RATIONALE: Complex adaptive chronic care (CACC) is a framework based upon complex adaptive systems' theory developed to address different stages in the patient journey in chronic illness. Simple, complicated, complex and chaotic phases are proposed as diagnostic types. AIMS: To categorize phases of the patient journey and evaluate their utility as diagnostic typologies. METHODS: A qualitative case study of two cohorts, identified as being at risk of avoidable hospitalization: 12 patients monitored to establish typologies, followed by 46 patients to validate the typologies. Patients were recruited from a general practitioner out-of-hours service. Self-rated health, medical and psychological health, social support, environmental concerns, medication adherence and health service use were monitored with phone calls made 3-5 times per week for an average of 4 weeks. Analysis techniques included frequency distributions, coding and categorization of patients' longitudinal data using a CACC framework. FINDINGS: Twelve and 46 patients, mean age 69 years, were monitored for average of 28 days in cohorts 1 and 2 respectively. Cohorts 1 and 2 patient journeys were categorized as being: stable complex 66.66% vs. 67.4%, unstable complex 25% vs. 26.08% and unstable complex chaotic 8.3% vs. 6.52% respectively. An average of 0.48, 0.75 and 2 interventions per person were provided in the stable, unstable and chaotic journeys. Instability was related to complex interactions between illness, social support, environment, as well as medication and medical care issues. CONCLUSION: Longitudinal patient journeys encompass different phases with characteristic dynamics and are likely to require different interventions and strategies - thus being 'adaptive' to the changing complex dynamics of the patient's illness and care needs. CACC journey types provide a clinical tool for health professionals to focus time and care interventions in response to patterns of instability in multiple domains in chronic illness care.
RATIONALE: Complex adaptive chronic care (CACC) is a framework based upon complex adaptive systems' theory developed to address different stages in the patient journey in chronic illness. Simple, complicated, complex and chaotic phases are proposed as diagnostic types. AIMS: To categorize phases of the patient journey and evaluate their utility as diagnostic typologies. METHODS: A qualitative case study of two cohorts, identified as being at risk of avoidable hospitalization: 12 patients monitored to establish typologies, followed by 46 patients to validate the typologies. Patients were recruited from a general practitioner out-of-hours service. Self-rated health, medical and psychological health, social support, environmental concerns, medication adherence and health service use were monitored with phone calls made 3-5 times per week for an average of 4 weeks. Analysis techniques included frequency distributions, coding and categorization of patients' longitudinal data using a CACC framework. FINDINGS: Twelve and 46 patients, mean age 69 years, were monitored for average of 28 days in cohorts 1 and 2 respectively. Cohorts 1 and 2 patient journeys were categorized as being: stable complex 66.66% vs. 67.4%, unstable complex 25% vs. 26.08% and unstable complex chaotic 8.3% vs. 6.52% respectively. An average of 0.48, 0.75 and 2 interventions per person were provided in the stable, unstable and chaotic journeys. Instability was related to complex interactions between illness, social support, environment, as well as medication and medical care issues. CONCLUSION: Longitudinal patient journeys encompass different phases with characteristic dynamics and are likely to require different interventions and strategies - thus being 'adaptive' to the changing complex dynamics of the patient's illness and care needs. CACC journey types provide a clinical tool for health professionals to focus time and care interventions in response to patterns of instability in multiple domains in chronic illness care.
Authors: Leire Ambrosio; David Perez-Manchon; Gloria Carvajal-Carrascal; Alejandra Fuentes-Ramirez; Neus Caparros; Manuel Ignacio Ruiz de Ocenda; Eva Timonet; Maria Victoria Navarta-Sanchez; Carmen Rodriguez-Blazquez Journal: Int J Environ Res Public Health Date: 2021-01-12 Impact factor: 3.390