Tron Anders Moger

Administrative health registry data are often promoted as key to more efficient, equitable, and evidence-informed chronic disease care. In theory, they allow healthcare utilization to be mapped across providers in near real time. In practice, their impact has been modest. Drawing on recent literature, this perspective article examines the limitations of registry data and how these may be addressed. We argue that registry data offer valuable insight into unintended variation in care at the system level. They expose gaps between clinical guidelines and real-world practices, identify subgroups at high risk for adverse outcomes, and enable cost-effective studies of policy changes and interventions. However, registry data cannot fully capture clinical decision-making, treatment content, patient preferences, or patient-centered outcomes. Despite comprehensive coverage, legislative barriers, data protection regulations, and incompatible software systems still prevent effective data sharing between healthcare sectors. Insufficient investment in skilled data analysts further limits their practical use for resource allocation, capacity planning, and equity analysis. To address these constraints, registry data should be combined with clinical and socioeconomic indicators, patient-reported outcomes, and perspectives from patients and providers. Practical utility depends on integration into organizational routines, analytic infrastructures, and team-based decision-making. Ideally, automated systems should deliver insights tailored to national policymakers, regional and local health managers, in order to directly inform decision-making. We propose a framework outlining key components of such a system to bridge the gap between data availability and actionable insights for chronic disease management.

Musculoskeletal disorders (MSDs) are among the most common reasons for patients seeking help from the healthcare system, with approximately one-third of the Norwegian population consulting healthca...

Isolating the effects of outpatient care on hospitalisation in observational data is challenging. We estimate the effects of factors believed to influence hospital admissions in patients with COPD. The factors were related to outpatient care and social factors, motivated by recommendations in COPD guidelines and the literature. We applied linked national and municipal registry data on 25,369 COPD patients in Oslo and Trondheim 2008–2019. Yearly frequency and type of healthcare contacts (respiratory and non-respiratory, across providers), together with comorbidities, were used as proxies for patients’ health status. We constructed samples matched on the full set of proxy variables to estimate the effect of each factor on future COPD hospital admissions. Overall, 9.8% of follow-up years had at least one COPD hospital admission. Findings indicated beneficial effects of several of the factors. Care interaction between general practitioner (GP) and other health providers, follow-up by GP within 30 days after COPD hospital discharge and counselling/psychotherapy by GP showed significant reductions of 2.9, 4.9 and 1.4% points in the rate of next-year COPD hospital admissions, respectively. The effects are noteworthy when extrapolated to the entire Norwegian COPD population. A reduction of 1% point could result in up to 1,500 fewer patients experiencing one or more COPD hospital admissions during a year. In the absence of detailed clinical information, creating samples that are multidimensionally matched on health service use and comorbidities as pragmatic proxies for health status could be a viable approach for estimating the effects of other factors.

Objective: To study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening program concerning cost-effectiveness and time savings for radiologists. Methods: In a decision tree model using recent data from AI vendors and the Cancer Registry of Norway, and assuming equal effectiveness of radiologists plus AI compared to standard practice, we simulated costs, effects and radiologist person-years over the next 20 years under different scenarios: 1) Assuming a €1 additional running cost of AI instead of the €3 assumed in the base case, 2) varying the AI-score thresholds for single vs. double readings, 3) varying the consensus and recall rates, and 4) reductions in the interval cancer rate compared to standard practice. Results: AI was unlikely to be cost-effective, even when only one radiologist was used alongside AI for all screening exams. This also applied when assuming a 10% reduction in the consensus and recall rates. However, there was a 30–50% reduction in the radiologists’ screen-reading volume. Assuming an additional running cost of €1 for AI, the costs were comparable, with similar probabilities of cost-effectiveness for AI and standard practice. Assuming a 5% reduction in the interval cancer rate, AI proved to be cost-effective across all willingness-to-pay values. Conclusions: AI may be cost-effective if the interval cancer rate is reduced by 5% or more, or if its additional cost is €1 per screening exam. Despite a substantial reduction in screening volume, this remains modest relative to the total radiologist person-years available within breast centers, accounting for only 3–4% of person-years.

Background: Chronic obstructive pulmonary disease (COPD) incurs significant healthcare costs, often accompanied by multimorbidity. Advanced patients may need short-term stays for rehabilitation, treatment, or respite to maintain home living. Aim: To identify predictors for a first short-term stay and study the healthcare utilization and costs compared with similar patients without a short-term stay. Patients and Methods: Data on COPD patients in the cities Oslo and Trondheim 2010– 2019 and including information on specialist, primary and long-term care, diagnoses, sociodemographics and -economics were collected from national and municipal registries, resulting in a sample of 24,613 patients. Using discrete time survival models, we identified predictors for a short-term stay. We described the costs before and after admission, and the duration of living at home, compared to non-recipients matched on age, comorbidities and healthcare use. Results: Depression, anxiety, mental disorders, alcoholism, prior hospitalization and reception of home care were associated with higher odds of short-term stays. One to two GP visits for respiratory diseases, being in the top quartile for GP visits for non-respiratory diseases, visits to specialists, and physiotherapist visits for non-respiratory issues were significantly associated with lower odds of short-term institutional stay. Patients admitted to short-term stays incurred markedly higher costs both in the year before admission and during subsequent years compared to matched non-recipients, primarily due to increased use of inpatient and home care services. Conclusion: Prior receipt of home care, unlike standard outpatient services, was linked to a higher likelihood of short-term stays. This suggests that some outpatient services may delay the need for such stays, or that patients already in municipal services are more readily admitted. Additionally, patients with psychosocial issues may have greater care needs, indicating that resource allocation aligns with these needs. The findings suggest that by the time short-term stays are required, health deterioration has already become considerable.

Chronic obstructive pulmonary disease (COPD) is a common condition associated with age, multimorbidity and frequently involves the use of health care across levels. Understanding the factors associated with the initiation of long-term care is important when planning the future need for services. We describe healthcare use before and after the reception of any home care. We further studied the associations between healthcare use and first registered home care service and from first registered home care service to nursing home admission or death. Patients residing in Oslo or Trondheim at the time of first contact with a COPD primary diagnosis, 2009-2018. Patient data were linked across national and municipal registries, covering healthcare and sociodemographics. The sample consisted of 16,738 individuals. There was a marked increase in inpatient and outpatient hospital contacts in the years prior to and after the reception of any home care. Adjusted for comorbidities and sociodemographics, high numbers of GP consultations, and inpatient and outpatient hospital contacts for respiratory diagnoses were associated with a significantly higher likelihood of receiving home care the next year (hazard odds ratios > 1.3). Following the reception of home care, the type of home care service received (e.g. home nursing or short-term rehabilitation/treatment) was more important than outpatient services in predicting next-year nursing home admission or death. Including data on prior outpatient care when predicting future need for home care is beneficial. A high frequency (top 10%) of yearly GP, in- or outpatient hospital contacts can imply that the patient may be in need of home care in the near future.

Background: Although chronic obstructive pulmonary disease (COPD) admissions put a substantial burden on hospitals, most of the patients’ contacts with health services are in outpatient care. Traditionally, outpatient care has been difficult to capture in population-based samples. In this study we describe outpatient service use in COPD patients and assess associations between outpatient care (contact frequency and specific factors) and next-year COPD hospital admissions or 90-day readmissions. Methods: Patients over 40 years of age residing in Oslo or Trondheim at the time of contact in the period 2009–2018 were identified from the Norwegian Patient Registry (in- and outpatient hospital contacts, rehabilitation) and the KUHR registry (contacts with GPs, contract specialists and physiotherapists). These were linked to the Regular General Practitioner registry (characteristics of the GP practice), long-term care data (home and institutional care, need for assistance), socioeconomic and–demographic data from Statistics Norway and the Cause of Death registry. Negative binomial models were applied to study associations between combinations of outpatient care, specific care factors and next-year COPD hospital admissions and 90-day readmissions. The sample consisted of 24,074 individuals. Results: A large variation in the frequency and combination of outpatient service use for respiratory diagnoses (GP, emergency room, physiotherapy, contract specialist and outpatient hospital contacts) was apparent. GP and outpatient hospital contact frequency were strongly associated to an increased number of next-year hospital admissions (1.2–3.2 times higher by increasing GP frequency when no outpatient hospital contacts, 2.4-5 times higher in combination with outpatient hospital contacts). Adjusted for healthcare use, comorbidities and sociodemographics, outpatient care factors associated with lower numbers of next-year hospitalisations were fees indicating interaction between providers (7% reduction), spirometry with GP or specialist (7%), continuity of care with GP (15%), and GP follow-up (8%) or rehabilitation (18%) within 30 days vs. later following any current year hospitalisations. For 90-day readmissions results were less evident, and most variables were non-significant. Conclusion: As increased use of outpatient care was strongly associated with future hospitalisations, this further stresses the need for good communication between providers when coordinating care for COPD patients. The results indicated possible benefits of care continuity within and interaction between providers.

In recent years there have been several political initiatives in Norway, requiring more research into how multimorbidity and health care pathways in the municipality affect outcomes such as work participation, hospital admissions, disability and quality of life for patients with chronic diseases. Most of the care is provided outside hospitals and has been difficult to capture in large, registry-based studies. Focusing on two important groups, patients with chronic obstructive pulmonary disease (COPD) and musculoskeletal disorders (MSD), the INOREG project aims to reduce these knowledge gaps. In the paper we present 1) the data that are used in the project, 2) the construction of samples, variables and possible methods for analysis and 3) an example on how the data and methods will be applied. The project database is constructed from a novel linkage of national health and welfare registries. The data cover social, primary and specialized care for all COPD and MSD patients in Norway, long-term care data from Oslo and Trondheim municipalities and functioning and quality of life for ca. 2,700 patients treated at physiotherapy clinics in the FYSIOPRIM project. This enables construction of care pathways and outcomes at the individual level from 2008 through 2019. The project will fill knowledge gaps regarding the patterns of care at different levels in the health care system, and the association to outcomes for chronic patient groups. If the project is successful, it will provide improved insight on how to further develop provision and coordination of services to the decision makers, and ideally reduce inequalities in health.