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Procurement characteristics of high- and low-performing OPOs as seen in OPTN/SRTR data.

Raymond J LynchBrianna L DobyDavid S GoldbergKevin J LeeArielle CimenoSeth J Karp
Published in: American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons (2021)
To meet new Centers for Medicare and Medicaid Services (CMS) metrics, organ procurement organizations (OPOs) will benefit from understanding performance across decedent and hospital types. We sought to determine the utility of existing data-reporting structures for this purpose by reviewing Scientific Registry of Transplant Recipient (SRTR) OPO-Specific Reports (OSRs) from 2013 to 2019. OSRs contain both the Standardized donation rate ratio (SDRR) metric and OPO-reported numbers of "eligible deaths" and donors by hospital. Donor hospitals were characterized using information from Homeland Infrastructure Foundation-Level Data, Dartmouth Atlas Hospital Service Area data, and the US Census Bureau. Hospital data reported by OPOs showed 51% higher eligible death donors and 140% higher noneligible death donors per 100 inpatient beds in CMS ranked top versus bottom-quartile OPOs. Top-quartile OPOs by the CMS metric recovered 78% more donors than those in the bottom quartile, but were indistinguishable by SDRR rankings. These differences persisted across hospital sizes, trauma case mix, and area demographics. OPOs with divergent performance were indistinguishable over time by SDRR, but showed changes to hospital-level recovery patterns in SRTR data. Contemporaneous recognition of underperformance across hospitals may provide important and actionable data for regulators and OPOs for focused quality improvement projects.
Keyphrases
  • healthcare
  • electronic health record
  • adverse drug
  • big data
  • acute care
  • mental health
  • palliative care
  • machine learning
  • data analysis
  • artificial intelligence
  • social media
  • patient safety