Segmenting Patients With Diabetes With the Navigator Service in Primary Care and a Description of the Self-Acting Patient Group: Cross-Sectional Study
Journal of medical Internet research(2023)
Abstract
Background: The aim of patient segmentation is to recognize patients with similar health care needs. The Finnish patient segmentation service Navigator segregates patients into 4 groups, including a self-acting group, who presumably manages their everyday life and coordinates their health care. Digital services could support their self-care. Knowledge on self-acting patients' characteristics is lacking. Objective: The study aims are to describe how Navigator assigns patients with diabetes to the 4 groups at nurses' appointments at a health center, the self-acting patient group's characteristics compared with other patient groups, and the concordance between the nurse's evaluation of the patient's group and the actual group assigned by Navigator (criterion validity). Methods: Patients with diabetes >= 18 years old visiting primary care were invited to participate in this cross-sectional study. Patients with disability preventing informed consent for participation were excluded. Nurses estimated the patients' upcoming group results before the appointment. We describe the concordance (%) between the evaluation and actual groups. Nurses used Navigator patients with diabetes (n=304) at their annual follow-up visits. The self-acting patients' diabetes care values (glycated hemoglobin [HbA1c], urine albumin to creatinine ratio, low-density lipoprotein cholesterol, blood pressure, BMI), chronic conditions, medication, smoking status, self-rated health, disability (World Health Organization Disability Assessment Schedule [WHODAS] 2.0), health-related quality of life (EQ-5D-5L), and well-being (Well-being Questionnaire [WBQ-12]) and the patients' responses to Navigator's question concerning their digital skills as outcome variables were compared with those of the other patients. We used descriptive statistics for the patients' distribution into the 4 groups and demographic data. We used the Mann-Whitney U test with nonnormally distributed variables, independent samples t test with normally distributed variables, and Pearson chi-square tests with categorized variables to compare the groups. Results: Most patients (259/304, 85.2%) were in the self-acting group. Hypertension, hyperlipidemia, and joint ailments were the most prevalent comorbidities among all patients. Self-acting patients had less ischemic cardiac disease (P=.001), depression or anxiety (P=.03), asthma or chronic obstructive pulmonary disease (P<.001), long-term pain (P<.001), and related medication. Self-acting patients had better self-rated health (P<.001), functional ability (P<.001), health-related quality of life (P<.001), and general well-being (P<.001). All patients considered their skills at using electronic services to be good. Conclusions: The patients in the self-acting group had several comorbidities. However, their functional ability was not yet diminished compared with patients in the other groups. Therefore, to prevent diabetic complications and disabilities, support for patients' self-management should be emphasized in their integrated care services. Digital services could be involved in the care of patients willing to use them. The study was performed in 1 health center, the participants were volunteers, and most patients were assigned to self-acting patient group. These facts limit the generalizability of our results.
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Key words
patient segmentation, Navigator, self-acting patient, diabetes, primary care, self-management, skills, care, nurse, medication, quality of life, well-being, digital, patient
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