A data-driven decision-support tool for population health policies

Michal Chorev; Lavi Shpigelman; Peter Bak; Avi Yaeli; Edwin Michael; Ya'ara Goldschmidt

doi:10.3233/978-1-61499-830-3-332

A data-driven decision-support tool for population health policies

Michal Chorev^*
, Lavi Shpigelman
, Peter Bak
, Avi Yaeli
, Edwin Michael
, Ya'ara Goldschmidt

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Epidemiological models are key tools in assessing intervention policies for population health management. Statistical models, fitted with survey or health system data, can be combined with lab and field studies to provide reliable predictions of future population-level disease dynamics distributions and the effects of interventions. All too often, however, the end result of epidemiological modeling and cost-effectiveness studies is in the form of a report or journal paper. These are inherently limited in their coverage of locations, policy options, and derived outcome measures. Here, we describe a tool to support population health policy planning. The tool allows users to explore simulations of various policies, to view and compare interventions spanning multiple variables, time points, and locations. The design's modular architecture, and data representation separate the modeling methods, the outcome measures calculations, and the visualizations, making each component easily replaceable. These advantages make it extremely versatile and suitable for multiple uses.

Original language	English
Title of host publication	MEDINFO 2017
Subtitle of host publication	Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
Editors	Adi V. Gundlapalli, Jaulent Marie-Christine, Zhao Dongsheng
Publisher	IOS Press BV
Pages	332-336
Number of pages	5
ISBN (Electronic)	9781614998297
DOIs	https://doi.org/10.3233/978-1-61499-830-3-332
State	Published - 2017
Externally published	Yes
Event	16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China Duration: 21 Aug 2017 → 25 Aug 2017

Publication series

Name	Studies in Health Technology and Informatics
Volume	245
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
Country/Territory	China
City	Hangzhou
Period	21/08/17 → 25/08/17

Bibliographical note

Publisher Copyright:
© 2017 International Medical Informatics Association (IMIA) and IOS Press.

Keywords

Computer-assisted decision making
Statistical models
Stochastic processes

Access to Document

10.3233/978-1-61499-830-3-332

Cite this

Chorev, M., Shpigelman, L., Bak, P., Yaeli, A., Michael, E., & Goldschmidt, Y. (2017). A data-driven decision-support tool for population health policies. In A. V. Gundlapalli, J. Marie-Christine, & Z. Dongsheng (Eds.), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics (pp. 332-336). (Studies in Health Technology and Informatics; Vol. 245). IOS Press BV. https://doi.org/10.3233/978-1-61499-830-3-332

Chorev, Michal ; Shpigelman, Lavi ; Bak, Peter et al. / A data-driven decision-support tool for population health policies. MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. editor / Adi V. Gundlapalli ; Jaulent Marie-Christine ; Zhao Dongsheng. IOS Press BV, 2017. pp. 332-336 (Studies in Health Technology and Informatics).

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title = "A data-driven decision-support tool for population health policies",

abstract = "Epidemiological models are key tools in assessing intervention policies for population health management. Statistical models, fitted with survey or health system data, can be combined with lab and field studies to provide reliable predictions of future population-level disease dynamics distributions and the effects of interventions. All too often, however, the end result of epidemiological modeling and cost-effectiveness studies is in the form of a report or journal paper. These are inherently limited in their coverage of locations, policy options, and derived outcome measures. Here, we describe a tool to support population health policy planning. The tool allows users to explore simulations of various policies, to view and compare interventions spanning multiple variables, time points, and locations. The design's modular architecture, and data representation separate the modeling methods, the outcome measures calculations, and the visualizations, making each component easily replaceable. These advantages make it extremely versatile and suitable for multiple uses.",

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author = "Michal Chorev and Lavi Shpigelman and Peter Bak and Avi Yaeli and Edwin Michael and Ya'ara Goldschmidt",

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Chorev, M, Shpigelman, L, Bak, P, Yaeli, A, Michael, E & Goldschmidt, Y 2017, A data-driven decision-support tool for population health policies. in AV Gundlapalli, J Marie-Christine & Z Dongsheng (eds), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 245, IOS Press BV, pp. 332-336, 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017, Hangzhou, China, 21/08/17. https://doi.org/10.3233/978-1-61499-830-3-332

A data-driven decision-support tool for population health policies. / Chorev, Michal; Shpigelman, Lavi; Bak, Peter et al.
MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. ed. / Adi V. Gundlapalli; Jaulent Marie-Christine; Zhao Dongsheng. IOS Press BV, 2017. p. 332-336 (Studies in Health Technology and Informatics; Vol. 245).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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ER -

Chorev M, Shpigelman L, Bak P, Yaeli A, Michael E, Goldschmidt Y. A data-driven decision-support tool for population health policies. In Gundlapalli AV, Marie-Christine J, Dongsheng Z, editors, MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. IOS Press BV. 2017. p. 332-336. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-830-3-332

A data-driven decision-support tool for population health policies

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this