Address correspondence to Wan-Tzu Connie Tai, Ph.D., Department of Clinical Analysis, Kaiser Permanente, 7469 Alpine Way, Tujunga CA 91042. Frank W. Porell, Ph.D., is with the Department of Gerontology, McCormack Graduate School of Policy Studies, University of Massachusetts, Boston. E. Kathleen Adams, Ph.D., is with the Department of Health Policy and Management, Rollins School of Public Health, Emory University, Atlanta.
Hospital Choice of Rural Medicare Beneficiaries: Patient, Hospital Attributes, and the Patient–Physician Relationship
Version of Record online: 8 NOV 2004
Health Services Research
Volume 39, Issue 6p1, pages 1903–1922, December 2004
How to Cite
Tai, W.-T. C., Porell, F. W. and Adams, E. K. (2004), Hospital Choice of Rural Medicare Beneficiaries: Patient, Hospital Attributes, and the Patient–Physician Relationship. Health Services Research, 39: 1903–1922. doi: 10.1111/j.1475-6773.2004.00324.x
This work was supported by dissertation grant (IPF 98-103) from the Health Care Financing Administration.
- Issue online: 8 NOV 2004
- Version of Record online: 8 NOV 2004
- Hospital choice;
- hospital bypassing;
- rural health;
- conditional choice model
Objective. To examine how patient and hospital attributes and the patient–physician relationship influence hospital choice of rural Medicare beneficiaries.
Data Sources. Medicare Current Beneficiary Survey (MCBS), Health Care Financing Administration (HCFA) Provider of Services (POS) file, American Hospital Association (AHA) Annual Survey, and Medicare Hospital Service Area (HSA) files for 1994 and 1995.
Study Design. The study sample consisted of 1,702 hospitalizations of rural Medicare beneficiaries. McFadden's conditional logit model was used to analyze hospital choices of rural Medicare beneficiaries. The model included independent variables to control for patients' and hospitals' attributes and the distance to hospital alternatives.
Principal Findings. The empirical results show strong preferences of aged patients for closer hospitals and those of greater scale and service capacity. Patients with complex acute medical conditions and those with more resources were more likely to bypass their closest rural hospitals. Beneficiaries were more likely to bypass their closest rural hospital if they had no regular physician, had a shorter patient–physician tie, were dissatisfied with the availability of health care, and had a longer travel time to their physician's office.
Conclusions. The significant influences of patients' socioeconomic, health, and functional status, their satisfaction with and access to primary care, and their strong preferences for certain hospital attributes should inform federal program initiatives about the likely impacts of policy changes on hospital bypassing behavior.