Factors related to potentially preventable hospitalizations among the elderly.

OBJECTIVES

The authors examine whether the odds of having a hospitalization associated with an ambulatory care sensitive condition can be explained by observed differences in a Medicare beneficiary's predisposing, enabling, and need characteristics.

METHODS

A multivariate cross-sectional analysis of Medicare's administrative inpatient claims data and the Medicare Current Beneficiary Survey was conducted on a nationally representative sample of Medicare beneficiaries. Each Medicare beneficiary's hospital utilization was classified into one of three categories: (1) no hospital admissions; (2) hospitalized, but no hospitalizations for a potentially preventable condition; and (3) at least one potentially preventable hospitalization.

RESULTS

The results suggest that being older, black, or living either in a core standard metropolitan statistical area (SMSA) county or a rural county significantly increases the odds of a preventable hospitalization, whereas having attended college, or having only Medicare insurance coverage reduces the odds of a preventable hospitalization. Further, those individuals who assess their health status as poor, have had coronary heart disease, a myocardial infarction, or diabetes, and required assistance with two or more of the six basic activities of daily living are at a greater risk of a preventable hospitalization.

CONCLUSIONS

Policy efforts aimed at reducing the number of preventable hospitalizations among the elderly should address the complex health care delivery needs of those Medicare beneficiaries who have special health care needs because they are very old, black, live in core SMSA or rural counties, have poor overall health status, and have physical limitations. Efforts to reduce the number of Medicare beneficiaries who experience a preventable hospitalization may be cost-effective as these beneficiaries may account for up to 17.4% of Medicare's reimbursement for inpatient, outpatient, and physician services in our data set.