Process mining to discover patterns in patient outcomes in a Psychological Therapies Service

Potts, Courtney; Bond, Raymond; Jordan, Joanne M.; Mulvenna, Maurice; Dyer, Karen; Moorhead, Anne; Elliott, Amy J.

doi:10.1007/s10729-023-09641-8

Cited by 3 publications

(1 citation statement)

References 47 publications

(63 reference statements)

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“…The first study used process mining to explore health care pathways for patients presenting to emergency departments with functional neurological disorders, where onward referral to psychological therapy formed part of the pathway [ 25 ]. The second study used data from a psychological therapies service but did so to explore transitions between pre- and posttherapy clinical outcome bands to investigate the impact of appointment attendance on patient outcomes [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study

Yardley,

Davis,

Eldridge

et al. 2024

JMIR Ment Health

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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.

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Section: Introductionmentioning

confidence: 99%

Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study

Yardley,

Davis,

Eldridge

et al. 2024

JMIR Ment Health

View full text Add to dashboard Cite

show abstract

Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study (Preprint)

Yardley,

Davis,

Eldridge

et al. 2023

Preprint

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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.

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Uncovering specific navigation patterns: user engagement of people with dementia and family caregivers with an advance care planning website (Preprint)

Dupont,

Smets,

Potts

et al. 2024

Preprint

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BACKGROUND Web-based tools have gained popularity to inform and empower individuals in advance care planning. We have developed an interactive website tailored to the unique needs of people with dementia and their families to support advance care planning. This website aims to break away from the rigid pathways shown in other tools that support advance care planning, in which advance care planning is shown as a linear process from information to reflection, communication, and documentation. OBJECTIVE To assess the website's usage by people with dementia and their family caregivers, identify distinct user engagement patterns, and visualise how users navigated the website. METHODS We analysed the website’s log data obtained from an eight-week evaluation study of the site. Interactions with the website were collected in the log data and included visited web pages or clicking on hyperlinks. Distinct user engagement patterns were identified using K-means clustering. Process mining was applied to visualise user pathways through the website. RESULTS 52 participants, 21 people with dementia and their family caregivers as dyads and 10 family caregivers were included in the study. Throughout the eight-week study, users spent an average of 35.3 (SD = 82.9) minutes over 5.5 (SD = 3.4) unique days on the website. Family caregivers mostly used the website (alone or with a person with dementia) throughout the eight-week study. Only three people with dementia used it on their own. Three distinct engagement patterns emerged: low, moderate, and high. Low-engagement participants spent less time on the website during the eight weeks, following a linear path from information to communication to documentation. Moderate and high-engagement users showed more dynamic patterns, frequently navigating between information pages and communication tools to facilitate exploration of aspects related to advance care planning. CONCLUSIONS The diverse engagement patterns underscore the need for personalised support in advance care planning and challenge the conventional linear advance care planning representations found in other web-based tools.

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Process mining to discover patterns in patient outcomes in a Psychological Therapies Service

Cited by 3 publications

References 47 publications

Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study

Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study

Data-Driven Exploration of National Health Service Talking Therapies Care Pathways Using Process Mining: Retrospective Cohort Study (Preprint)

Uncovering specific navigation patterns: user engagement of people with dementia and family caregivers with an advance care planning website (Preprint)

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