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

• ClinicalTrials.gov Identifier: NCT01386047
• Recruitment Status: Completed
• First Posted: June 30, 2011
• Last Update Posted: October 4, 2012
• Sponsor: Northwell Health
• Collaborators: Icahn School of Medicine at Mount Sinai; Agency for Healthcare Research and Quality (AHRQ)
• Information provided by (Responsible Party): Thomas McGinn, Northwell Health

Study Description

Brief 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).

Condition or disease	Intervention/treatment	Phase
Strep Pharyngitis; Pneumonia	Other: Integrated Clinical Prediction Rule (iCPR)	Not Applicable

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 Design

• Study Type: Interventional (Clinical Trial)
• Actual Enrollment: 168 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Masking: Single (Outcomes Assessor)
• Primary Purpose: Health Services Research
• Official Title: Evidence Based Decision Making: Integrating Clinical Prediction Rules Into Electronic Health Records
• Study Start Date: August 2010
• Actual Primary Completion Date: January 2012
• Actual Study Completion Date: July 2012

Arms and Interventions

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).

Outcome Measures

Primary Outcome Measures :

1. 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. [ Time Frame: Comparisons between case and control ordering will be measured after a year of using the EMR tool ]
   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.

Eligibility Criteria

• Ages Eligible for Study: Child, Adult, Older Adult
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

Criteria

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

Contacts and Locations

Locations

United States, New York

Mount Sinai School of Medicine

New York, New York, United States, 10029

Sponsors and Collaborators

Northwell Health

Icahn School of Medicine at Mount Sinai

Agency for Healthcare Research and Quality (AHRQ)

Investigators

• Principal Investigator: Thomas M McGinn, MD, MPH; Northwell Health

More Information

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):

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.

• Responsible Party: Thomas McGinn, Chair and Professor for the Hofstra North Shore-LIJ School of Medicine, Northwell Health
• ClinicalTrials.gov Identifier: NCT01386047
• Other Study ID Numbers: GCO-09-0337; 5R18HS018491 ( U.S. AHRQ Grant/Contract )
• First Posted: June 30, 2011
• Last Update Posted: October 4, 2012
• Last Verified: October 2012

Keywords provided by Thomas McGinn, Northwell Health:

Clinical Prediction Rules; Electronic Health Records; Walsh Clinical Prediction Rule; Heckerling Clinical Prediction Rule

Additional relevant MeSH terms:

Pharyngitis; Respiratory Tract Infections; Infections; Respiratory Tract Diseases; Pharyngeal Diseases; Stomatognathic Diseases; Otorhinolaryngologic Diseases