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

ABSTRACT:

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 le

SUBMITTER: Penfold RB 

PROVIDER: S-EPMC11493183 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature