CDS in a Learning Health Care System: Identifying Physicians' Reasons for Rejection of Best-Practice Recommendations in Pneumonia through Computerized Clinical Decision Support.

BACKGROUND: Local implementation of guidelines for pneumonia care is strongly recommended, but the context of care that affects implementation is poorly understood. In a learning health care system, computerized clinical decision support (CDS) provides an opportunity to both improve and track practice, providing insights into the implementation process. OBJECTIVES: This article examines physician interactions with a CDS to identify reasons for rejection of guideline recommendations. METHODS: We implemented a multicenter bedside CDS for the emergency department management of pneumonia that integrated patient data with guideline-based recommendations. We examined the frequency of adoption versus rejection of recommendations for site-of-care and antibiotic selection. We analyzed free-text responses provided by physicians explaining their clinical reasoning for rejection, using concept mapping and thematic analysis. RESULTS: Among 1,722 patient episodes, physicians rejected recommendations to send a patient home in 24%, leaving text in 53%; reasons for rejection of the recommendations included additional or alternative diagnoses beyond pneumonia, and comorbidities or signs of physiologic derangement contributing to risk of outpatient failure that were not processed by the CDS. Physicians rejected broad-spectrum antibiotic recommendations in 10%, leaving text in 76%; differences in pathogen risk assessment, additional patient information, concern about antibiotic properties, and admitting physician preferences were given as reasons for rejection. CONCLUSION: While adoption of CDS recommendations for pneumonia was high, physicians rejecting recommendations frequently provided feedback, reporting alternative diagnoses, additional individual patient characteristics, and provider preferences as major reasons for rejection. CDS that collects user feedback is feasible and can contribute to a learning health system.

Impact of an Electronic Clinical Decision Support Tool for Emergency Department Patients With Pneumonia.

STUDY OBJECTIVE: Despite evidence that guideline adherence improves clinical outcomes, management of pneumonia patients varies in emergency departments (EDs). We study the effect of a real-time, ED, electronic clinical decision support tool that provides clinicians with guideline-recommended decision support for diagnosis, severity assessment, disposition, and antibiotic selection. METHODS: This was a prospective, controlled, quasi-experimental trial in 7 Intermountain Healthcare hospital EDs in Utah's urban corridor. We studied adults with International Classification of Diseases, Ninth Revision codes and radiographic evidence for pneumonia during 2 periods: baseline (December 2009 through November 2010) and post-tool deployment (December 2011 through November 2012). The tool was deployed at 4 intervention EDs in May 2011, leaving 3 as usual care controls. We compared 30-day, all-cause mortality adjusted for illness severity, using a mixed-effect, logistic regression model. RESULTS: The study population comprised 4,758 ED pneumonia patients; 14% had health care-associated pneumonia. Median age was 58 years, 53% were female patients, and 59% were admitted to the hospital. Physicians applied the tool for 62.6% of intervention ED study patients. There was no difference overall in severity-adjusted mortality between intervention and usual care EDs post-tool deployment (odds ratio [OR]=0.69; 95% confidence interval [CI] 0.41 to 1.16). Post hoc analysis showed that patients with community-acquired pneumonia experienced significantly lower mortality (OR=0.53; 95% CI 0.28 to 0.99), whereas mortality was unchanged among patients with health care-associated pneumonia (OR=1.12; 95% CI 0.45 to 2.8). Patient disposition from the ED postdeployment adhered more to tool recommendations. CONCLUSION: This study demonstrates the feasibility and potential benefit of real-time electronic clinical decision support for ED pneumonia patients.

Development and early usage patterns of a consumer-facing family health history tool.

Personalized medicine will require detailed clinical patient profiles, and a particular focus on capturing data that is useful in forecasting risk. A detailed family health history is considered a critical component of these profiles, insomuch that it has been coined as 'the best genetic test available'. Despite this, tools aimed at capturing this information for use in electronic health records have been characterized as inadequate. In this manuscript we detail the creation of a patient-facing family health history tool known as OurFamilyHealth, whose long-term emphasis is to facilitate risk assessment and clinical decision support. We present the rationale for such a tool, describe its development and release as a component of Intermountain Healthcare's patient portal, and detail early usage statistics surrounding the application. Data derived from the tool since its release are also compared against family history charting patterns in Intermountain's electronic health records, revealing differences in data availability.