Electronic health record feedback to improve antibiotic prescribing for acute respiratory infections.
ABSTRACT To examine whether the Acute Respiratory Infection (ARI) Quality Dashboard, an electronic health record (EHR)-based feedback system, changed antibiotic prescribing.
Cluster randomized, controlled trial.
We randomly assigned 27 primary care practices to receive the ARI Quality Dashboard or usual care. The primary outcome was the intent-to-intervene antibiotic prescribing rate for ARI visits. We also compared antibiotic prescribing between ARI Quality Dashboard users and nonusers.
During the 9-month intervention, there was no difference between intervention and control practices in antibiotic prescribing for all ARI visits (47% vs 47%; P = .87), antibiotic-appropriate ARI visits (65% vs 64%; P = .68), or non–antibiotic-appropriate ARI visits (38% vs 40%; P = .70). Among the 258 intervention clinicians, 72 (28%) used the ARI Quality Dashboard at least once. These clinicians had a lower overall ARI antibiotic prescribing rate (42% vs 50% for nonusers; P = .02). This difference was due to less antibiotic prescribing for non-antibiotic-appropriate ARIs (32% vs 43%; P = .004), including nonstreptococcal pharyngitis (31% vs 41%; P = .01) and nonspecific upper respiratory infections (19% vs 34%; P = .01).
The ARI Quality Dashboard was not associated with an overall change in antibiotic prescribing for ARIs, although when used, it was associated with improved antibiotic prescribing. EHR-based quality reporting, as part of "meaningful use," may not improve care in the absence of other changes to primary care practice.
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ABSTRACT: To provide high-quality and safe care, clinicians must be able to optimally collect, distill, and interpret patient information. Despite advances in text summarization, only limited research exists on clinical summarization, the complex and heterogeneous process of gathering, organizing and presenting patient data in various forms. To develop a conceptual model for describing and understanding clinical summarization in both computer-independent and computer-supported clinical tasks. Based on extensive literature review and clinical input, we developed a conceptual model of clinical summarization to lay the foundation for future research on clinician workflow and automated summarization using electronic health records (EHRs). Our model identifies five distinct stages of clinical summarization: (1) Aggregation, (2) Organization, (3) Reduction and/or Transformation, (4) Interpretation and (5) Synthesis (AORTIS). The AORTIS model describes the creation of complex, task-specific clinical summaries and provides a framework for clinical workflow analysis and directed research on test results review, clinical documentation and medical decision-making. We describe a hypothetical case study to illustrate the application of this model in the primary care setting. Both practicing physicians and clinical informaticians need a structured method of developing, studying and evaluating clinical summaries in support of a wide range of clinical tasks. Our proposed model of clinical summarization provides a potential pathway to advance knowledge in this area and highlights directions for further research.Journal of Biomedical Informatics 03/2011; 44(4):688-99. DOI:10.1016/j.jbi.2011.03.008 · 2.19 Impact Factor
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ABSTRACT: The implementation of an electronic health record is a dramatic change in a healthcare organization; however, little is known about how nurse attitudes toward the electronic health record change over time. The purpose of this research project was to compare nurses' attitudes before and at 6 and 18 months after implementation of a comprehensive electronic health record. A presurvey-postsurvey design using a modified Nurses' Attitudes Toward Computerization Questionnaire was implemented with a population of nurses employed at an academic medical center. On average, the nurses' attitude about the electronic health record became less positive between preimplementation (n = 312) and 6 months after implementation (n = 410) (74.2 vs 65.9, P < .0001) and preimplementation and 18 months after implementation (n = 262) groups (74.2 vs 67.7, P < .0001). No significant improvement between 6 and 18 months after implementation groups (P = .16) was noted. Prior to electronic health record implementation, the nurses were uncertain yet hopeful about the benefits. However, 18 months after implementing a comprehensive electronic health record, challenges remain regarding cumbersome documentation processes and promoting interdisciplinary communication. Thus, the results demonstrate a gap between preimplementation expectations and the postimplementation reality of the actual experience. Nonetheless, some subjects have experienced positive benefits after implementation of the comprehensive electronic health record and remain hopeful for the future.Computers, informatics, nursing: CIN 05/2012; 30(10):521-30. DOI:10.1097/NXN.0b013e3182573b04 · 0.72 Impact Factor
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ABSTRACT: Objective: To assess the effect of a clinical decision support system (CDSS) integrated into an electronic health record (EHR) on antibiotic prescribing for acute respiratory infections (ARIs) in primary care. Materials and methods: Quasi-experimental design with nine intervention practices and 61 control practices in the Practice Partner Research Network, a network of practices which all use the same EHR (Practice Partner). The nine intervention practices were located in nine US states. The design included a 3-month baseline data collection period (October through December 2009) before the introduction of the intervention and 15 months of follow-up (January 2010 through March 2011). The main outcome measures were the prescribing of antibiotics in ARI episodes for which antibiotics are inappropriate and prescribing of broad-spectrum antibiotics in all ARI episodes. Results: In adult patients, prescribing of antibiotics in ARI episodes where antibiotics are inappropriate declined more (-0.6%) among intervention practices than in control practices (+4.2%) (p=0.03). However, among adults, the CDSS intervention improved prescribing of broad-spectrum antibiotics, with a decline of 16.6% among intervention practices versus an increase of 1.1% in control practices (p<0.0001). A similar effect on broad-spectrum antibiotic prescribing was found in pediatric patients with a decline of 19.7% among intervention practices versus an increase of 0.9% in control practices (p<0.0001). Conclusions: A CDSS embedded in an EHR had a modest effect in changing prescribing for adults where antibiotics were inappropriate but had a substantial impact on changing the overall prescribing of broad-spectrum antibiotics among pediatric and adult patients.Journal of the American Medical Informatics Association 07/2012; 20(2). DOI:10.1136/amiajnl-2011-000701 · 3.50 Impact Factor