The research, led by Elahe Karimi-Shahrbabak and Meta van den Heuvel, used a sequential mixed-methods design, a structure in which each stage feeds the next. First came in-depth interviews with nine purposively selected caregivers about their financial experiences during neonatal intensive care admission and the follow-up period. Those qualitative findings then shaped a cross-sectional survey of 110 caregivers, which measured financial strain, practical problems, and access to financial support. Finally, caregivers, healthcare providers, and researchers gathered in a co-design workshop to interpret the combined evidence and collaboratively draft the program specifications. This triangulation of interview, survey, and workshop data is what gives the study its technical weight: the numbers reveal the scale of the problem, while the stories and the workshop reveal what a solution must actually look like.

The survey results are stark. Respondents were predominantly female (94 of 109, or 86.2 percent) and from two-parent households (96 of 109, or 88.1 percent), yet 43 of 106 caregivers (40.6 percent) reported difficulty making ends meet, and 31 of 107 (29.0 percent) screened positive for household food insecurity. More than half (58 of 108, or 53.7 percent) had no assistance at all navigating financial programs, and 39 of 108 (36.1 percent) reported a financial problem within the past week. These are families already stretched by the demands of caring for a medically fragile infant, and the data suggest that financial distress is not an edge case but a routine feature of the neonatal follow-up population.

The interviews added texture to those figures. Caregivers described income loss during prolonged hospitalization, high out-of-pocket costs for travel, meals, and parking, and the sheer complexity of benefit and tax processes. Programs such as the Ontario Disability Support Program (ODSP), Assistance for Children with Severe Disabilities (ACSD), and the Northern Health Travel Grant exist on paper, but families reported limited hospital-based financial support to help them access them. The interviews also surfaced something the survey could not: a clear appetite for a hospital-based financial navigator, a dedicated person embedded in the clinical team who could walk families through the paperwork while their child is still in care and after discharge.

Financial hardship in neonatal care is not a new observation, but the SickKids study is among the first to systematically characterize it in a neurodevelopmental follow-up clinic and to translate that characterization into a co-designed service specification. The concept draws on the emerging model of medical-financial partnerships (MFPs), in which healthcare systems integrate financial support services directly into clinical care, and on the medical-financial navigator role that has been piloted in adult oncology, where navigators help patients with insurance, benefits, and debt. Adapting that model to neonatal follow-up required understanding a different set of stressors: parents of NICU graduates face years of therapy appointments, equipment costs, and caregiving demands that keep one parent out of the workforce long after discharge.

The co-design workshop, the study’s third and most distinctive stage, brought caregivers, clinicians, social workers, legal health professionals, and researchers to the same table. Participants identified six design themes and prioritized four key specifications: universal access, meaning the navigator should be offered to all families rather than only those who self-identify as struggling; flexible communication, so families can engage by phone, email, or in person at their convenience; timely post-discharge engagement, because financial problems often peak in the weeks after a baby comes home; and a defined set of key services covering benefits applications, tax credits, insurance, and travel supports. The emphasis on universal access is technically significant: it sidesteps the screening problem, in which families who most need help are least likely to disclose distress, and instead normalizes financial navigation as part of standard care.

That normalization matters because financial toxicity, the term borrowed from oncology to describe the harm caused by the cost of care, is increasingly recognized as a determinant of child health. Food insecurity in nearly a third of surveyed households is not merely a budgeting issue; it is a risk factor for poorer developmental outcomes in the very children the NNFU clinic exists to monitor. The study’s authors argue that integrating financial navigation into the follow-up clinic could improve equitable access to financial resources, and that the next step is to pilot and implement the co-designed program and formally evaluate its impact.

The study is formative by design, meaning it was built to shape a future intervention rather than to test one. The authors are explicit that the next phase is to pilot the Financial Navigator Program and evaluate whether it actually improves families’ access to benefits and reduces financial strain. That evaluation will need to account for the realities of a tertiary pediatric hospital: staffing, funding, and the challenge of reaching families who may disengage from follow-up care precisely because of the financial pressures the program is meant to relieve.

What makes the SickKids work resonate beyond Toronto is its methodological honesty. The team did not assume they knew what families needed; they asked, measured, and then co-designed with the people who would use the service. Caregivers were not subjects but partners, including a lived-experience advisor embedded in the author team. The result is a program specification grounded in evidence and shaped by the families it is meant to serve, a model that other hospitals with neonatal follow-up clinics, and indeed any pediatric service where the cost of care quietly erodes family stability, could adapt. The study’s findings, published open access, offer a blueprint for turning a hidden crisis into a structured, navigable pathway.

The broader implication is that financial navigation belongs in the clinical team, not in a pamphlet rack. Nearly a third of surveyed households faced food insecurity, and more than half had no help navigating the supports that exist for exactly their situation. If a hospital can embed a navigator in the follow-up clinic, the argument goes, it can convert a fragmented, opaque benefits landscape into a structured pathway, and in doing so address a determinant of child health that has long been invisible in the exam room. The SickKids team has now built the specifications; the pilot will tell whether the model delivers on its promise.

Subject of Research: Co-designing a financial navigator program in the neonatal neurodevelopmental follow-up clinic: a formative mixed-methods study

Article Title: Co-designing a financial navigator program in the neonatal neurodevelopmental follow-up clinic: a formative mixed-methods study

Article References: Karimi-Shahrbabak, E., Nadarajah, J., Buchanan, F., Perera, S., Danguecan, A., Casey, M., Masemann, R., Medeiros, P., Beck, R., Koziorz, D., Lazor, T., Meserve, A., Ly, L. G., Birken, C. S., & van den Heuvel, M. (2026). Co-designing a financial navigator program in the neonatal neurodevelopmental follow-up clinic: a formative mixed-methods study. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15693-7

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15693-7

Keywords: Co-designing, financial, navigator, program, neonatal, neurodevelopmental, follow-up, clinic, formative, mixed-methods, scientific research

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