Photo Credit: Sefa Ozel
The following is a summary of “A Surgical Desirability of Outcome Ranking (DOOR) Reveals Complex Relationships Between Race/Ethnicity, Insurance Type, and Neighborhood Deprivation” published in the February 2024 issue of Surgery by Jacobs, et al.
Create an ordinal Desirability of Outcome Ranking (DOOR) for surgery results to examine the complicated links between Social Determinants of Health. Health differences might not be found in studies examining single or binary outcomes. For a study, researchers sought to look at three healthcare system cohort studies using NSQIP from 2013 to 2019 that were linked with EHR and risk-adjusted for frailty, preoperative acute serious conditions (PASC), case status, and operative stress. They also looked at the relationships between race/ethnicity, insurance type (Private 13,957; Medicare 15,198; Medicaid 28,35; Uninsured 29,63), and the Area Deprivation Index (ADI) on DOOR and the binary Textbook Outcomes (TO).
Patients who lived in areas with a high level of deprivation (ADI>85) were more likely to have PASC (aOR=1.13, CI=1.02–1.25, P<0.001) and urgent or emergency cases (aOR=1.23, CI=1.16–1.31, P<0.001). Patients identified as Black versus White and on Medicare, Medicaid, or Uninsured versus Private insurance were likelier to have better or lower acceptable DOOR values. Before insurance was considered, patients with an ADI above 85 had a lower chance of TO (aOR=0.91, CI=0.85–0.97, P=0.006). On the other hand, patients with an ADI of more than 85 had a higher chance of a higher DOOR (aOR=1.07, CI=1.01–1.14, P<0.021) even after insurance was taken into account. Still, the odds were the same after PASC and urgent/emergency cases were considered.
DOOR showed that race or ethnicity, type of insurance, and lack of resources in the neighborhood combine in complicated ways. ADI levels above 85 were linked to worse DOOR results, but TO did not show this effect of ADI. The results showed that presentation sharpness is a key factor in why patients from poor areas without insurance have worse outcomes. Quality measures could be more accurate if they considered the risk of living in poor areas and having urgent or emergency treatments.
