Patient activation in older people with long-term conditions and multimorbidity: correlates and change in a cohort study in the United Kingdom

Amy Blakemore, Mark Hann, Kelly Howells, Maria Panagioti, Mark Sidaway, David Reeves, Peter Bower, Amy Blakemore, Mark Hann, Kelly Howells, Maria Panagioti, Mark Sidaway, David Reeves, Peter Bower

Abstract

Background: Patient Activation is defined as the knowledge, skill, and confidence a patient has in managing their health. Higher levels of patient activation are associated with better self-management, better health outcomes, and lower healthcare costs. Understanding the drivers of patient activation can allow better tailoring of patient support and interventions. There are few data on patient activation in UK patients with long-term conditions.

Methods: A prospective cohort design was used. Questionnaires were mailed to 12,989 patients over the age of 65 years with at least one long-term condition in Salford, UK. They completed the Patient Activation Measure and self-report measures of: depression, health literacy, social support, health-related quality of life, and impact of multimorbidity. We report descriptive data on baseline activation and change over time, and use multivariate regression to model associations with patient activation at baseline and predictors of change in Activation over 6 months.

Results: The cohort included 4377 (33.6 %) older people, of whom 4225 were mailed a further questionnaire at 6 months; 3390 returned it complete (80.2 %). At baseline, 15 % self-reported PAM level 1, 16 % level 2, 45 % level 3, and 25 % level 4. Across all patients, depression had the strongest association with patient activation. Other important factors were: older age, being retired, poor health literacy, health-related quality of life, and social support. Total number of self-reported comorbidities and the perceived impact of comorbidities were also important for patients with more than one long-term condition. Patient activation scores were reasonably enduring over time (r = 0.43 between baseline and at six months), although nearly half changed 'levels' of activation over that time. Few variables predicted change in activation over 6 months.

Conclusions: This is the first large scale assessment of patient activation in the UK. Our data may be useful in identifying patients who need support with patient activation, and allow interventions (such as health coaching) to be tailored to better support older patients with long-term conditions who have symptoms of depression, poor social support and impaired health literacy. Further analyses of longitudinal studies will be necessary to better understand the causal relationships between patient activation and variables such as depression.

Keywords: Depression; Health-related quality of life; Long-term conditions; Multimorbidity; Patient activation; Self-management.

Figures

Fig. 1
Fig. 1
Flow of participants

References

    1. Kennedy A, Rogers A, Bower P. Support for self care for patients with chronic disease. Br Med J. 2007;335:968. doi: 10.1136/bmj.39372.540903.94.
    1. Coleman K, Austin B, Brach C, Wagner E. Evidence on the chronic care model in the new millenium. Health Aff. 2009;28(1):75–85. doi: 10.1377/hlthaff.28.1.75.
    1. Clark N, Becker M, Janz N, Lorig K, Rakowski W, Anderson L. Self-management of chronic disease by older adults: a review and questions for research. J Aging Health. 1991;3(1):3–27. doi: 10.1177/089826439100300101.
    1. Wagner E, Austin B, Von Korff M. Organizing care for patients with chronic illness. Millbank Q. 1996;74(4):511–544. doi: 10.2307/3350391.
    1. Lorig K, Seleznick M, Lubeck D, Chastain R, Holman H. The beneficial outcomes of the arthritis self-management course are not adequatley explained by behaviour change. Arthritis Rheum. 1989;32(1):91–95. doi: 10.1002/anr.1780320116.
    1. Lorig K, Sobel D, Stewart a, Brown B, Bandura A, Ritter P, et al. Evidence suggesting that a chronic disease self-management program can improve health staus while reducing hospitalization: a randomized trial. Med Care. 1999;31(1):5–14. doi: 10.1097/00005650-199901000-00003.
    1. Richardson G, Kennedy A, Reeves D, Bower P, Lee V, Middleton E, et al. Cost effectiveness of the expert patients programme (EEP) for patietnts with chronic conditions. J Epidemiol Community Health. 2008;62(4):361–367. doi: 10.1136/jech.2006.057430.
    1. Baron R, Kenny D. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–1182. doi: 10.1037/0022-3514.51.6.1173.
    1. Kraemer H, Wilson G, Fairburn C, Agras W. Mediators and moderators of treatment effects in randomized clincial trials. Arch Gen Psychiatry. 2002;59:877–883. doi: 10.1001/archpsyc.59.10.877.
    1. Reeves D, Kennedy A, Fullwood C, Bower P, Gardner C, Gately C, et al. Predicting who will benefit from an Expert Patient Programme self-management course. BrJ Gen Pract. 2008;58(548):198–203. doi: 10.3399/bjgp08X277320.
    1. Hibbard J, Stockard J, Mahoney E, Tusler M. Development of the Patient Activation Measure (PAM): Conceptualizing and measuring activation in patients and consumers. Health Serv Res. 2004;39(4):1005–1026. doi: 10.1111/j.1475-6773.2004.00269.x.
    1. Hibbard J, Mahoney E, Stockard J, Tusler M. Development and testing of a short form of the patient activation measure (PAM) Health Serv Res. 2005;40(6):1918–1930. doi: 10.1111/j.1475-6773.2005.00438.x.
    1. Hibbard J, Gilburt H. Supporting people to manage their health: An introduction to patient activation. 2014. The King’s Fund. 25-12-0016. .
    1. Sacks R, Greene J, Hibbard J, Overton V. How well do patient activation scores predict depression outcomes 1 year later? J Affect Disord. 2014;169:1–6. doi: 10.1016/j.jad.2014.07.030.
    1. O’Shea L. Is the NHS missing a vital sign? 2014. 14-3-2016. .
    1. Skolasky R, Green A, Scharfstein D, Boult C, Reider L, Wegener S. Psychometric properties of the patient activation measure among multimorbid older adults. Health Serv Res. 2011;46(2):457–478. doi: 10.1111/j.1475-6773.2010.01210.x.
    1. Campbell J, Smith P, Nissen S, Bower P, Elliot M, Rowland M. The GP Patient Survey for use in primary care in the National Health Service in the UK - development and psychometric characterisitcs. BMC Fam Pract. 2009;10:57. doi: 10.1186/1471-2296-10-57.
    1. Morris N, Maclaren C, Chew L, Littenberg B. The single item literacy screener: Evaluation of a brielf instrument to identofy limited reading ability. BMC Fam Pract. 2006;7:21. doi: 10.1186/1471-2296-7-21.
    1. Jeppesen K, Coyle J, Miser W. Screening questions to predict limited health literacy: a cross sectional study of patients with diabetes mellitus. Ann Fam Med. 2009;7(1):24–31. doi: 10.1370/afm.919.
    1. Bayliss E, Ellis J, Steiner J. Seniors’ self-reported multimorbidity captured biopsychosocial factors not incorporated in two other data-based morbidity measures. J Clin Epidemiol. 2009;62:550–557. doi: 10.1016/j.jclinepi.2008.05.002.
    1. Brooks R. EuroQol: the current state of play. Health Policy. 1996;37(1):53–72. doi: 10.1016/0168-8510(96)00822-6.
    1. van Hout B, Janssen M, Feng Y, Kohlman T, Busschbach J, Golicki D, et al. Interim scoring for the EQ-5D-5 L: Mapping the EQ-5D-5 L to EQ-5D-3 L value sets. Value Health. 2012;15(5):708–715. doi: 10.1016/j.jval.2012.02.008.
    1. Janssen M, Birnie E, Haagsma J, Bonsel G. Comparing the standard EQ-5D three-level system with a five-level version. Value Health. 2008;11:275–284. doi: 10.1111/j.1524-4733.2007.00230.x.
    1. Agborsangaya C, Lahtinen M, Cooke T, Johnson J. Comparing the EQ-5D 3 L and 5 L: measurement properties and association with chronic conditions and multimorbidity in the general population. Health Qual Life Outcomes. 2014;12:74. doi: 10.1186/1477-7525-12-74.
    1. Guthrie E, Dickens C, Blakemore A, Watson J, Chew-Graham C, Lovell K, et al. Depression predicts future emergency hospital admissions in primary care patients with chronic physical illness. J Psychosom Res. 2016;82:54–61. doi: 10.1016/j.jpsychores.2014.10.002.
    1. Berwick D, Murphy J, Goldman P, Ware J, Barsky A, Weinstein M. Performance of a five-item mental health screening test. Med Care. 1991;29(2):169–176. doi: 10.1097/00005650-199102000-00008.
    1. Ware J. SF-36 Health Survey: manual and interpretation guide. Boston: Nimrod Press; 1993.
    1. Yamazaki S, Fukuhara S, Green J. Usefulness of five-item and three-item Mental Health Inventories to screen for depressive symptoms in the general population of Japan. Health Qual Life Outcomes. 2005;3:48. doi: 10.1186/1477-7525-3-48.
    1. Kelly M, Dunstan F, Lloyd K, Fone D. Evaluating cutpoints for the MHI-5 and the MCS using the GHQ-12: a comparison of five different methods. BMC Psychiatry. 2008;8:10. doi: 10.1186/1471-244X-8-10.
    1. Mitchell P, Powell L, Blumenthal J, Norten J, Ironson G, Rogers Pitula C, et al. A short social support measure for patients recovering from myocardial infarction. J Cardiopulm Rehabil. 2003;23:398–403. doi: 10.1097/00008483-200311000-00001.
    1. May C, Eton D, Boehmber K, Gallacher K, Hunt K, MacDonald S. Rethinking the patient: using burden of treatment theory to understand the changing dynamics of illness. BMC Health Serv Res. 2014;14:281. doi: 10.1186/1472-6963-14-281.
    1. Sav A, King M, Whitty J, Kendall E, Mcmillan S, Kelly F. Burden of treatment for chronic illness: a concept analysis amd review of the literature. Health Expect. 2013;15:351–359.
    1. Gibbons C, Kenning C, Coventry P, Bee P, Bundy C, Fisher L, et al. Development of a mulitmorbidity illness perceptions scale (MULTIPleS) PLoS One. 2013;8(12):e81852. doi: 10.1371/journal.pone.0081852.
    1. Kenning C, Coventry P, Gibbons C, Bee P, Fisher L, Bower P. Does patient experience of multimorbidity predict self-management and health outcomes in a prospective study in primary care. Fam Pract. 2015;32(3):311-16.
    1. Van Breukelen G. ANCOVA versus change from baseline had more power in randomiszed studies and more bias in nonrandomized studies. J Clin Epidemiol. 2006;59:920–925. doi: 10.1016/j.jclinepi.2006.02.007.
    1. Roberts N, Kidd L, Dougall N, Patel I, McNarry S, Nixon C. Measuring patient activation: The utility of the Patient Activation Measure within a UK context-Results from four exemplar studies and potential future applications. Patient Educ Couns. 2016;99(10):1739–46. doi: 10.1016/j.pec.2016.05.006.
    1. Reeves D, Hann M, Rick J, Rowe K, Small N, Burt J, et al. Care plans and care planning in the management of long term conditions in the United Kingdom: a controlled prospective cohort study. Br J Gen Pract. 2014;64(626):e568–e575. doi: 10.3399/bjgp14X681385.
    1. Magnezi R, Glasser S, Shalev H, Sheiber A, Reuveni H. Patient activation, depression and quality of life. Patient Educ Couns. 2014;94(3):432–437. doi: 10.1016/j.pec.2013.10.015.
    1. Hibbard J, Mahoney E, Stock R, Tusler M. Self-management and health care utilization: Do increased in patient activation result in improved self-management behaviors? Health Serv Res. 2007;42(2):1443–1463. doi: 10.1111/j.1475-6773.2006.00669.x.
    1. Goodworth M, Stapleman L, Hibbard J, Johns L, Wright D, Hughes M, et al. Variables associated with patient activation in persons with multiple sclerosis. J Health Psychol. 2016;21(1):82–92. doi: 10.1177/1359105314522085.
    1. Williams M, Baker D, Parker R, Nurrs J. Relationship of fucntional health literacy to patients’ knowledge of their chronic disease: A study patients with hypertension and diabetes. Arch Intern Med. 1998;158(2):166–172. doi: 10.1001/archinte.158.2.166.
    1. Friis K, Lasgaard M, Osborne R, Maindal H. Gaps in understanding health and engagement with healthcare providers across common long-term conditions: a population survey of health literacy in 29 473 Danish citizens. BMJ Open 2016; 5 (e009627).
    1. Rademakers J, Nijman J, Brabers A, de Jong J. The relative effect of health literacy and patient activation on provider choice in the Netherlands. Health Policy. 2014;114:200–206. doi: 10.1016/j.healthpol.2013.07.020.
    1. Schiotz M, Bogelund M, Almdal T, Jensen B, Willaing I. Social support and self-management behaviour among patients with Type 2 diabetes. Diabetes Med: j Br Med Assoc. 2012;29(5):654–661. doi: 10.1111/j.1464-5491.2011.03485.x.
    1. Haslbeck J, McCorkle R, Scharffer D. Chronic illness self-management while living alone in later life: A systematic integrative review. Res Ageing. 2012;1:41.
    1. National Institute for Health and Care Excellence. Multimorbidity: clinical assessment and management. Draft for consultation. 2016.
    1. Dunn G, Emsley R, Liu H, Landau S, Green J, White I, et al. Evalutaiton and validation of social and psychological markers in randomised trials of complex interventions in mental health. Health Technol Assess. 2015;19(93):1–115. doi: 10.3310/hta19930.
    1. Bower P, Kontopantelis E, Sutton A, Kendrick T, Richards D, Gilbody S, et al. Influence of initial severity of depression on effectiveness of low intensity interventions: meta-analysis of individual patient data. BMJ. 2013;346:f540. doi: 10.1136/bmj.f540.

Source: PubMed

Patrocinadores y Colaboradores

Condiciones médicas

Intervenciones de drogas

3
Suscribir