Saturday, October 5, 2024
10/5/2024
The use of algorithmic decision-making (ADM) tools poses unique risks for people with disabilities, especially when these tools are incorporated into the decision-making process for allocation of home and community-based services (HCBS). However, few studies of algorithmic bias have focused specifically on disability, and existing research on algorithmic bias and disability has primarily taken the form of case studies or theoretical analyses. My dissertation addresses this gap by using a three-paper format to explore how disabled people conceptualize fairness in situations where algorithmic tools are frequently adopted, and analyzing two different algorithmic tools and their impact on people with disabilities. The project I describe in my narrative is one of these three studies, and examines how changing the process for allocation of HCBS to be strictly reliant on an algorithmic tool in Arkansas impacted (1) hours of in-home services, and (2) related outcomes (preventable ED visits, hospitalization, and institutional placement). Although this change received media attention as a result of lawsuits filed against the state following the change, there has not yet been systematic research on the impact of this or other algorithmic tools used in HCBS decision-making on beneficiaries. Growing use of both the specific tool adopted in Arkansas and similar algorithmic tools means that understanding how their integration into HCBS decision-making affects beneficiaries is a critical area of study for disability outcomes research. Findings from my dissertation will contribute to the emerging discussion of regulation of ADM tools and support efforts to reduce disability bias within scoring tools that are incorporated into health, healthcare, and HCBS decision-making. Additionally, results may help demonstrate the need for greater consideration of disability in ways that go beyond seeing it as an outcome or a risk factor, and will add to the existing conversation around developing an understanding of people with disabilities as a health disparity population.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
