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Background/Aims: Hemodialysis (HD) patients are hospitalized more frequently than patients with other chronic diseases, averaging 11.5 hospital days/patient/year. Hospital costs attributable to renal failure in the US exceed $2 billion per year. The present healthcare climate continues to force dialysis providers to focus on these issues in order to optimize patient care while limiting cost. Methods: We used a novel method for analyzing hospitalization risk, a multiple-event Cox proportional hazards model, to identify factors that influenced hospitalization in a HD unit population over a two-year period. This model allows individual patients to contribute multiple failure events to the model while controlling for the serial dependency of events. Results: 178 HD patients were retrospectively examined. There were 381 hospitalizations during the study period, averaging out to 1.9 hospitalizations and 10.5 hospital days/patient-year. Substance abuse and diabetes conveyed the largest risks for hospitalization (diabetes RR: 2.09; substance abuse RR: 2.24) in the study cohort, exposing the necessity for examining practice patterns and behavioral interventions as means for improving HD patient care. Conclusion: Despite the small numbers of patients in this single-center HD population, the model achieved adequate statistical power. Therefore, it has the potential to serve as a continuous quality improvement (CQI) tool in particular HD patient sub-groups, or in individual HD units.

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