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P60– Decision support capabilities of commercial EHRS and implications for guideline developers
Poster
P60– Decision support capabilities of commercial EHRS and implications for guideline developers Adam Wright, PhD (Presenter) (Brigham and Women’s Hospital, Boston, Massachusetts); Justine E. Pang (Brigham and Women’s Hospital, Boston, Massachusetts); Sapna Sharma (OHSU, Portland, Oregon); Dean F. Sittig, PhD (UT Houston, Houston, Texas); Blackford Middleton, MD (Partners HealthCare, Wellesley, Massachusetts) PRIMARY TRACK: Guideline implementation SECONDARY TRACK: Computer-based decision support BACKGROUND (INTRODUCTION): Guidelines are often implemented as clinical decision support (CDS) in commercial electronic health record systems. However, the CDS capabilities of commercial EHR systems differ widely, and these differences have important implications for guideline developers. LEARNING OBJECTIVES (TRAINING GOALS): 1. Identify clinical decision support features of electronic health record systems. 2. Understand differences in the CDS features of various commercial EHR systems. 3. Understand the implications of these differences for guideline development. METHODS: We compared the capabilities of nine commercially available clinical information systems against the 42 functional taxa from a published taxonomy of CDS capabilities. The taxonomy has four axes: 1) Triggers: events that cause a decision support rule to be invoked (e.g., ordering a laboratory test); 2) Input data: data used by a rule to make inferences (e.g., the patient’s problem list); 3) Interventions: possible actions a decision support module can take (e.g., showing a guideline); 4) Offered choices: many decision support events require users of a clinical system to make a choice, e.g., choosing a safer drug. RESULTS: Overall, there was a great deal of variability among capabilities of the systems possessed. The two weakest systems evaluated were missing 18 of 42 capabilities, while the strongest system was missing only a single capability. Four of nine unique triggers (order entered, outpatient encounter opened, user request, and time) were available in all systems, seven of 14 input data elements were universally available, two of seven interventions (notify and show data entry template) were available in all systems, and only three of 12 offered choices were available in all nine systems. DISCUSSION (CONCLUSION): The clinical decision support (CDS) capabilities of these CCHIT-certified EHRs were variable, and none of the systems had every capability. Guideline authors and implementers should design guidelines with knowledge of the varying capabilities of EHRs and, preferably, guidelines should degrade gracefully in the absence of certain CDS capabilities or EHR data. TARGET AUDIENCE(S): 1. Guideline developer 2. Guideline implementer
109 3. Developer of guideline-based products 4. Health care policy analyst/policy-maker
P61– Delphi consensus on the feasibility of translating the American College of Emergency Physicians clinical policies into computerized clinical decision support Edward R. Melnick, MD (Presenter) (North Shore University Hospital, Long Island City, New York); Jeffrey A. Nielson, MD (Akron City Hospital, Akron, Ohio); John T. Finnell, MD (Indiana University School of Medicine, Indianapolis, Indiana); Saumil J. Patel, BS (North Shore University Hospital, Manhasset, New York); Lynne D. Richardson, MD (Mount Sinai School of Medicine, New York, New York) PRIMARY TRACK: Guideline implementation SECONDARY TRACK: Computer-based decision support BACKGROUND (INTRODUCTION): The American College of Emergency Physicians (ACEP) Clinical Policies have been shown to be safe and effective. However, these evidencebased practice guidelines face barriers to effective implementation. Translation of the ACEP Clinical Policies into computerized Clinical Decision Support (CDS) could help address these barriers and improve clinician decision-making at the point of care. LEARNING OBJECTIVES (TRAINING GOALS): 1. Assess the feasibility of translating the ACEP Clinical Policies into CDS. 2. Improve future ACEP guideline development with the goal of implementation into CDS. METHODS: The investigators convened an informatics expert panel of 14 emergency physicians chosen for their expertise in CDS. The recommendation sections from the six most recent ACEP Clinical Policies were distributed to the panel for review. Four rounds of the Delphi consensus process were performed using SurveyMonkey, a web-based survey tool. With the goal of working toward consensus, anonymous responses from the prior round of the Delphi process were provided for the panelists’ consideration. RESULTS: The panel members had a 100% completion rate for all four rounds of the Delphi process. All 14 members of the panel signed the resulting consensus document. The panel identified four limitations to translation, including: guidelines that are too vague, are not comprehensive enough, require additional physician input or knowledge for translation, and when translated would impede clinical workflow due to excessive data entry. The panel made the following recommendations for future guideline development and implementation with the goal of implementation into CDS: provide actionable recommendations, include informatics specialist input throughout guideline development, and CDS should be deployed using a modular approach to allow for future flexibility and customization.
P60– Decision support capabilities of commercial EHRS and implications for guideline developers Adam Wright, PhD (Presenter) (Brigham and Women’s Hospital, Boston, Massachusetts); Justine E. Pang (Brigham and Women’s Hospital, Boston, Massachusetts); Sapna Sharma (OHSU, Portland, Oregon); Dean F. Sittig, PhD (UT Houston, Houston, Texas); Blackford Middleton, MD (Partners HealthCare, Wellesley, Massachusetts) PRIMARY TRACK: Guideline implementation SECONDARY TRACK: Computer-based decision support BACKGROUND (INTRODUCTION): Guidelines are often implemented as clinical decision support (CDS) in commercial electronic health record systems. However, the CDS capabilities of commercial EHR systems differ widely, and these differences have important implications for guideline developers. LEARNING OBJECTIVES (TRAINING GOALS): 1. Identify clinical decision support features of electronic health record systems. 2. Understand differences in the CDS features of various commercial EHR systems. 3. Understand the implications of these differences for guideline development. METHODS: We compared the capabilities of nine commercially available clinical information systems against the 42 functional taxa from a published taxonomy of CDS capabilities. The taxonomy has four axes: 1) Triggers: events that cause a decision support rule to be invoked (e.g., ordering a laboratory test); 2) Input data: data used by a rule to make inferences (e.g., the patient’s problem list); 3) Interventions: possible actions a decision support module can take (e.g., showing a guideline); 4) Offered choices: many decision support events require users of a clinical system to make a choice, e.g., choosing a safer drug. RESULTS: Overall, there was a great deal of variability among capabilities of the systems possessed. The two weakest systems evaluated were missing 18 of 42 capabilities, while the strongest system was missing only a single capability. Four of nine unique triggers (order entered, outpatient encounter opened, user request, and time) were available in all systems, seven of 14 input data elements were universally available, two of seven interventions (notify and show data entry template) were available in all systems, and only three of 12 offered choices were available in all nine systems. DISCUSSION (CONCLUSION): The clinical decision support (CDS) capabilities of these CCHIT-certified EHRs were variable, and none of the systems had every capability. Guideline authors and implementers should design guidelines with knowledge of the varying capabilities of EHRs and, preferably, guidelines should degrade gracefully in the absence of certain CDS capabilities or EHR data. TARGET AUDIENCE(S): 1. Guideline developer 2. Guideline implementer
109 3. Developer of guideline-based products 4. Health care policy analyst/policy-maker
P61– Delphi consensus on the feasibility of translating the American College of Emergency Physicians clinical policies into computerized clinical decision support Edward R. Melnick, MD (Presenter) (North Shore University Hospital, Long Island City, New York); Jeffrey A. Nielson, MD (Akron City Hospital, Akron, Ohio); John T. Finnell, MD (Indiana University School of Medicine, Indianapolis, Indiana); Saumil J. Patel, BS (North Shore University Hospital, Manhasset, New York); Lynne D. Richardson, MD (Mount Sinai School of Medicine, New York, New York) PRIMARY TRACK: Guideline implementation SECONDARY TRACK: Computer-based decision support BACKGROUND (INTRODUCTION): The American College of Emergency Physicians (ACEP) Clinical Policies have been shown to be safe and effective. However, these evidencebased practice guidelines face barriers to effective implementation. Translation of the ACEP Clinical Policies into computerized Clinical Decision Support (CDS) could help address these barriers and improve clinician decision-making at the point of care. LEARNING OBJECTIVES (TRAINING GOALS): 1. Assess the feasibility of translating the ACEP Clinical Policies into CDS. 2. Improve future ACEP guideline development with the goal of implementation into CDS. METHODS: The investigators convened an informatics expert panel of 14 emergency physicians chosen for their expertise in CDS. The recommendation sections from the six most recent ACEP Clinical Policies were distributed to the panel for review. Four rounds of the Delphi consensus process were performed using SurveyMonkey, a web-based survey tool. With the goal of working toward consensus, anonymous responses from the prior round of the Delphi process were provided for the panelists’ consideration. RESULTS: The panel members had a 100% completion rate for all four rounds of the Delphi process. All 14 members of the panel signed the resulting consensus document. The panel identified four limitations to translation, including: guidelines that are too vague, are not comprehensive enough, require additional physician input or knowledge for translation, and when translated would impede clinical workflow due to excessive data entry. The panel made the following recommendations for future guideline development and implementation with the goal of implementation into CDS: provide actionable recommendations, include informatics specialist input throughout guideline development, and CDS should be deployed using a modular approach to allow for future flexibility and customization.