Abstract
Background: A proactive person-centred care process is advocated for people with multimorbidity. To that aim, general practitioners may benefit from support in the identification of high-need patients, i.e. patients who are high or suboptimal users of health services and/or have a poor quality of life. To develop such support, we examined whether knowledge about patients’ illness perceptions and personal resources to manage their health and care is useful to identify high-need patients among multimorbid general practice populations.
Methods: Survey data, collected in 2016 and 2017, of 601 patients with two or more chronic diseases (e.g. COPD, diabetes, Parkinson’s disease) registered with 40 general practices in the Netherlands were analysed by logistic regression analysis to predict frequent contact with the general practice, contact with general practice out-of-office services, unplanned hospitalisations and poor health related quality of life. Patients’ illness perceptions and personal resources (education, health literacy, mastery, mental health status, financial resources, social support) were included as predictors.
Results: The four outcomes were only weakly associated among themselves (Phi .07–.19). Patients’ illness perceptions and personal resources were of limited value to predict potentially suboptimal health service use, but they were important predictors of health related quality of life. Patients with a poor health related quality of life could be identified by their previously reported illness perceptions (attributing many symptoms to their chronic conditions (B = 1.479, P < .001), a high level of concern (B = 0.844, P = .002) and little perceived control over their illness (B = -0.728, P = .006)) combined with an experienced lack of social support (B = -0.527, P = .042) and a poor mental health status (B = -0.966, P = .001) (sensitivity 80.7%; specificity 68.1%). (Continued on next page) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a cre