Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved]
Rising pressure from chronic diseases means that we need to learn how to deal with challenges at a different level, including the use of systems approaches that better connect across fragments, such as disciplines, stakeholders, institutions, and technologies. By learning from progress in leading ar...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2017-03-01
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| Series: | F1000Research |
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| Online Access: | https://f1000research.com/articles/6-309/v1 |
| _version_ | 1811222768868392960 |
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| author | Michael Rebhan |
| author_facet | Michael Rebhan |
| author_sort | Michael Rebhan |
| collection | DOAJ |
| description | Rising pressure from chronic diseases means that we need to learn how to deal with challenges at a different level, including the use of systems approaches that better connect across fragments, such as disciplines, stakeholders, institutions, and technologies. By learning from progress in leading areas of health innovation (including oncology and AIDS), as well as complementary indications (Alzheimer’s disease), I try to extract the most enabling innovation paradigms, and discuss their extension to additional areas of application within a systems approach. To facilitate such work, a Precision, P4 or Systems Medicine platform is proposed, which is centered on the representation of health states that enable the definition of time in the vision to provide the right intervention for the right patient at the right time and dose. Modeling of such health states should allow iterative optimization, as longitudinal human data accumulate. This platform is designed to facilitate the discovery of links between opportunities related to a) the modernization of diagnosis, including the increased use of omics profiling, b) patient-centric approaches enabled by technology convergence, including digital health and connected devices, c) increasing understanding of the pathobiological, clinical and health economic aspects of disease progression stages, d) design of new interventions, including therapies as well as preventive measures, including sequential intervention approaches. Probabilistic Markov models of health states, e.g. those used for health economic analysis, are discussed as a simple starting point for the platform. A path towards extension into other indications, data types and uses is discussed, with a focus on regenerative medicine and relevant pathobiology. |
| first_indexed | 2024-04-12T08:20:31Z |
| format | Article |
| id | doaj.art-f88d42911896408a82a97ef417977d0b |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-04-12T08:20:31Z |
| publishDate | 2017-03-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-f88d42911896408a82a97ef417977d0b2022-12-22T03:40:36ZengF1000 Research LtdF1000Research2046-14022017-03-01610.12688/f1000research.11085.111956Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved]Michael Rebhan0Novartis Institutes for Biomedical Research, Basel, 4056, SwitzerlandRising pressure from chronic diseases means that we need to learn how to deal with challenges at a different level, including the use of systems approaches that better connect across fragments, such as disciplines, stakeholders, institutions, and technologies. By learning from progress in leading areas of health innovation (including oncology and AIDS), as well as complementary indications (Alzheimer’s disease), I try to extract the most enabling innovation paradigms, and discuss their extension to additional areas of application within a systems approach. To facilitate such work, a Precision, P4 or Systems Medicine platform is proposed, which is centered on the representation of health states that enable the definition of time in the vision to provide the right intervention for the right patient at the right time and dose. Modeling of such health states should allow iterative optimization, as longitudinal human data accumulate. This platform is designed to facilitate the discovery of links between opportunities related to a) the modernization of diagnosis, including the increased use of omics profiling, b) patient-centric approaches enabled by technology convergence, including digital health and connected devices, c) increasing understanding of the pathobiological, clinical and health economic aspects of disease progression stages, d) design of new interventions, including therapies as well as preventive measures, including sequential intervention approaches. Probabilistic Markov models of health states, e.g. those used for health economic analysis, are discussed as a simple starting point for the platform. A path towards extension into other indications, data types and uses is discussed, with a focus on regenerative medicine and relevant pathobiology.https://f1000research.com/articles/6-309/v1Health Systems & Services Research |
| spellingShingle | Michael Rebhan Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved] F1000Research Health Systems & Services Research |
| title | Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved] |
| title_full | Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved] |
| title_fullStr | Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved] |
| title_full_unstemmed | Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved] |
| title_short | Towards a systems approach for chronic diseases, based on health state modeling [version 1; referees: 2 approved] |
| title_sort | towards a systems approach for chronic diseases based on health state modeling version 1 referees 2 approved |
| topic | Health Systems & Services Research |
| url | https://f1000research.com/articles/6-309/v1 |
| work_keys_str_mv | AT michaelrebhan towardsasystemsapproachforchronicdiseasesbasedonhealthstatemodelingversion1referees2approved |