongly agreed that not feeling well‐enough trained was a barrier to entering the field; 42% (40 of 96) were agreed in some form that they were unsure of what training they needed; 39% (37 of 95) were unsure about where positions are available. Seven percent (7 of 98) of respondents were less likely to choose to practice Primary Care (PC) pediatrics because of hospitalists. Of respondents choosing PC, 59% (34 of 58) prefer or must have PH to work within their future practices, while 12% (7 of 58) prefer not to, or definitely do not want to, work with PH.

DISCUSSION

In 2006, the American Board of Pediatrics (ABP) General Pediatrics Career Survey found that 1% of first‐time applicants were taking a hospitalist position.8 In 2007, this number grew to 3% choosing a position in Pediatric Hospital Medicine.9, 10 The 2009‐2010 survey data found that 7.6% of first‐time applicants would be taking a job as hospitalist as of July 1.11 Our data suggest this number will continue to grow over the next few years. The growth of PHM has prompted an in‐depth look at the field by the ABP.1, 12, 13 PHM programs appear to have become part of the fabric of pediatric care, with the majority of hospitals with PHM programs planning to continue the programs despite the need to pay for value‐added by hospitalists beyond revenue received for their direct clinical service.13 Looking forward, when the Institute of Medicine recommendations to further restrict resident work hours to 16 hour shifts are implemented, many programs plan on increasing their PHM programs.14, 15 Therefore, residents' views of a career in PHM are important, as they give perspective on attitudes of those who might be, or interact with, hospitalists in the future, and should impact training programs for residents regardless of their interest in a career in PHM.

Our national data support local, large institution studies that hospitalists are positively impacting education.27 However, this study suggests that this is not only a local or large academic center phenomenon, but a national trend towards providing a different and positive education experience for pediatric residents. This mirrors the opinion of the majority of residency and clerkship directors who feel that hospitalists are more accessible to trainees than traditional attendings.12 Training programs should consider this impact when selecting attending hospitalists and supporting their roles as mentors and educators.

As residents finish their training and seek positions as pediatric hospitalists, programs need to be aware that a significant percentage of residents in our survey see PHM as a short‐term career option and/or fail to see a difference between a PH job and their own. Program Directors also need to be aware of the breadth of PHM practice which can include areas our respondents felt were less likely to be part of PHM, such as other inpatient areas and the expectation of research.

While 1 option to address some of these issues is fellowship training, this is not a simple decision. PHM needs to determine if fellowship is truly the best option for future hospitalists and, if so, what the fellowship should look like in terms of duration and scope. While the needs of optimal training should be paramount, resident preferences to not commit to an additional 3 years of training must be considered. Many residents fail to see a difference between the role of PH and their own role during training, and feel that the current format of residency training is all the preparation needed to step into a career as a PH. This demonstrates a clear gap between resident perceptions of PHM and the accepted definition of a hospitalist,16 which reaches far beyond direct inpatient care. While The Core Competencies for Pediatric Hospital Medicine17 address a number of these areas, neither trainees nor hospitalists themselves have fully integrated these into their practice. PH must recognize and prepare for their position as mentors and role models to residents. This responsibility should differentiate PH role from that of a resident, demonstrating roles PH play in policy making, patient safety and quality initiatives, in administration, and in providing advanced thinking in direct patient care. Finally, PH and their employers must work to build programs that present PHM as a long‐term career option for residents.

There is a significant impact on the field if those who enter it see it only as something to do while waiting for a position elsewhere. While some of these new‐careerists may stay with the field once they have tried it and become significant contributors, inherent in these answers are the issues of turnover and lack of senior experience many Hospital Medicine programs currently face. Additionally, and outside the scope of this survey, it is unclear what those next positions are and how a brief experience as a hospitalist might impact their future practice.

It is a significant change that residents entering a Primary Care career expect to work with pediatric hospitalists and, in general, see this as a benefit and necessity. The 2007 American Board of Pediatrics' survey found that 27% of respondents planned a career in General Pediatrics with little or no inpatient care.10 Hospitalists of the near future will likely face a dichotomy of needs between primary care providers who trained before, and those who trained after, the existence of hospitalists. Hospitalists will need to understand and address the ongoing needs of both of these groups in order to adequately serve them and their patient‐bases.

Limitations of our study include our small sample size, with a response rate of 43% at best (individual question response rate varied). Though the group was nationally representative, it was skewed towards first year respondents, likely due to the time of year in which it was distributed. There is likely some bias due to the low response rate, in that those more interested in careers as hospitalists might be more likely to respond. This might potentially inflate the percentages of those who state they are interested in being a hospitalist. In addition, given that the last round of the survey went out at the very end of the academic year, graduating residents had a lower response rate.

We were unable to compare opinions across unexposed and exposed residents because only 6.5% reported knowing nothing about the field, and only 2 respondents had not had any exposure to pediatric hospitalists to date. Given that most residencies have PHM services,12 this distinction is unlikely to be significant. In looking at training desires, we did not compare them to residents considering entering other fields of medicine. It may be true that residents considering other fellowships do not desire to do 3 years of fellowship training. That being said, it in no way diminishes the implication that 3‐year fellowships for PHM may not be the right answer for future training.

Strengths of the study include that it is, to our knowledge, the first national study of a group of residents regarding exposure to, and career plans as related to, PH. In addition, the group is gender‐balanced, and represents residents from a range of training sites (urban, suburban, rural) and program sizes. This study offers important information that must be considered in the further development of the field of Pediatric Hospital Medicine.

CONCLUSION

This was the first national study of residents regarding Pediatric Hospital Medicine. Almost all residents are exposed to PH during their training, though a gap of no exposure still exists. More work needs to be done to improve the perception of PHM as a viable long‐term career. Nevertheless, PHM has become a career consideration for trainees. Nearly half agreed that some type of specialized training would be helpful. This information should impact on the development of PHM training programs.

The number of pediatric hospitalists (PH) in the United States is increasing rapidly. The membership of the American Academy of Pediatrics (AAP) Section on Hospital Medicine has grown to 880 (7/10, AAP Section on Hospital Medicine), and there over 10,000 members of the Society of Hospital Medicine of which an estimated 5% care for children (7/10, Society of Hospital Medicine). Little is known about the educational contributions of pediatric hospitalists, residents' perceptions of hospitalists' roles, or how hospitalists may influence residents' eventual career plans even though 89% of pediatric hospitalists report they serve as teaching attendings.1 Teaching by hospitalists is well received and valued by residents, but, to date, all such data are from single institution studies of individual hospitalist programs.27 Less is known regarding what residents perceive about the differences in patient care provided by hospitalists as compared with traditional pediatric teaching attendings. There is a paucity of information about the level of interest of current pediatric residents in becoming hospitalists, including how many plan such a career, reasons why residents might prefer to become hospitalists, and their perceptions of Pediatric Hospital Medicine (PHM) careers as either long or short term. In addition, the effects of new residency graduates going into Hospital Medicine on the overall pediatric workforce, and how the availability of Hospital Medicine careers affects the choice of practice in Primary Care Pediatrics have not been examined.

We surveyed a national, randomly selected representative sample of pediatric residents to determine their level of exposure to hospitalist attending physicians during training. We asked the resident cohort about their educational experiences with hospitalists, patient care provided by hospitalists on their team, and career plans regarding becoming a hospitalist, including perceived needs for different or additional training. We obtained further information about reasons why hospitalist positions were appealing and about the current relationship between careers in Pediatric Hospital Medicine and Primary Care. To our knowledge, this is the first national study of how pediatric hospitalists might influence residents in the domains of education, patient care, and career planning.

METHODS

We conducted a survey of randomly selected pediatric residents from the AAP membership database. The selection was done by random generation by the AAP Department of Research from the membership database, in the same way members are selected for the annual Survey of Fellows and the annual pediatric level 3 (PL3) survey. Permission was obtained from the American Academy of Pediatrics Section on Residents (AAP SORe) to survey a selection of US pediatric residents in June 2007. The full sample of US pediatric residents included 9569 residents. The AAP SORe had 7694 e‐mail addresses from which the AAP Department of Research generated a random sample of 300 for our use, including Medicine‐Pediatric, Pediatric, and Pediatric Chief residents. One of the researchers (A.H.) sent an e‐mail with the title $200 AAP Career Raffle Survey containing a link to a SurveyMonkey survey (see Supporting Appendix AQuestionnaire in the online version of this article) and offering incentivized participation with a raffle. The need for informed consent was waived, as consent was implied by participation in the survey. The survey was taken anonymously by connecting through the link, and when it was completed, residents were asked to separately e‐mail a Section on Hospital Medicine address if they wished to participate in the raffle. Their raffle request was not linked to their survey results in any way. The $200 was supplied by the AAP Section on Hospital Medicine. The survey was sent 3 times. We analyzed responses with descriptive statistics. Institutional Review Board approval was obtained from Concord Hospital in Concord, New Hampshire.

RESULTS

The respondents are described in Figure 1 and Table 1. For their exposure to PHM, 54% (73 of 111) reported PH attendings in medical school; 90% (75 of 83) did have or will have PH attendings during residency, with no significant variation by program size (small, medium, large, or extra large). The degree of exposure was not asked. To learn about PHM, 47% (46 of 97 respondents) asked a PH in their program, while 28% (27 of 99) visited the AAP web site. Sixty‐eight percent (73 of 108) felt familiar or very familiar with PHM.

Figure 1

Table 2 summarizes the respondents' perception of PHM. They report a positive opinion of the field and overwhelmingly feel that PHM is a growing/developing field. Almost none feel PHM will not survive. A small percentage (10%, 28 of 99) felt there was no difference between PH and residents, with 25% (25 of 99) feeling some ambiguity about whether the PH role differs from that of a resident. Many (35 of 99) did not disagree that there is little difference between PH and resident positions, although most did. Sixty percent (59 of 99) agreed or strongly agreed that a PH position would be a good job for the short‐term. Forty‐seven percent (46 of 99) agreed in some form that PHM gives you something to do while you are waiting for another position. Given the choice of PHM as a long‐term opportunity, short‐term opportunity, either or not sure: 21% (21 of 98) saw PHM as a short‐term option only; 26% (25 of 98) saw PHM as a long‐term career only; 49% (48 of 98) saw it as either a short‐term option or long‐term career. Most (65%, 64 of 99) believed PH were better than primary care providers at caring for complex inpatients, but only 28% (28 of 99) thought PH provided better care for routine admissions. Most (82%, 81 of 99) agreed in some form that working with pediatric hospitalists enhances a resident's education.

On a 5‐point scale ranging from would definitely not include to might or might not include to would definitely include, the majority of respondents felt a PHM job would definitely include Pediatric Wards (86%, 84 of 98) and Inpatient Consultant for Specialists (54%, 52 of 97). Only 47% (46/97) felt the responsibilities would probably or definitely include Medical Student and Resident Education (47%, 46 of 97). The respondents were less certain (might or might not response) if PHM should include Normal Newborn Nursery (37%, 36 of 98), Delivery Room (42%, 41 of 98), Intensive Care Nursery (35%, 34 of 98), ED/Urgent Care (34%, 33 of 98), or Research (50%, 49 of 98). A majority of respondents felt PHM unlikely to include, or felt the job might not or might include: Outpatient Clinics (77%, 75 of 98), Outpatient Consults (81%, 79 of 98), and Pediatric Intensive Care Unit work (70%, 68 of 98).

Of categorical pediatric trainees answering the question, 35% (28 of 80) are considering a PHM career. Immediately post‐residency, 30% (24 of 80) of categorical trainees plan to enter Primary Care (PC), 4% (3 of 80) plan on PHM, and 3% (2 of 80) plan to pursue PH fellowship.

Of all respondents given the choice of whether a factor plays no role, limited role, or strong role in considering a career in PHM: flexible hours (96%, 94 of 98), opportunities to participate in education (97%, 95 of 98), and better salary than PC (94%, 91 of 97) would influence their decision to choose PHM. For 49% (48 of 98), ability to do the job without fellowship would play a strong role in choosing a career in PHM.

Forty‐five percent (44 of 97) support training in addition to residency; 16.5% (16 of 97) are against it; the remaining 38% (37 of 97) are unsure. Three percent (3 of 98) thought 3‐year fellowship best, while 28% (27 of 98) preferred 2‐year fellowship; 29% (28 of 98) would like a hospitalist‐track residency; 28% (27 of 98) believe standard residency sufficient; and 4% (4 of 98) felt a chief year adequate. If they were to pursue PHM, 31% (30 of 98) would enter PH fellowship, 34% (33 of 98) would not, and 36% (35 of 98) were unsure.

On a 5‐point scale, respondents were asked about barriers identified to choosing a career in PHM: 28% (27 of 96) agreed or strongly agreed that not feeling well‐enough trained was a barrier to entering the field; 42% (40 of 96) were agreed in some form that they were unsure of what training they needed; 39% (37 of 95) were unsure about where positions are available. Seven percent (7 of 98) of respondents were less likely to choose to practice Primary Care (PC) pediatrics because of hospitalists. Of respondents choosing PC, 59% (34 of 58) prefer or must have PH to work within their future practices, while 12% (7 of 58) prefer not to, or definitely do not want to, work with PH.

DISCUSSION

In 2006, the American Board of Pediatrics (ABP) General Pediatrics Career Survey found that 1% of first‐time applicants were taking a hospitalist position.8 In 2007, this number grew to 3% choosing a position in Pediatric Hospital Medicine.9, 10 The 2009‐2010 survey data found that 7.6% of first‐time applicants would be taking a job as hospitalist as of July 1.11 Our data suggest this number will continue to grow over the next few years. The growth of PHM has prompted an in‐depth look at the field by the ABP.1, 12, 13 PHM programs appear to have become part of the fabric of pediatric care, with the majority of hospitals with PHM programs planning to continue the programs despite the need to pay for value‐added by hospitalists beyond revenue received for their direct clinical service.13 Looking forward, when the Institute of Medicine recommendations to further restrict resident work hours to 16 hour shifts are implemented, many programs plan on increasing their PHM programs.14, 15 Therefore, residents' views of a career in PHM are important, as they give perspective on attitudes of those who might be, or interact with, hospitalists in the future, and should impact training programs for residents regardless of their interest in a career in PHM.

Our national data support local, large institution studies that hospitalists are positively impacting education.27 However, this study suggests that this is not only a local or large academic center phenomenon, but a national trend towards providing a different and positive education experience for pediatric residents. This mirrors the opinion of the majority of residency and clerkship directors who feel that hospitalists are more accessible to trainees than traditional attendings.12 Training programs should consider this impact when selecting attending hospitalists and supporting their roles as mentors and educators.

As residents finish their training and seek positions as pediatric hospitalists, programs need to be aware that a significant percentage of residents in our survey see PHM as a short‐term career option and/or fail to see a difference between a PH job and their own. Program Directors also need to be aware of the breadth of PHM practice which can include areas our respondents felt were less likely to be part of PHM, such as other inpatient areas and the expectation of research.

While 1 option to address some of these issues is fellowship training, this is not a simple decision. PHM needs to determine if fellowship is truly the best option for future hospitalists and, if so, what the fellowship should look like in terms of duration and scope. While the needs of optimal training should be paramount, resident preferences to not commit to an additional 3 years of training must be considered. Many residents fail to see a difference between the role of PH and their own role during training, and feel that the current format of residency training is all the preparation needed to step into a career as a PH. This demonstrates a clear gap between resident perceptions of PHM and the accepted definition of a hospitalist,16 which reaches far beyond direct inpatient care. While The Core Competencies for Pediatric Hospital Medicine17 address a number of these areas, neither trainees nor hospitalists themselves have fully integrated these into their practice. PH must recognize and prepare for their position as mentors and role models to residents. This responsibility should differentiate PH role from that of a resident, demonstrating roles PH play in policy making, patient safety and quality initiatives, in administration, and in providing advanced thinking in direct patient care. Finally, PH and their employers must work to build programs that present PHM as a long‐term career option for residents.

There is a significant impact on the field if those who enter it see it only as something to do while waiting for a position elsewhere. While some of these new‐careerists may stay with the field once they have tried it and become significant contributors, inherent in these answers are the issues of turnover and lack of senior experience many Hospital Medicine programs currently face. Additionally, and outside the scope of this survey, it is unclear what those next positions are and how a brief experience as a hospitalist might impact their future practice.

It is a significant change that residents entering a Primary Care career expect to work with pediatric hospitalists and, in general, see this as a benefit and necessity. The 2007 American Board of Pediatrics' survey found that 27% of respondents planned a career in General Pediatrics with little or no inpatient care.10 Hospitalists of the near future will likely face a dichotomy of needs between primary care providers who trained before, and those who trained after, the existence of hospitalists. Hospitalists will need to understand and address the ongoing needs of both of these groups in order to adequately serve them and their patient‐bases.

Limitations of our study include our small sample size, with a response rate of 43% at best (individual question response rate varied). Though the group was nationally representative, it was skewed towards first year respondents, likely due to the time of year in which it was distributed. There is likely some bias due to the low response rate, in that those more interested in careers as hospitalists might be more likely to respond. This might potentially inflate the percentages of those who state they are interested in being a hospitalist. In addition, given that the last round of the survey went out at the very end of the academic year, graduating residents had a lower response rate.

We were unable to compare opinions across unexposed and exposed residents because only 6.5% reported knowing nothing about the field, and only 2 respondents had not had any exposure to pediatric hospitalists to date. Given that most residencies have PHM services,12 this distinction is unlikely to be significant. In looking at training desires, we did not compare them to residents considering entering other fields of medicine. It may be true that residents considering other fellowships do not desire to do 3 years of fellowship training. That being said, it in no way diminishes the implication that 3‐year fellowships for PHM may not be the right answer for future training.

Strengths of the study include that it is, to our knowledge, the first national study of a group of residents regarding exposure to, and career plans as related to, PH. In addition, the group is gender‐balanced, and represents residents from a range of training sites (urban, suburban, rural) and program sizes. This study offers important information that must be considered in the further development of the field of Pediatric Hospital Medicine.

CONCLUSION

This was the first national study of residents regarding Pediatric Hospital Medicine. Almost all residents are exposed to PH during their training, though a gap of no exposure still exists. More work needs to be done to improve the perception of PHM as a viable long‐term career. Nevertheless, PHM has become a career consideration for trainees. Nearly half agreed that some type of specialized training would be helpful. This information should impact on the development of PHM training programs.

The American healthcare system produces a product whose quality, safety, reliability, and cost would be incompatible with corporate survival, were they created by a business operating in a competitive industry. Care fails to comport with best evidence nearly half of the time.1 Tens of thousands of Americans die yearly from preventable medical mistakes.2 The healthcare inflation rate is nearly twice that of the rest of the economy, rapidly outstripping the ability of employers, tax revenues, and consumers to pay the mounting bills.

Increasingly, the healthcare system is being held accountable for this lack of value. Whether through a more robust accreditation and regulatory environment, public reporting of quality and safety metrics, or pay for performance (or no pay for errors) initiatives, outside stakeholders are creating performance pressures that scarcely existed a decade ago.

Healthcare organizations and providers have begun to take notice and act, often by seeking answers from industries outside healthcare and thoughtfully importing these lessons into medicine. For example, the use of checklists has been adopted by healthcare (from aviation), with impressive results.3, 4 Many quality methods drawn from industry (Lean, Toyota, Six Sigma) have been used to try to improve performance and remove waste from complex processes.5, 6

While these efforts have been helpful, their focus has generally been at the point‐of‐careimproving the care of patients with acute myocardial infarction or decreasing readmissions. However, while the business community has long recognized that poor management and structure can thwart most efforts to improve individual processes, healthcare has paid relatively little attention to issues of organizational structure and leadership. The question arises: Could methods that have been used to learn from top‐performing businesses be helpful to healthcare's efforts to improve its own organizational performance?

In this article, we describe perhaps the best known effort to identify top‐performing corporations, compare them to carefully selected organizations that failed to achieve similar levels of performance, and glean lessons from these analyses. This effort, described in a book entitled Good to Great: Why Some Companies Make the Leapand Others Don't, has sold more than 3 million copies in its 35 languages, and is often cited by business leaders as a seminal work. We ask whether the methods of Good to Great might be applicable to healthcare organizations seeking to produce the kinds of value that patients and purchasers need and deserve.

GOOD TO GREAT METHODOLOGY

In 2001, business consultant Jim Collins published Good to Great. Its methods can be divided into 3 main components: (1) a gold standard metric to identify top organizations; (2) the creation of a control group of organizations that appeared similar to the top performers at the start of the study, but failed to match the successful organizations' performance over time; and (3) a detailed review of the methods, leadership, and structure of both the winning and laggard organizations, drawing lessons from their differences. Before discussing whether these methods could be used to analyze healthcare organizations, it is worth describing Collins' methods in more detail.

The first component of Good to Great's structure was the use of 4 metrics to identify top‐performing companies (Table 1). To select the good to great companies, Collins and his team began with a field of 1435 companies drawn from Fortune magazine's rankings of America's largest public companies. They then used the criteria in Table 1 to narrow the list to their final 11 companies, which formed the experimental group for the analysis.

After identifying these 11 top‐performing companies, Collins created a control group, composed of companies with similar attributes that could have made the transition, but failed to do so.7 To create the control group, Collins matched and scored a pool of control group candidates based on the following criteria: similarities of business model, size, age, and cumulative stock returns prior to the good to great transition. When there were several potential controls, Collins chose companies that were larger, more profitable, and had a stronger market position and reputation prior to the transition, in order to increase the probability that the experimental companies' successes were not incidental.8 Table 2 lists the paired experimental and control companies.

Finally, Collins performed a detailed historical analysis on the experimental and control groups, using materials (such as major articles published on the company, books, academic case studies, analyst reports, and financial and annual reports) that assessed the companies in real time. Good to Great relied on evidence from the period of interest (ie, accrued prior to the transition point) to avoid biases that would likely result from relying on retrospective sources of data.9

This analysis identified a series of factors that were generally present in good to great companies and absent in the control organizations. In brief, they were: building a culture of discipline, making change through gradual and consistent improvement, having a leader with a paradoxical blend of personal humility and professional will, and relentlessly focusing on hiring and nurturing the best employees. Over 6000 articles and 5 years of analysis support these conclusions.8

EFFORTS TO DATE TO ANALYZE HEALTHCARE ORGANIZATIONAL CHARACTERISTICS

We reviewed a convenience sample of the literature on organizational change in healthcare, and found only 1 study that utilized a similar methodology to that of Good to Great: an analysis of the academic medical centers that participate in the University HealthSystem Consortium (UHC). Drawing inspiration from Collins' methodologies, the UHC study developed a holistic measure of quality, based on safety, mortality, compliance with evidence‐based practices, and equity of care. Using these criteria, the investigators selected 3 UHC member organizations that were performing extremely well, and 3 others performing toward the middle and bottom of the pack. Experts on health system organization then conducted detailed site visits to these 6 academic medical centers. The researchers were blinded to these rankings at the time of the visits, but were able to perfectly predict which cohort the organizations were in.

The investigators analyzed the factors that seemed to be present in the top‐performing organizations, but were absent in the laggards, and found: hospital leadership emphasizing a patients‐first mission, an alignment of departmental objectives to reduce conflict, a concrete accountability structure for quality, a relentless focus on measurable improvement, and a culture promoting interprofessional collaboration on quality.10

While the UHC study is among the most robust exploration of healthcare organization dynamics in the literature, it has a few limitations. The first is that it studied a small, relatively specialized population: UHC members, which are large, mostly urban, well‐resourced teaching hospitals. While studying segments of populations can limit the generalizability of some of the UHC studies' findings, their approach can be a useful model to apply to studying other types of healthcare institutions. (And, to be fair, Good to Great also studies a specialized populationFortune 500 companiesand thus its lessons need to be extrapolated to other businesses, such as small companies, with a degree of caution.) The study also suffers from the relative paucity of publicly accessible organizational data in healthcare. The fact that the UHC investigators depended on both top‐performing and laggard hospitals, to voluntarily release their organizational data and permit a detailed site visit, potentially introduces a selection bias into the survey population, a bias not present in Good to Great due to Collins' protocol for matching cases and controls.

There have been several other efforts, using different methods, to determine organizational predictors of success in healthcare. The results of several important studies are shown in Table 3. Taken together, they indicate that higher performing organizations make practitioners accountable for performance measurements, and implement systems designed to both reduce errors and facilitate adherence to evidence‐based guidelines. In addition to these studies, several consulting organizations and foundations have performed focused reviews of high‐performing healthcare organizations in an effort to identify key success factors.11 These studies, while elucidating factors that influence organizational performance, suffer from variable quality measures and subjective methods for gathering organizational data, both of which are addressed within a good to great‐style analysis.12

Perhaps the best‐known study on healthcare organizational performance is The Dartmouth Atlas, an analysis that (though based on data accumulated over more than 30 years) has received tremendous public attention, in recent years, in the context of the debate over healthcare reform.13 However, by early 2010, the Dartmouth analysis was stirring controversy, with some observers expressing concerns over its focus on care toward the end of life, its methods for adjusting for case‐mix and sociodemographic predictors of outcomes and costs, and its exclusive use of Medicare data.14, 15 These limitations are also addressed by a good to great‐style analysis.

WOULD A GOOD TO GREAT ANALYSIS BE POSSIBLE IN HEALTHCARE?

While this review of prior research on organizational success factors in healthcare illustrates considerable interest in this area, none of the studies, to date, matches Good to Great in the robustness of the analysis or, obviously, its impact on the profession. Could a good to great analysis be carried out in healthcare? It is worth considering this by assessing each of Collins' 3 key steps: identifying the enterprises that made a good to great leap, selecting appropriate control organizations, and determining the factors that contributed to the successes of the former group.

Good to Great used an impressive elevation in stock price as a summary measure of organizational success. In the for‐profit business world, it is often assumed that Adam Smith's invisible hand makes corporate information available to investors, causing an organization's stock price to capture the overall success of its business strategy, including its product quality and operational efficiency.16 In the healthcare world, mostly populated by non‐profit organizations that are simultaneously working toward a bottom line and carrying out a social mission, there is no obvious equivalent to the stock price for measuring overall organizational performance and value. All of the methods for judging top hospitals, for example, are flaweda recent study found that the widely cited U.S. News & World Report's America's Best Hospitals list is largely driven by hospital reputation,17 while another study found glaring inconsistencies among methods used to calculate risk‐adjusted mortality rates.18 A generally accepted set of metrics defining the value of care produced by a healthcare organization (including quality, safety, access, patient satisfaction, and efficiency) would be needed to mirror the first good to great step: defining top‐performing organizations using a gold standard.19 The summary measure used in the UHC study is the closest we have seen to a good to great‐style summary performance measure in healthcare.10

While it is important to identify a gold‐standard measure of organizational quality, careful selection of a control organization may be the most important step in conducting a good to great analysis. Although Collins' use of stock price as a summary measure of organizational performance is the best measure available in business, it is by no means perfect. Despite this shortcoming, however, Collins believes that the central requirement is not finding a perfect measure of organizational success, but rather determining what correlates with a divergence of performance in stock price (J. Collins, oral communication, July 2010). Similar to clinical trials, meticulous matching of a good to great organization with a control has the advantage of canceling out extraneous environmental factors, thereby enabling the elucidation of organizational factors that contribute to divergent performance. Good to Great's methods depended on substantial historical background to define top performers and controls. Unfortunately, healthcare lacks an analog to the business world's robust historical and publicly accessible record of performance and organizational data. Therefore, even if a certain organization was determined to be a top performer based on a gold‐standard measure, selecting a control organization by matching its organizational and performance data to the top performer's would be unfeasible.

Finally, the lack of a historical record in healthcare also places substantial roadblocks in the way of looking under the organization's hood. Even in pioneering organizational analyses by Shortell et al.,20 Knaus et al.,21 and Jha et al.,22 substantial parts of their analyses relied on retrospective accounts to determine organizational characteristics. To remove the bias that comes from knowing the organization's ultimate performance, Collins was careful to base his analysis of organizational structures and leadership on documents available before the good to great transition. Equivalent data in healthcare are extremely difficult to find.

While it is best to rely on an historical record, it may be possible to carry out a good to great‐type analysis through meticulous structuring of personal interviews. Collins has endorsed a non‐healthcare study that utilized the good to great matching strategy but used personal interviews to make up for lack of access to a substantial historical record.23 To reduce the bias inherent in relying on interviews, the research team ensured that the good to great transition was sustained for many years, and that the practices elicited from the interviews started before the good to great transition. Both of these techniques helped increase the probability that the identified practices contributed to the transition to superior results (in this case, in public education outcomes) and, thus, that the adoption of these practices could result in improvements elsewhere (J. Collins, oral communication, July 2010).

To make such a study possible in healthcare, more organizational data are required. Without prodding by outside stakeholders, most healthcare organizations have been reluctant to publicize performance data for fear of malpractice risk,24 or based on their belief that current data paint an incomplete or inaccurate picture of their quality.25 Trends toward required reporting of quality data (such as via Medicare's Hospital Compare Web site) offer hope that future comparisons could rely on robust organizational quality and safety data. Instituting healthcare analogs to Securities & Exchange Commission (SEC) reporting mandates would further ameliorate this information deficit.26

While we believe that Good to Great offers lessons relevant to healthcare, there are limitations that are worth considering. First, the extraordinary complexity of healthcare organizations makes it likely that a matched‐pair‐type study would need to be accompanied by other types of analyses, including more quantitative analyses of large datasets, to give a full picture of structural and leadership predictors of strong performance. Moreover, before embracing the good to great method, some will undoubtedly point to the demise of Circuit City and Fannie Mae (2 of the Good to Great companies; Table 2) as a cautionary note. Collins addresses this issue with the commonsensical argument that the success of a company needs to be judged in the context of the era. By way of analogy, he points to the value of studying a sports team, such as the John Wooden‐coached UCLA teams of the 1960s and 1970s, notwithstanding the less stellar performance of today's UCLA team. In fact, Collins' recent book mines some of these failures for their important lessons.27

GOOD TO GREAT IN HEALTHCARE

Breaking through healthcare's myopia to explore solutions drawn from other industries, such as checklists, simulation, and industrial approaches to quality improvement, has yielded substantial insights and catalyzed major improvements in care. Similarly, we believe that finding ways to measure the performance of healthcare organizations on both cost and quality, to learn from those organizations achieving superior performance, and to create a policy and educational environment that rewards superior performance and helps poor performers improve, is a defining issue for healthcare. This will be particularly crucial as the policy environment changestransitions to Accountable Care Organizations28 and bundled payments29 are likely to increase the pressure on healthcare organizations to learn the secrets of their better‐performing brethren. These shifts are likely to put an even greater premium on the kinds of leadership, organizational structure, and ability to adapt to a changing environment that Collins highlighted in his analysis. After all, it is under the most challenging conditions that top organizations often prove their mettle.

Although there are considerable challenges in performing a good to great analysis in healthcare (Table 4), the overall point remains: Healthcare is likely to benefit from rigorous, unbiased methods to distinguish successful from less successful organizations, to learn the lessons of both, and to apply these lessons to improvement efforts.

The American healthcare system produces a product whose quality, safety, reliability, and cost would be incompatible with corporate survival, were they created by a business operating in a competitive industry. Care fails to comport with best evidence nearly half of the time.1 Tens of thousands of Americans die yearly from preventable medical mistakes.2 The healthcare inflation rate is nearly twice that of the rest of the economy, rapidly outstripping the ability of employers, tax revenues, and consumers to pay the mounting bills.

Increasingly, the healthcare system is being held accountable for this lack of value. Whether through a more robust accreditation and regulatory environment, public reporting of quality and safety metrics, or pay for performance (or no pay for errors) initiatives, outside stakeholders are creating performance pressures that scarcely existed a decade ago.

Healthcare organizations and providers have begun to take notice and act, often by seeking answers from industries outside healthcare and thoughtfully importing these lessons into medicine. For example, the use of checklists has been adopted by healthcare (from aviation), with impressive results.3, 4 Many quality methods drawn from industry (Lean, Toyota, Six Sigma) have been used to try to improve performance and remove waste from complex processes.5, 6

While these efforts have been helpful, their focus has generally been at the point‐of‐careimproving the care of patients with acute myocardial infarction or decreasing readmissions. However, while the business community has long recognized that poor management and structure can thwart most efforts to improve individual processes, healthcare has paid relatively little attention to issues of organizational structure and leadership. The question arises: Could methods that have been used to learn from top‐performing businesses be helpful to healthcare's efforts to improve its own organizational performance?

In this article, we describe perhaps the best known effort to identify top‐performing corporations, compare them to carefully selected organizations that failed to achieve similar levels of performance, and glean lessons from these analyses. This effort, described in a book entitled Good to Great: Why Some Companies Make the Leapand Others Don't, has sold more than 3 million copies in its 35 languages, and is often cited by business leaders as a seminal work. We ask whether the methods of Good to Great might be applicable to healthcare organizations seeking to produce the kinds of value that patients and purchasers need and deserve.

GOOD TO GREAT METHODOLOGY

In 2001, business consultant Jim Collins published Good to Great. Its methods can be divided into 3 main components: (1) a gold standard metric to identify top organizations; (2) the creation of a control group of organizations that appeared similar to the top performers at the start of the study, but failed to match the successful organizations' performance over time; and (3) a detailed review of the methods, leadership, and structure of both the winning and laggard organizations, drawing lessons from their differences. Before discussing whether these methods could be used to analyze healthcare organizations, it is worth describing Collins' methods in more detail.

The first component of Good to Great's structure was the use of 4 metrics to identify top‐performing companies (Table 1). To select the good to great companies, Collins and his team began with a field of 1435 companies drawn from Fortune magazine's rankings of America's largest public companies. They then used the criteria in Table 1 to narrow the list to their final 11 companies, which formed the experimental group for the analysis.

After identifying these 11 top‐performing companies, Collins created a control group, composed of companies with similar attributes that could have made the transition, but failed to do so.7 To create the control group, Collins matched and scored a pool of control group candidates based on the following criteria: similarities of business model, size, age, and cumulative stock returns prior to the good to great transition. When there were several potential controls, Collins chose companies that were larger, more profitable, and had a stronger market position and reputation prior to the transition, in order to increase the probability that the experimental companies' successes were not incidental.8 Table 2 lists the paired experimental and control companies.

Finally, Collins performed a detailed historical analysis on the experimental and control groups, using materials (such as major articles published on the company, books, academic case studies, analyst reports, and financial and annual reports) that assessed the companies in real time. Good to Great relied on evidence from the period of interest (ie, accrued prior to the transition point) to avoid biases that would likely result from relying on retrospective sources of data.9

This analysis identified a series of factors that were generally present in good to great companies and absent in the control organizations. In brief, they were: building a culture of discipline, making change through gradual and consistent improvement, having a leader with a paradoxical blend of personal humility and professional will, and relentlessly focusing on hiring and nurturing the best employees. Over 6000 articles and 5 years of analysis support these conclusions.8

EFFORTS TO DATE TO ANALYZE HEALTHCARE ORGANIZATIONAL CHARACTERISTICS

We reviewed a convenience sample of the literature on organizational change in healthcare, and found only 1 study that utilized a similar methodology to that of Good to Great: an analysis of the academic medical centers that participate in the University HealthSystem Consortium (UHC). Drawing inspiration from Collins' methodologies, the UHC study developed a holistic measure of quality, based on safety, mortality, compliance with evidence‐based practices, and equity of care. Using these criteria, the investigators selected 3 UHC member organizations that were performing extremely well, and 3 others performing toward the middle and bottom of the pack. Experts on health system organization then conducted detailed site visits to these 6 academic medical centers. The researchers were blinded to these rankings at the time of the visits, but were able to perfectly predict which cohort the organizations were in.

The investigators analyzed the factors that seemed to be present in the top‐performing organizations, but were absent in the laggards, and found: hospital leadership emphasizing a patients‐first mission, an alignment of departmental objectives to reduce conflict, a concrete accountability structure for quality, a relentless focus on measurable improvement, and a culture promoting interprofessional collaboration on quality.10

While the UHC study is among the most robust exploration of healthcare organization dynamics in the literature, it has a few limitations. The first is that it studied a small, relatively specialized population: UHC members, which are large, mostly urban, well‐resourced teaching hospitals. While studying segments of populations can limit the generalizability of some of the UHC studies' findings, their approach can be a useful model to apply to studying other types of healthcare institutions. (And, to be fair, Good to Great also studies a specialized populationFortune 500 companiesand thus its lessons need to be extrapolated to other businesses, such as small companies, with a degree of caution.) The study also suffers from the relative paucity of publicly accessible organizational data in healthcare. The fact that the UHC investigators depended on both top‐performing and laggard hospitals, to voluntarily release their organizational data and permit a detailed site visit, potentially introduces a selection bias into the survey population, a bias not present in Good to Great due to Collins' protocol for matching cases and controls.

There have been several other efforts, using different methods, to determine organizational predictors of success in healthcare. The results of several important studies are shown in Table 3. Taken together, they indicate that higher performing organizations make practitioners accountable for performance measurements, and implement systems designed to both reduce errors and facilitate adherence to evidence‐based guidelines. In addition to these studies, several consulting organizations and foundations have performed focused reviews of high‐performing healthcare organizations in an effort to identify key success factors.11 These studies, while elucidating factors that influence organizational performance, suffer from variable quality measures and subjective methods for gathering organizational data, both of which are addressed within a good to great‐style analysis.12

Perhaps the best‐known study on healthcare organizational performance is The Dartmouth Atlas, an analysis that (though based on data accumulated over more than 30 years) has received tremendous public attention, in recent years, in the context of the debate over healthcare reform.13 However, by early 2010, the Dartmouth analysis was stirring controversy, with some observers expressing concerns over its focus on care toward the end of life, its methods for adjusting for case‐mix and sociodemographic predictors of outcomes and costs, and its exclusive use of Medicare data.14, 15 These limitations are also addressed by a good to great‐style analysis.

WOULD A GOOD TO GREAT ANALYSIS BE POSSIBLE IN HEALTHCARE?

While this review of prior research on organizational success factors in healthcare illustrates considerable interest in this area, none of the studies, to date, matches Good to Great in the robustness of the analysis or, obviously, its impact on the profession. Could a good to great analysis be carried out in healthcare? It is worth considering this by assessing each of Collins' 3 key steps: identifying the enterprises that made a good to great leap, selecting appropriate control organizations, and determining the factors that contributed to the successes of the former group.

Good to Great used an impressive elevation in stock price as a summary measure of organizational success. In the for‐profit business world, it is often assumed that Adam Smith's invisible hand makes corporate information available to investors, causing an organization's stock price to capture the overall success of its business strategy, including its product quality and operational efficiency.16 In the healthcare world, mostly populated by non‐profit organizations that are simultaneously working toward a bottom line and carrying out a social mission, there is no obvious equivalent to the stock price for measuring overall organizational performance and value. All of the methods for judging top hospitals, for example, are flaweda recent study found that the widely cited U.S. News & World Report's America's Best Hospitals list is largely driven by hospital reputation,17 while another study found glaring inconsistencies among methods used to calculate risk‐adjusted mortality rates.18 A generally accepted set of metrics defining the value of care produced by a healthcare organization (including quality, safety, access, patient satisfaction, and efficiency) would be needed to mirror the first good to great step: defining top‐performing organizations using a gold standard.19 The summary measure used in the UHC study is the closest we have seen to a good to great‐style summary performance measure in healthcare.10

While it is important to identify a gold‐standard measure of organizational quality, careful selection of a control organization may be the most important step in conducting a good to great analysis. Although Collins' use of stock price as a summary measure of organizational performance is the best measure available in business, it is by no means perfect. Despite this shortcoming, however, Collins believes that the central requirement is not finding a perfect measure of organizational success, but rather determining what correlates with a divergence of performance in stock price (J. Collins, oral communication, July 2010). Similar to clinical trials, meticulous matching of a good to great organization with a control has the advantage of canceling out extraneous environmental factors, thereby enabling the elucidation of organizational factors that contribute to divergent performance. Good to Great's methods depended on substantial historical background to define top performers and controls. Unfortunately, healthcare lacks an analog to the business world's robust historical and publicly accessible record of performance and organizational data. Therefore, even if a certain organization was determined to be a top performer based on a gold‐standard measure, selecting a control organization by matching its organizational and performance data to the top performer's would be unfeasible.

Finally, the lack of a historical record in healthcare also places substantial roadblocks in the way of looking under the organization's hood. Even in pioneering organizational analyses by Shortell et al.,20 Knaus et al.,21 and Jha et al.,22 substantial parts of their analyses relied on retrospective accounts to determine organizational characteristics. To remove the bias that comes from knowing the organization's ultimate performance, Collins was careful to base his analysis of organizational structures and leadership on documents available before the good to great transition. Equivalent data in healthcare are extremely difficult to find.

While it is best to rely on an historical record, it may be possible to carry out a good to great‐type analysis through meticulous structuring of personal interviews. Collins has endorsed a non‐healthcare study that utilized the good to great matching strategy but used personal interviews to make up for lack of access to a substantial historical record.23 To reduce the bias inherent in relying on interviews, the research team ensured that the good to great transition was sustained for many years, and that the practices elicited from the interviews started before the good to great transition. Both of these techniques helped increase the probability that the identified practices contributed to the transition to superior results (in this case, in public education outcomes) and, thus, that the adoption of these practices could result in improvements elsewhere (J. Collins, oral communication, July 2010).

To make such a study possible in healthcare, more organizational data are required. Without prodding by outside stakeholders, most healthcare organizations have been reluctant to publicize performance data for fear of malpractice risk,24 or based on their belief that current data paint an incomplete or inaccurate picture of their quality.25 Trends toward required reporting of quality data (such as via Medicare's Hospital Compare Web site) offer hope that future comparisons could rely on robust organizational quality and safety data. Instituting healthcare analogs to Securities & Exchange Commission (SEC) reporting mandates would further ameliorate this information deficit.26

While we believe that Good to Great offers lessons relevant to healthcare, there are limitations that are worth considering. First, the extraordinary complexity of healthcare organizations makes it likely that a matched‐pair‐type study would need to be accompanied by other types of analyses, including more quantitative analyses of large datasets, to give a full picture of structural and leadership predictors of strong performance. Moreover, before embracing the good to great method, some will undoubtedly point to the demise of Circuit City and Fannie Mae (2 of the Good to Great companies; Table 2) as a cautionary note. Collins addresses this issue with the commonsensical argument that the success of a company needs to be judged in the context of the era. By way of analogy, he points to the value of studying a sports team, such as the John Wooden‐coached UCLA teams of the 1960s and 1970s, notwithstanding the less stellar performance of today's UCLA team. In fact, Collins' recent book mines some of these failures for their important lessons.27

GOOD TO GREAT IN HEALTHCARE

Breaking through healthcare's myopia to explore solutions drawn from other industries, such as checklists, simulation, and industrial approaches to quality improvement, has yielded substantial insights and catalyzed major improvements in care. Similarly, we believe that finding ways to measure the performance of healthcare organizations on both cost and quality, to learn from those organizations achieving superior performance, and to create a policy and educational environment that rewards superior performance and helps poor performers improve, is a defining issue for healthcare. This will be particularly crucial as the policy environment changestransitions to Accountable Care Organizations28 and bundled payments29 are likely to increase the pressure on healthcare organizations to learn the secrets of their better‐performing brethren. These shifts are likely to put an even greater premium on the kinds of leadership, organizational structure, and ability to adapt to a changing environment that Collins highlighted in his analysis. After all, it is under the most challenging conditions that top organizations often prove their mettle.

Although there are considerable challenges in performing a good to great analysis in healthcare (Table 4), the overall point remains: Healthcare is likely to benefit from rigorous, unbiased methods to distinguish successful from less successful organizations, to learn the lessons of both, and to apply these lessons to improvement efforts.

The American healthcare system produces a product whose quality, safety, reliability, and cost would be incompatible with corporate survival, were they created by a business operating in a competitive industry. Care fails to comport with best evidence nearly half of the time.1 Tens of thousands of Americans die yearly from preventable medical mistakes.2 The healthcare inflation rate is nearly twice that of the rest of the economy, rapidly outstripping the ability of employers, tax revenues, and consumers to pay the mounting bills.

Increasingly, the healthcare system is being held accountable for this lack of value. Whether through a more robust accreditation and regulatory environment, public reporting of quality and safety metrics, or pay for performance (or no pay for errors) initiatives, outside stakeholders are creating performance pressures that scarcely existed a decade ago.

Healthcare organizations and providers have begun to take notice and act, often by seeking answers from industries outside healthcare and thoughtfully importing these lessons into medicine. For example, the use of checklists has been adopted by healthcare (from aviation), with impressive results.3, 4 Many quality methods drawn from industry (Lean, Toyota, Six Sigma) have been used to try to improve performance and remove waste from complex processes.5, 6

While these efforts have been helpful, their focus has generally been at the point‐of‐careimproving the care of patients with acute myocardial infarction or decreasing readmissions. However, while the business community has long recognized that poor management and structure can thwart most efforts to improve individual processes, healthcare has paid relatively little attention to issues of organizational structure and leadership. The question arises: Could methods that have been used to learn from top‐performing businesses be helpful to healthcare's efforts to improve its own organizational performance?

In this article, we describe perhaps the best known effort to identify top‐performing corporations, compare them to carefully selected organizations that failed to achieve similar levels of performance, and glean lessons from these analyses. This effort, described in a book entitled Good to Great: Why Some Companies Make the Leapand Others Don't, has sold more than 3 million copies in its 35 languages, and is often cited by business leaders as a seminal work. We ask whether the methods of Good to Great might be applicable to healthcare organizations seeking to produce the kinds of value that patients and purchasers need and deserve.

GOOD TO GREAT METHODOLOGY

In 2001, business consultant Jim Collins published Good to Great. Its methods can be divided into 3 main components: (1) a gold standard metric to identify top organizations; (2) the creation of a control group of organizations that appeared similar to the top performers at the start of the study, but failed to match the successful organizations' performance over time; and (3) a detailed review of the methods, leadership, and structure of both the winning and laggard organizations, drawing lessons from their differences. Before discussing whether these methods could be used to analyze healthcare organizations, it is worth describing Collins' methods in more detail.

The first component of Good to Great's structure was the use of 4 metrics to identify top‐performing companies (Table 1). To select the good to great companies, Collins and his team began with a field of 1435 companies drawn from Fortune magazine's rankings of America's largest public companies. They then used the criteria in Table 1 to narrow the list to their final 11 companies, which formed the experimental group for the analysis.

After identifying these 11 top‐performing companies, Collins created a control group, composed of companies with similar attributes that could have made the transition, but failed to do so.7 To create the control group, Collins matched and scored a pool of control group candidates based on the following criteria: similarities of business model, size, age, and cumulative stock returns prior to the good to great transition. When there were several potential controls, Collins chose companies that were larger, more profitable, and had a stronger market position and reputation prior to the transition, in order to increase the probability that the experimental companies' successes were not incidental.8 Table 2 lists the paired experimental and control companies.

Finally, Collins performed a detailed historical analysis on the experimental and control groups, using materials (such as major articles published on the company, books, academic case studies, analyst reports, and financial and annual reports) that assessed the companies in real time. Good to Great relied on evidence from the period of interest (ie, accrued prior to the transition point) to avoid biases that would likely result from relying on retrospective sources of data.9

This analysis identified a series of factors that were generally present in good to great companies and absent in the control organizations. In brief, they were: building a culture of discipline, making change through gradual and consistent improvement, having a leader with a paradoxical blend of personal humility and professional will, and relentlessly focusing on hiring and nurturing the best employees. Over 6000 articles and 5 years of analysis support these conclusions.8

EFFORTS TO DATE TO ANALYZE HEALTHCARE ORGANIZATIONAL CHARACTERISTICS

We reviewed a convenience sample of the literature on organizational change in healthcare, and found only 1 study that utilized a similar methodology to that of Good to Great: an analysis of the academic medical centers that participate in the University HealthSystem Consortium (UHC). Drawing inspiration from Collins' methodologies, the UHC study developed a holistic measure of quality, based on safety, mortality, compliance with evidence‐based practices, and equity of care. Using these criteria, the investigators selected 3 UHC member organizations that were performing extremely well, and 3 others performing toward the middle and bottom of the pack. Experts on health system organization then conducted detailed site visits to these 6 academic medical centers. The researchers were blinded to these rankings at the time of the visits, but were able to perfectly predict which cohort the organizations were in.

The investigators analyzed the factors that seemed to be present in the top‐performing organizations, but were absent in the laggards, and found: hospital leadership emphasizing a patients‐first mission, an alignment of departmental objectives to reduce conflict, a concrete accountability structure for quality, a relentless focus on measurable improvement, and a culture promoting interprofessional collaboration on quality.10

While the UHC study is among the most robust exploration of healthcare organization dynamics in the literature, it has a few limitations. The first is that it studied a small, relatively specialized population: UHC members, which are large, mostly urban, well‐resourced teaching hospitals. While studying segments of populations can limit the generalizability of some of the UHC studies' findings, their approach can be a useful model to apply to studying other types of healthcare institutions. (And, to be fair, Good to Great also studies a specialized populationFortune 500 companiesand thus its lessons need to be extrapolated to other businesses, such as small companies, with a degree of caution.) The study also suffers from the relative paucity of publicly accessible organizational data in healthcare. The fact that the UHC investigators depended on both top‐performing and laggard hospitals, to voluntarily release their organizational data and permit a detailed site visit, potentially introduces a selection bias into the survey population, a bias not present in Good to Great due to Collins' protocol for matching cases and controls.

There have been several other efforts, using different methods, to determine organizational predictors of success in healthcare. The results of several important studies are shown in Table 3. Taken together, they indicate that higher performing organizations make practitioners accountable for performance measurements, and implement systems designed to both reduce errors and facilitate adherence to evidence‐based guidelines. In addition to these studies, several consulting organizations and foundations have performed focused reviews of high‐performing healthcare organizations in an effort to identify key success factors.11 These studies, while elucidating factors that influence organizational performance, suffer from variable quality measures and subjective methods for gathering organizational data, both of which are addressed within a good to great‐style analysis.12

Perhaps the best‐known study on healthcare organizational performance is The Dartmouth Atlas, an analysis that (though based on data accumulated over more than 30 years) has received tremendous public attention, in recent years, in the context of the debate over healthcare reform.13 However, by early 2010, the Dartmouth analysis was stirring controversy, with some observers expressing concerns over its focus on care toward the end of life, its methods for adjusting for case‐mix and sociodemographic predictors of outcomes and costs, and its exclusive use of Medicare data.14, 15 These limitations are also addressed by a good to great‐style analysis.

WOULD A GOOD TO GREAT ANALYSIS BE POSSIBLE IN HEALTHCARE?

While this review of prior research on organizational success factors in healthcare illustrates considerable interest in this area, none of the studies, to date, matches Good to Great in the robustness of the analysis or, obviously, its impact on the profession. Could a good to great analysis be carried out in healthcare? It is worth considering this by assessing each of Collins' 3 key steps: identifying the enterprises that made a good to great leap, selecting appropriate control organizations, and determining the factors that contributed to the successes of the former group.

Good to Great used an impressive elevation in stock price as a summary measure of organizational success. In the for‐profit business world, it is often assumed that Adam Smith's invisible hand makes corporate information available to investors, causing an organization's stock price to capture the overall success of its business strategy, including its product quality and operational efficiency.16 In the healthcare world, mostly populated by non‐profit organizations that are simultaneously working toward a bottom line and carrying out a social mission, there is no obvious equivalent to the stock price for measuring overall organizational performance and value. All of the methods for judging top hospitals, for example, are flaweda recent study found that the widely cited U.S. News & World Report's America's Best Hospitals list is largely driven by hospital reputation,17 while another study found glaring inconsistencies among methods used to calculate risk‐adjusted mortality rates.18 A generally accepted set of metrics defining the value of care produced by a healthcare organization (including quality, safety, access, patient satisfaction, and efficiency) would be needed to mirror the first good to great step: defining top‐performing organizations using a gold standard.19 The summary measure used in the UHC study is the closest we have seen to a good to great‐style summary performance measure in healthcare.10

While it is important to identify a gold‐standard measure of organizational quality, careful selection of a control organization may be the most important step in conducting a good to great analysis. Although Collins' use of stock price as a summary measure of organizational performance is the best measure available in business, it is by no means perfect. Despite this shortcoming, however, Collins believes that the central requirement is not finding a perfect measure of organizational success, but rather determining what correlates with a divergence of performance in stock price (J. Collins, oral communication, July 2010). Similar to clinical trials, meticulous matching of a good to great organization with a control has the advantage of canceling out extraneous environmental factors, thereby enabling the elucidation of organizational factors that contribute to divergent performance. Good to Great's methods depended on substantial historical background to define top performers and controls. Unfortunately, healthcare lacks an analog to the business world's robust historical and publicly accessible record of performance and organizational data. Therefore, even if a certain organization was determined to be a top performer based on a gold‐standard measure, selecting a control organization by matching its organizational and performance data to the top performer's would be unfeasible.

Finally, the lack of a historical record in healthcare also places substantial roadblocks in the way of looking under the organization's hood. Even in pioneering organizational analyses by Shortell et al.,20 Knaus et al.,21 and Jha et al.,22 substantial parts of their analyses relied on retrospective accounts to determine organizational characteristics. To remove the bias that comes from knowing the organization's ultimate performance, Collins was careful to base his analysis of organizational structures and leadership on documents available before the good to great transition. Equivalent data in healthcare are extremely difficult to find.

While it is best to rely on an historical record, it may be possible to carry out a good to great‐type analysis through meticulous structuring of personal interviews. Collins has endorsed a non‐healthcare study that utilized the good to great matching strategy but used personal interviews to make up for lack of access to a substantial historical record.23 To reduce the bias inherent in relying on interviews, the research team ensured that the good to great transition was sustained for many years, and that the practices elicited from the interviews started before the good to great transition. Both of these techniques helped increase the probability that the identified practices contributed to the transition to superior results (in this case, in public education outcomes) and, thus, that the adoption of these practices could result in improvements elsewhere (J. Collins, oral communication, July 2010).

To make such a study possible in healthcare, more organizational data are required. Without prodding by outside stakeholders, most healthcare organizations have been reluctant to publicize performance data for fear of malpractice risk,24 or based on their belief that current data paint an incomplete or inaccurate picture of their quality.25 Trends toward required reporting of quality data (such as via Medicare's Hospital Compare Web site) offer hope that future comparisons could rely on robust organizational quality and safety data. Instituting healthcare analogs to Securities & Exchange Commission (SEC) reporting mandates would further ameliorate this information deficit.26

While we believe that Good to Great offers lessons relevant to healthcare, there are limitations that are worth considering. First, the extraordinary complexity of healthcare organizations makes it likely that a matched‐pair‐type study would need to be accompanied by other types of analyses, including more quantitative analyses of large datasets, to give a full picture of structural and leadership predictors of strong performance. Moreover, before embracing the good to great method, some will undoubtedly point to the demise of Circuit City and Fannie Mae (2 of the Good to Great companies; Table 2) as a cautionary note. Collins addresses this issue with the commonsensical argument that the success of a company needs to be judged in the context of the era. By way of analogy, he points to the value of studying a sports team, such as the John Wooden‐coached UCLA teams of the 1960s and 1970s, notwithstanding the less stellar performance of today's UCLA team. In fact, Collins' recent book mines some of these failures for their important lessons.27

GOOD TO GREAT IN HEALTHCARE

Breaking through healthcare's myopia to explore solutions drawn from other industries, such as checklists, simulation, and industrial approaches to quality improvement, has yielded substantial insights and catalyzed major improvements in care. Similarly, we believe that finding ways to measure the performance of healthcare organizations on both cost and quality, to learn from those organizations achieving superior performance, and to create a policy and educational environment that rewards superior performance and helps poor performers improve, is a defining issue for healthcare. This will be particularly crucial as the policy environment changestransitions to Accountable Care Organizations28 and bundled payments29 are likely to increase the pressure on healthcare organizations to learn the secrets of their better‐performing brethren. These shifts are likely to put an even greater premium on the kinds of leadership, organizational structure, and ability to adapt to a changing environment that Collins highlighted in his analysis. After all, it is under the most challenging conditions that top organizations often prove their mettle.

Although there are considerable challenges in performing a good to great analysis in healthcare (Table 4), the overall point remains: Healthcare is likely to benefit from rigorous, unbiased methods to distinguish successful from less successful organizations, to learn the lessons of both, and to apply these lessons to improvement efforts.

Hospitalists are the fastest growing segment of physicians in the United States.1 Given the growing field of Pediatric Hospital Medicine (PHM) and the need to define strategic direction, the Society of Hospital Medicine (SHM), the American Academy of Pediatrics (AAP), and the Academic Pediatric Association (APA) sponsored a strategic planning meeting in February 2009 that brought together 22 PHM leaders to discuss the future of the field.

PHM is at a critical juncture in terms of clinical practice, research, workforce issues, and quality improvement. The field has developed sufficiently to produce leaders capable of setting an agenda and moving forward. A discussion with the American Board of Pediatrics (ABP) by PHM leaders from the AAP, APA, and SHM at the Pediatric Hospital Medicine 2007 Conference regarding subspecialty designation stimulated convening the PHM Strategic Planning Roundtable to address the task of coordinating further development of PHM (Table 1).

The objective of this article is to describe: (1) the Strategic Planning Roundtable's vision for the field of pediatric hospital medicine; (2) the generation and progress on specific initiatives in clinical practice, quality, research, and workforce identified by the Strategic Planning Roundtable; and (3) issues in the designation of PHM as a subspecialty.

METHODS

The PHM Strategic Planning Roundtable was conducted by a facilitator (S.M.) during a 2‐day retreat using established healthcare strategic planning methods.2

Participants were the existing PHM leaders from the AAP, APA, and SHM, as well as other national leaders in clinical practice, quality, research, and workforce. Development of the vision statement was a key step in which the participants developed a consensus‐based aspirational view of the future. The draft version of the vision statement was initially developed after extensive interviews with key stakeholders and experts in PHM, and was revised by the participants in the course of a facilitated group discussion during the retreat. Following creation of the vision statement, the group then defined the elements of transformation pertaining to PHM and detailed the components of the vision.

Analysis of internal and external environmental factors was critical in the strategic planning process. This type of analysis, detailing the current state of PHM practice, permitted the strategic planners to understand the gaps that existed between the aspirational vision statement and today's reality, and set the stage to identify and implement initiatives to achieve the vision. Several months before the meeting, 4 expert panels comprised of PHM specialists representing a variety of academic and clinical practice settings were brought together via e‐mail and conference calls to focus on 4 domains of PHM: clinical practice, quality of care, research, and workforce. These groups were asked to describe the current status, challenges, and opportunities in these areas. Combining literature review and key stakeholder interviews, their findings and recommendations were distilled into brief summaries that were presented at the Roundtable meeting. Following the presentations, the participants, working in small groups representing all areas of focus,provided additional feedback.

Following the creation of a consensus vision statement and review of internal and external factors, the participants worked to identify specific initiatives in the 4 domains that would advance the field towards the goals contained in the vision statement. These initiatives were grouped into categories. Initiatives by category were scored and prioritized according to predetermined criteria including potential impact, cost, operational complexity, and achievability.

For each initiative selected, the group developed targets and metrics that would be used to track progress. Assigning leadership, accountability, and a timeline to each of the selected projects completed the implementation plan. In addition, the group developed an organizational structure to provide oversight for the overall process, and designated individuals representing the sponsoring organizations into those roles. In conclusion, the group discussed potential structures to guide the future of PHM.

CLINICAL PRACTICE

The Roundtable defined clinical practice for PHM as the general medical care of the hospitalized child, including direct patient care and leadership of the inpatient service. Clinical practice is affected by a number of current national trends including: fewer primary care providers interested in, or with the time to provide, inpatient care; resident work hour restrictions; increasing complexity of clinical issues; and increasing availability of pediatric hospitalists. At the hospital level, clinical practice is affected by increasing need for quality and safety measures, electronic health records and computerized physician order entry, and mounting financial pressures on the hospital system. Hospitalists are assuming more roles in leading quality and safety initiatives, creating computerized systems that address children's needs, and creating financially viable systems of quality pediatric care.3 Hospitalists' clinical care and leadership roles are emerging, and therefore the field faces training and mentorship issues.

Progress to date in this area includes 2 textbooks that define a scope of knowledge and practice, and a newly developed journal in PHM. Core competencies in PHM have been published and provide further refinement of scope and a template for future training.4

Multiple opportunities exist for hospitalists to establish themselves as clinical leaders. Hospitalists can become the preferred providers for hospitalized chronically ill children, with specific initiatives to improve care coordination and multidisciplinary communication. In addition to care coordination and decreasing length of stay, hospitalists, with their intimate knowledge of hospital operations, can be leaders in hospital capacity management and patient flow to increase operational efficiency. Hospitalists can expand evidence‐based guidelines for, and data about, inpatient conditions, and explore the effect of workload and hours on patient care. In addition, there is an expanding role into administrative areas, as well as alternate care arenas, such as: intensive care support (pediatric and neonatal), transport, sedation, palliative care, and pain management. Activities in administrative and alternate care areas have profound direct affects on patient care, as well as providing value added services and additional revenue streams which can further support clinical needs. Finally, achieving quality targets will likely be increasingly linked to payment, so hospitalists may play a key role in the incentives paid to their hospitals. Meeting these challenges will further solidify the standing of hospitalists in the clinical realm.

QUALITY

National and governmental agencies have influenced quality and performance improvement measurements in adult healthcare, resulting in improvements in adult healthcare quality measurement.5 There is limited similar influence or measure development in pediatric medicine, so the quality chasm between adult and child healthcare has widened. Few resources are invested in improving quality and safety of pediatric inpatient care. Of the 18 private health insurance plans' quality and pay for performance programs identified by Leapfrog, only 17% developed pediatric‐specific inpatient measures.6 Only 5 of 40 controlled trials of quality improvement efforts for children published between 1980 and 1998 addressed inpatient problems.7

There have been recent efforts at the national level addressing these issues, highlighted by the introduction of The Children's Health Care Quality Act, in 2007. Early studies in PHM systems focused on overall operational efficiency, documenting 9% to 16% decreases in length of stay and cost compared to traditional models of care.8 Conway et al. identified higher reported adherence to evidence‐based care for hospitalists compared to community pediatricians.9 However, Landrigan et al. demonstrated that there is still large variation in care that exists in the management of common inpatient diagnoses, lacking strong evidence‐based guidelines even among pediatric hospitalists.10 Moreover, there have been no significant studies reviewing the impact of pediatric hospitalists on safety of inpatient care. Magnifying these challenges is the reality that our healthcare system is fragmented with various entities scrambling to define, measure, and compare the effectiveness and safety of pediatric healthcare.

These challenges create an opportunity for PHM to develop a model of how to deliver the highest quality and safest care to our patients. The solution is complex and will take cooperation at many levels of our healthcare system. Improving the safety and quality of care for children in all settings of inpatient care in the United States may best be accomplished via an effective collaborative. This collaborative should be comprehensive and inclusive, and focused on demonstrating and disseminating how standardized, evidence‐based care in both clinical and safety domains can lead to high‐value and high‐quality outcomes. The success of PHM will be measured by its ability to deliver a clear value proposition to all consumers and payers of healthcare. The creation of a robust national collaborative network is a first step towards meeting this goal and will take an extraordinary effort. A PHM Quality Improvement (QI) Collaborative workgroup was created in August 2009. Three collaboratives have been commissioned: (1) Reduction of patient identification errors; (2) Improving discharge communication to referring primary care providers for pediatric hospitalist programs, and (3) Reducing the misuse and overuse of bronchodilators for bronchiolitis. All the collaborative groups have effectively engaged key groups of stakeholders and utilized standard QI tools, demonstrating improvement by the fall of 2010 (unpublished data, S.N.).

RESEARCH

Despite being a relatively young field, there is a critical mass of pediatric hospitalist‐investigators who are establishing research career paths for themselves by securing external grant funding for their work, publishing, and receiving mentorship from largely non‐hospitalist mentors. Some hospitalists are now in a position to mentor junior investigators. These hospitalist‐investigators identified a collective goal of working together across multiple sites in a clinical research network. The goal is to conduct high‐quality studies and provide the necessary clinical information to allow practicing hospitalists to make better decisions regarding patient care. This new inpatient evidence‐base will have the added advantage of helping further define the field of PHM.

The Pediatric Research in Inpatient Settings Network (PRIS) was identified as the vehicle to accomplish these goals. A series of objectives were identified to redesign PRIS in order to accommodate and organize this new influx of hospitalist‐investigators. These objectives included having hospitalist‐investigators commit their time to the prioritization, design, and execution of multicenter studies, drafting new governance documents for PRIS, securing external funding, redefining the relationships of the 3 existing organizations that formed PRIS (AAP, APA, SHM), defining how new clinical sites could be added to PRIS, creating a pipeline for junior hospitalist‐investigators to transition to leadership roles, securing a data coordinating center with established expertise in conducting multicenter studies, and establishing an external research advisory committee of leaders in pediatric clinical research and QI.

Several critical issues were identified, but funding remained a priority for the sustainability of PRIS. Comparative effectiveness (CE) was recognized as a potential important source of future funding. Pediatric studies on CE (eg, surgery vs medical management) conducted by PRIS would provide important new data to allow hospitalists to practice evidence‐based medicine and to improve quality.

A Research Leadership Task Force was created with 4 members of the PHM Strategic Planning Roundtable to work on the identified issues. The APA leadership worked with PRIS to establish a new Executive Council (comprised of additional qualified hospitalist‐investigators). The Executive Council was charged with accomplishing the tasks outlined from the Strategic Planning Roundtable. They have created the governance documents and standard operating procedures necessary for PRIS to conduct multicenter studies, defined a strategic framework for PRIS including the mission, vision and values, and funding strategy. In February 2010, PRIS received a 3‐year award for over $1 million from the Child Health Corporation of America to both fund the infrastructure of PRIS and to conduct a Prioritization Project. The Prioritization Project seeks to identify the conditions that are costly, prevalent, and demonstrate high inter‐hospital variation in resource utilization, which signals either lack of high‐quality data upon which to base medical decisions, and/or an opportunity to standardize care across hospitals. Some of these conditions will warrant further investigation to define the evidence base, whereas other conditions may require implementation studies to reliably introduce evidence into practice. Members of the Executive Council received additional funding to investigate community settings, as most children are hospitalized outside of large children's hospitals. PRIS also reengaged all 3 societies (APA, AAP, and SHM) for support for the first face‐to‐face meeting of the Executive Council. PRIS applied for 2 Recovery Act stimulus grants, and received funding for both of approximately $12 million. The processes used to design, provide feedback, and shepherd these initial studies formed the basis for the standard operating procedures for the Network. PRIS is now reengaging its membership to establish how sites may be able to conduct research, and receive new ideas to be considered for study in PRIS.

Although much work remains to be done, the Executive Council is continuing the charge with quarterly face‐to‐face meetings, hiring of a full‐time PRIS Coordinator, and carrying out these initial projects, while maintaining the goal of meeting the needs of the membership and PHM. If PRIS is to accomplish its mission of improving the health of, and healthcare delivery to, hospitalized children and their families, then the types of studies undertaken will include not only original research questions, but also comparative implementation methods to better understand how hospitalists in a variety of settings can best translate research findings into clinical practice and ultimately improve patient outcomes.

WORKFORCE

The current number of pediatric hospitalists is difficult to gauge11; estimates range from 1500 to 3000 physicians. There are groups of pediatric hospitalists within several national organizations including the AAP, APA, and SHM, in addition to a very active listserve community. It is likely that only a portion of pediatric hospitalists are represented by membership in these organizations.

Most physicians entering the field of PHM come directly out of residency. A recent survey by Freed et al.12 reported that 3% of current pediatric residents are interested in PHM as a career. In another survey by Freed et al., about 6% of recent pediatric residency graduates reported currently practicing as pediatric hospitalists.13 This difference may indicate a number of pediatricians practicing transiently as pediatric hospitalists.

There are numerous issues that will affect the growth and sustainability of PHM. A large number of pediatric residents entering the field will be needed to maintain current numbers. With 45% of hospitalists in practice less than 3 years,11 the growth of PHM in both numbers and influence will require an increasing number of hospitalists with sustained careers in the field. Recognition as experts in inpatient care, as well as expansion of the role of hospitalists beyond the clinical realm to education, research, and hospital leadership, will foster long‐term career satisfaction. The increasingly common stature of hospital medicine as an independent division, equivalent to general pediatrics and subspecialty divisions within a department, may further bolster the perception of hospital medicine as a career.

The majority of pediatric hospitalists believe that current pediatric residency training does not provide all of the skills necessary to practice as a pediatric hospitalist,14 though there is disagreement regarding how additional training in pediatric hospital medicine should be achieved: a dedicated fellowship versus continuing medical education (CME). There are several initiatives with the potential to transform the way pediatric hospitalists are trained and certified. The Residency Review and Redesign Project indicates that pediatric residency is likely to be reformed to better meet the training demands of the individual resident's chosen career path. Changing residency to better prepare pediatric residents to take positions in pediatric hospital medicine will certainly affect the workforce emerging from residency programs and their subsequent training needs.15 The American Board of Internal Medicine and the American Board of Family Medicine have approved a Recognition of Focused Practice in Hospital Medicine. This recognition is gained through the Maintenance of Certification (MOC) Program of the respective boards after a minimum of 3 years of practice. SHM is offering fellow recognition in tiered designations of Fellow of Hospital Medicine (FHM), Senior Fellow of Hospital Medicine, and Master of Hospital Medicine. Five hundred hospitalists, including many pediatric hospitalists, received the inaugural FHM designation in 2009. Organizational recognition is a common process in many other medical fields, although previously limited in pediatrics to Fellow of the AAP. FHM is an important step, but cannot substitute for specific training and certification.

Academic fellowships in PHM will aid in the training of hospitalists with scholarly skills and will help produce more pediatric hospitalists with clinical, quality, administrative, and leadership skills. A model of subspecialty fellowship training and certification of all PHM physicians would require a several‐fold increase in available fellowships, currently approximately 15.

Ongoing CME offerings are also critical to sustaining and developing the workforce. The annual national meetings of the APA, AAP, and SHM all offer PHM‐dedicated content, and there is an annual PHM conference sponsored by these 3 organizations. There are now multiple additional national and regional meetings focused on PHM, reflecting the growing audience for PHM CME content. The AAP offers a PHM study guide and an Education in quality improvement for pediatric practice (eQIPP) module on inpatient asthma, specifically designed to facilitate the MOC process for pediatric hospitalists.

Some form of ABP recognition may be necessary to provide the status for PHM to be widely recognized as a viable academic career in the larger pediatric community. This would entail standardized fellowships that will ensure graduates have demonstrated proficiency in the core competencies. PHM leaders have engaged the ABP to better understand the subspecialty approval process and thoughtfully examine the ramifications of subspecialty status, specifically what subspecialty certification would mean for PHM providers and hospitals. Achieving ABP certification may create a new standard of care meaning that noncertified PHM providers will be at a disadvantage. It is unknown what the impact on pediatric inpatient care would be if a PHM standard was set without the supply of practitioners to provide that care.

STRUCTURE

The efforts of the Roundtable demonstrate the potential effectiveness of the current structure that guides the field: that of the cooperative interchange between the PHM leaders within the APA, AAP, and SHM. It may be that, similar to Pediatric Emergency Medicine (PEM), no formal, unifying structure is necessary. Alternatively, both Adolescent Medicine and Behavioral and Developmental Pediatrics (BDP) have their own organizations that guide their respective fields. A hybrid model is that of Pediatric Cardiology which has the Joint Council on Congenital Heart Disease. This structure assures that the leaders of the various organizations concerned with congenital heart disease meet at least annually to report on their activities and coordinate future efforts. Its makeup is similar to how the planning committee of the annual national PHM conference is constructed. Although PHM has largely succeeded with the current organizational structure, it is possible that a more formal structure is needed to continue forward.

CONCLUSION

The Roundtable members developed the following vision for PHM: Pediatric hospitalists will transform the delivery of hospital care for children. This will be done by achieving 7 goals (Table 2).

Attaining this vision will take tremendous dedication, effort, and collaboration. As a starting point, the following initiatives were proposed and implemented as noted:

Hospitalists are the fastest growing segment of physicians in the United States.1 Given the growing field of Pediatric Hospital Medicine (PHM) and the need to define strategic direction, the Society of Hospital Medicine (SHM), the American Academy of Pediatrics (AAP), and the Academic Pediatric Association (APA) sponsored a strategic planning meeting in February 2009 that brought together 22 PHM leaders to discuss the future of the field.

PHM is at a critical juncture in terms of clinical practice, research, workforce issues, and quality improvement. The field has developed sufficiently to produce leaders capable of setting an agenda and moving forward. A discussion with the American Board of Pediatrics (ABP) by PHM leaders from the AAP, APA, and SHM at the Pediatric Hospital Medicine 2007 Conference regarding subspecialty designation stimulated convening the PHM Strategic Planning Roundtable to address the task of coordinating further development of PHM (Table 1).

The objective of this article is to describe: (1) the Strategic Planning Roundtable's vision for the field of pediatric hospital medicine; (2) the generation and progress on specific initiatives in clinical practice, quality, research, and workforce identified by the Strategic Planning Roundtable; and (3) issues in the designation of PHM as a subspecialty.

METHODS

The PHM Strategic Planning Roundtable was conducted by a facilitator (S.M.) during a 2‐day retreat using established healthcare strategic planning methods.2

Participants were the existing PHM leaders from the AAP, APA, and SHM, as well as other national leaders in clinical practice, quality, research, and workforce. Development of the vision statement was a key step in which the participants developed a consensus‐based aspirational view of the future. The draft version of the vision statement was initially developed after extensive interviews with key stakeholders and experts in PHM, and was revised by the participants in the course of a facilitated group discussion during the retreat. Following creation of the vision statement, the group then defined the elements of transformation pertaining to PHM and detailed the components of the vision.

Analysis of internal and external environmental factors was critical in the strategic planning process. This type of analysis, detailing the current state of PHM practice, permitted the strategic planners to understand the gaps that existed between the aspirational vision statement and today's reality, and set the stage to identify and implement initiatives to achieve the vision. Several months before the meeting, 4 expert panels comprised of PHM specialists representing a variety of academic and clinical practice settings were brought together via e‐mail and conference calls to focus on 4 domains of PHM: clinical practice, quality of care, research, and workforce. These groups were asked to describe the current status, challenges, and opportunities in these areas. Combining literature review and key stakeholder interviews, their findings and recommendations were distilled into brief summaries that were presented at the Roundtable meeting. Following the presentations, the participants, working in small groups representing all areas of focus,provided additional feedback.

Following the creation of a consensus vision statement and review of internal and external factors, the participants worked to identify specific initiatives in the 4 domains that would advance the field towards the goals contained in the vision statement. These initiatives were grouped into categories. Initiatives by category were scored and prioritized according to predetermined criteria including potential impact, cost, operational complexity, and achievability.

For each initiative selected, the group developed targets and metrics that would be used to track progress. Assigning leadership, accountability, and a timeline to each of the selected projects completed the implementation plan. In addition, the group developed an organizational structure to provide oversight for the overall process, and designated individuals representing the sponsoring organizations into those roles. In conclusion, the group discussed potential structures to guide the future of PHM.

CLINICAL PRACTICE

The Roundtable defined clinical practice for PHM as the general medical care of the hospitalized child, including direct patient care and leadership of the inpatient service. Clinical practice is affected by a number of current national trends including: fewer primary care providers interested in, or with the time to provide, inpatient care; resident work hour restrictions; increasing complexity of clinical issues; and increasing availability of pediatric hospitalists. At the hospital level, clinical practice is affected by increasing need for quality and safety measures, electronic health records and computerized physician order entry, and mounting financial pressures on the hospital system. Hospitalists are assuming more roles in leading quality and safety initiatives, creating computerized systems that address children's needs, and creating financially viable systems of quality pediatric care.3 Hospitalists' clinical care and leadership roles are emerging, and therefore the field faces training and mentorship issues.

Progress to date in this area includes 2 textbooks that define a scope of knowledge and practice, and a newly developed journal in PHM. Core competencies in PHM have been published and provide further refinement of scope and a template for future training.4

Multiple opportunities exist for hospitalists to establish themselves as clinical leaders. Hospitalists can become the preferred providers for hospitalized chronically ill children, with specific initiatives to improve care coordination and multidisciplinary communication. In addition to care coordination and decreasing length of stay, hospitalists, with their intimate knowledge of hospital operations, can be leaders in hospital capacity management and patient flow to increase operational efficiency. Hospitalists can expand evidence‐based guidelines for, and data about, inpatient conditions, and explore the effect of workload and hours on patient care. In addition, there is an expanding role into administrative areas, as well as alternate care arenas, such as: intensive care support (pediatric and neonatal), transport, sedation, palliative care, and pain management. Activities in administrative and alternate care areas have profound direct affects on patient care, as well as providing value added services and additional revenue streams which can further support clinical needs. Finally, achieving quality targets will likely be increasingly linked to payment, so hospitalists may play a key role in the incentives paid to their hospitals. Meeting these challenges will further solidify the standing of hospitalists in the clinical realm.

QUALITY

National and governmental agencies have influenced quality and performance improvement measurements in adult healthcare, resulting in improvements in adult healthcare quality measurement.5 There is limited similar influence or measure development in pediatric medicine, so the quality chasm between adult and child healthcare has widened. Few resources are invested in improving quality and safety of pediatric inpatient care. Of the 18 private health insurance plans' quality and pay for performance programs identified by Leapfrog, only 17% developed pediatric‐specific inpatient measures.6 Only 5 of 40 controlled trials of quality improvement efforts for children published between 1980 and 1998 addressed inpatient problems.7

There have been recent efforts at the national level addressing these issues, highlighted by the introduction of The Children's Health Care Quality Act, in 2007. Early studies in PHM systems focused on overall operational efficiency, documenting 9% to 16% decreases in length of stay and cost compared to traditional models of care.8 Conway et al. identified higher reported adherence to evidence‐based care for hospitalists compared to community pediatricians.9 However, Landrigan et al. demonstrated that there is still large variation in care that exists in the management of common inpatient diagnoses, lacking strong evidence‐based guidelines even among pediatric hospitalists.10 Moreover, there have been no significant studies reviewing the impact of pediatric hospitalists on safety of inpatient care. Magnifying these challenges is the reality that our healthcare system is fragmented with various entities scrambling to define, measure, and compare the effectiveness and safety of pediatric healthcare.

These challenges create an opportunity for PHM to develop a model of how to deliver the highest quality and safest care to our patients. The solution is complex and will take cooperation at many levels of our healthcare system. Improving the safety and quality of care for children in all settings of inpatient care in the United States may best be accomplished via an effective collaborative. This collaborative should be comprehensive and inclusive, and focused on demonstrating and disseminating how standardized, evidence‐based care in both clinical and safety domains can lead to high‐value and high‐quality outcomes. The success of PHM will be measured by its ability to deliver a clear value proposition to all consumers and payers of healthcare. The creation of a robust national collaborative network is a first step towards meeting this goal and will take an extraordinary effort. A PHM Quality Improvement (QI) Collaborative workgroup was created in August 2009. Three collaboratives have been commissioned: (1) Reduction of patient identification errors; (2) Improving discharge communication to referring primary care providers for pediatric hospitalist programs, and (3) Reducing the misuse and overuse of bronchodilators for bronchiolitis. All the collaborative groups have effectively engaged key groups of stakeholders and utilized standard QI tools, demonstrating improvement by the fall of 2010 (unpublished data, S.N.).

RESEARCH

Despite being a relatively young field, there is a critical mass of pediatric hospitalist‐investigators who are establishing research career paths for themselves by securing external grant funding for their work, publishing, and receiving mentorship from largely non‐hospitalist mentors. Some hospitalists are now in a position to mentor junior investigators. These hospitalist‐investigators identified a collective goal of working together across multiple sites in a clinical research network. The goal is to conduct high‐quality studies and provide the necessary clinical information to allow practicing hospitalists to make better decisions regarding patient care. This new inpatient evidence‐base will have the added advantage of helping further define the field of PHM.

The Pediatric Research in Inpatient Settings Network (PRIS) was identified as the vehicle to accomplish these goals. A series of objectives were identified to redesign PRIS in order to accommodate and organize this new influx of hospitalist‐investigators. These objectives included having hospitalist‐investigators commit their time to the prioritization, design, and execution of multicenter studies, drafting new governance documents for PRIS, securing external funding, redefining the relationships of the 3 existing organizations that formed PRIS (AAP, APA, SHM), defining how new clinical sites could be added to PRIS, creating a pipeline for junior hospitalist‐investigators to transition to leadership roles, securing a data coordinating center with established expertise in conducting multicenter studies, and establishing an external research advisory committee of leaders in pediatric clinical research and QI.

Several critical issues were identified, but funding remained a priority for the sustainability of PRIS. Comparative effectiveness (CE) was recognized as a potential important source of future funding. Pediatric studies on CE (eg, surgery vs medical management) conducted by PRIS would provide important new data to allow hospitalists to practice evidence‐based medicine and to improve quality.

A Research Leadership Task Force was created with 4 members of the PHM Strategic Planning Roundtable to work on the identified issues. The APA leadership worked with PRIS to establish a new Executive Council (comprised of additional qualified hospitalist‐investigators). The Executive Council was charged with accomplishing the tasks outlined from the Strategic Planning Roundtable. They have created the governance documents and standard operating procedures necessary for PRIS to conduct multicenter studies, defined a strategic framework for PRIS including the mission, vision and values, and funding strategy. In February 2010, PRIS received a 3‐year award for over $1 million from the Child Health Corporation of America to both fund the infrastructure of PRIS and to conduct a Prioritization Project. The Prioritization Project seeks to identify the conditions that are costly, prevalent, and demonstrate high inter‐hospital variation in resource utilization, which signals either lack of high‐quality data upon which to base medical decisions, and/or an opportunity to standardize care across hospitals. Some of these conditions will warrant further investigation to define the evidence base, whereas other conditions may require implementation studies to reliably introduce evidence into practice. Members of the Executive Council received additional funding to investigate community settings, as most children are hospitalized outside of large children's hospitals. PRIS also reengaged all 3 societies (APA, AAP, and SHM) for support for the first face‐to‐face meeting of the Executive Council. PRIS applied for 2 Recovery Act stimulus grants, and received funding for both of approximately $12 million. The processes used to design, provide feedback, and shepherd these initial studies formed the basis for the standard operating procedures for the Network. PRIS is now reengaging its membership to establish how sites may be able to conduct research, and receive new ideas to be considered for study in PRIS.

Although much work remains to be done, the Executive Council is continuing the charge with quarterly face‐to‐face meetings, hiring of a full‐time PRIS Coordinator, and carrying out these initial projects, while maintaining the goal of meeting the needs of the membership and PHM. If PRIS is to accomplish its mission of improving the health of, and healthcare delivery to, hospitalized children and their families, then the types of studies undertaken will include not only original research questions, but also comparative implementation methods to better understand how hospitalists in a variety of settings can best translate research findings into clinical practice and ultimately improve patient outcomes.

WORKFORCE

The current number of pediatric hospitalists is difficult to gauge11; estimates range from 1500 to 3000 physicians. There are groups of pediatric hospitalists within several national organizations including the AAP, APA, and SHM, in addition to a very active listserve community. It is likely that only a portion of pediatric hospitalists are represented by membership in these organizations.

Most physicians entering the field of PHM come directly out of residency. A recent survey by Freed et al.12 reported that 3% of current pediatric residents are interested in PHM as a career. In another survey by Freed et al., about 6% of recent pediatric residency graduates reported currently practicing as pediatric hospitalists.13 This difference may indicate a number of pediatricians practicing transiently as pediatric hospitalists.

There are numerous issues that will affect the growth and sustainability of PHM. A large number of pediatric residents entering the field will be needed to maintain current numbers. With 45% of hospitalists in practice less than 3 years,11 the growth of PHM in both numbers and influence will require an increasing number of hospitalists with sustained careers in the field. Recognition as experts in inpatient care, as well as expansion of the role of hospitalists beyond the clinical realm to education, research, and hospital leadership, will foster long‐term career satisfaction. The increasingly common stature of hospital medicine as an independent division, equivalent to general pediatrics and subspecialty divisions within a department, may further bolster the perception of hospital medicine as a career.

The majority of pediatric hospitalists believe that current pediatric residency training does not provide all of the skills necessary to practice as a pediatric hospitalist,14 though there is disagreement regarding how additional training in pediatric hospital medicine should be achieved: a dedicated fellowship versus continuing medical education (CME). There are several initiatives with the potential to transform the way pediatric hospitalists are trained and certified. The Residency Review and Redesign Project indicates that pediatric residency is likely to be reformed to better meet the training demands of the individual resident's chosen career path. Changing residency to better prepare pediatric residents to take positions in pediatric hospital medicine will certainly affect the workforce emerging from residency programs and their subsequent training needs.15 The American Board of Internal Medicine and the American Board of Family Medicine have approved a Recognition of Focused Practice in Hospital Medicine. This recognition is gained through the Maintenance of Certification (MOC) Program of the respective boards after a minimum of 3 years of practice. SHM is offering fellow recognition in tiered designations of Fellow of Hospital Medicine (FHM), Senior Fellow of Hospital Medicine, and Master of Hospital Medicine. Five hundred hospitalists, including many pediatric hospitalists, received the inaugural FHM designation in 2009. Organizational recognition is a common process in many other medical fields, although previously limited in pediatrics to Fellow of the AAP. FHM is an important step, but cannot substitute for specific training and certification.

Academic fellowships in PHM will aid in the training of hospitalists with scholarly skills and will help produce more pediatric hospitalists with clinical, quality, administrative, and leadership skills. A model of subspecialty fellowship training and certification of all PHM physicians would require a several‐fold increase in available fellowships, currently approximately 15.

Ongoing CME offerings are also critical to sustaining and developing the workforce. The annual national meetings of the APA, AAP, and SHM all offer PHM‐dedicated content, and there is an annual PHM conference sponsored by these 3 organizations. There are now multiple additional national and regional meetings focused on PHM, reflecting the growing audience for PHM CME content. The AAP offers a PHM study guide and an Education in quality improvement for pediatric practice (eQIPP) module on inpatient asthma, specifically designed to facilitate the MOC process for pediatric hospitalists.

Some form of ABP recognition may be necessary to provide the status for PHM to be widely recognized as a viable academic career in the larger pediatric community. This would entail standardized fellowships that will ensure graduates have demonstrated proficiency in the core competencies. PHM leaders have engaged the ABP to better understand the subspecialty approval process and thoughtfully examine the ramifications of subspecialty status, specifically what subspecialty certification would mean for PHM providers and hospitals. Achieving ABP certification may create a new standard of care meaning that noncertified PHM providers will be at a disadvantage. It is unknown what the impact on pediatric inpatient care would be if a PHM standard was set without the supply of practitioners to provide that care.

STRUCTURE

The efforts of the Roundtable demonstrate the potential effectiveness of the current structure that guides the field: that of the cooperative interchange between the PHM leaders within the APA, AAP, and SHM. It may be that, similar to Pediatric Emergency Medicine (PEM), no formal, unifying structure is necessary. Alternatively, both Adolescent Medicine and Behavioral and Developmental Pediatrics (BDP) have their own organizations that guide their respective fields. A hybrid model is that of Pediatric Cardiology which has the Joint Council on Congenital Heart Disease. This structure assures that the leaders of the various organizations concerned with congenital heart disease meet at least annually to report on their activities and coordinate future efforts. Its makeup is similar to how the planning committee of the annual national PHM conference is constructed. Although PHM has largely succeeded with the current organizational structure, it is possible that a more formal structure is needed to continue forward.

CONCLUSION

The Roundtable members developed the following vision for PHM: Pediatric hospitalists will transform the delivery of hospital care for children. This will be done by achieving 7 goals (Table 2).

Attaining this vision will take tremendous dedication, effort, and collaboration. As a starting point, the following initiatives were proposed and implemented as noted:

Hospitalists are the fastest growing segment of physicians in the United States.1 Given the growing field of Pediatric Hospital Medicine (PHM) and the need to define strategic direction, the Society of Hospital Medicine (SHM), the American Academy of Pediatrics (AAP), and the Academic Pediatric Association (APA) sponsored a strategic planning meeting in February 2009 that brought together 22 PHM leaders to discuss the future of the field.

PHM is at a critical juncture in terms of clinical practice, research, workforce issues, and quality improvement. The field has developed sufficiently to produce leaders capable of setting an agenda and moving forward. A discussion with the American Board of Pediatrics (ABP) by PHM leaders from the AAP, APA, and SHM at the Pediatric Hospital Medicine 2007 Conference regarding subspecialty designation stimulated convening the PHM Strategic Planning Roundtable to address the task of coordinating further development of PHM (Table 1).

The objective of this article is to describe: (1) the Strategic Planning Roundtable's vision for the field of pediatric hospital medicine; (2) the generation and progress on specific initiatives in clinical practice, quality, research, and workforce identified by the Strategic Planning Roundtable; and (3) issues in the designation of PHM as a subspecialty.

METHODS

The PHM Strategic Planning Roundtable was conducted by a facilitator (S.M.) during a 2‐day retreat using established healthcare strategic planning methods.2

Participants were the existing PHM leaders from the AAP, APA, and SHM, as well as other national leaders in clinical practice, quality, research, and workforce. Development of the vision statement was a key step in which the participants developed a consensus‐based aspirational view of the future. The draft version of the vision statement was initially developed after extensive interviews with key stakeholders and experts in PHM, and was revised by the participants in the course of a facilitated group discussion during the retreat. Following creation of the vision statement, the group then defined the elements of transformation pertaining to PHM and detailed the components of the vision.

Analysis of internal and external environmental factors was critical in the strategic planning process. This type of analysis, detailing the current state of PHM practice, permitted the strategic planners to understand the gaps that existed between the aspirational vision statement and today's reality, and set the stage to identify and implement initiatives to achieve the vision. Several months before the meeting, 4 expert panels comprised of PHM specialists representing a variety of academic and clinical practice settings were brought together via e‐mail and conference calls to focus on 4 domains of PHM: clinical practice, quality of care, research, and workforce. These groups were asked to describe the current status, challenges, and opportunities in these areas. Combining literature review and key stakeholder interviews, their findings and recommendations were distilled into brief summaries that were presented at the Roundtable meeting. Following the presentations, the participants, working in small groups representing all areas of focus,provided additional feedback.

Following the creation of a consensus vision statement and review of internal and external factors, the participants worked to identify specific initiatives in the 4 domains that would advance the field towards the goals contained in the vision statement. These initiatives were grouped into categories. Initiatives by category were scored and prioritized according to predetermined criteria including potential impact, cost, operational complexity, and achievability.

For each initiative selected, the group developed targets and metrics that would be used to track progress. Assigning leadership, accountability, and a timeline to each of the selected projects completed the implementation plan. In addition, the group developed an organizational structure to provide oversight for the overall process, and designated individuals representing the sponsoring organizations into those roles. In conclusion, the group discussed potential structures to guide the future of PHM.

CLINICAL PRACTICE

The Roundtable defined clinical practice for PHM as the general medical care of the hospitalized child, including direct patient care and leadership of the inpatient service. Clinical practice is affected by a number of current national trends including: fewer primary care providers interested in, or with the time to provide, inpatient care; resident work hour restrictions; increasing complexity of clinical issues; and increasing availability of pediatric hospitalists. At the hospital level, clinical practice is affected by increasing need for quality and safety measures, electronic health records and computerized physician order entry, and mounting financial pressures on the hospital system. Hospitalists are assuming more roles in leading quality and safety initiatives, creating computerized systems that address children's needs, and creating financially viable systems of quality pediatric care.3 Hospitalists' clinical care and leadership roles are emerging, and therefore the field faces training and mentorship issues.

Progress to date in this area includes 2 textbooks that define a scope of knowledge and practice, and a newly developed journal in PHM. Core competencies in PHM have been published and provide further refinement of scope and a template for future training.4

Multiple opportunities exist for hospitalists to establish themselves as clinical leaders. Hospitalists can become the preferred providers for hospitalized chronically ill children, with specific initiatives to improve care coordination and multidisciplinary communication. In addition to care coordination and decreasing length of stay, hospitalists, with their intimate knowledge of hospital operations, can be leaders in hospital capacity management and patient flow to increase operational efficiency. Hospitalists can expand evidence‐based guidelines for, and data about, inpatient conditions, and explore the effect of workload and hours on patient care. In addition, there is an expanding role into administrative areas, as well as alternate care arenas, such as: intensive care support (pediatric and neonatal), transport, sedation, palliative care, and pain management. Activities in administrative and alternate care areas have profound direct affects on patient care, as well as providing value added services and additional revenue streams which can further support clinical needs. Finally, achieving quality targets will likely be increasingly linked to payment, so hospitalists may play a key role in the incentives paid to their hospitals. Meeting these challenges will further solidify the standing of hospitalists in the clinical realm.

QUALITY

National and governmental agencies have influenced quality and performance improvement measurements in adult healthcare, resulting in improvements in adult healthcare quality measurement.5 There is limited similar influence or measure development in pediatric medicine, so the quality chasm between adult and child healthcare has widened. Few resources are invested in improving quality and safety of pediatric inpatient care. Of the 18 private health insurance plans' quality and pay for performance programs identified by Leapfrog, only 17% developed pediatric‐specific inpatient measures.6 Only 5 of 40 controlled trials of quality improvement efforts for children published between 1980 and 1998 addressed inpatient problems.7

There have been recent efforts at the national level addressing these issues, highlighted by the introduction of The Children's Health Care Quality Act, in 2007. Early studies in PHM systems focused on overall operational efficiency, documenting 9% to 16% decreases in length of stay and cost compared to traditional models of care.8 Conway et al. identified higher reported adherence to evidence‐based care for hospitalists compared to community pediatricians.9 However, Landrigan et al. demonstrated that there is still large variation in care that exists in the management of common inpatient diagnoses, lacking strong evidence‐based guidelines even among pediatric hospitalists.10 Moreover, there have been no significant studies reviewing the impact of pediatric hospitalists on safety of inpatient care. Magnifying these challenges is the reality that our healthcare system is fragmented with various entities scrambling to define, measure, and compare the effectiveness and safety of pediatric healthcare.

These challenges create an opportunity for PHM to develop a model of how to deliver the highest quality and safest care to our patients. The solution is complex and will take cooperation at many levels of our healthcare system. Improving the safety and quality of care for children in all settings of inpatient care in the United States may best be accomplished via an effective collaborative. This collaborative should be comprehensive and inclusive, and focused on demonstrating and disseminating how standardized, evidence‐based care in both clinical and safety domains can lead to high‐value and high‐quality outcomes. The success of PHM will be measured by its ability to deliver a clear value proposition to all consumers and payers of healthcare. The creation of a robust national collaborative network is a first step towards meeting this goal and will take an extraordinary effort. A PHM Quality Improvement (QI) Collaborative workgroup was created in August 2009. Three collaboratives have been commissioned: (1) Reduction of patient identification errors; (2) Improving discharge communication to referring primary care providers for pediatric hospitalist programs, and (3) Reducing the misuse and overuse of bronchodilators for bronchiolitis. All the collaborative groups have effectively engaged key groups of stakeholders and utilized standard QI tools, demonstrating improvement by the fall of 2010 (unpublished data, S.N.).

RESEARCH

Despite being a relatively young field, there is a critical mass of pediatric hospitalist‐investigators who are establishing research career paths for themselves by securing external grant funding for their work, publishing, and receiving mentorship from largely non‐hospitalist mentors. Some hospitalists are now in a position to mentor junior investigators. These hospitalist‐investigators identified a collective goal of working together across multiple sites in a clinical research network. The goal is to conduct high‐quality studies and provide the necessary clinical information to allow practicing hospitalists to make better decisions regarding patient care. This new inpatient evidence‐base will have the added advantage of helping further define the field of PHM.

The Pediatric Research in Inpatient Settings Network (PRIS) was identified as the vehicle to accomplish these goals. A series of objectives were identified to redesign PRIS in order to accommodate and organize this new influx of hospitalist‐investigators. These objectives included having hospitalist‐investigators commit their time to the prioritization, design, and execution of multicenter studies, drafting new governance documents for PRIS, securing external funding, redefining the relationships of the 3 existing organizations that formed PRIS (AAP, APA, SHM), defining how new clinical sites could be added to PRIS, creating a pipeline for junior hospitalist‐investigators to transition to leadership roles, securing a data coordinating center with established expertise in conducting multicenter studies, and establishing an external research advisory committee of leaders in pediatric clinical research and QI.

Several critical issues were identified, but funding remained a priority for the sustainability of PRIS. Comparative effectiveness (CE) was recognized as a potential important source of future funding. Pediatric studies on CE (eg, surgery vs medical management) conducted by PRIS would provide important new data to allow hospitalists to practice evidence‐based medicine and to improve quality.

A Research Leadership Task Force was created with 4 members of the PHM Strategic Planning Roundtable to work on the identified issues. The APA leadership worked with PRIS to establish a new Executive Council (comprised of additional qualified hospitalist‐investigators). The Executive Council was charged with accomplishing the tasks outlined from the Strategic Planning Roundtable. They have created the governance documents and standard operating procedures necessary for PRIS to conduct multicenter studies, defined a strategic framework for PRIS including the mission, vision and values, and funding strategy. In February 2010, PRIS received a 3‐year award for over $1 million from the Child Health Corporation of America to both fund the infrastructure of PRIS and to conduct a Prioritization Project. The Prioritization Project seeks to identify the conditions that are costly, prevalent, and demonstrate high inter‐hospital variation in resource utilization, which signals either lack of high‐quality data upon which to base medical decisions, and/or an opportunity to standardize care across hospitals. Some of these conditions will warrant further investigation to define the evidence base, whereas other conditions may require implementation studies to reliably introduce evidence into practice. Members of the Executive Council received additional funding to investigate community settings, as most children are hospitalized outside of large children's hospitals. PRIS also reengaged all 3 societies (APA, AAP, and SHM) for support for the first face‐to‐face meeting of the Executive Council. PRIS applied for 2 Recovery Act stimulus grants, and received funding for both of approximately $12 million. The processes used to design, provide feedback, and shepherd these initial studies formed the basis for the standard operating procedures for the Network. PRIS is now reengaging its membership to establish how sites may be able to conduct research, and receive new ideas to be considered for study in PRIS.

Although much work remains to be done, the Executive Council is continuing the charge with quarterly face‐to‐face meetings, hiring of a full‐time PRIS Coordinator, and carrying out these initial projects, while maintaining the goal of meeting the needs of the membership and PHM. If PRIS is to accomplish its mission of improving the health of, and healthcare delivery to, hospitalized children and their families, then the types of studies undertaken will include not only original research questions, but also comparative implementation methods to better understand how hospitalists in a variety of settings can best translate research findings into clinical practice and ultimately improve patient outcomes.

WORKFORCE

The current number of pediatric hospitalists is difficult to gauge11; estimates range from 1500 to 3000 physicians. There are groups of pediatric hospitalists within several national organizations including the AAP, APA, and SHM, in addition to a very active listserve community. It is likely that only a portion of pediatric hospitalists are represented by membership in these organizations.

Most physicians entering the field of PHM come directly out of residency. A recent survey by Freed et al.12 reported that 3% of current pediatric residents are interested in PHM as a career. In another survey by Freed et al., about 6% of recent pediatric residency graduates reported currently practicing as pediatric hospitalists.13 This difference may indicate a number of pediatricians practicing transiently as pediatric hospitalists.

There are numerous issues that will affect the growth and sustainability of PHM. A large number of pediatric residents entering the field will be needed to maintain current numbers. With 45% of hospitalists in practice less than 3 years,11 the growth of PHM in both numbers and influence will require an increasing number of hospitalists with sustained careers in the field. Recognition as experts in inpatient care, as well as expansion of the role of hospitalists beyond the clinical realm to education, research, and hospital leadership, will foster long‐term career satisfaction. The increasingly common stature of hospital medicine as an independent division, equivalent to general pediatrics and subspecialty divisions within a department, may further bolster the perception of hospital medicine as a career.

The majority of pediatric hospitalists believe that current pediatric residency training does not provide all of the skills necessary to practice as a pediatric hospitalist,14 though there is disagreement regarding how additional training in pediatric hospital medicine should be achieved: a dedicated fellowship versus continuing medical education (CME). There are several initiatives with the potential to transform the way pediatric hospitalists are trained and certified. The Residency Review and Redesign Project indicates that pediatric residency is likely to be reformed to better meet the training demands of the individual resident's chosen career path. Changing residency to better prepare pediatric residents to take positions in pediatric hospital medicine will certainly affect the workforce emerging from residency programs and their subsequent training needs.15 The American Board of Internal Medicine and the American Board of Family Medicine have approved a Recognition of Focused Practice in Hospital Medicine. This recognition is gained through the Maintenance of Certification (MOC) Program of the respective boards after a minimum of 3 years of practice. SHM is offering fellow recognition in tiered designations of Fellow of Hospital Medicine (FHM), Senior Fellow of Hospital Medicine, and Master of Hospital Medicine. Five hundred hospitalists, including many pediatric hospitalists, received the inaugural FHM designation in 2009. Organizational recognition is a common process in many other medical fields, although previously limited in pediatrics to Fellow of the AAP. FHM is an important step, but cannot substitute for specific training and certification.

Academic fellowships in PHM will aid in the training of hospitalists with scholarly skills and will help produce more pediatric hospitalists with clinical, quality, administrative, and leadership skills. A model of subspecialty fellowship training and certification of all PHM physicians would require a several‐fold increase in available fellowships, currently approximately 15.

Ongoing CME offerings are also critical to sustaining and developing the workforce. The annual national meetings of the APA, AAP, and SHM all offer PHM‐dedicated content, and there is an annual PHM conference sponsored by these 3 organizations. There are now multiple additional national and regional meetings focused on PHM, reflecting the growing audience for PHM CME content. The AAP offers a PHM study guide and an Education in quality improvement for pediatric practice (eQIPP) module on inpatient asthma, specifically designed to facilitate the MOC process for pediatric hospitalists.

Some form of ABP recognition may be necessary to provide the status for PHM to be widely recognized as a viable academic career in the larger pediatric community. This would entail standardized fellowships that will ensure graduates have demonstrated proficiency in the core competencies. PHM leaders have engaged the ABP to better understand the subspecialty approval process and thoughtfully examine the ramifications of subspecialty status, specifically what subspecialty certification would mean for PHM providers and hospitals. Achieving ABP certification may create a new standard of care meaning that noncertified PHM providers will be at a disadvantage. It is unknown what the impact on pediatric inpatient care would be if a PHM standard was set without the supply of practitioners to provide that care.

STRUCTURE

The efforts of the Roundtable demonstrate the potential effectiveness of the current structure that guides the field: that of the cooperative interchange between the PHM leaders within the APA, AAP, and SHM. It may be that, similar to Pediatric Emergency Medicine (PEM), no formal, unifying structure is necessary. Alternatively, both Adolescent Medicine and Behavioral and Developmental Pediatrics (BDP) have their own organizations that guide their respective fields. A hybrid model is that of Pediatric Cardiology which has the Joint Council on Congenital Heart Disease. This structure assures that the leaders of the various organizations concerned with congenital heart disease meet at least annually to report on their activities and coordinate future efforts. Its makeup is similar to how the planning committee of the annual national PHM conference is constructed. Although PHM has largely succeeded with the current organizational structure, it is possible that a more formal structure is needed to continue forward.

CONCLUSION

The Roundtable members developed the following vision for PHM: Pediatric hospitalists will transform the delivery of hospital care for children. This will be done by achieving 7 goals (Table 2).

Attaining this vision will take tremendous dedication, effort, and collaboration. As a starting point, the following initiatives were proposed and implemented as noted: