Measuring the health of people in places: a scoping review of OECD member countries

ABSTRACTBackgroundDefining and measuring population health in places is fundamental for local and national planning and conducting within-country and cross-national health comparisons. Yet availability and comparability of place-level health data is unknown.MethodsA scoping review was performed to identify how Organisation for Economic Co-operation and Development (OECD) countries measure overall health for sub-national geographies within each country. The search was conducted across MEDLINE, Scopus and Google Scholar, supplemented by searching all 38 OECD countries statistical agency and public health institute websites.ResultsSixty publications were selected, plus extracted information from 37 of 38 OECD countries statistical agency and/or public health institute websites. Data sources varied by categorisation into mortality (n=7) or morbidity (n=5) health indicators: the former mostly from national statistical agencies and the latter from population-level surveys. Region was the most common geographic scale: eight indicators for 26 countries, two indicators for 24 countries and one indicator for 20 countries. Similar but slightly fewer indicators were available for urban areas (max countries per most frequent indicator = 24), followed by municipality (range of 1-14 countries per indicator). Other geographies, particularly those at smaller granularity, were infrequently available across health indicators and countries.ConclusionHealth indicator data at sub-national geographies are generally only available for a limited number of indicators at large administrative boundaries. Relative uniformity of health indicator question format allows cross-national comparisons. However, wider availability of health indicators at smaller, and non-administrative, geographies is needed to explore the best way to measure population health in local areas.

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Artificial intelligence for good health: a scoping review of the ethics literature

BMC Medical Ethics ◽

10.1186/s12910-021-00577-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Kathleen Murphy ◽

Erica Di Ruggiero ◽

Ross Upshur ◽

Donald J. Willison ◽

Neha Malhotra ◽

...

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Global Health ◽

Population Health ◽

Health Systems ◽

Scoping Review ◽

Industrial Revolution ◽

Ethical Issues ◽

Grey Literature ◽

Ethical Implications

Abstract Background Artificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective? Methods Eight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed. Results Upon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs). Conclusions The ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere.

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Opioid mortality, public health care expenditures, and cross-national homicide rates: findings from 25 OECD countries, 2000–2017

Social Psychiatry and Psychiatric Epidemiology ◽

10.1007/s00127-021-02177-8 ◽

2021 ◽

Author(s):

Alexander Testa ◽

Douglas B. Weiss ◽

Mateus R. Santos

Keyword(s):

Public Health ◽

Health Care ◽

Health Care Expenditures ◽

Oecd Countries ◽

Public Health Care ◽

Homicide Rates ◽

Cross National

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National Public Health Institute Legal Framework: A Tool to Build Public Health Capacity

Health Security ◽

10.1089/hs.2019.0093 ◽

2020 ◽

Vol 18 (S1) ◽

pp. S-43-S-52 ◽

Cited By ~ 2

Author(s):

Emily L. Rosenfeld ◽

Sue Binder ◽

C. Adam Brush ◽

Ellen A. Spotts Whitney ◽

Dennis Jarvis ◽

...

Keyword(s):

Public Health ◽

Legal Framework ◽

National Public Health Institute ◽

Health Institute ◽

National Public Health ◽

Public Health Institute

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Disease modeling for public health: added value, challenges, and institutional constraints

Journal of Public Health Policy ◽

10.1057/s41271-019-00206-0 ◽

2019 ◽

Vol 41 (1) ◽

pp. 39-51 ◽

Cited By ~ 5

Author(s):

Mirjam Kretzschmar

Keyword(s):

Public Health ◽

Mathematical Modeling ◽

Disease Modeling ◽

Scientific Evidence ◽

Policy Support ◽

Added Value ◽

National Public Health Institute ◽

Health Institute ◽

National Public Health ◽

Public Health Institute

AbstractPublic health policymakers face increasingly complex questions and decisions and need to deal with an increasing quantity of data and information. For policy advisors to make use of scientific evidence and to assess available intervention options effectively and therefore indirectly for those deciding on and implementing public health policies, mathematical modeling has proven to be a useful tool. In some areas, the use of mathematical modeling for public health policy support has become standard practice at various levels of decision-making. To make use of this tool effectively within public health organizations, it is necessary to provide good infrastructure and ensure close collaboration between modelers and policymakers. Based on experience from a national public health institute, we discuss the strategic requirements for good modeling practice for public health. For modeling to be of maximal value for a public health institute, the organization and budgeting of mathematical modeling should be transparent, and a long-term strategy for how to position and develop mathematical modeling should be in place.

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Occupational Medicine in cardiovascular risk prevention by ergometry and psycho test implementing physical activities in Public Health Institute employees

Journal of Hospital Administration ◽

10.5430/jha.v4n6p89 ◽

2015 ◽

Vol 4 (6) ◽

pp. 89

Author(s):

Lalić Hrvoje

Keyword(s):

Public Health ◽

Occupational Medicine ◽

Stress Test ◽

Physical Activities ◽

Bicycle Ergometry ◽

Health Institute ◽

Short Period ◽

Burden Test ◽

Project Objectives ◽

Public Health Institute

Within the WHO global action against chronic noninfectious diseases the local action in cooperation of Occupational Medicine and Sports and Public Health Institute in Rijeka, Croatia has been undertaken. The Project objectives were improvement of psychophysical condition of women employed in the Institute and also to spark their interest in health and physical activities. The research comprised ergometry testing 19 female employees and so the levels of glucose and lactate were tested before and after ergometry burden. They have undergone the battery of psycho tests, stress test, test of anxiety as condition, test of anxiety as trait personality and test of depression. They had 6 weeks of physical exercises 1 hour twice a week monitored by a kinesiologist. After the exercises the results proved positive but not statistically due to short period of exercises. The Scout lactate test p = .357, p > .05 indicated a minor increase of lactate after the bicycle ergometry burden test and conducted programmed exercises in relation to the bicycle ergometry burden test before the exercises. Bionime glucose test after the burden and exercise showed a decrease but smaller compared to the burden test before exercises, p = .250, p > .05 which indicates improved fitness though not significant. Concerning psychic parameters the exercises resulted in significant differences in depression, p = .0197, p < .05. In conclusion, besides the importance of carrying out such programmed physical activities, diagnosed Electrocardiograph (ECG) changes, of 19 employees one was cosmetic and one cardiac organic change, point to the significance of screening in Occupational Medicine and Sports in diagnosing potential cardiac diseases in working population.

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