Analysis of primary healthcare center closures following the Finnish structural reform

Abstract Background While accessible primary healthcare is a cornerstone of well-functioning health systems, various factors, such as health system reforms, may affect the provision of services. The recent Finnish structural reform is a good example, as the new counties, driven by budgetary deficits, are currently adjusting their service networks, leading to public health center closures. To understand and examine the local policy process, our aim was to examine the determinants of health center closure decisions. Methods We utilized publicly available policy documents to specify the health centers facing closures, merging this information with municipality and county-level register data encompassing population characteristics, geographics, current service network, and reform-related factors. Using logistic regression analysis, we examined the factors associated with health center closures in a municipality. Results Our preliminary results indicate that 82 municipalities out of 295 were facing a health center closure. Factors associated with increased odds of a health center closure included a higher number of current public health centers (OR: 14.16, CI: 4.02-49.87), better medical desert index value (OR: 2.05, CI: 1.52-2.75), and the county being a new actor with no previous joint administration (OR: 7.47, CI: 1.82-30.57). Meanwhile, higher number of private health centers (OR: 0.24, CI: 0.07-0.82) and greater population growth (OR: 0.21, CI: 0.09-0.52) were associated with lower odds of health center closure. Conclusions The planned health center closures focus on municipalities with shrinking populations, but above average existing service networks. This signifies that decision-makers have managed to some extent target the actions appropriately. Counties with no previous collaboration between municipalities face higher service reform debt, which has implications for future reform planning. The reform outcomes and service access must be further analyzed in the future. Key messages • The health center closures in post-reform Finland appear to be directed relatively fairly, as better service network areas are targeted instead of rural areas already dealing with poor accessibility. • The closures appear to be driven mainly by service network characteristics, rather than political or reform-related factors, suggesting that the decision-making of the county councils is limited.

Authors

Institutions

Publication Details

Journal
European Journal of Public Health
Published
2025-10-01
DOI
https://doi.org/10.1093/eurpub/ckaf161.1568
Citations
1
Primary Topic
Primary Care and Health Outcomes
Type
article
Field-Weighted Citation Impact
2.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of primary healthcare center closures following the Finnish structural reform

Timo Sinervo, Visa Väisänen
1 citations
European Journal of Public Health
Primary Care and Health Outcomes
2.82
article

Analysis of primary healthcare center closures following the Finnish structural reform

Timo Sinervo, Visa Väisänen
article en
1 citations

Abstract

Abstract Background While accessible primary healthcare is a cornerstone of well-functioning health systems, various factors, such as health system reforms, may affect the provision of services. The recent Finnish structural reform is a good example, as the new counties, driven by budgetary deficits, are currently adjusting their service networks, leading to public health center closures. To understand and examine the local policy process, our aim was to examine the determinants of health center closure decisions. Methods We utilized publicly available policy documents to specify the health centers facing closures, merging this information with municipality and county-level register data encompassing population characteristics, geographics, current service network, and reform-related factors. Using logistic regression analysis, we examined the factors associated with health center closures in a municipality. Results Our preliminary results indicate that 82 municipalities out of 295 were facing a health center closure. Factors associated with increased odds of a health center closure included a higher number of current public health centers (OR: 14.16, CI: 4.02-49.87), better medical desert index value (OR: 2.05, CI: 1.52-2.75), and the county being a new actor with no previous joint administration (OR: 7.47, CI: 1.82-30.57). Meanwhile, higher number of private health centers (OR: 0.24, CI: 0.07-0.82) and greater population growth (OR: 0.21, CI: 0.09-0.52) were associated with lower odds of health center closure. Conclusions The planned health center closures focus on municipalities with shrinking populations, but above average existing service networks. This signifies that decision-makers have managed to some extent target the actions appropriately. Counties with no previous collaboration between municipalities face higher service reform debt, which has implications for future reform planning. The reform outcomes and service access must be further analyzed in the future. Key messages • The health center closures in post-reform Finland appear to be directed relatively fairly, as better service network areas are targeted instead of rural areas already dealing with poor accessibility. • The closures appear to be driven mainly by service network characteristics, rather than political or reform-related factors, suggesting that the decision-making of the county councils is limited.

European Journal of Public HealthVol. 35(Supplement_4)
University of Eastern Finland (FI)
Openalex Percentile: Top 8%
Primary Care and Health Outcomes
2.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.