Does patient experience of multimorbidity predict self-management and health outcomes in a prospective study in primary care?
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Cassandra Kenning1, Peter A Coventry2, Chris Gibbons3
1Institute of Population Health, NIHR School for Primary Care Research, Centre for Primary Care, Manchester Academic Health Science Centre (MAHSC), Cassandra.kenning@manchester.ac.uk.
Background:
There is a need to better understand the mechanisms which lead to poor outcomes in patients with multimorbidity, especially those factors that might be amenable to intervention.
Objective:
This research aims to explore what factors predict self-management behaviour and health outcomes in patients with multimorbidity in primary care in the UK.
Methods:
A prospective study design was used. Questionnaires were mailed out to 1460 patients with multimorbidity. Patients were asked to complete a range of self-report measures including measures of multimorbidity, measures of their experience of multimorbidity and service delivery and outcomes (three measures of self-management: behaviours, Self-monitoring and Insight and medication adherence; and a measure of self-reported health).
Results:
In total, 36% (n = 499) of patients responded to the baseline survey and 80% of those respondents completed follow-up. Self-management behaviour at 4 months was predicted by illness perceptions around the consequences of individual conditions. Self-monitoring and Insight at 4 months was predicted by patient experience of 'Hassles' in health services. Self-reported medication adherence at 4 months was predicted by health status, Self-monitoring and Insight and 'Hassles' in health services. Perceived health status at 4 months was predicted by age and patient experience of multimorbidity.
Conclusions:
This research shows that different factors, particularly around patients' experiences of health care and control over their treatment, impact on various types of self-management. Patient experience of multimorbidity was not a critical predictor of self-management but did predict health status in the short term. The findings can help to develop and target interventions that might improve outcomes in patients with multimorbidity.
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