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Rationale, Design, and Implementation Protocol of an Electronic Health Record Integrated Clinical Prediction Rule (iCPR) Randomized Trial in Primary Care

Overview
Journal Implement Sci
Publisher Biomed Central
Specialty Health Services
Date 2011 Sep 21
PMID 21929769
Citations 30
Authors
Affiliations
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Abstract

Background: Clinical prediction rules (CPRs) represent well-validated but underutilized evidence-based medicine tools at the point-of-care. To date, an inability to integrate these rules into an electronic health record (EHR) has been a major limitation and we are not aware of a study demonstrating the use of CPR's in an ambulatory EHR setting. The integrated clinical prediction rule (iCPR) trial integrates two CPR's in an EHR and assesses both the usability and the effect on evidence-based practice in the primary care setting.

Methods: A multi-disciplinary design team was assembled to develop a prototype iCPR for validated streptococcal pharyngitis and bacterial pneumonia CPRs. The iCPR tool was built as an active Clinical Decision Support (CDS) tool that can be triggered by user action during typical workflow. Using the EHR CDS toolkit, the iCPR risk score calculator was linked to tailored ordered sets, documentation, and patient instructions. The team subsequently conducted two levels of 'real world' usability testing with eight providers per group. Usability data were used to refine and create a production tool. Participating primary care providers (n = 149) were randomized and intervention providers were trained in the use of the new iCPR tool. Rates of iCPR tool triggering in the intervention and control (simulated) groups are monitored and subsequent use of the various components of the iCPR tool among intervention encounters is also tracked. The primary outcome is the difference in antibiotic prescribing rates (strep and pneumonia iCPR's encounters) and chest x-rays (pneumonia iCPR only) between intervention and control providers.

Discussion: Using iterative usability testing and development paired with provider training, the iCPR CDS tool leverages user-centered design principles to overcome pervasive underutilization of EBM and support evidence-based practice at the point-of-care. The ongoing trial will determine if this collaborative process will lead to higher rates of utilization and EBM guided use of antibiotics and chest x-ray's in primary care.

Trial Registration: ClinicalTrials.gov Identifier NCT01386047.

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References
1.
Tonelli M . The limits of evidence-based medicine. Respir Care. 2001; 46(12):1435-40; discussion 1440-1. View

2.
Brook R . The end of the quality improvement movement: long live improving value. JAMA. 2010; 304(16):1831-2. DOI: 10.1001/jama.2010.1555. View

3.
McGinn T, Guyatt G, Wyer P, Naylor C, Stiell I, Richardson W . Users' guides to the medical literature: XXII: how to use articles about clinical decision rules. Evidence-Based Medicine Working Group. JAMA. 2000; 284(1):79-84. DOI: 10.1001/jama.284.1.79. View

4.
Walsh B, Bookheim W, Johnson R, Tompkins R . Recognition of streptococcal pharyngitis in adults. Arch Intern Med. 1975; 135(11):1493-7. View

5.
McGinn T, DeLuca J, Ahlawat S, Mobo Jr B, Wisnivesky J . Validation and modification of streptococcal pharyngitis clinical prediction rules. Mayo Clin Proc. 2003; 78(3):289-93. DOI: 10.4065/78.3.289. View