Pneumonia Clinical Trial
Official title:
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).
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.
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Allocation: Randomized, Intervention Model: Parallel Assignment, Masking: Single Blind (Outcomes Assessor), Primary Purpose: Health Services Research
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