Cost of organ procurement and transplantation network data collection for a large transplant center

The prognostic value of kidney transplant center report cards

SRTR report cards provide the basis for quality measurement of US transplant centers. There is limited data evaluating the prognostic value of report cards, informing whether they are predictive of prospective patient outcomes. Using national SRTR data, we simulated report cards and calculated standardized mortality ratios (SMR) for kidney transplant centers over five distinct eras. We ranked centers based on SMR and evaluated outcomes for patients transplanted the year following reports. Recipients transplanted at the 50th, 100th and 200th ranked centers had 18% (AHR = 1.18, 1.13-1.22), 38% (AHR = 1.38, 1.28-1.49) and 91% (AHR = 1.91, 1.64-2.21) increased hazard for 1-year mortality relative to recipients at the top-ranked center. Risks were attenuated but remained significant for long-term outcomes. Patients transplanted at centers meeting low-performance criteria in the prior period had 40% (AHR = 1.40, 1.22-1.68) elevated hazard for 1-year mortality in the prospective period. Centers' SMR from the report card was highly predictive (c-statistics > 0.77) for prospective center SMRs and there was significant correlation between centers' SMR from the report card period and the year following (ρ = 0.57, p < 0.001). Although results do not mitigate potential biases of report cards for measuring quality, they do indicate strong prognostic value for future outcomes. Findings also highlight that outcomes are associated with center ranking across a continuum rather than solely at performance margins.

Report of a consensus conference on transplant program quality and surveillance

Public reports of organ transplant program outcomes by the US Scientific Registry of Transplant Recipients have been both groundbreaking and controversial. The reports are used by regulatory agencies, private insurance providers, transplant centers and patients. Failure to adequately adjust outcomes for risk may cause programs to avoid performing transplants involving suitable but high-risk candidates and donors. At a consensus conference of stakeholders held February 13-15, 2012, the participants recommended that program-specific reports be better designed to address the needs of all users. Additional comorbidity variables should be collected, but innovation should also be protected by excluding patients who are in approved protocols from statistical models that identify underperforming centers. The potential benefits of hierarchical and mixed-effects statistical methods should be studied. Transplant centers should be provided with tools to facilitate quality assessment and performance improvement. Additional statistical methods to assess outcomes at small-volume transplant programs should be developed. More data on waiting list risk and outcomes should be provided. Monitoring and reporting of short-term living donor outcomes should be enhanced. Overall, there was broad consensus that substantial improvement in reporting outcomes of transplant programs in the United States could and should be made in a cost-effective manner.

Predictive ability of pretransplant comorbidities to predict long-term graft loss and death

Whether to include additional comorbidities beyond diabetes in future kidney allocation schemes is controversial. We investigated the predictive ability of multiple pretransplant comorbidities for graft and patient survival. We included first-kidney transplant deceased donor recipients if Medicare was the primary payer for at least one year pretransplant. We extracted pretransplant comorbidities from Medicare claims with the Clinical Classifications Software (CCS), Charlson and Elixhauser comorbidities and used Cox regressions for graft loss, death with function (DWF) and death. Four models were compared: (1) Organ Procurement Transplant Network (OPTN) recipient and donor factors, (2) OPTN + CCS, (3) OPTN + Charlson and (4) OPTN + Elixhauser. Patients were censored at 9 years or loss to follow-up. Predictive performance was evaluated with the c-statistic. We examined 25 270 transplants between 1995 and 2002. For graft loss, the predictive value of all models was statistically and practically similar (Model 1: 0.61 [0.60 0.62], Model 2: 0.63 [0.62 0.64], Models 3 and 4: 0.62 [0.61 0.63]). For DWF and death, performance improved to 0.70 and was slightly better with the CCS. Pretransplant comorbidities derived from administrative claims did not identify factors not collected on OPTN that had a significant impact on graft outcome predictions. This has important implications for the revisions to the kidney allocation scheme.

Linking the US transplant registry to administrative claims data: expanding the potential of transplant research

OBJECTIVE

In the United States, data on transplanted and waitlisted patients collected by the Organ Procurement and Transplantation Network (OPTN) have been widely used in transplantation research. Administrative claims data, collected by health plans for reimbursement purposes, are also commonly used in health-services research. This study linked OPTN and private payer claims data to assess the relationship between data elements common to both sources.

METHODS

All transplanted or waitlisted patients in the registry were considered for inclusion. A multistep match algorithm was employed to link OPTN and payer data from years 1995 to 2004. Variables common to both datasets that contained relevant information for similar time periods were compared.

RESULTS

A total of 21,419 solid organ transplant recipients and 8808 waitlist patients were included in the final linked database. Organ type and demographic variable distributions in the linked dataset were similar to the overall OPTN database. Using claims as the reference group, sensitivity and specificity values were on average 0.72 and 0.69, respectively, and were highest for the indicators of immunosuppression use at discharge and follow-up.

CONCLUSION

This comparison of payer data with information reported by transplant centers to the OPTN provides important insight into the value of both data sources. Using administrative claims to augment the registry data with utilization and cost information will be useful for evaluation of both economic and clinical endpoints in solid organ transplantation.