Journal of Evaluation in Clinical Practice


Published on

Paper describing the Patient Journey clinical model published in the Journal of Evaluation in Clinical Practice

Published in: Health & Medicine, Business
  • Be the first to comment

  • Be the first to like this

No Downloads
Total Views
On Slideshare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Journal of Evaluation in Clinical Practice

  1. 1. Journal of Evaluation in Clinical Practice ISSN 1365-2753Complex adaptive chronic care – typologies of patientjourney: a case study jep_1670 1..5Carmel M. Martin MBBS MSc PhD MRCGP FAFPHM FRACGP,1 Deirdre Grady BSc MSc,2Susan Deaconking MBBS,4 Catherine McMahon RN,4 Atieh ZarabzadehPhD Post. Dip. Stats. Post. Dip. Health Inf. BSc Soft. Eng.3 and Brendan O’Shea FRCGP MICGP51 Visiting Professor, National Digital Research Centre, Department of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland andAssociate Professor of Family Medicine, NOSM, Canada2 Clinical Research Assistant, 3Health Informatics Software Engineer, National Digital Research Centre, Dublin, Ireland4 Clinical Advisor, National Digital Research Centre, Dublin, Ireland5 Lecturer in General Practice, Trinity College Dublin, Dublin, Ireland and Specialist in Occupational Medicine, General Practitioner and MedicalDirector, Kildare and County West Wicklow Doctors on Call, Kildare, IrelandKeywords Abstractcase management, chronic illness, complexadaptive systems, diagnostic typologies, Rationale Complex adaptive chronic care (CACC) is a framework based upon complexhealth services research, life course adaptive systems’ theory developed to address different stages in the patient journey inanalysis, observations of daily living, patient chronic illness. Simple, complicated, complex and chaotic phases are proposed as diagnosticjourney, primary care types. Aims To categorize phases of the patient journey and evaluate their utility as diagnosticCorrespondence typologies.Associate Professor Carmel M. Martin Methods A qualitative case study of two cohorts, identified as being at risk of avoidableNational Digital Research Centre, Crane hospitalization: 12 patients monitored to establish typologies, followed by 46 patients toStreet, Dublin 8, Ireland validate the typologies. Patients were recruited from a general practitioner out-of-hoursE-mail: service. Self-rated health, medical and psychological health, social support, environmental concerns, medication adherence and health service use were monitored with phone callsAccepted for publication: 23 March 2011 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 adoi:10.1111/j.1365-2753.2011.01670.x 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.The patient journey in the complex There are multiple discernable phases or patterns across theadaptive chronic care (CACC) disease and illness journey over time, which are associated withtheoretical framework considerable expenditure variation [4]. Stages of the patient journey vary according to the dynamics and interconnected feed-A CACC framework aims to describe the interdependent elements back loops among the bio-psycho-social, health care and environ-of the personal care experience and the complex dynamic interac- mental domains as well as chronic disease progression [5,6].tions between a patient and his or her health care providers withinthe broader health system over time as a complex adaptive system[1].1 The CACC model was designed to address the complex non-linearity in a system (i.e. many components are interacting and inter- dependent such as in a primary health care environment), its behaviour cansystems nature of the chronic care model [2,3]. be unpredictable, and interventions frequently lead to unintended conse- quences. Understanding and changing the behaviour of such a complex1 The term ‘complex system’ formally refers to an interdependent system dynamic system requires an appreciation of its key patterns, leverageof many parts that is coupled in a non-linear fashion. When there is much points and constraints.© 2011 Blackwell Publishing Ltd, Journal of Evaluation in Clinical Practice 1
  2. 2. Complex adaptive care – patient journeys C.M. Martin et al.Based upon the Cynefin framework [7], patient journeys as typologies, and subsequently a second cohort would be monitoredcomplex adaptive systems were operationalized as simple, com- with support interventions. This aimed to validate the typologies inplicated, complex and chaotic phases in CACC. a larger group and evaluate their clinical usefulness in identifying the need for different frequency and intensity of community-based care interventions. Interventions were non-clinical and aimed toStable – simple or complicated care phases of identify early signs of instability and provide information, supportchronic conditions or refer back to the general practitioner (GP) or appropriate socialSimple – people are well, functioning and stable; the aim of care is slow the progress of risk factors, single disease or a diseasecluster and optimize quality of life and prevent complications andco-morbidities – for example, raised cholesterol, high blood pres- Methodssure, pre-diabetes or diabetes. Patients identified as being at risk of avoidable hospitalization At this stage, medical care is stable; that is, patient care and attending Kildare and West Wicklow Doctors on Call (KDOC) GPhealth states do not involve unstable dynamics and linear protocols cooperative out-of-hours service (OOH) were recruited. Theare generally appropriate. Conversely at another level, public KDOC database (October 2010–February 2011) was screened. Allhealth ‘care’ may involve dynamic complex individual and societal unplanned home visits, all encounters resulting in transfers byinterventions. For example, smoking cessation involves interven- ambulance, referrals to hospital or advised to attend Accident andtions in a diverse range of complex systems from economics and Emergency were secondarily screened for the inclusion criteria:markets, legislation, media as well as in health care with the • one chronic condition (>6 months), presenting as subacute orprovision of ‘simple’ quitting advice [8,9]. chronic flare-up, not acute surgical problem, not in long-term Complicated – multiple factors cause morbidity, which usually care;are chronic, and include bio-psycho-social environment compo- • 18 years or older;nents; the aim is to balance self-care, health and pharmaceutical • have had a recent unplanned hospital admission to a medicalinterventions and health-related co-morbidity. Treatment and ward, ormonitoring become more frequent and there are an increased • had a recent attendance at an emergency department, andnumber of providers and care settings involved. Yet, health is • are able to record their health status online with an electronicstable or deteriorating imperceptibly. diary or family or caregiver or take regular phone calls about their health. Summary data and outcomes of adult encounters were pro-Complex (unpredictable dynamics) or chaotic vided to the team of two GPs, one nurse and one research assis-(out-of-control) phases of chronic conditions tant in de-identified format. Potential cases were identified byComplex – acute or subacute-on-chronic exacerbations, flares two team members. Full case notes were then reviewed to iden-because of potential destabilization in bio-psycho-social environ- tify a list of eligible cases, which, if confirmed as suitable byment components including self-care, health and pharmaceutical their GPs, were recruited. The research team conducted an initialinterventions or health-related co-morbidity. Care may include assessment of consenting participants and caregivers in theirpre-terminal phase, frailty, risk of falls, depression and/or disease home and began daily health monitoring during working days offlare-up stages. the week. Chaotic – destabilization of multiple dimensions: falls, loss ofdiabetic control, severe pain, shortness of breath, additional diag- Monitoring daily healthnosis of cancer, mental health crisis and/or additional acute con-ditions such as pneumonia resulting in environmental ‘blowouts’. Patients were phoned at a time suitable to their needs. The dailyAppropriate and timely community-based primary/primary health health survey questions included health-related questions includ-care interventions can avoid these chaotic states. Chaotic states of ing self-rated health status, if their health status had changedchronic illness have a high risk of leading to death (total stability), since the last interview, and if they had any other concerns. Psy-but also may revert back to a stable trajectory or to an ongoing but chological questions included how often they felt very nervous,increasing unstable health journey. calm and peaceful, and happy. Social questions included if they Patients in these abovementioned states generally incur the had someone to take them out if needed, would there begreatest health care expenditures, resulting from expensive someone to help cooking and cleaning and also if there had beenhospitalization and re-hospitalization with its associated high- any changes to the patient’s caregiver and family supporttechnology treatments, compared to people with similar diagnoses network. There were open-text fields available for the appropri-who are more stable. ate questions where more information could be added. After each daily interview, a summary of the interview was compiled to complete the survey.AimsThe study aims to categorize phases of the patient journey andevaluate their utility as diagnostic typologies using a case study of Findingstwo cohorts, identified as being at risk of avoidable hospitalization. A total of 19 000 KDOC encounters (1/9/2010 to 7/11/2010 –The first cohort would be monitored to describe patient journey cohort 1) and (17/12/10 to 17/2/2011 – cohort 2) were screened.2 © 2011 Blackwell Publishing Ltd
  3. 3. C.M. Martin et al. Complex adaptive care – patient journeysFigure 1 Cohort 1 and cohort 2 profiles.Using a method of consecutive sampling 12 patients wererecruited to cohort 1 in October 2010 and 48 to cohort 2 inDecember 2010, providing 286 and 720 daily monitoring reportsrespectively. The profiles of cohort 1 and cohort 2 are described inFig. 1. Cohort 1 was a purely monitoring phase, while cohort 2involved active care management by the project team. Key elements of the patient journey are reported in fivedimensions of daily living – the presence of daily concerns, fluc-tuations in self-rated health, fluctuations in caregiver and per-ceived social support availability, medication changes and healthcare changes. Patterns of the patient journey were graphed and cate- Figure 2 Types of patient journey identified. ‘Stable patient’ demon-gorized as stable, unstable being complex or chaotic. This was strates an absence of daily concerns, and stability in self-rated health,carried out by C. M. and D. G. initially on an independent support, medication and health care. ‘Unstable patient’ demonstratesbasis and consensus was reached on a case by case basis for daily concerns about pain which preceded a worsening of self-ratedcohort 1. health followed by a change in medication and eventually re-stabilizes, These predominant patient journey patterns were identified in while social support does not change, as he lives alone. ‘Chaotic patient’the following proportions described in Fig. 2. Key types of patient demonstrates caregiver support issues as the root cause which are notnarratives from cohort 1 are described using pseudonyms. Figure 3 resolved and trigger a chaotic phase of illness in her and her motherdescribes the frequency of interventions and average length of resulting in hospitalization and death. Support change 1 = yes, 2 = no;phone calls for different types of patient journey. concerns 1 = yes; 2 = no; medication change 1 = yes; 2 = no; health care change 1 = yes; 2 = no and self-rated health was scored very poor = 0; poor = 2; fair = 4; good = 6; very good = 8 and excellent = 10. RIP, rest in peace (deceased).Stable complexPatient 1 – EileenEileen is 93 years old and lives with her daughter, Sharon, and Unstable complexher family in a very comfortable home. Her problems are chronicshortness of breath because of chronic obstructive pulmonary Complex and chaotic re-stabilizing patientdisease, cardiac problems including coronary artery bypass graft- Patient 2 – Billing, back pain and early Alzheimer’s disease. She has moved inwith her family following hospitalization for chronic obstructive Bill is 63 years old and lives on his own in a hostel with a landlady.pulmonary disease. Throughout the monitoring phase, Eileen He has type 2 diabetes, vertigo and dizziness of unclear aetiology.remains very well and her social support and medical condition He suffered a fall and fractured several ribs, with recurrent chestremains stable despite a complicated medical condition with pains and vertigo 1 month before entering the study. Brian strugglesmultiple morbidity. with chronic pain and vertigo, despite taking a 2-week holiday. On© 2011 Blackwell Publishing Ltd 3
  4. 4. Complex adaptive care – patient journeys C.M. Martin et al. Journey type Stable complex Unstable complex Unstable complex on the Death edge of chaos Cohort 1 66.6% 26.8% 6.6% 1 Cohort 2 67.4% 26.8% 5.8% 0 Rates of intervention 31 patients, 15 12 patients, 16 3 patients, 6 (case management) interventions interventions interventions Figure 3 Frequency of ‘types’ of patient journey over 4-week monitoring in cohort 1 Phone call duration 1–2 minutes >2–5 minutes >5 minutes and interventions and call for cohort 2 – according to category of participant.return from his holiday, he suffered an attack of dizziness on the terol for some years. She lives with her daughter Margaret whoplane and was admitted via a KDOC attendance. Subsequently, he was widowed 8 months previously, and who works in her ownmade three visits to Accident and Emergency and was admitted business as well as caring for her mother. Mary has becometwice, without going through his GP or KDOC. increasingly difficult to manage as she is not sleeping at night, and Margaret is becoming increasingly stressed and her blood pressure which is normal has become elevated associated withEdge of chaos – stable complex–chronic, severely her chronic exhaustion because of her mother’s insomnia.impaired and remains at risk of destabilization Margaret reported daily concerns and issues and was increas-Patient 3 – Ann ingly depressed and fatigued. The insomnia predated the stress, and Margaret required an emergency visit to the OOH whereAnn is 32 years old and she has poor quality of life for 13 years her blood pressure was found to be exceedingly high. And hos-since she developed Crohn’s disease. Her quality of life deterio- pital admission was suggested, despite medication for stressrated when she developed abdominal sepsis and underwent Margaret’s condition worsened. Mary became increasingly agi-unsuccessful surgery which involved incision and drainage. tated and concerned that she was being rejected, and went intoSince the birth of her daughter 12 years ago, she has been in an acute anxiety state when she was admitted for respite care.chronic pain with recurrent infection. She lives with her daughter She was diagnosed as having acute heart failure (probably thebut cannot leave the house as she has unpredictable and explo- cause for her insomnia at home) but was unable to recover andsive bowel movements. She presents to Dr Jones daily for pain was admitted to hospital and died. The admission diagnosis andrelief injections and also received a pain injection from her cause of death was heart failure, but the root cause of thepublic health nurse on weekday mornings. She requires the assis- problem was apparent 2 weeks earlier as daily concerns and car-tance with pain relief of an OOH service at the weekends. She egiver reporting represented a complex interplay of early demen-suffers from panic attacks and depression as a result of her tia, incipient heart failure, caregiver bereavement and stress andcomplex physical state and social isolation. Since her worsening state, she has lost her job and her friends. She frequently Unstable journeys reflected a dynamic interplay of physical,takes her anger out on her daughter. Her daughter is also at risk psycho-social, caregiver-related, medication and medical issues,of social isolation and neglect which Ann is aware of. Ann has rather than purely a disease flare-up. Greater instability reflectschronic poor self-rated health and very severe pain and consti- the need for more interventions. Phone calls varied in lengthpation with frequent medication changes. She has been referred depending on the journey phase of the participant, as well as theto hospital numerous times but refuses to be admitted because of occurrence of any health or social concerns requiring an inter-concerns over the care of her daughter. She is trying to move vention. Phone calls to stable participants were typically 1–2house to be closer to her Mum which also would allow her minutes in duration if there were no reported concerns, withdaughter to be closer to her friends. She is addicted to morphine topics of conversation varying from one patient to the next.and continually requires antibiotics and pain relief. Her pelvic Phone calls to participants with greater instability were longer inabscesses continually flare and require draining with increasing duration as there were more issues to discuss and longer again infrequency. She is on the edge of chaos with frequent suicidal the cases with problem identification and interventions.thoughts and is at risk of requiring emergency surgery. Ann Over 1 month – there were an average of 0.48 interventions perstates that she really benefits from the support of monitoring 5 patient in the complex stable group; 0.75 interventions per patientdays a week because her life is so difficult and needs encour- in the ‘unstable complex and chaotic re-stabilizing’ and 2 inter-agement and social support on a daily basis. ventions per person in the edge of chaos group. Interventions included advice to visit/call GP/practice nurse in response to symptoms that were new or worsening including pain, and mentalUnstable chaotic leading to death distress; to contact the pharmacist in relation to problems with medication adherence; to contact public health or social servicesPatient 4 – Mary for social, environmental or housing needs including heating. Car-Mary is 88 years old, widowed for 15 years, has very early egiver issues were addressed through referral to local services ordementia and has been treated for hypertension and high choles- alerting the GP.4 © 2011 Blackwell Publishing Ltd
  5. 5. C.M. Martin et al. Complex adaptive care – patient journeys chronic conditions can be stable or unstable, simple, complex orDiscussion chaotic. Each pattern can be identified early and responds well toPatterns of patient journey in patients at high risk of hospitaliza- problem-specific care approaches, be it medical, social or carertion were identified using a CACC model. The majority of patients support. CCAC is operationalized as adaptively responding towere classified as stable complex, with no patients being simple or phases and instability in the patient journey.complicated. About 30% were unstable complex or on the edge ofchaos. Both cohorts scored highly on the probability of repeatadmissions score [10], indicating that OOH service contact may Referencesoffer a potential screening opportunity for avoidable hospitaliza- 1. Martin, C. & Sturmberg, J. (2009) Complex adaptive chronic care.tions. The lives of people with unstable journeys were both diffi- Journal of Evaluation in Clinical Practice, 15 (3), 571–577.cult for them and their caregivers and challenging for the health 2. Wagner, E. H., Austin, B. T. & Von Korff, M. (1996) Improvingcare providers to continually monitor and respond to their risk outcomes in chronic illness. Managed Care Quarterly, 4 (2), 12–25. 3. Martin, C. M., Biswas, R., Sturmberg, J. P., Topps, D., Ellaway, R. &of destabilization, even with frequent visits to the GP. Recogniz- Smith, K. (2010) Patient Journey Record Systems (PaJR) for prevent-ing the typologies of dynamics of patient journeys is a new and ing ambulatory care sensitive conditions: a developmental framework.innovative method of ongoing risk evaluation that enables the In User-Driven Healthcare and Narrative Medicine: Utilizing Colla-implementation of complex adaptive care in response to the char- borative Social Networks and Technologies (eds R. Biswas & C. M.acteristics and domains of the at-risk dynamics. It overcomes Martin), PP. 93–112. Hershey, PA: IGI Global.the current episodic care perspective ‘after the event’. Reasons 4. Bigelow, J. H. (2005) Introduction. In Analysis of Healthcare Inter-for de-compensation and avoidable hospitalization can thus be ventions That Change Patient Trajectories (eds J. H. Bigelow, K.addressed by prospective analysis encompassing the whole bio- Fonkych, C. Fung & J. Wang), pp. 41–42. Santa Monica, CA: Randpsycho-social environmental and illness treatment rather than Corporation.solely focusing on disease and functional status. Instability can 5. Martin, C. M., Biswas, R., Joshi, A. & Sturmberg, J. P. (2010) Patient Journey Record Systems (PaJR): the development of a conceptualstabilize or homeostasis can break down leading to death. Tradi- framework for a patient journey system. In User-Driven Healthcaretionally, the GP knew their patients and their journeys, but as and Narrative Medicine: Utilizing Collaborative Social Networks andprimary care has become more specialized with a loss of personal Technologies (eds R. Biswas & C. Martin), pp. 75–92. Hershey, PA:continuity and with the developing roles of care management and IGI Global.guides, there is a need to externalize and make explicit the nature 6. Murray, S. A., Kendall, M., Boyd, K., Grant, L., Highet, G. & Sheikh,of patient journeys in order to plan and deliver integrated services A. (2010) Archetypal trajectories of social, psychological, and spiri-that meet the patient’s needs in a timely fashion. tual wellbeing and distress in family care givers of patients with lung The importance of personal continuity and social aspects of cancer: secondary analysis of serial qualitative interviews. Britishdaily monitoring is evident within the typologies of participant Medical Journal, 340, c2581.groups. Monitoring daily health also contributed greatly to social 7. Kurtz, C. & Snowden, D. (2003) The new dynamics of strategy: sense-making in a complex and complicated world. IBM Systemscare with patients reporting the value of the monitoring as a social Journal, 42 (3), 462–483.outlet and connection as well as a health monitoring system. Inter- 8. McDaniel, P. A., Intinarelli, G. & Malone, R. E. (2008) Tobaccoventions carried out varied from lifestyle change suggestions, industry issues management organizations: creating a global corporateadvice to consult a medical professional, arranging immediate network to undermine public health. Globalization and Health, 4 (2), 2.medical attention in the case of a medical emergency, to interven- 9. Young, D., Borland, R. & Coghill, K. (2010) An actor-network theorytions to improve social and environmental circumstances. analysis of policy innovation for smoke-free places: understanding This paper presents a practical application of a number of theo- change in complex systems. American Journal of Public Health, 100retical streams which converge in pattern recognition approach (7), 1208–1217.within a complex adaptive systems framework. These streams 10. Sidorov, J. & Shull, R. (2002) ‘My patients are sicker’: using the Prainclude life events analysis which has been found particularly risk survey for case finding and examining primary care site utilization patterns in a medicare-risk MCO. American Journal of Manag Care, 8useful in understanding stress and depression in older people [11], (6), 569–575.observations of daily living input into personal health records[12] 11. Kraaij, V., Arensman, E. & Spinhoven, P. (2002) Negative life eventsand the original chronic illness narrative research [13]. Further and depression in elderly persons: a meta-analysis. The Journals ofdevelopments will build on mixed-methods analytics – ranging Gerontology. Series B, Psychological Sciences and Social Sciences, 57from qualitative approaches to mathematical modelling techniques (1), P87–P94.and machine learning [14,15]. 12. Brennan, P. F., Downs, S. & Casper, G. (2010) Project health design: rethinking the power and potential of personal health records. Journal of Biomedical Informatics, 43 (5 Suppl.), S3–S5.Conclusion 13. Glaser, B. & Strauss, A. (1967) Discovery of Grounded Theory. Strat- egies for Qualitative Research. New York: Sociology Press.This paper presents a ‘novel tool’ to apply pattern recognition 14. Murray, M. A., Fiset, V., Young, S. & Kryworuchko, J. (2009) Wheretechniques to health care-related life event analysis such that it the dying live: a systematic review of determinants of place of end-may help health professionals predict illness trajectories towards of-life cancer care. Oncology Nursing Forum, 36 (1), 69–77.timely intervention. Observing the longitudinal patient journey 15. Cooper, G. F., Abraham, V., Aliferis, C. F., et al. (2005) Predicting direthrough health and illness is central to providing successful outcomes of patients with community acquired pneumonia. Journal ofCACC. Types of patient journey in an older at-risk group with Biomedical Informatics, 38 (5), 347–366.© 2011 Blackwell Publishing Ltd 5