Chandy Ellimoottil1, Zaojun Ye2, Apurba K Chakrabarti3, Michael J Englesbe4, David C Miller2, John T Wei5, Amit K Mathur6. 1. Department of Urology, University of Michigan, Ann Arbor, MI; Center for Healthcare Outcomes & Policy, University of Michigan, Ann Arbor, MI. Electronic address: cellimoo@med.umich.edu. 2. Department of Urology, University of Michigan, Ann Arbor, MI; Center for Healthcare Outcomes & Policy, University of Michigan, Ann Arbor, MI. 3. Department of Surgery, Section of Transplantation, University of Michigan, Ann Arbor, MI. 4. Center for Healthcare Outcomes & Policy, University of Michigan, Ann Arbor, MI; Department of Surgery, Section of Transplantation, University of Michigan, Ann Arbor, MI. 5. Department of Urology, University of Michigan, Ann Arbor, MI. 6. Division of Transplant Surgery, Department of Surgery, Mayo Clinic, Phoenix, AZ; Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Phoenix, AZ.
Abstract
OBJECTIVE: To examine the magnitude and sources of inpatient cost variation for kidney transplantation. METHODS: We used the 2005-2009 Nationwide Inpatient Sample to identify patients who underwent kidney transplantation. We first calculated the patient-level cost of each transplantation admission and then aggregated costs to the hospital level. We fit hierarchical linear regression models to identify sources of cost variation and to estimate how much unexplained variation remained after adjusting for case-mix variables commonly found in administrative datasets. RESULTS: We identified 8866 living donor (LDRT) and 5589 deceased donor (DDRT) renal transplantations. We found that higher costs were associated with the presence of complications (LDRT, 14%; P <.001; DDRT, 24%; P <.001), plasmapheresis (LDRT, 27%; P <.001; DDRT, 27%; P <.001), dialysis (LDRT, 4%; P <.001), and prolonged length of stay (LDRT, 84%; P <.001; DDRT, 82%; P <.001). Even after case-mix adjustment, a considerable amount of unexplained cost variation remained between transplant centers (DDRT, 52%; LDRT, 66%). CONCLUSION: Although significant inpatient cost variation is present across transplant centers, much of the cost variation for kidney transplantation is not explained by commonly used risk-adjustment variables in administrative datasets. These findings suggest that although there is an opportunity to achieve savings through payment reforms for kidney transplantation, policymakers should seek alternative sources of information (eg, clinical registry data) to delineate sources of warranted and unwarranted cost variation. Published by Elsevier Inc.
OBJECTIVE: To examine the magnitude and sources of inpatient cost variation for kidney transplantation. METHODS: We used the 2005-2009 Nationwide Inpatient Sample to identify patients who underwent kidney transplantation. We first calculated the patient-level cost of each transplantation admission and then aggregated costs to the hospital level. We fit hierarchical linear regression models to identify sources of cost variation and to estimate how much unexplained variation remained after adjusting for case-mix variables commonly found in administrative datasets. RESULTS: We identified 8866 living donor (LDRT) and 5589 deceased donor (DDRT) renal transplantations. We found that higher costs were associated with the presence of complications (LDRT, 14%; P <.001; DDRT, 24%; P <.001), plasmapheresis (LDRT, 27%; P <.001; DDRT, 27%; P <.001), dialysis (LDRT, 4%; P <.001), and prolonged length of stay (LDRT, 84%; P <.001; DDRT, 82%; P <.001). Even after case-mix adjustment, a considerable amount of unexplained cost variation remained between transplant centers (DDRT, 52%; LDRT, 66%). CONCLUSION: Although significant inpatient cost variation is present across transplant centers, much of the cost variation for kidney transplantation is not explained by commonly used risk-adjustment variables in administrative datasets. These findings suggest that although there is an opportunity to achieve savings through payment reforms for kidney transplantation, policymakers should seek alternative sources of information (eg, clinical registry data) to delineate sources of warranted and unwarranted cost variation. Published by Elsevier Inc.
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