Population Characteristics and Organ Procurement Organization Performance Metrics.

IMPORTANCE

In 2020, the Centers for Medicare & Medicaid Services (CMS) issued a final rule updating the Organ Procurement Organization (OPO) Conditions for Coverage. This rule evaluates OPO performance based on an unadjusted donation rate and an age-adjusted transplant rate; however, neither considers other underlying population differences.

OBJECTIVE

To evaluate whether adjusting for age and/or area deprivation index yields the same tier assignments as the cause, age, and location consistent (CALC) tier used by CMS.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cross-sectional study examined the performance of 58 OPOs from 2018 to 2020 across the entire US. A total of 12 041 778 death records were examined from the 2017 to 2020 National Center for Health Statistics' Restricted Vital Statistics Detailed Multiple Cause of Death files; 399 530 of these met the definition of potential deceased donor. Information about 42 572 solid organ donors from the Scientific Registry of Transplant Recipients was also used. Statistical analysis was performed from January 2017 to December 2020.

EXPOSURE

Area deprivation of donation service areas and age of potential donors.

MAIN OUTCOME AND MEASURES

OPO performance as measured by donation and transplant rates.

RESULTS

A total of 399 530 potential deceased donors and 42 572 actual solid donor organs were assigned to 1 of 58 OPOs. Age and ADI adjustment resulted in 19.0% (11 of 58) to 31.0% (18 of 58) reclassification of tier ratings for the OPOs, with 46.6% of OPOs (27 of 58) changing tier ranking at least once during the 3-year period. Between 6.9% (4 of 58) and 12.1% (7 of 58) moved into tier 1 and up to 8.6% (5 of 58) moved into tier 3.

CONCLUSIONS AND RELEVANCE

This cross-sectional study of population characteristics and OPO performance metrics found that adjusting for area deprivation and age significantly changed OPO measured performance and tier classifications. These findings suggest that underlying population characteristics may alter processes of care and characterize donation and transplant rates independent of OPO performance. Risk adjustment accounting for population characteristics warrants consideration in prospective policy and further evaluation of quality metrics.