Evidence map›Paper›PMID 40962934›Full record

ArticleScientific reports2025

Impact of primary, specialist, and hospital care data on disease frequency estimates in older adults in Sweden.

Katharina Schmidt-Mende, Maria Feychting, Eric Chen, Javier Louro, Karin Modig

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Katharina Schmidt-MendeAcademic Primary Health Care Centre, Stockholm Region, Stockholm, Sweden.
Maria FeychtingUnit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Eric ChenAcademic Primary Health Care Centre, Stockholm Region, Stockholm, Sweden.
Javier LouroUnit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Karin ModigUnit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. karin.modig@ki.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nordic countries have a long-standing tradition of using administrative healthcare data from specialist and hospital settings to study disease frequency and etiological associations. While similar data are increasingly available elsewhere, large-scale primary care data remain limited. Understanding how data source affects disease identification is therefore critical. We conducted a register-based study including all individuals aged ≥ 60 years residing in Region Stockholm, Sweden, from 2017 to 2022. ICD-10 codes from primary care, specialist outpatient, and hospital care were grouped into 60 disease categories. One-year cumulative incidence and prevalence were estimated and compared. Disease patterns were broadly similar across care settings, with hypertension being the most common diagnosis. However, underestimation was generally greater for incidence than for prevalence. Hospital and specialist care data primarily captured acute and severe conditions, e.g., stroke, ischemic heart disease, falls, and cancer, while primary care data more effectively identified chronic risk factors such as diabetes, hypertension, hyperlipidemia, and psychiatric disorders, particularly for incident cases. Age-related differences in underestimation varied by disease but showed no consistent pattern. Primary, specialist, and hospital care data each capture distinct aspects of the disease landscape in older adults. Excluding primary care data leads to systematic underestimation of many common and chronic conditions, especially for newly diagnosed cases. This study provides guidance for epidemiological research using administrative health registers and highlights the importance of integrating data from multiple levels of care to improve the accuracy of disease burden estimates in epidemiological research using administrative health registers.

Indexed as

Primary Health CareAgedAged, 80 and overFemaleHospitalizationHumansIncidenceMaleMiddle AgedPrevalenceRegistriesRisk FactorsSweden

Identifiers

PMID40962934
PMCPMC12443952

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.