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This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

The study examines the impact of socio-economic governance on economic growth in Nigeria. It measures socio-economic governance from the perspective of fiscal policy, using indicators such as investment in education, research and development (R&D) and health.

This study employs the Autoregressive Distributive Lag (ARDL) Bound Testing method to achieve its objective.

The study finds that socio-economic policies aimed at increasing investment in education are crucial for Nigeria’s long-term economic growth. Additionally, investment in R&D positively impacts economic growth. However, the study reveals that investment in health negatively affects economic growth in Nigeria in the long run. This suggests that if a country overinvests in health, it may divert resources from other vital sectors such as education, infrastructure and R&D, which can hinder overall economic growth. The short-run parameter is, however, not statistically significant in this study.

The study’s originality lies in its exploration of the relationship between socio-economic governance and economic growth in Nigeria, specifically from a fiscal policy perspective. It highlights the importance of investing in education and R&D for long-term economic growth. Additionally, the finding that overinvestment in health may have a negative impact on long-term economic growth provides valuable insight for policymakers in Nigeria and other developing countries. Overall, this study’s findings can be beneficial for policymakers and researchers interested in the intersection between socio-economic governance and economic growth in developing countries.

Research has examined how new ventures strengthen local economic outcomes; however, limited research examines health-oriented ventures and their impact on social outcomes, including health outcomes. Increased VC investment in healthcare service start-ups signals more activity toward this end, and the need for further academic inquiry. We examine the relationship between these start-ups and county-level health outcomes, health factors, and hospital utilization.

Data on start-ups funded via institutional venture capital from PitchBook were merged with US county-level outcomes from the County Health Rankings and Area Health Resources Files for 2010 to 2019. We investigated how the number of VC-funded healthcare service start-ups, as well as a subset defined as innovative, were associated with county-level health measures. We used panel models with two-way fixed effects and Propensity Score Matched (PSM), controlling for demographics and socioeconomic factors.

Each additional VC-funded healthcare service start-up was related to a significant 0.01 percentage point decrease in diabetes prevalence (p < 0.01), a decrease of 1.54 HIV cases per 100,000 population (p < 0.1), a 0.02 percentage point decrease in obesity rates (p < 0.01), and a 0.03 percentage point decrease in binge drinking (p < 0.01). VC-funded healthcare service start-ups were not related to hospital utilization.

This work expands our understanding of how industry-specific start-ups, in this case healthcare start-ups, relate to positive social outcomes. The results underscore the importance of evidence-based evaluation, the need for expanded outcome measures for VC investment, and the possibilities for integration of healthcare services and entrepreneurship ecosystems.

Some progress have been made over time in improving health conditions in Sub-Saharan Africa (SSA). There are, however, contradicting reports on the relationship between health outcomes and economic growth in the region. The paper aimed at assessing the effect of health outcome on economic growth in SSA.

Data for 41 countries from 2000 to 2018 were obtained from WDI and WGI and analyzed using system generalized method of moment (sGMM) which is appropriate for the present scenario. AR(1) and AR(2) tests were used to assess the validity of the model while Sargan and Hansen tests were adopted to examine the validity of the instrumental variables. The robustness of the estimation was confirmed using the pooled OLS and fixed effect regression.

Health outcome (proxied by life expectancy), lagged GDP per capita, capital formation, labor force (LF), health expenditure (HE), foreign direct investment (FDI) and trade openness (TOP) significantly affected economic growth emphasizing the importance of health in the process of economic growth in the region. AR(1) and AR(2) tests for serial correlation and Sargan/Hansen tests confirmed the validity of the estimated model and the instrumental variables respectively. Robustness of the GMM results was established from the pooled OLS and the fixed effect model results.

Improvement in the national health system possibly through the widespread adoption of National Health Insurance, increase government spending on healthcare alongside increased beneficial trade and ease of doing business to facilitate investment were recommended to enhance.

The study used up-to-date data with appropriate methodology.

The study aims to determine whether there is a bidirectional causality relationship between health expenditures and per capita income in Brazil, Russia, India, China, South Africa and Turkey (BRICS+T).

For that purpose, the 2000–2018 period data of the variables were tested with the Kónya (2006) panel causality test. Additionally, the causality relationships between public and private health expenditures and per capita income were also investigated in the study.

According to the analysis results, there is no statistically significant causality relationship from total health expenditures and public health expenditures to per capita income in the relevant countries. Besides, there is a unidirectional causality relationship from private health expenditures to per capita income only in Turkey. On the other hand, a unidirectional causality relationship from per capita income to total health expenditures in China, Russia, Turkey and South Africa and from per capita income to public health expenditures in India, Russia, Turkey and South Africa were determined. Consequently, a causality relationship from per capita income to private health expenditures was found out in Russia and Turkey.

The variables are tested for the first time for BRICS+T countries, vis-à-vis the period under consideration and the method used.

Health for all is an ideal goal that all governments aspire to reach. The purpose of this paper is to assess the definitions of the key terms used to better appreciate the role of the WHO member states in their efforts to achieve improved healthcare systems that suit each nation’s particular needs.

Definitions of the terms disease, illness and health are discussed against health concepts as a means of assessing the most effective approach toward achieving an effective universal healthcare system.

Universal health and treatment of sickness and disease have improved globally, but the target of achieving total wellness still remains as a goal for the future and may be impeded by diseases that have not yet evolved. The implementation of a universal health coverage system is a positive step toward achieving the goals of health and wellness for the present times.

This is a commentary piece.

The economic shock posed by the current COVID-19 outbreak brought out a worldwide public health emergency with a close relationship between the industrial marketing practices, the health level of society and its economic development. The purpose of this study is to analyse the industrial dynamics in health care and their impact on economic growth and health status.

To empirically investigate the relationship between growth and health, the authors use a data set drawn from 29 selected Organisation for Economic Co-operation and Development (OECD) countries over the period 2000 and 2019. Using panel regressions, the authors investigate the impact of the health-care industry measured in terms of health status, health expenditure, sales on pharmaceutical products, the number of persons working in health care and the coverage by private health insurances. Fixed effect and random effect regressions are used to estimate this model.

Overall, the results are suggestive of a nexus between the industrial marketing dynamics of health-care context and economic growth – both interacting and improving each other. As the quality of the health-care market enhances, the economy grows richer and the health status of the population improves considerably.

To support health-care markets in OECD countries, health policymakers need to formulate a long-term industrial health policy that addresses all the social and individual determinants of health.

To the best of the knowledge, this is the first study to provide a better understanding of the relationship between health-care industrial dynamics and economic growth in OECD countries along different dimensions.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Previous research has identified associations between quality management and employee health. This study's purpose was to (1) examine those associations in a public healthcare organisation and (2) explore and describe the association between digitalisation and employee health.

An online questionnaire including indices to measure quality management values, employee health and digitalisation was answered by 118 managers in Swedish public healthcare. Correlation analysis was used to analyse the data. Based on the survey results, 12 qualitative, in-depth interviews were conducted with healthcare managers.

The findings show that employee health is associated with quality management and digitalisation. Categories were defined to describe the managers' views of the relationship between digitalisation and health.

Causality was not explicitly tested and cannot be assumed. However, the results strengthen the body of research showing that quality management is related to employee health, and associations between health and digitalisation were identified.

The findings and model should be helpful for healthcare managers in a digitalising environment who aim to preserve or enhance employee health whilst ensuring high service quality.

The results were used to create an integrated conceptual model depicting the association between quality, digitalisation and health. This association has not previously been studied.