Acceptability of linking individual credit, financial, and public records data to healthcare records for suicide risk machine learning models.

Autor:	Penfold RB; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101-1466, United States., Yoo HI; Loughborough Business School, Loughborough University, Loughborough, Leicestershire LE11 3TU, United Kingdom., Richards JE; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101-1466, United States., Crossnohere NL; College of Medicine, The Ohio State University, Columbus, OH 43210, United States., Johnson E; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101-1466, United States., Pabiniak CJ; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101-1466, United States., Renz AD; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101-1466, United States., Campoamor NB; College of Medicine, The Ohio State University, Columbus, OH 43210, United States., Simon GE; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101-1466, United States., Bridges JFP; College of Medicine, The Ohio State University, Columbus, OH 43210, United States.; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, United States.
Jazyk:	angličtina
Zdroj:	JAMIA open [JAMIA Open] 2024 Oct 21; Vol. 7 (4), pp. ooae113. Date of Electronic Publication: 2024 Oct 21 (Print Publication: 2024).
DOI:	10.1093/jamiaopen/ooae113
Abstrakt:	Objectives: Individual-level information about negative life events (NLE) such as bankruptcy, foreclosure, divorce, and criminal arrest might improve the accuracy of machine learning models for suicide risk prediction. Individual-level NLE data is routinely collected by vendors such as Equifax. However, little is known about the acceptability of linking this NLE data to healthcare data. Our objective was to assess preferences for linking external NLE data to healthcare records for suicide prevention. Materials and Methods: We conducted a discrete choice experiment (DCE) among Kaiser Permanente Washington (KPWA) members. Patient partners assisted in the design and pretesting of the DCE survey. The DCE included 12 choice tasks involving 4 data linking program attributes and 3 levels within each attribute. We estimated latent class conditional logit models to derive preference weights. Results: There were 743 participants. Willingness to link data varied by type of information to be linked, demographic characteristics, and experience with NLE. Overall, 65.1% of people were willing to link data and 34.9% were more private. Trust in KPWA to safeguard data was the strongest predictor of willingness to link data. Discussion: Most respondents supported linking NLE data for suicide prevention. Contrary to expectations, People of Color and people who reported experience with NLEs were more likely to be willing to link their data. Conclusions: A majority of participants were willing to have their credit and public records data linked to healthcare records provided that conditions are in place to protect privacy and autonomy. Competing Interests: R.B.P. reports receiving research funding to his institution from SAGE Therapeutics and the Lundbeck Foundation. (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu