Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study.
Background: The National Health Service (NHS) Talking Therapies program treats people with common mental health problems in England according to "stepped care," in which lower-intensity interventions are offered in the first instance, where clinically appropriate. Limited resources and pressure to a...
| Publicado en: | JMIR Mental Health Vol. 11; pp. 1 - 17 |
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| Autores principales: | , , , |
| Formato: | critical path research tables/charts Journal Article |
| Publicado: |
JMIR Publications Inc.
2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180451846&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180451846 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23687959 MUYH jtl: JMIR Mental Health issn: 23687959 maglogo: N pubinfo: dt: 2024 vid: 11 pid: 21567 pub: JMIR Publications Inc. place: Toronto, Ontario artinfo: ui: 180451846 180451846 180451846 10.2196/53894 180451846 ppf: 1 ppct: 16 formats: tig: atl: Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study. aug: au: Yardley, Elizabeth Davis, Alice Eldridge, Chris Vasilakis, Christos affil: School of Management, University of Bath, Bath, United Kingdom sug: subj: Mental Disorders Therapy Psychotherapy National Health Programs Critical Path Data Mining Electronic Health Records Human Male Female Adult Middle Age Retrospective Design Record Review Prospective Studies Stakeholder Participation England Descriptive Statistics Comparative Studies Quality Assessment Practice Guidelines Data Analysis Software Routinely Collected Health Data Waiting Lists Referral and Consultation Mental Health Funding Source Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: Background: The National Health Service (NHS) Talking Therapies program treats people with common mental health problems in England according to "stepped care," in which lower-intensity interventions are offered in the first instance, where clinically appropriate. Limited resources and pressure to achieve service standards mean that program providers are exploring all opportunities to evaluate and improve the flow of patients through their service. Existing research has found variation in clinical performance and stepped care implementation across sites and has identified associations between service delivery and patient outcomes. Process mining offers a data-driven approach to analyzing and evaluating health care processes and systems, enabling comparison of presumed models of service delivery and their actual implementation in practice. The value and utility of applying process mining to NHS Talking Therapies data for the analysis of care pathways have not been studied. Objective: A better understanding of systems of service delivery will support improvements and planned program expansion. Therefore, this study aims to demonstrate the value and utility of applying process mining to NHS Talking Therapies care pathways using electronic health records. Methods: Routine collection of a wide variety of data regarding activity and patient outcomes underpins the Talking Therapies program. In our study, anonymized individual patient referral records from two sites over a 2-year period were analyzed using process mining to visualize the care pathway process by mapping the care pathway and identifying common pathway routes. Results: Process mining enabled the identification and visualization of patient flows directly from routinely collected data. These visualizations illustrated waiting periods and identified potential bottlenecks, such as the wait for higher-intensity cognitive behavioral therapy (CBT) at site 1. Furthermore, we observed that patients discharged from treatment waiting lists appeared to experience longer wait durations than those who started treatment. Process mining allowed analysis of treatment pathways, showing that patients commonly experienced treatment routes that involved either low- or high-intensity interventions alone. Of the most common routes, >5 times as many patients experienced direct access to high-intensity treatment rather than stepped care. Overall, 3.32% (site 1: 1507/45,401) and 4.19% (site 2: 527/12,590) of all patients experienced stepped care. Conclusions: Our findings demonstrate how process mining can be applied to Talking Therapies care pathways to evaluate pathway performance, explore relationships among performance issues, and highlight systemic issues, such as stepped care being relatively uncommon within a stepped care system. Integration of process mining capability into routine monitoring will enable NHS Talking Therapies service stakeholders to explore such issues from a process perspective. These insights will provide value to services by identifying areas for service improvement, providing evidence for capacity planning decisions, and facilitating better quality analysis into how health systems can affect patient outcomes. pubtype: Academic Journal doctype: critical path research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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