Public health economics: a systematic review of guidance for the economic evaluation of public health interventions and discussion of key methodological issues

Public health has been described as the organized activities of society to improve and protect the health of the population. Health economics applied to public health is the study of how we allocate our scarce societal resources to meet our public health wants and needs in the best way possible. This book presents current thinking on health economics methodology and application to the evaluation of public health interventions (PHIs). It is for health economists working in higher education and public healthcare systems, challenged with the economic evaluation of PHIs, when they have been used to applying health economics and the methods of economic evaluation to narrower clinical interventions in primary or secondary care settings. This book will also be of interest to public health practitioners wanting to incorporate health economics into their daily work. This book covers the history of economics of public health and the economic rationale for government investment in prevention; principles of health economics including scarcity, choice, and opportunity cost; evidence synthesis; key methods of economic evaluation with accompanying case studies; economic modelling of public health interventions; return on investment analysis with national and international case studies; and application of programme budgeting and marginal analysis (PBMA) to the prioritization of PHIs. It concludes with priorities for research in the field of public health economics, spanning an acknowledgement of the role played by the natural environment in promoting better health, through to precision public health, recognizing the role of genetics, the environment, and socioeconomic status in determining population health.

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Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094499 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4499

Author(s):

Anil Babu Payedimarri ◽

Diego Concina ◽

Luigi Portinale ◽

Massimo Canonico ◽

Deborah Seys ◽

...

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Machine Learning ◽

Systematic Review ◽

Public Transportation ◽

Prediction Models ◽

Positive Impact ◽

Health Interventions ◽

Public Health Interventions ◽

Commercial Activities

Artificial Intelligence (AI) and Machine Learning (ML) have expanded their utilization in different fields of medicine. During the SARS-CoV-2 outbreak, AI and ML were also applied for the evaluation and/or implementation of public health interventions aimed to flatten the epidemiological curve. This systematic review aims to evaluate the effectiveness of the use of AI and ML when applied to public health interventions to contain the spread of SARS-CoV-2. Our findings showed that quarantine should be the best strategy for containing COVID-19. Nationwide lockdown also showed positive impact, whereas social distancing should be considered to be effective only in combination with other interventions including the closure of schools and commercial activities and the limitation of public transportation. Our findings also showed that all the interventions should be initiated early in the pandemic and continued for a sustained period. Despite the study limitation, we concluded that AI and ML could be of help for policy makers to define the strategies for containing the COVID-19 pandemic.

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The use of modelling approaches for the economic evaluation of public health interventions

Applied Health Economics for Public Health Practice and Research ◽

10.1093/med/9780198737483.003.0011 ◽

2019 ◽

pp. 248-278

Author(s):

Hazel Squires ◽

Kathleen Boyd

Keyword(s):

Public Health ◽

Health Economic ◽

Economic Evaluation ◽

Health Economic Evaluation ◽

Health Interventions ◽

Primary Data ◽

Public Health Interventions ◽

Modelling Framework ◽

Decision Analytic Modelling ◽

Complex Relationships

This chapter considers the use of modelling for public health economic evaluation. The approach to decision analytic modelling within health economic evaluation is described and five key challenges relating to modelling public health interventions are highlighted: incorporating equity; extrapolating multi-component intervention effectiveness beyond study data; capturing relevant complex relationships and feedback loops of a dynamically complex system; modelling human behaviour; and capturing relevant non-health costs and outcomes and the relationship between individual and social determinants. The chapter describes current practice and the latest methodological research in these areas. It outlines two general approaches which could help to address these challenges by (i) adopting an iterative approach to the evaluation by using early-stage decision modelling to guide primary data collection, and (ii) a conceptual modelling framework to guide the model development process.

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A systematic review of economic evaluations of public health interventions targeting alcohol, tobacco, illicit drug use and problematic gambling: Using a case study to assess transferability

Health Policy ◽

10.1016/j.healthpol.2020.09.002 ◽

2021 ◽

Vol 125 (1) ◽

pp. 54-74

Author(s):

Camilla Nystrand ◽

Mihretab Gebreslassie ◽

Richard Ssegonja ◽

Inna Feldman ◽

Filipa Sampaio

Keyword(s):

Public Health ◽

Systematic Review ◽

Drug Use ◽

Illicit Drug ◽

Illicit Drug Use ◽

Health Interventions ◽

Economic Evaluations ◽

Public Health Interventions ◽

Problematic Gambling

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OP06 Evaluating Public Health Interventions: A Neglected Area In HTA

International Journal of Technology Assessment in Health Care ◽

10.1017/s0266462319000850 ◽

2019 ◽

Vol 35 (S1) ◽

pp. 1-1

Author(s):

Irene Lenoir-Wijnkoop ◽

Jovana Stojanovic ◽

Eva Reviriego Rodrigo ◽

Alexia Campbell Burton ◽

Grace Hampson ◽

...

Keyword(s):

Public Health ◽

Budget Impact ◽

Health Interventions ◽

Organizational Impact ◽

Global Level ◽

Methodological Issues ◽

Public Health Interventions ◽

Health Outcomes Research ◽

Complex Design ◽

Methodological Aspects

IntroductionPublic health (PH) interventions are crucial for ensuring sustainable healthcare infrastructures. Nevertheless, they represent a neglected area in HTA due to various methodological issues and their complex design that goes beyond clinical setting. Our study provides an environmental scan of HTA initiatives related to the assessment of PH technologies on a global level.MethodsThe Initiative for Public Health Outcomes Research and Measurement (INPHORM) interest group has conducted a survey among European and international societies, health bodies and networks during September 2018. The questionnaire evaluates what kind of PH technologies and/or interventions have been evaluated in the last five years, or are planned for the future.ResultsOur preliminary findings from November 2018 indicate a total of 94 initiated and 44 completed surveys. Among the completed ones, the majority of respondents came from European countries (36%), followed by North (30%) and South America (16%) countries. Sixty-eight percent of institutions reported engagement in any aspect of HTA in the area of PH (N = 30). Medical aspects of the PH technology are considered by 83 percent of the institutions, followed by organizational impact (67%), economic evaluation (60%) and societal consequences (60%). An average of four PH technologies has been evaluated by the responding institutions in the last five years. In reference to methodological aspects, 90 percent of institutions used a classical HTA approach for evaluating PH interventions, while 40 percent used budget impact analyses. Among the barriers for reaching a decision, conflicting stakeholder priorities, lack of data and clear methodological frameworks were most commonly cited.ConclusionsData analysis is currently on-going and final results will be presented during the Cologne meeting. This study will allow to raise awareness about the importance of PH interventions in HTA, identify existing gaps and propose future methodological developments.

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