Projecting Multimorbidity and Mortality under Demographic Change and Preventive Interventions
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866908468808515584 |
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| author | Ledebur, Katharina Kautzky-Willer, Alexandra Thurner, Stefan Klimek, Peter |
| author_facet | Ledebur, Katharina Kautzky-Willer, Alexandra Thurner, Stefan Klimek, Peter |
| contents | As populations age, the rise of multimorbidity poses a significant healthcare challenge. However, our ability to quantitatively forecast the progression of multimorbidity remains limited. Leveraging a nationwide dataset comprising approximately 45 million hospital stays spanning 17 years in Austria, we develop a new compartmental model for chronic disease trajectories across 132 distinct multimorbidity patterns (compartments). Each compartment represents a distinct constellation of co-occurring chronic conditions, with transitions modeled as age- and sex-dependent probabilities. We use the compartmental disease trajectory model (CDTM) to simulate disease trajectories to 2030, estimating the frequency of all empirically observed co-occurrence patterns among more than 100 diagnosis groups. We demonstrate the model's utility in identifying high-impact prevention targets. A 5% reduction in new cases of hypertensive disease (I10--I15) leads to a 0.57 (SD 0.06)% reduction in all-cause mortality over a 15-year period, and a 0.57 (SD 0.07)% reduction in mortality for malignant neoplasms (C00--C97). We also evaluate long-term impacts of SARS-CoV-2 sequelae, projecting earlier and more frequent hospitalizations across a range of diagnoses. Our fully data-driven modelling approach identifies leverage points for proactive preparation by physicians and policymakers to reduce the overall disease burden in the population, emphasizing patient-centered healthcare planning in aging societies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_14296 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Projecting Multimorbidity and Mortality under Demographic Change and Preventive Interventions Ledebur, Katharina Kautzky-Willer, Alexandra Thurner, Stefan Klimek, Peter Physics and Society As populations age, the rise of multimorbidity poses a significant healthcare challenge. However, our ability to quantitatively forecast the progression of multimorbidity remains limited. Leveraging a nationwide dataset comprising approximately 45 million hospital stays spanning 17 years in Austria, we develop a new compartmental model for chronic disease trajectories across 132 distinct multimorbidity patterns (compartments). Each compartment represents a distinct constellation of co-occurring chronic conditions, with transitions modeled as age- and sex-dependent probabilities. We use the compartmental disease trajectory model (CDTM) to simulate disease trajectories to 2030, estimating the frequency of all empirically observed co-occurrence patterns among more than 100 diagnosis groups. We demonstrate the model's utility in identifying high-impact prevention targets. A 5% reduction in new cases of hypertensive disease (I10--I15) leads to a 0.57 (SD 0.06)% reduction in all-cause mortality over a 15-year period, and a 0.57 (SD 0.07)% reduction in mortality for malignant neoplasms (C00--C97). We also evaluate long-term impacts of SARS-CoV-2 sequelae, projecting earlier and more frequent hospitalizations across a range of diagnoses. Our fully data-driven modelling approach identifies leverage points for proactive preparation by physicians and policymakers to reduce the overall disease burden in the population, emphasizing patient-centered healthcare planning in aging societies. |
| title | Projecting Multimorbidity and Mortality under Demographic Change and Preventive Interventions |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2403.14296 |