The potential of artificial intelligence in reducing the economic burden of chronic diseases

Abstract Background In Slovenia, chronic diseases (CD), including dementia, musculoskeletal and connective tissue diseases (MSCTD) represent a severe public health problem and a major economic burden (EB). New solutions for managing these issues are needed. One of the key innovative factors in the future should be the use of artificial intelligence (AI). The aim of this study was to analyze the EB of dementia and MSCTD and to discuss where AI can have an impact on reducing the EB. Methods At the National Institute of Public Health (NIJZ), in collaboration with the Faculty of Economics of the University of Ljubljana, we calculated the EB of dementia and 6 most common MSCTD for the period 2020 - 2023 in Slovenia. Direct costs were calculated based on national routine health data, while indirect costs were estimated using the National Transfer Accounts (NTA) methodology. Results The calculated EB of 6 most common MSCTD represented 5% of total health expenditure (THE) or 0.5% of Slovenian gross domestic product on average. The estimated EB of dementia was around €11.2 million, or 0.23% of THE. However, the costs of dementia are significantly underestimated, as only routine data were included. Conclusions The EB of dementia and MSCTD is high in Slovenia and would be significantly higher considering social care costs and all diagnoses of MSCTD. In the light of the aging population the research requires the innovative inclusion of AI which has great potential to make a significant contribution to preventing/delaying CD, more accurate diagnosis and timely action to prevent long-term complications and reduce the need for prolonged rehabilitation or complex surgery, contributing to lower EB. However, AI cannot completely substitute professionals. Key messages • Raising awareness of CD, highlighting early detection and AI’s potential, should be a key public health priority. • With an aging population, prevention focusing on MSCTD and dementia must intensify to reduce EB.

Publication Details

Journal
European Journal of Public Health
Published
2025-10-01
DOI
https://doi.org/10.1093/eurpub/ckaf161.1079
Primary Topic
Cambodian History and Society
Type
article
Field-Weighted Citation Impact
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article

The potential of artificial intelligence in reducing the economic burden of chronic diseases

European Journal of Public Health
Cambodian History and Society
article

The potential of artificial intelligence in reducing the economic burden of chronic diseases

article en

Abstract

Abstract Background In Slovenia, chronic diseases (CD), including dementia, musculoskeletal and connective tissue diseases (MSCTD) represent a severe public health problem and a major economic burden (EB). New solutions for managing these issues are needed. One of the key innovative factors in the future should be the use of artificial intelligence (AI). The aim of this study was to analyze the EB of dementia and MSCTD and to discuss where AI can have an impact on reducing the EB. Methods At the National Institute of Public Health (NIJZ), in collaboration with the Faculty of Economics of the University of Ljubljana, we calculated the EB of dementia and 6 most common MSCTD for the period 2020 - 2023 in Slovenia. Direct costs were calculated based on national routine health data, while indirect costs were estimated using the National Transfer Accounts (NTA) methodology. Results The calculated EB of 6 most common MSCTD represented 5% of total health expenditure (THE) or 0.5% of Slovenian gross domestic product on average. The estimated EB of dementia was around €11.2 million, or 0.23% of THE. However, the costs of dementia are significantly underestimated, as only routine data were included. Conclusions The EB of dementia and MSCTD is high in Slovenia and would be significantly higher considering social care costs and all diagnoses of MSCTD. In the light of the aging population the research requires the innovative inclusion of AI which has great potential to make a significant contribution to preventing/delaying CD, more accurate diagnosis and timely action to prevent long-term complications and reduce the need for prolonged rehabilitation or complex surgery, contributing to lower EB. However, AI cannot completely substitute professionals. Key messages • Raising awareness of CD, highlighting early detection and AI’s potential, should be a key public health priority. • With an aging population, prevention focusing on MSCTD and dementia must intensify to reduce EB.

European Journal of Public HealthVol. 35(Supplement_4)
Reduced inequalities
Openalex Percentile: Top 35%
Cambodian History and Society
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The potential of artificial intelligence in reducing the economic burden of chronic diseases · European Journal of Public Health (2025) | TGRS Research Map | TGRS