Clinical trial NCT01386047: Evidence Based Decision Making: Integrating Clinical Prediction Rules
Official title: Evidence Based Decision Making: Integrating Clinical Prediction Rules Into Electronic Health Records
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Strep Pharyngitis
Pneumonia
Keywords: Clinical Prediction Rules
Electronic Health Records
Walsh Clinical Prediction Rule
Heckerling Clinical Prediction Rule
Lead sponsor: Northwell Health
Sponsor class: OTHER
Collaborators: name: Icahn School of Medicine at Mount Sinai
name: Agency for Healthcare Research and Quality (AHRQ)
First posted: 2011-06-30
Enrollment: 168
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

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).

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 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

Primary outcomes:
measure: 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.
timeFrame: Comparisons between case and control ordering will be measured after a year of using the EMR tool
Secondary outcomes:
Other outcomes:
Locations:
city: New York
country: United States
facility: Mount Sinai School of Medicine
state: New York
Study officials:
affiliation: Northwell Health
name: Thomas M McGinn, MD, MPH
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.