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Conference Abstracts

Identifying “high need” patients with multimorbidity within primary healthcare to initiate a proactive person-centred care process

Authors:

Mieke Rijken ,

Nivel / University of Eastern Finland, Netherlands, NL
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Marianne Heins,

NL
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Joke Korevaar

NL
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Abstract

Introduction

To provide proactive person-centred care, primary care professionals need to be able to identify “high need” patients, i.e. multimorbid patients who have a high risk of suboptimal health service use and/or a poor quality of life. We examined whether such patients could be identified based on: 1. data from patients’ general practice electronic health records (EHRs), and 2. patient-reported illness perceptions and personal resources to manage their health and care.

Methods

Data from general practice EHRs of 245,065 multimorbid patients, linked with hospital data, were analysed by logistic regression to predict frequent contact with the general practice, ED visits and unplanned hospitalisations. Predictors were age, sex, morbidity, healthcare use and medication use in the previous year.

Furthermore, data from 601 general practice patients with multimorbidity were analysed by logistic regression to predict frequent contact with the general practice, unplanned hospitalisations and poor quality of life (EQ-5D). Predictors were previously assessed illness perceptions (BIPQ) and resources (social support, education level, financial resources, health literacy, mastery, mental health).

Results

Frequent contact with the general practice was predicted by general practice contacts in the previous year (AUC 0.82). Patient-reported data were of little predictive value, although a high level of concern increased the likelihood of frequent contact with the general practice, whereas a sense of mastery decreased this likelihood.

ED visits and unplanned hospitalisations were unpredictable from general practice EHR data (AUC 0.67 and 0.70). Patient-reported data could neither accurately predict unplanned hospitalisations, although lacking personal control was a significant predictor. A strong emotional response increased the likelihood of using out-of-office services, but prediction from patient-reported information was unsatisfactory. Illness perceptions and personal resources were useful to predict a poor quality of life, particularly attributing many symptoms to one’s conditions, a high level of concern, experiencing little control, a lack of social support and depressive symptoms.

 

Discussion

To provide person-centred care proactively, it is crucial that care professionals can identify “high need” patients. However, high needs from a health system perspective (high or suboptimal service use) are not the same as high needs from the patient perspective (poor quality of life). Primary care professionals should be aware that they may have “high need” patients whom they do not see frequently.

Conclusions

Multimorbid patients who will frequently contact the general practice can be identified by their previous use of general practice services. Patients at risk of a poor quality of life can be identified from previously assessed illness beliefs, depressive symptoms and unmet social needs. Early identification of patients with a high risk of future use of acute services remains difficult.

Lessons learned

Multimorbid patients who frequently contact the general practice, use general practice out-of-office services, have ED visits or unplanned hospitalisations or a poor quality of life are largely distinct “high need” groups.

Suggestions for future research

Identification of “high need” patients may be improved by also including data about the use of hospital services.

How to Cite: Rijken M, Heins M, Korevaar J. Identifying “high need” patients with multimorbidity within primary healthcare to initiate a proactive person-centred care process. International Journal of Integrated Care. 2022;22(S1):62. DOI: http://doi.org/10.5334/ijic.ICIC21036
Published on 08 Apr 2022.

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