Population Health Management: principles, models and areas of application in public health
Keywords:
Population Health Management, Public HealthAbstract
There is no single model for Population Health Management (PHM) and different definitions have been proposed. All PHM models and definitions share the overall aim of improving population health and reduce healthcare costs. To achieve these objectives, PHM makes use of conceptual tools such as the Chronic Care Model and predictive medicine, and technical tools such as information systems and computational and record-linkage techniques to collect and analyse data. Using these tools, it makes it feasible to articulate PHM approaches in the following steps: identification of a population, stratification of individuals according to risk levels, mapping of health needs and development of targeted interventions and models of care. PHM has been applied in a variety of national and regional settings, proving to have great potential. However, the success of PHM models depends on a number of factors. In particular, few key points have emerged that must be taken into consideration when planning and implementing PHM programs. They include PHM funding schemes, strategies to ensure people adherence, the equity dimension in its multiple aspects, and the privacy of personal data. In addition to these challenges, there is the need to act in a legislative context appropriate to the implementation of PHM.
References
Signorelli C. Igiene e Sanità Pubblica, 3° Edizione. Società Editrice Universo; 2021.
Listed NA. Revisione di letteratura per l’identificazione di modelli specifici per la costruzione di un profilo di Salute nelle ASP della Regione Sicilia. Fondo Europeo di Sviluppo Regionale; 2013.
Amelung V. Handbook Integrated Care, 2° Edition. Springer International Publishing, 2021. doi: 10.1007/978-3-030-69262-9.
Steenkamer BM, Drewes HW, Heijink R, Baan CA, Struijs JN. Defining Population Health Management: A Scoping Review of the Literature. Popul Health Manag. 2017 Feb;20(1):74-85. doi: 10.1089/pop.2015.0149.
Berwick DM, Nolan TW, Whittington J. The triple aim: care, health, and cost. Health Aff (Millwood). 2008 May-Jun;27(3):759-69. doi: 10.1377/hlthaff.27.3.759.
Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract. 1998;1(1):2-4. PMID: 10345255
Wasfy JH, Ferris TG. The Business Case for Population Health Management. Prim Care. 2019 Dec;46(4):623-629. doi: 10.1016/j.pop.2019.07.003.
Kaiser Permanente Washington Population Health Program Description. Mar. 2020. https://wa.kaiserpermanente.org/static/pdf/public/about/population-health-2020.pdf (accessed Mar 28, 2023).
Hibbard JH, Greene J, Sacks RM, Overton V, Parrotta C. Improving Population Health Management Strategies: Identifying Patients Who Are More Likely to Be Users of Avoidable Costly Care and Those More Likely to Develop a New Chronic Disease. Health Serv Res. 2017 Aug;52(4):1297-1309. doi: 10.1111/1475-6773.12545.
Morando V, Tozzi V. Population health management e PDTA: prove tecniche di implementazione. In: Rapporto OASI; 2015.
Regione Lombardia. DGR N° X/6164. Governo della domanda: avvio della presa in carico di pazienti cronici e fragili. Determinazioni in attuazione dell’art. 9 della Legge n. 23/2015; 2017.
Signorelli C, Odone A, Oradini-Alacreu A, Pelissero G. Universal Health Coverage in Italy: lights and shades of the Italian National Health Service which celebrated its 40th anniversary. Health Policy. 2020 Jan;124(1):69-74. doi: 10.1016/j.healthpol.2019.11.002.
Fernandez-Lazaro CI, García-González JM, Adams DP, Fernandez-Lazaro D, Mielgo-Ayuso J, Caballero-Garcia A, et al. Adherence to treatment and related factors among patients with chronic conditions in primary care: a cross-sectional study. BMC Fam Pract. 2019 Sep 14;20(1):132. doi: 10.1186/s12875-019-1019-3.
White K, Lawrence JA, Tchangalova N, Huang SJ, Cummings JL. Socially-assigned race and health: a scoping review with global implications for population health equity. Int J Equity Health. 2020 Feb 10;19(1):25. doi: 10.1186/s12939-020-1137-5.
Blandi L, Sabbatucci M, Dallagiacoma G, Alberti F, Bertuccio P, Odone A. Digital Information Approach through Social Media among Gen Z and Millennials: The Global Scenario during the COVID-19 Pandemic. Vaccines (Basel). 2022 Oct 28;10(11):1822. doi: 10.3390/vaccines10111822.
Garante della Privacy. Provvedimento del 24 febbraio 2022 [9752221]. https://www.garanteprivacy.it/web/guest/home
/docweb/-/docweb-display/docweb/9752221 (accessed Mar25, 2023).
Garante della Privacy. Valutazione di impatto sulla protezione dati relativa al trattamento [9808839]. https://www.garanteprivacy.it/web/guest/home/docweb/-/docweb-display/docweb/9808839 (accessed Mar 25, 2023).
Corti MC, Avossa F, Schievano E, Gallina P, Ferroni E, Alba N, et al. A case-mix classification system for explaining healthcare costs using administrative data in Italy. Eur J Intern Med. 2018 Aug;54:13-16. doi: 10.1016/j.ejim.2018.02.035.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Lorenzo Blandi, Leonardo Pegollo, Leandro Gentile, Anna Odone
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Transfer of Copyright and Permission to Reproduce Parts of Published Papers.
Authors retain the copyright for their published work. No formal permission will be required to reproduce parts (tables or illustrations) of published papers, provided the source is quoted appropriately and reproduction has no commercial intent. Reproductions with commercial intent will require written permission and payment of royalties.