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Predicting rural health care utilization with archival data

D D Wright, R L Kane, A Kronhaus

Journal of Community Health

|January 1, 1982

Summary

Archival data can effectively predict rural health care utilization. Adding just one archival variable, the percentage of local births, significantly improved prediction accuracy to 95%.

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Area of Science:

Health Services Research
Rural Health
Predictive Modeling

Background:

Accurate prediction of rural health care utilization is crucial for resource allocation and planning.
Existing methods may be costly or require independent data collection.
Archival data offers a potentially low-cost alternative for feasibility assessments.

Purpose of the Study:

To evaluate the utility of archival data for predicting rural health care utilization.
To develop a cost-effective predictive model for healthcare planners.
To identify key archival variables that enhance utilization prediction.

Main Methods:

A regression model was employed to predict observed utilization using expected values derived from national age- and sex-specific rates.
Archival data, including historical utilization indicators and available services, were incorporated to refine predictions.
The predictive model was validated on independent rural communities after initial testing on eight counties.

Main Results:

The initial model, based on age- and sex-adjusted national rates, showed a high correlation (r = 0.92) with observed utilization.
Incorporating the percentage of local births significantly improved the model's predictive power.
The final predictor equation, including this single archival variable, explained approximately 95% of the variance in observed rural health care utilization.

Conclusions:

Archival data, particularly the percentage of local births, provides a highly accurate and cost-effective method for predicting rural health care utilization.
This approach offers a valuable tool for planners needing convenient market feasibility estimates for new healthcare projects.
The model facilitates the establishment of realistic intermediate goals and incentives during the early stages of project development.

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