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Automated identification of a physician's primary patients
Thomas A Lasko1, Steven J Atlas, Michael J Barry
1MIT CSAIL, 32 Vassar Street, 32-252, Cambridge, MA 02139, USA. tlasko@mit.edu
Journal of the American Medical Informatics Association : JAMIA
|October 14, 2005
Summary
A new automated method accurately identifies patients under a primary care physician's responsibility using electronic health data. This tool enhances care coordination by precisely defining physician clinical responsibility.
Area of Science:
- Health Informatics
- Primary Care Medicine
- Clinical Workflow Optimization
Background:
- Defining physician clinical responsibility is crucial for patient care coordination and resource allocation.
- Current methods for determining physician responsibility can be manual and time-consuming.
- Automated approaches are needed to efficiently identify patient panels for primary care physicians.
Purpose of the Study:
- To develop and validate an automated method for determining the patient cohort for whom a primary care physician holds overall clinical responsibility.
- To assess the accuracy of a predictive model using readily available electronic health record data.
Main Methods:
- A study included 16,185 adult patients and 18 primary care physicians over three years.
- Physicians self-identified primary responsibility for patients.
- Statistical models predicted physician designations using appointment and demographic data.
Main Results:
- A minimal set of six variables accurately predicted physician responsibility.
- The model achieved a median area under the receiver-operating characteristic curve (AUC) of 0.92.
- High positive predictive value (PPV) of 0.94 and sensitivity of 0.95 were observed.
Conclusions:
- An automated statistical model using electronic data can accurately predict physician clinical responsibility.
- This method offers a precise way to define patient panels for primary care physicians.
- Further validation in diverse healthcare settings is recommended.
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