RESUMEN
Algorithms for guiding health care decisions have come under increasing scrutiny for being unfair to certain racial and ethnic groups. The authors describe their multistep process, using data from 3,465 individuals, to reduce racial and ethnic bias in an algorithm developed to identify state Medicaid beneficiaries experiencing homelessness and chronic health needs who were eligible for coordinated health care and housing supports. Through an iterative process of adjusting inputs, reviewing outputs with diverse stakeholders, and performing quality assurance, the authors developed an algorithm that achieved racial and ethnic parity in the selection of eligible Medicaid beneficiaries.
Asunto(s)
Algoritmos , Personas con Mala Vivienda , Medicaid , Humanos , Estados Unidos , Personas con Mala Vivienda/estadística & datos numéricos , Medicaid/estadística & datos numéricos , Racismo , Accesibilidad a los Servicios de Salud/estadística & datos numéricos , Disparidades en Atención de Salud/etnología , ViviendaRESUMEN
OBJECTIVES: This study aimed to examine outcomes of a pilot program designed to increase inpatient medications for opioid use disorder (MOUD) induction and to support MOUD adherence after discharge. METHODS: This retrospective cohort analysis examined Medicaid adults diagnosed with opioid use disorder discharged from 2 freestanding inpatient withdrawal management facilities between October 1, 2018, and December 31, 2019. Participants had ≥90 days of continuous Medicaid enrollment before and after admission. Odds ratios (ORs) examined associations of inpatient MOUD induction with discharge against medical advice, 7- and 30-day all-cause hospital readmission, and postdischarge MOUD adherence. Mixed-effect models examined changes associated with MOUD induction and postdischarge MOUD adherence in acute service utilization and opioid overdose in the 90-day postdischarge period. RESULTS: Of the 2332 patients discharged, 493 started MOUD inpatient care (21.1%), with most initiating buprenorphine (76.5%). Induction of MOUD was associated with a lower likelihood of discharge against medical advice (OR, 0.49; 95% confidence interval [CI], 0.37-0.64), 30-day all-cause hospital readmission (OR, 0.61; 95% CI, 0.47-0.80), and higher odds of postdischarge MOUD adherence (OR, 3.83; 95% CI, 3.06-4.81). In the 90 days after discharge, MOUD adherent patients had significant reductions in emergency department visits for behavioral health, inpatient days, withdrawal management episodes, and opioid overdoses compared with the 90-day preadmission period. CONCLUSIONS: Inpatient MOUD induction is associated with a higher likelihood of short-term MOUD adherence after discharge, which in turn is associated with significant reductions in short-term service utilization and opioid overdose after discharge.