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Improving the SRTR Methodology Used To Identify Potentially Underperforming Transplant Programs in the United States

N. Salkowski, E. Edwards, T. Leighton, A. Israni, B. Kasiske, J. Snyder

Scientific Registry of Transplant Recipients, Minneapolis Medical Research Foundation, Minneapolis, MN
United Network for Organ Sharing, Richmond, VA

Meeting: 2013 American Transplant Congress

Abstract number: 546

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In Feb. 2012, SRTR and OPTN jointly hosted a consensus conference on transplant program quality and surveillance. One recommendation was to study Bayesian hierarchical modeling strategies. Coincident with the conference, CMS commissioned a report from the Committee of Presidents of Statistical Societies entitled, "Statistical Issues on Assessing Hospital Performance," which also recommended a Bayesian approach. SRTR is thus exploring Bayesian modeling strategies. The current methodology yields an observed/expected ratio (O/E) with a P value from a hypothesis test of whether the program is performing as expected. The Bayesian approach produces a distribution of the probability that a center is underperforming; the figure shows 3 examples.

The posterior mean hazard ratio is indicated on each histogram along with a 95% credible interval. A decision rule can then be constructed to identify programs for further scrutiny. SRTR explored a decision rule to review programs with a >75% probability that they are performing >25% worse than expected or a >10% probability that they are performing >150% worse than expected. We compared this approach with the current flagging methodology against final determinations from past OPTN reviews from 2007 (Table 1).

Comparison with MPSC final actions for centers flagged Jan 2007-Jan 2008
Program Current False Positives Bayesian False Positives Current True Positives Bayesian True Positives
Heart 56 24 43 25
Kidney 82 41 73 70
Liver 51 18 38 27
Lung 21 12 18 15
Current = current flagging methodology. A false positive indicated a program was flagged by the formula specified in the OPTN bylaws, but the MPSC took no action. A true positive indicated a program was flagged and the MPSC took some action (e.g., informal discussion, peer visit) to follow-up with the program.

Simulations suggest that the Bayesian flag has a low false-positive flag rate for all center volumes and better detects underperformance for mid-volume programs. SRTR will continue exploring this approach.

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To cite this abstract in AMA style:

Salkowski N, Edwards E, Leighton T, Israni A, Kasiske B, Snyder J. Improving the SRTR Methodology Used To Identify Potentially Underperforming Transplant Programs in the United States [abstract]. Am J Transplant. 2013; 13 (suppl 5). https://atcmeetingabstracts.com/abstract/improving-the-srtr-methodology-used-to-identify-potentially-underperforming-transplant-programs-in-the-united-states/. Accessed April 20, 2021.

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