Abstract
Background
Population health monitoring, the regular and institutionalized production and dissemination of information and knowledge about the health status of a population, is an essential element of public health. Nevertheless, while epidemiology and biostatistics, for example, are well-recognized disciplines, this does not (yet) apply to population health monitoring. Over the past decade, however, it has matured as a distinct field of expertise.
Objectives
This paper presents a comprehensive model for population health monitoring and describes its current status as a field of expertise. It concludes with an overview of the most important developments that are likely to shape the health information systems and population health monitoring practices of the future.
Results and conclusions
Combining the information pyramid (an application of the data–information–knowledge–wisdom hierarchy), describing outputs, and a so-called monitoring chain, describing activities, results in a comprehensive model for population health monitoring. The steps of the activity chain can be viewed as a stairway by which the information pyramid is climbed, reaching evidence-informed policymaking at the top. Population health monitoring has several inherent strengths, such as its high societal relevance; its integrative, comprehensive, and structured approach; and the fact that it makes use of routinely collected data. In practice, however, secondary use of routine data is often hampered by technical, motivational, economic, political, ethical, and legal barriers. Important developments that will shape health information systems and population health monitoring practices of the future include digitalization and data-driven technology, citizen science, and the growing need for intersectoral approaches. Population health monitoring practice will need to adapt in order to counteract the risks and reap the benefits that these developments hold.
Zusammenfassung
Hintergrund
Gesundheitsmonitoring auf Bevölkerungsebene – verstanden als regelmäßige und institutionalisierte Erhebung und Verbreitung von Informationen über den Gesundheitszustand einer Bevölkerung einschließlich Gesundheitsberichterstattung – ist eine wichtige Aufgabe des Öffentlichen Gesundheitsdienstes. Doch während z. B. die Epidemiologie und Biostatistik anerkannte Disziplinen sind, gilt dies für das Gesundheitsmonitoring (noch) nicht. In den letzten zehn Jahren hat es sich jedoch zunehmend zu einem eigenständigen Gebiet entwickelt.
Zielsetzungen
Dieser Artikel stellt ein umfassendes Modell eines Gesundheitsmonitorings der Bevölkerung vor und beschreibt dessen aktuellen Status als Fachbereich. Der Artikel schließt mit einem Überblick über die wichtigsten Entwicklungen, die Gesundheitsinformationssysteme und die Praxis des Gesundheitsmonitorings in Zukunft prägen dürften.
Ergebnisse und Schlussfolgerung
Das vorgestellte Modell eines Gesundheitsmonitorings kombiniert die Informationspyramide (eine Anwendung der Daten-Information-Wissen-Weisheit-Hierarchie), die die Ergebnisse beschreibt, und den sog. Monitoringprozess, der die Aktivitäten beschreibt. Der Monitoringprozess kann als Treppe verstanden werden, über die die Informationspyramide erklommen wird, um an der Spitze eine evidenzbasierte Politikgestaltung zu erreichen. Ein so verstandenes Gesundheitsmonitoring hat mehrere inhärente Stärken. Zu diesen gehören eine hohe gesellschaftliche Relevanz, der integrative, umfassende und strukturierte Ansatz sowie die Nutzung von routinemäßig erhobenen Daten. In der Praxis stößt die sekundäre Nutzung von Routinedaten jedoch häufig auf technische, wirtschaftliche, politische, ethische und rechtliche Barrieren. Zu den wichtigen Entwicklungen, die Gesundheitsinformationssysteme und Gesundheitsmonitoring in der Zukunft prägen werden, gehören Digitalisierung und datengesteuerte Technologien, Bürgerwissenschaft (Citizen Science) und der wachsende Bedarf an sektorenübergreifenden Ansätzen. Gesundheitsmonitoring wird sich anpassen müssen, um den Risiken entgegenzuwirken und die Vorteile zu nutzen, die diese Entwicklungen mit sich bringen.
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Notes
As yet unpublished findings of the nine health information system assessments carried out within the InfAct Joint Action (see reference [11]). Personal communications with Neville Calleja, Ministry of Health, Malta, and Petronille Bogaert, Sciensano, Belgium, who were involved in the assessments.
As yet unpublished findings of the nine health information system assessments carried out within the InfAct Joint Action (see reference [11]). Personal communications with Neville Calleja, Ministry of Health, Malta, and Petronille Bogaert, Sciensano, Belgium, who were involved in the assessments.
References
Verschuuren M, van Oers H (2019) Introduction. In: Verschuuren M, van Oers H (eds) Population Health Monitoring. Climbing the Information Pyramid. Springer Nature, Cham, Switzerland, P 1–9. https://doi.org/10.1007/978-3-319-76562-4_1
Graunt J (1662) Natural and political observations made upon the bills of mortality. London
WHO (2020). EPHO1: Surveillance of population health and wellbeing. http://www.euro.who.int/en/health-topics/Health-systems/public-health-services/policy/the-10-essential-public-health-operations/epho1-surveillance-of-population-health-and-wellbeing Accessed: 25 February 2020
Ackoff R‑L (1989) From data to wisdom. J Appl Syst Analysis 16:3–9
Rechel B, Rosenkoetter N, Verschuuren M and van Oers H (2019) Health Information Systems. In: Verschuuren M, van Oers H (eds) Population Health Monitoring. Climbing the Information Pyramid. Springer Nature, Cham, Switzerland, P 11–34. https://doi.org/10.1007/978-3-319-76562-4_2
Institute of Medicine (2011) The Learning Health System and its Innovation Collaboratives. Update Report. http://www.nationalacademies.org/hmd/Activities/Quality/~/media/Files/Activity%20Files/Quality/VSRT/Core%20Documents/ForEDistrib.pdf Accessed: 25 February 2020
Krumholz H‑M, Terry S‑F, MA; Waldstreicher J (2016) Data Acquisition, Curation, and Use for a Continuously Learning Health System. JAMA 316(16):1669–1670
Jansen T, Coppen R, Urbanus T, Bos N, Verheij R (2019) Naar een lerend zorgsysteem voor de ambulancezorg: haalbaarheidsstudie hergebruik en gegevenskoppeling routine zorgdata. https://www.nivel.nl/nl/publicatie/naar-een-lerend-zorgsysteem-voor-de-ambulancezorg-haalbaarheidsstudie-hergebruik-en. Accessed 25 Feb 2020
Dahlgren G, Whitehead M (1991) Policies and strategies to promote social equity in health. https://www.iffs.se/en/publications/working-papers/policies-and-strategies-to-promote-social-equity-in-health/. Accessed 25 Feb 2020
EUPHA (2020) Public Health Monitoring and Reporting. https://eupha.org/public-health-monitoring-and-reporting. Accessed 25 Feb 2020
Verschuuren M, Diallo K, Calleja N, Burazeri G, Stein C (2016) First experiences with a WHO tool for assessing health information systems. Public Health. Panorama 2(3):249–400
InfAct Joint Action on Health Information (2020) WP 5: Status of health information systems in MS and regions. https://www.inf-act.eu/wp5 Accessed: 25 February 2020
Bogaert P, Van Oyen H; for BRIDGE Health (2017) An integrated and sustainable EU health information system: national public health institutes’ needs and possible benefits. Arch Public Health 75:3
van Panhuis W‑G, Paul P, Emerson C et al (2014) A systematic review of barriers to data sharing in public health. Bmc Public Health 14(1144). https://doi.org/10.1186/1471-2458-14-1144
van Veen E‑B (2018) Observational health research in Europe: understanding the General Data Protection Regulation and underlying debate. Eur J Cancer 104:70–80
Chico V (2018) The impact of the General Data Protection Regulation on health research. Br Med Bull 128(1):109–118
Clarke N, Vale G, Reeves E‑P et al (2019) GDPR: an impediment to research? Ir J Med Sci 188:1129–1135
Ministry of Social Affairs and Health (2020) Secondary use of health and social data. https://stm.fi/en/secondary-use-of-health-and-social-data. Accessed 25 Feb 2020
OECD (2019) Health in the 21st Century: Putting Data to Work for Stronger Health Systems. OECD Health Policy Studies. https://www.oecd-ilibrary.org/social-issues-migration-health/health-in-the-21st-century_e3b23f8e-en Accessed: 25 February 2020
Oderkirk J (2017) Readiness of electronic health record systems to contribute to national health information and research. OECD Health Working Papers, No. 99. https://www.oecd-ilibrary.org/social-issues-migration-health/readiness-of-electronic-health-record-systems-to-contribute-to-national-health-information-and-research_9e296bf3-en. Accessed 25 Feb 2020
European Commission (2019) European Commission (2019) State of Health in the EU: Companion Report. https://ec.europa.eu/health/sites/health/files/state/docs/2019_companion_en.pdf. Accessed 25 Feb 2020
Latulippe K, Hamel C, Giroux D (2017) Social health inequalities and ehealth: A literature review with qualitative synthesis of theoretical and empirical studies. J Med Internet Res 19(4):e136
Weiss D, Rydland H‑T, Øversveen E, Jensen M‑R, Solhaug S, Krokstad S (2018) Innovative technologies and social inequalities in health: A scoping review of the literature. PLoS ONE 13(4):e195447
University of Wisconsin System (2020) What Is Big Data? https://datasciencedegree.wisconsin.edu/data-science/what-is-big-data/ Accessed: 25 February 2020
Deville P, Linard C, Martin S, Gilbert M, Stevens F‑R, Gaughan A‑E et al (2014) Dynamic population mapping using mobile phone data. PNAS 111(45):15888–15893
Tijhuis M, Finger J, Slobbe L, Sund R, Tolonen H (2019) Data Collection. In: Verschuuren M, van Oers H (eds) Population Health Monitoring. Climbing the Information Pyramid. Springer Nature, Cham, Switzerland, P 59–81. https://doi.org/10.1007/978-3-319-76562-4_4
Ledford H (2019) Millions of black people affected by racial bias in health-care algorithms. Nature 574(7780):608–609
Henley J, Booth R (2020) Welfare surveillance system violates human rights, Dutch court rules. https://amp-theguardian-com.cdn.ampproject.org/c/s/amp.theguardian.com/technology/2020/feb/05/welfare-surveillance-system-violates-human-rights-dutch-court-rules. Accessed 25 Feb 2020
Follett R, Strezov V (2015) An analysis of citizen science based research: Usage and publication patterns. PLoS ONE 10(11):e143687
RIVM (2015) iSPEX goes Europe: citizens measure air pollution with smartphone. https://www.rivm.nl/en/news/ispex-goes-europe-citizens-measure-air-pollution-with-smartphone Accessed: 25 February 2020
McKee M, Middleton J (2019) Information wars: tackling the threat from disinformation on vaccines. BMJ 365:l2144
WHO (2020) Urgent health challenges for the next decade. https://www.who.int/news-room/photo-story/photo-story-detail/urgent-health-challenges-for-the-next-decade Accessed: 25 February 2020
United Nations (2020) Sustainable Development Goals. https://sustainabledevelopment.un.org/?menu=1300 Accessed: 25 February 2020
WHO (2020) Sustainable Development Goals (SDGs). https://www.who.int/sdg/en/ Accessed: 25 February 2020
WHO (2018) Multisectoral and intersectoral action for improved health and well-being for all: mapping of the WHO European Region. http://www.euro.who.int/__data/assets/pdf_file/0005/371435/multisectoral-report-h1720-eng.pdf?ua=1 Accessed: 25 February 2020
United Nations (2018). The Sustainable Development Goals Report 2018. A Data Revolution in Motion. https://unstats.un.org/sdgs/report/2018/data_revolution Accessed: 25 February 2020
United Nations (2015) A/RES/70/1 Resolution adopted by the General Assembly on 25 September 2015. 70/1. Transforming our world: the 2030 Agenda for Sustainable Development. https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E Accessed: 25 February 2020
Eurostat (2016) Sustainable development in the European Union. A statistical glance from the viewpoint of the UN Sustainable Development Goals. https://ec.europa.eu/eurostat/documents/3217494/7745644/KS-02-16-996-EN-N.pdf Accessed: 25 February 2020
United Nations Secretary-General’s Independent Expert Advisory Group on a Data Revolution for Sustainable Development (2014) A World that Counts. Mobilising the Data Revolution for Sustainable Development. https://www.undatarevolution.org/wp-content/uploads/2014/11/A-World-That-Counts.pdf Accessed: 25 February 2020
Nunes A‑R, Lee K, O’Riordan T (2016) The importance of an integrating framework for achieving the Sustainable Development Goals: the example of health and well-being. Bmj Glob Health 1:e68
Kickbusch I (2010) Health in all policies: where to from here? Health Promot Int 25(3):261–264
Bambra C, Gibson M, Sowden A et al (2010) Tackling the wider social determinants of health and health inequalities: evidence from systematic reviews. J Epidemiol Community Health 64:284–291
Rutter H‑M‑B, Savona N, Glonti K, Bibby J, Cummins S, Finegood D‑T et al (2017) The need for a complex systems model of evidence for public health. The Lancet 390(10112):2602–2604
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M. Verschuuren and H. van Oers declare that they have no competing interests.
This article does not contain any studies with human or animal subjects.
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Verschuuren, M., van Oers, H. Population health monitoring: an essential public health field in motion. Bundesgesundheitsbl 63, 1134–1142 (2020). https://doi.org/10.1007/s00103-020-03205-9
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DOI: https://doi.org/10.1007/s00103-020-03205-9