To determine whether profit status is associated with differences in hospital days per patient, an outcome that may also be influenced by provider financial goals.
United States Renal Data System Standard Analysis Files and Centers for Medicare and Medicaid Services cost reports.
We compared the number of hospital days per patient per year across for‐profit and nonprofit dialysis facilities during 2003. To address possible referral bias in the assignment of patients to dialysis facilities, we used an instrumental variable regression method and adjusted for selected patient‐specific factors, facility characteristics such as size and chain affiliation, as well as metrics of market competition.
All patients who received in‐center hemodialysis at any time in 2003 and for whom Medicare was the primary payer were included (=170,130; roughly two‐thirds of the U.S. hemodialysis population). Patients dialyzed at hospital‐based facilities and patients with no dialysis facilities within 30 miles of their residence were excluded.
Overall, adjusted hospital days per patient were 17±5 percent lower in nonprofit facilities. The difference between nonprofit and for‐profit facilities persisted with the correction for referral bias. There was no association between hospital days per patient per year and chain affiliation, but larger facilities had inferior outcomes (facilities with 73 or more patients had a 14±1.7 percent increase in hospital days relative to facilities with 35 or fewer patients). Differences in outcomes among for‐profit and nonprofit facilities translated to 1,600 patient‐years in hospital that could be averted each year if the hospital utilization rates in for‐profit facilities were to decrease to the level of their nonprofit counterparts.
Hospital days per patient‐year were statistically and clinically significantly lower among nonprofit dialysis providers. These findings suggest that the indirect incentives in Medicare's current payment system may provide insufficient incentive for for‐profit providers to achieve optimal patient outcomes.
