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

This study has been completed.
Sponsor:
Collaborators:
Mount Sinai School of Medicine
Information provided by (Responsible Party):
Thomas McGinn, North Shore Long Island Jewish Health System
ClinicalTrials.gov Identifier:
NCT01386047
First received: June 28, 2011
Last updated: October 3, 2012
Last verified: October 2012
  Purpose

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 Intervention
Strep Pharyngitis
Pneumonia
Other: Integrated Clinical Prediction Rule (iCPR)

Study Type: Interventional
Study Design: Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single Blind (Outcomes Assessor)
Primary Purpose: Health Services Research
Official Title: Evidence Based Decision Making: Integrating Clinical Prediction Rules Into Electronic Health Records

Resource links provided by NLM:


Further study details as provided by North Shore Long Island Jewish Health System:

Primary Outcome Measures:
  • 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 ] [ Designated as safety issue: No ]
    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.


Enrollment: 168
Study Start Date: August 2010
Study Completion Date: July 2012
Primary Completion Date: January 2012 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
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).

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.

  Eligibility

Genders Eligible for Study:   Both
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
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

Please refer to this study by its ClinicalTrials.gov identifier: NCT01386047

Locations
United States, New York
Mount Sinai School of Medicine
New York, New York, United States, 10029
Sponsors and Collaborators
North Shore Long Island Jewish Health System
Mount Sinai School of Medicine
Investigators
Principal Investigator: Thomas M McGinn, MD, MPH North Shore Long Island Jewish Health System
  More Information

No publications provided by North Shore Long Island Jewish Health System

Additional publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
Responsible Party: Thomas McGinn, Chair and Professor for the Hofstra North Shore-LIJ School of Medicine, North Shore Long Island Jewish Health System
ClinicalTrials.gov Identifier: NCT01386047     History of Changes
Other Study ID Numbers: GCO-09-0337, 5R18HS018491
Study First Received: June 28, 2011
Last Updated: October 3, 2012
Health Authority: United States: Institutional Review Board

Keywords provided by North Shore Long Island Jewish Health System:
Clinical Prediction Rules
Electronic Health Records
Walsh Clinical Prediction Rule
Heckerling Clinical Prediction Rule

Additional relevant MeSH terms:
Pharyngitis
Pneumonia
Pharyngeal Diseases
Stomatognathic Diseases
Respiratory Tract Infections
Respiratory Tract Diseases
Otorhinolaryngologic Diseases
Lung Diseases

ClinicalTrials.gov processed this record on August 27, 2014