Assessment of Disruptive Life Events for Individuals Diagnosed With Schizophrenia or Bipolar I Disorder Using Data From a Consumer Credit Reporting Agency

Abstract

ImportanceThere is a dearth of population-level data on major disruptive life events (defined here as arrests by a legal authority, address changes, bankruptcy, lien, and judgment filings) for patients with bipolar I disorder (BPI) or schizophrenia, which has limited studies on mental health and treatment outcomes.ObjectiveTo conduct a population-level study on disruptive life events by using publicly available data on disruptive life events, aggregated by a consumer credit reporting agency in conjunction with electronic health record (EHR) data.Design, Setting, and ParticipantsThis study used EHR data from 2 large, integrated health care systems, Kaiser Permanente Southern California and Henry Ford Health. Cohorts of patients diagnosed from 2007 to 2019 with BPI or schizophrenia were matched 1:1 by age at analysis, age at diagnosis (if applicable), sex, race and ethnicity, and Medicaid status to (1) an active comparison group with diagnoses of major depressive disorder (MDD) and (2) a general health (GH) cohort without diagnoses of BPI, schizophrenia, or MDD. Patients with diagnoses of BPI or schizophrenia and their respective comparison cohorts were matched to public records data aggregated by a consumer credit reporting agency (98% match rate). Analysis took place between November 2020 and December 2022.Main Outcomes and MeasuresThe differences in the occurrence of disruptive life events among patients with BPI or schizophrenia and their comparison groups.ResultsOf 46 167 patients, 30 008 (65%) had BPI (mean [SD] age, 42.6 [14.2] years) and 16 159 (35%) had schizophrenia (mean [SD], 41.4 [15.1] years). The majoriy of patients were White (30 167 [65%]). In addition, 18 500 patients with BPI (62%) and 6552 patients with schizophrenia (41%) were female. Patients with BPI were more likely to change addresses than patients in either comparison cohort (with the incidence ratio being as high as 1.25 [95% CI, 1.23-1.28]) when compared with GH cohort. Patients with BPI were also more likely to experience any of the financial disruptive life events with odds ratio ranging from 1.15 [95% CI, 1.07-1.24] to 1.50 [95% CI, 1.42-1.58]). The largest differences in disruptive life events were seen in arrests of patients with either BPI or schizophrenia compared with GH peers (3.27 [95% CI, 2.84-3.78] and 3.04 [95% CI, 2.57-3.59], respectively). Patients with schizophrenia had fewer address changes and were less likely to experience a financial event than their matched comparison cohorts.Conclusions and RelevanceThis study demonstrated that data aggregated by a consumer credit reporting agency can support population-level studies on disruptive life events among patients with BPI or schizophrenia.

Stressful life events in electronic health records: a scoping review

“…These citations were focused on statistical analysis. Another publication linked a credit history report to identify serious nancial events in patients' lives, such as bankruptcy [35]. One more citation utilized the interview format for events identi cation and compared them to what was documented in EHR and found that health records "generally failed to include social contexts salient to patients" [36].…”

Stressful life events in electronic health records: a scoping review

“…One more citation utilized the interview format for events identi cation and compared them to what is documented in EHR and found that health records "generally failed to include social contexts salient to patients" [29]. Another publication linked a credit history report to identify serious nancial events in patients' lives, such as bankruptcy [30]. One citation [31] discussed issues of using external data sources linked to EHR for capturing " nancial, legal, life event and sociodemographic data" to improve suicide screening models.…”

Stressful life events in electronic health records: a scoping review

“…These citations were focused on statistical analysis. Another publication linked a credit history report to identify serious financial events in patients’ lives, such as bankruptcy [ 35 ]. One more citation utilized the interview format for events identification and compared them to what was documented in EHR and found that health records “generally failed to include social contexts salient to patients” [ 36 ].…”