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Challenges and benefits of adding laboratory data to a mortality risk adjustment method
Elizabeth McCullough1, Christopher Sullivan, Pamela Banning
13M Health Information Systems, Inc, Wallingford, Connecticut 06492, USA.
Quality Management in Health Care
|October 6, 2011
Summary
Linking electronic laboratory data with claims data improves hospital mortality predictions. This study demonstrates the feasibility and modest statistical benefits of integrating these data sources for enhanced risk of mortality assessments.
Area of Science:
- Health Informatics
- Biostatistics
- Healthcare Administration
Background:
- Growing need for improved hospital mortality rate comparisons.
- Current risk of mortality (ROM) models lack comprehensive data integration.
- Focus on enhancing statistical performance and clinical acceptance of mortality predictions.
Purpose of the Study:
- Assess feasibility of linking electronic laboratory data with claims data.
- Identify specific laboratory data elements that improve mortality predictions.
- Enhance the accuracy of All-Patient Refined Diagnosis Related Groups (APRDRG) ROM classifications.
Main Methods:
- Recruited 15 Florida hospitals for data linkage.
- Standardized computer code terminology for laboratory data.
- Merged laboratory data with administrative claims data for patient-level analysis.
- Evaluated improvements in APRDRG ROM predictions using combined data.
Main Results:
- Successfully linked electronic laboratory data with standard claims data.
- Addition of 11 clinical laboratory tests improved the C statistic by 0.574%.
- Observed a 4.53% increase in R2 with the integrated data, indicating enhanced predictive power.
Conclusions:
- Linking laboratory data elements with claims data is feasible.
- This integration modestly improves commonly used risk of mortality models.
- Supports enhanced ROM assessments through data fusion for public reporting.
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