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Dialysis Facility Characteristics and Variation in Employment Rates: A National Study

Rehabilitation/Quality of Life Special Studies Center, United States Renal Data System, Emory University, Atlanta, Georgia

Correspondence: Dr. Nancy Kutner, Department of Rehabilitation Medicine, Emory University, Atlanta, GA 30322. Phone: 404-712-5561; Fax: 404-712-5895; E-mail: nkutner{at}emory.edu

Background: Investigation of factors associated with variation in dialysis patient employment has focused primarily on patient-level factors. Little is known about facility-level factors that may be associated with patient employment.

Design, setting, participants, and measurements: The ESRD Facility Survey (CMS-2744A) began in 2004 to collect counts of employed patients aged 18 to 54, in addition to dialysis unit census, types and timing of treatments offered, and staffing. Using the 2004 ESRD Facility Survey File, we investigated dialysis unit characteristics and facility employment rate of patients aged 18 to 54 in a logistic regression analysis that included hospital-based chronic renal care facilities, nonhospital renal disease treatment centers, independent special purpose renal dialysis facilities, and renal disease treatment centers.

Results: Across all facilities, 18.9% of prevalent patients aged 18 to 54 were employed, but facility employment rates ranged from 0 to 100%. Facility employment rate was positively associated independently with availability of a 5 p.m. or later dialysis shift (odds ratio (OR) 1.54, 95% confidence interval (CI) 1.42 to 1.68), availability of peritoneal dialysis or home hemodialysis (HD) training (OR 1.19, 95% CI 1.11 to 1.28), and provision of frequent HD (OR 1.26, 95% CI 1.07 to 1.49), after adjusting for patient/social worker ratio, rurality of unit location, and unit size. In addition, patient receipt of Vocational Rehabilitation (VR) services was more often reported in facilities with higher employment rates.

Conclusions: Promoting gainful employment among ESRD patients continues to be a quality improvement need. A dataset that allows adjustment for patient-level variables would facilitate increased understanding of the contribution of dialysis facility variables to patient employment.