A mixed-methods study exploring the benefits, drawbacks, and utilization of data in care: Findings from the EPI-CAL early psychosis learning health care network

Sabrina Ereshefsky, Regina Gemignani, Mark Savill, Katherine C. Sanford, Lindsay M. Banks, Valerie L. Tryon, Kathleen E. Nye, Katherine M. Pierce, Madison J. Miles, Chelyah Miller, Khanh Linh H. Nguyen, Nitasha Sharma, Merissa Kado-Walton, Christopher K. Hakusui, Leigh Smith, Viviana E. Padilla, Amanda P. McNamara, Maliha Safdar, Andrew J. Padovani, Rachel L. LoewyAdam B. Wilcox, Laura M. Tully, Tara A. Niendam

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Using data collected in routine care delivery to inform treatment is a key feature of a learning health system (LHS). In this study, we explored the experiences of service users and providers adopting measurement-based care (MBC) in early psychosis (EP) specialty care settings. Qualitative interviews were conducted with 32 providers and 12 service users across 18 programs in the Early Psychosis Intervention Network of California (EPI-CAL). These findings were compared with quantitative data from Beehive, EPI-CAL's data collection and review application. Regarding the clinical benefits of MBC in EP, three broad themes were identified – supporting safety monitoring and response, the assessment process, and delivery of psychotherapy. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation Outside of direct clinical care, Beehive was considered to support clinical supervision and external reporting, while service users reported data collection facilitated selfreflection. In the quantitative Beehive application data collected from 23 EP programs, high utilization of the safety alert system was evident (349 alerts in total, of which 338 [96.85 %] were resolved at a median of 2.03 days). However, service users' key survey data was only reviewed by assigned providers in 32.22 % (142 of 441) of cases. While providers and service users saw many benefits to Beehive, utilization was highly inconsistent outside of the alert system. Going forward, further consideration of how best to support EP providers to consistently use data in care is necessary to maximize the utility of the LHS approach and positively impact outcomes.

Original languageEnglish
Pages (from-to)157-166
Number of pages10
JournalSchizophrenia research
Volume276
DOIs
StatePublished - Feb 2025

Keywords

  • Coordinated specialty care
  • Early psychosis
  • eHealth
  • EPINET
  • Learning health systems
  • Measurement-based care
  • Qualitative data

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