Mitigating Racial Bias in Health Care Algorithms: Improving Fairness in Access to Supportive Housing.

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.

Intensive Outpatient Treatment (IOP) of Behavioral Health (BH) Problems: Engagement Factors Predicting Subsequent Service Utilization.

The purpose of the study is to 1) better understand patterns of utilization of Intensive Outpatient Treatment (IOP) Programs and Services in the State of Connecticut by adult Medicaid recipients experiencing a serious mental illness, substance use disorder, or co-occurring disorders; and 2) to determine the relationship between the duration of an IOP episode and connection to care rates for higher (i.e., rehospitalization) or lower levels of care following discharge.