Evidence Based Decision Making: Integrating Clinical Prediction Rules (iCPR and EHR)

Evidence Based Decision Making: Integrating Clinical Prediction Rules Into Electronic Health Records

Clinical prediction rules (CPRs) are frontline decision aids that help physicians make evidence-based, cost-effective decisions that benefit their patients. The aims of this project are to incorporate two well validated CPRs (Streptococcal Pharyngitis Prediction Rule and the Pneumonia Clinical Prediction Rule) into an outpatient Electronic Medical Record System (EMR) and to perform a randomized controlled trial of the effectiveness of integrated CPRs impact on doctor's behaviors (e.g. test ordering and medication prescribing).

Study Overview

• Status: Completed
• Conditions: Pneumonia; Strep Pharyngitis
• Intervention / Treatment: Other: Integrated Clinical Prediction Rule (iCPR)

Detailed Description

Clinical prediction rules (CPRs) are frontline decision aids that help physicians make evidence-based, cost-effective decisions that benefit their patients. CPRs are proven tools that translate evidence into practice, increase quality while reducing costs, and can be used by physicians in a wide variety of clinical settings, such as primary care offices, emergency rooms, and hospitals. While many CPRs have been developed and validated over the years, health care providers have yet to incorporate them into everyday care.

CPRs aid providers in assessing the impact of individual components of a patient's history, physical examination, and basic lab results to estimate probability of disease or potential response to a treatment. Prediction rules use data that is readily available at the time of a patient encounter and often reduce unnecessary treatments and diagnostic testing. CPRs differ from reminder systems or alerts in that CPRs pull in aspects of the history and physical exam and in an evidence based fashion estimate probabilities, prognosis, or make treatment recommendations.

The goal of this study is to utilize patient electronic health records to incorporate CPRs into the face-to-face patient encounter. We propose to select certain clinical situations where well-validated CPRs are available and likely to be needed on a frequent basis. We will randomly assign an integrated CPR versus usual care into the point of care and evaluate the impact of this integration on doctor behavior and evidence-based decision making. Mount Sinai's Division of General Internal Medicine (DGIM) has significant experience with all aspects of CPRs, including derivation, validation, implementation, and systematic review. Furthermore, the Division has developed an interactive web library of CPRs for clinical use that is one of the most widely sites of its kind. We propose to collaborate with Epic, one of the nation's largest and most respected electronic medical record (EMR) companies, to integrate validated CPRs into EMRs and assess the impact on provider behavior and patient care.

• Study Type: Interventional
• Enrollment (Actual): 168
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • New York
    • New York, New York, United States, 10029
      • Mount Sinai School of Medicine

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Providers who are part of Mount Sinai's Division of General Internal Medicine

Exclusion Criteria:

• Not a provider at Mount Sinai's Division of General Internal Medicine

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: iCPR randomized providers; The physician population for the proposed study will comprise primary care providers (physicians, internal medicine residents, or licensed nurse practitioners; practicing in the outpatient primary care clinics at Mount Sinai Medical Center. The iCPR tool will automatically trigger for providers randomized into the iCPR intervention arm when they initiated an encounter for a patient that meets the criteria for possible evaluation of Strep Pharyngitis or Pneumonia.	Other: Integrated Clinical Prediction Rule (iCPR); Integrated clinical prediction rule for Strep Pharyngitis based on Walsh clinical prediction rule (CPR) criteria and rule for Pneumonia based on Hecklering CPR criteria.
No Intervention: Control providers; The physician population for the proposed study will comprise primary care providers (physicians, internal medicine residents, or licensed nurse practitioners; practicing in the outpatient primary care clinics at Mount Sinai Medical Center. These providers will conduct visits for Strep Pharyngitis and Pneumonia in their manner (usual care).

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The primary outcome of this study will be focused on changes in doctor behavior and the comparison of the number of diagnostic tests ordered (chest x-rays) and antibiotics prescribed per patient encountered per diagnosis.	The data for the intervention and control groups will be compared for each of the two diagnostic areas. For example, for all patients presenting with URI symptoms or sore throat, data will be collected from Epic on the number of prescriptions for antibiotics written by providers randomized to the iCPR compared to usual-care arms, respectively. Among patients presenting with suspicion of pneumonia, the number of chest x-rays ordered and antibiotics prescribed at the clinical encounter will be determined.	Comparisons between case and control ordering will be measured after a year of using the EMR tool

Collaborators and Investigators

• Sponsor: Northwell Health
• Collaborators: Icahn School of Medicine at Mount Sinai; Agency for Healthcare Research and Quality (AHRQ)
• Investigators: Principal Investigator: Thomas M McGinn, MD, MPH, Northwell Health

Publications and helpful links

General Publications

• McGinn TG, McCullagh L, Kannry J, Knaus M, Sofianou A, Wisnivesky JP, Mann DM. Efficacy of an evidence-based clinical decision support in primary care practices: a randomized clinical trial. JAMA Intern Med. 2013 Sep 23;173(17):1584-91. doi: 10.1001/jamainternmed.2013.8980.
• Mann DM, Kannry JL, Edonyabo D, Li AC, Arciniega J, Stulman J, Romero L, Wisnivesky J, Adler R, McGinn TG. Rationale, design, and implementation protocol of an electronic health record integrated clinical prediction rule (iCPR) randomized trial in primary care. Implement Sci. 2011 Sep 19;6:109. doi: 10.1186/1748-5908-6-109.

Study record dates

Study Major Dates

• Study Start: August 1, 2010
• Primary Completion (Actual): January 1, 2012
• Study Completion (Actual): July 1, 2012

Study Registration Dates

• First Submitted: June 28, 2011
• First Submitted That Met QC Criteria: June 29, 2011
• First Posted (Estimate): June 30, 2011

Study Record Updates

• Last Update Posted (Estimate): October 4, 2012
• Last Update Submitted That Met QC Criteria: October 3, 2012
• Last Verified: October 1, 2012

More Information

Terms related to this study

• Keywords: Electronic Health Records; Clinical Prediction Rules; Walsh Clinical Prediction Rule; Heckerling Clinical Prediction Rule
• Additional Relevant MeSH Terms: Infections; Respiratory Tract Infections; Respiratory Tract Diseases; Pharyngeal Diseases; Stomatognathic Diseases; Otorhinolaryngologic Diseases; Pharyngitis
• Other Study ID Numbers: GCO-09-0337; 5R18HS018491 (U.S. AHRQ Grant/Contract)