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Adding Laboratory Data to Hospital Claims Data to Improve Risk Adjustment of Inpatient/30-Day Postdischarge Outcomes.

Michael Pine¹, Donald E Fry¹, Edward L Hannan²

¹1 MPA Healthcare Solutions, Inc., Chicago, IL.

American Journal of Medical Quality : the Official Journal of the American College of Medical Quality

|February 27, 2016

Summary

Adding numerical laboratory data to administrative claims significantly improves inpatient predictive models for mortality and prolonged length of stay. This enhancement is crucial for better clinical outcome predictions in healthcare.

Keywords:

cardiovascular disease clinically enhanced claims data patient outcomes patient safety (measurement)quality of care risk adjustment

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Area of Science:

Health Informatics
Clinical Epidemiology
Biostatistics

Background:

Administrative claims data are widely used for inpatient predictive modeling.
Limitations exist in predicting patient outcomes solely with administrative data.
Numerical laboratory data offer potential for enhancing predictive accuracy.

Purpose of the Study:

To compare the predictive performance of models using administrative data alone versus administrative data plus numerical laboratory variables.
To assess model improvements for inpatient mortality and prolonged length of stay.
To evaluate model performance across specific cardiac conditions.

Main Methods:

Developed predictive models for inpatient/30-day mortality and risk-adjusted prolonged length of stay.
Utilized administrative data exclusively for baseline models.
Incorporated numerical laboratory variables alongside administrative data for enhanced models.
Compared model discrimination, calibration, and goodness of fit.

Main Results:

Models incorporating laboratory data demonstrated improved discrimination and calibration for both mortality and prolonged length of stay.
Enhanced models outperformed administrative data-only models across acute myocardial infarction, congestive heart failure, coronary artery bypass grafting, and percutaneous cardiac interventions.
The most significant improvements in goodness of fit were observed in acute myocardial infarction and percutaneous cardiac interventions.

Conclusions:

Integrating numerical laboratory data with administrative claims data offers a practical and efficient method to clinically enhance inpatient outcome prediction.
This approach improves the accuracy of models for mortality and length of stay, particularly for acute myocardial infarction and percutaneous cardiac interventions.
The widespread adoption of electronic medical records facilitates the incorporation of laboratory data for superior predictive modeling.