Implementation of complex adaptive chronic care: the P atient J ourney R ecord system (PaJR)
Abstract
Background: The P atient J ourney R ecord system (P a JR) is an application of a complex adaptive chronic care model in which early detection of adverse changes in patient biopsychosocial trajectories prompts tailored care, constitute the cornerstone of the model. Aims: To evaluate the P a JR system's impact on care and the experiences of older people with chronic illness, who were at risk of repeat admissions over 12 months. Design: Community‐based cohort study – random assignment into intervention and usual care group, with process and outcome evaluation. Study population: Adult and older patients with multiple morbidity, one or more chronic diseases with one or more overnight hospitalizations, and seven or more general practice visits in the past 6 months. Complex intervention: P a JR lay care guides/advocates call patients and their caregivers. The care guides summarize their semi‐structured conversations about health concerns and well‐being. Predictive modelling and rules‐based algorithms trigger alerts in relation to online call summaries. Alerts are acted upon according to agreed guidelines. Analysis: Descriptive and comparative statistics. Outcomes: Impact on unplanned emergency ambulatory care sensitive admissions (ACSC) with an overnight stay; sensitivity of alerts and predictions; rates of care guides‐supported activities. Findings: Five part‐time lay care guides and a care manager monitored 153 intervention patients for 500 person months with 5050 phone calls. The 153 patients in the intervention group were comparable to the 61 controls. The intervention group reported in 50% of calls that their health limited their social activities; and one‐third of calls reported immediate health concerns. Predictive analytics were highly sensitive to risk of hospitalization. ACSC admissions were reduced by 50% compared to controls across the sites. Discussion: The initial implementation of a complex patient‐centred adaptive chronic care model using lay care guides, supported by machine learning, appeared sensitive to risk of hospitalization and capable of stabilizing illness journeys in older patients with multi‐morbidity. Conclusion: Actions based on alerts produced in this study appeared to significantly reduce hospitalizations. This paves the way for further testing of the model.
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Martin et al.'s proposed methodology obtained a 70% positive predictive value for unplanned events.
“A 70% positive predictive value was obtained for unplanned events by their proposed methodology.”
From Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective (2020) · cites this paper as [99]
Martin et al.'s methodology depicted a reduction rate of 50% in the number of participants in unplanned events of hospitals in the group compared with custom alert generating mechanism.
“This methodology depicted a reduction rate of 50% in the number of participants in unplanned events of hospitals in the group when compared with custom alert generating mechanism.”
From Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective (2020) · cites this paper as [99]
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Self-citation
- Authors
- Martin, C. M., Vogel, C., Grady, D., Zarabzadeh, A., Hederman, L., Kellett, J., Smith, K., & O’ Shea, B.
- Affiliations
- Trinity College Dublin (IE)
- University College Cork (IE)
- NOSM University (CA)
- Department of Public Health and Primary Care Trinity College Dublin Dublin Ireland
- Venue
- Journal of Evaluation in Clinical Practice
- Publisher
- Wiley
- Published
- 2012-07-22
- Volume
- 18
- Issue
- 6
- Pages
- 1226-1234
- ISSN
- 1356-1294 (ISSN-L)
- 1365-2753
- OpenAlex
- W1594029017
- Cited by
- 48
- References
- 28
- Citations by year
- 2026: 5 · 2025: 2 · 2024: 3 · 2023: 1 · 2022: 1 · 2021: 4 · 2020: 6 · 2019: 5 · 2018: 4 · 2017: 4 · 2016: 4 · 2015: 2 · 2014: 4 · 2013: 1 · 2012: 2
- FWCI
- 2.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Evaluation in Clinical Practice (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Health Sciences › Health Professions › General Health Professions › Primary Care and Health Outcomes
- Health Sciences › Health Professions › General Health Professions › Geriatric Care and Nursing Homes
- Keywords
- care managers, hospital readmission prevention, ambulatory care sensitive conditions, multimorbidity, predictive analytics, patient-centered care, community-based intervention, implementation evaluation
- MeSH terms
- Aged, Aged, 80 and over, Algorithms, Artificial Intelligence, Chronic Disease, Clinical Protocols, Emergency Service, Hospital, Environment, Female, Health Promotion, Health Services, Health Status, Humans, Male, Middle Aged, Social Support, Cohort Studies, Disease Management
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