Finnish Questionnaire Tool Shows Promise for Sorting Diabetes Patients by Real Needs

Health systems around the world face a deceptively simple question: which patients need the most intensive care, and which would do just as well with lighter-touch support? Answering it well can mean the difference between scarce nursing hours going to the people who truly need them and those hours being spread thinly and indiscriminately. A new study from Finland, published in BMC Health Services Research, puts one candidate solution — a questionnaire-based service called Navigator — through a rigorous statistical examination, and the results suggest the tool may earn a place alongside the algorithms increasingly used to sort patient populations.

Patient segmentation, the practice of dividing a patient population into groups with similar needs, has become a cornerstone of modern health service planning. Most current approaches rely on register data: diagnoses, medication purchases, hospital admissions, and cost histories crunched by statistical or machine-learning models. These methods are powerful, but they see only the administrative shadow of a patient’s life. What they cannot easily capture is how a person actually copes day to day — whether they feel enabled to manage their own health, whether their values and functional ability align with the care they receive, and how they experience their own health status. Navigator, developed in Finland, was designed to fill precisely that gap by asking patients and the professionals who care for them directly.

The service works through paired questionnaires. Patients answer questions covering their individual values, mood, and ability to function in everyday life, while nurses and other professionals assess the patient’s health status and how well current care is fulfilling the patient’s needs. Because Navigator draws on this human-reported information, its developers argue it can supplement data-driven segmentation with a richer, more personal picture of each individual. Until now, however, a fundamental question hung over the tool: did it actually measure what it claimed to measure? That question — the issue of validity — is what the research team led by Riikka Riihimies of Tampere University set out to answer.

The study took place at Valkeakoski Health Center in Finland, where sixteen nurses used Navigator with 304 diabetic patients receiving primary care. Diabetes was a deliberate choice of study population: people living with diabetes typically have multiple interacting health concerns, long-term relationships with primary care services, and wide variation in how well they cope with daily self-management, making them an ideal group for testing whether a segmentation tool can distinguish meaningful differences between individuals. The study received ethical approval from Tampere University Hospital’s Ethics Committee, and all participants gave written informed consent.

The researchers ran two complementary tests. The first, construct validity, asked whether Navigator’s internal structure matched its theoretical design. Using exploratory factor analysis, a statistical technique that searches for hidden patterns underlying responses to a set of questions, the team examined whether the questionnaire items clustered into the dimensions Navigator was built around. The second test, concurrent validity, asked whether Navigator’s scores moved in step with established, well-validated instruments measuring similar things. If Navigator’s functional ability dimension correlated strongly with a recognized disability measure, for example, that would be evidence the tool is capturing something real.

The factor analyses delivered encouraging news for the tool’s designers. In the patient questionnaire, the analysis identified two coherent factors, which the researchers labeled the patient’s mood and the patient’s enablement — the sense of being equipped and empowered to manage one’s own situation. In the professional questionnaire, two further factors emerged: fulfilling care, reflecting how well the patient’s needs are being met by current services, and the patient’s health status. These four factors lined up neatly with the dimensions Navigator was intended to measure, providing statistical confirmation that the questionnaires hang together in a theoretically sensible way rather than producing noise.

The construct validity checks extended beyond internal structure. The team derived factor scores and tested specific hypotheses about how different groups should respond. They predicted that men and women would show only small differences in their Navigator responses, and that patients aged 75 and older would differ markedly from younger patients on dimensions tied to enablement, fulfilling care, and health status. Both predictions were largely borne out: gender differences were modest, while age-group differences were significant on most factor scores. A tool that behaves exactly as theory says it should, in the directions theory says it should, gains credibility as a genuine measuring instrument rather than an arbitrary scoring exercise.

The concurrent validity results were equally substantive. Navigator’s functional ability dimension correlated strongly and significantly with four established patient-reported measures: the World Health Organization Disability Assessment Schedule 2.0, a comprehensive disability instrument; self-rated health; the EuroQol Visual Analog Scale, which captures health-related quality of life on a single scale; and a twelve-item well-being questionnaire. All of these correlations were highly significant. Meanwhile, the professional-assessed health status dimension correlated significantly with objective clinical indicators, including the number of chronic conditions the patient reported, the total amount of medication used, glycated hemoglobin reflecting blood sugar control, the urine albumin-to-creatinine ratio signaling kidney involvement, smoking status, and body-mass index. In other words, what patients and nurses reported through Navigator tracked closely with both validated subjective measures and hard clinical data.

For clinicians and health service managers, the significance of these findings lies in what Navigator could add to existing segmentation practice. Data-based methods excel at identifying high-cost, high-need patients from administrative records, but they are blind to the personal experience of illness. A patient whose records look moderate on paper may in fact be struggling badly with daily life, while another with an intimidating diagnosis list may be coping confidently and needs little extra support. By adding structured information about mood, enablement, functional ability, and how well care is fulfilling individual needs, Navigator offers a way to refine the groups produced by register-based algorithms and to direct resources with finer granularity. The authors conclude that the tool appears valid for measuring patients’ coping in everyday life and health status, and may therefore supplement data-based segmentation by deepening understanding of the individuals within patient groups.

Cautions remain, as they do with any validation study. The research was cross-sectional, capturing a single moment in time rather than following patients over months and years, and it involved a single Finnish health center and a specific population of diabetic patients. Whether Navigator performs equally well in other patient groups, other regions, and other health system contexts will require further study, as will evidence that using the tool actually improves outcomes or reduces costs in practice. Still, the study marks an important step for a tool built on a simple premise: that the best way to understand how patients are coping is to ask them, in a structured and scientifically validated way, and to pair their answers with the observations of the professionals who know their care. As health systems everywhere search for ways to personalize care without exploding budgets, instruments like Navigator — now with evidence behind them — may prove that the human voice belongs at the heart of population health analytics.

Subject of Research: Validation of the Navigator patient segmentation service for diabetic patients in Finnish primary care

Article Title: Construct and concurrent validity of the Navigator patient segmentation service: cross-sectional study among diabetic patients in Finnish primary care

Article References: Riihimies, R., Tolvanen, E., Helminen, M., Kosunen, E., & Koskela, T. (2026). Construct and concurrent validity of the Navigator patient segmentation service: cross-sectional study among diabetic patients in Finnish primary care. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15684-8

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15684-8

Keywords: patient segmentation, Navigator, diabetes, primary care, construct validity, concurrent validity, exploratory factor analysis, Finland, health services research, functional ability, questionnaires, eHealth