Transplant Center Performance (transplant + center_performance)

Distribution by Scientific Domains


Selected Abstracts


Innovations in the Assessment of Transplant Center Performance: Implications for Quality Improvement

AMERICAN JOURNAL OF TRANSPLANTATION, Issue 4p2 2009
D. A. Axelrod
Continuous quality improvement efforts have become a central focus of leading health care organizations. The transplant community has been a pioneer in periodic review of clinical outcomes to ensure the optimal use of limited donor organs. Through data collected from the Organ Procurement and Transplantation Network (OPTN) and analyzed by the Scientific Registry of Transplant Recipients (SRTR), transplantation professionals have intermittent access to specific, accurate and clinically relevant data that provides information to improve transplantation. Statistical process control techniques, including cumulative sum charts (CUSUM), are designed to provide continuous, real-time assessment of clinical outcomes. Through the use of currently collected data, CUSUMs can be constructed that provide risk-adjusted program-specific data to inform quality improvement programs. When retrospectively compared to currently available data reporting, the CUSUM method was found to detect clinically significant changes in center performance more rapidly, which has the potential to inform center leadership and enhance quality improvement efforts. [source]


Effect of Comorbidity Adjustment on CMS Criteria for Kidney Transplant Center Performance

AMERICAN JOURNAL OF TRANSPLANTATION, Issue 3 2009
E. D. Weinhandl
The Centers for Medicare & Medicaid Services (CMS) uses kidney transplant outcomes, unadjusted for standard comorbidity, to identify centers with sufficiently higher than expected rates of graft failure or patient death (underperforming centers) that they may be denied Medicare participation. To examine whether comorbidity adjustment would affect this determination, we identified centers that would have failed to meet 1-year graft survival criteria, 1992,2005, with and without adjustment using the Elixhauser Comorbidity Index. Adjustment was performed for each U.S. center for 24 consecutive (overlapping) 30-month intervals, including 102 176 adult deceased-donor and living-donor kidney transplant patients with Medicare as primary payer 6 months pretransplant. For each interval, we determined percent positive agreement (PPA) (number of centers underperforming both before and after adjustment, divided by number underperforming either before or after adjustment). Overall PPA was 80.8%, with no evidence of a trend over time. Among deceased-donor recipients, 10 of 31 comorbid conditions were predictors of graft failure in at least half of the intervals, as were six conditions among living-donor recipients. Lack of comorbidity adjustment may disadvantage centers willing to accept higher risk patients. Risk of jeopardizing Medicare funding may give centers incentive to deny transplantation to higher risk patients. [source]


Prediction Models Assessing Transplant Center Performance: Can a Little Knowledge be a Dangerous Thing?

AMERICAN JOURNAL OF TRANSPLANTATION, Issue 2 2006
J. D. Schold
No abstract is available for this article. [source]


CMS oversight, OPOs and transplant centers and the law of unintended consequences

CLINICAL TRANSPLANTATION, Issue 6 2009
Richard J. Howard
Abstract:, The Health Resources and Services Administration launched collaboratives with the goals of increasing donation rates, increasing the number of organs transplanted, eliminating deaths on the waiting list and improving outcomes. The Center for Medicare and Medicaid Services (CMS) recently published requirements for organ procurement organizations (OPOs) and transplant centers. Failure to meet CMS performance measures could result in OPOs losing their service area or transplant centers losing their CMS certification. CMS uses analyses by the Scientific Registry of Transplant Recipients (SRTR) to evaluate a transplant center's performance based on risk-adjusted outcomes. However, CMS also uses a more liberal (one-sided) statistical test rendering more centers likely to qualify as low performing. Furthermore, the SRTR model does not incorporate some important patient variables in its statistical model which may result in biased determinations of quality of care. Cumulatively, there is much unexplained variation for transplant outcomes as suggested by the low predictive ability of survival models compared to other disease contexts. OPOs and transplant centers are unlikely to quietly accept their elimination. They may take certain steps that can result in exclusion of candidates who might otherwise benefit from transplantation and/or result in fewer transplants through restricted use of organs thought to carry higher risk of failure. CMS should join with transplant organizations to ensure that the goals of the collaborative are not inhibited by their performance measures. [source]