Evidence Based Decision Making: Integrating Clinical Prediction Rules

Pneumonia Clinical Trial

— iCPR and EHR  

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT01386047
• Other study ID #: GCO-09-0337
• Secondary ID: 5R18HS018491
• Status: Completed
• Phase: N/A
• First received: June 28, 2011
• Last updated: October 3, 2012
• Start date: August 2010
• Est. completion date: July 2012

Study information

• Verified date: October 2012
• Source: Northwell Health
• Contact: n/a
• Is FDA regulated: No
• Health authority: United States: Institutional Review Board
• Study type: Interventional

Clinical Trial Summary

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).

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 168
• Est. completion date: July 2012
• Est. primary completion date: January 2012
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Both
• Age group: N/A and older

Eligibility

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 Design

Allocation: Randomized, Intervention Model: Parallel Assignment, Masking: Single Blind (Outcomes Assessor), Primary Purpose: Health Services Research

Related Conditions & MeSH terms

• Pharyngitis
• Pneumonia
• Strep Pharyngitis

Intervention

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.

Locations

Country	Name	City	State
United States	Mount Sinai School of Medicine	New York	New York

Sponsors (3)

Lead Sponsor	Collaborator
Northwell Health	Agency for Healthcare Research and Quality (AHRQ), Icahn School of Medicine at Mount Sinai

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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	No