Income and Technology as Drivers of Australian Healthcare Expenditures

Contribution of high-technology procedures to public healthcare expenditures: the case of ischemic heart disease in Portugal, 2002-2015

The magnitude of the impact of technological innovations on healthcare expenditure is unclear. This paper estimated the impact of high-technology procedures on public healthcare expenditure for patients with ischemic heart disease (IHD) in Portugal. The Blinder-Oaxaca decomposition method was applied to Portuguese NHS administrative data for IHD discharges during two periods, 2008-2015 vs. 2002-2007 (N = 434,870). We modelled per episode healthcare expenditures on the introduction of new technologies, adjusting for GDP, patient age, and comorbidities. The per episode healthcare expenditure was significantly higher in 2008-2015 compared to 2002-2007 for IHD discharges. The increase in the use of high-technology procedures contributed to 28.6% of this growth among all IHD patients, and to 18.4%, 6.8%, 11.1%, and 29.2% for acute myocardial infarction, unstable angina, stable angina, and other IHDs, respectively. Changes in the use of stents and embolic protection and/or coronary brachytherapy devices were the largest contributors to expenditure growth. High-technology procedures were confirmed as a key driver of public healthcare expenditure growth in Portugal, contributing to more than a quarter of this growth.

Factors influencing inequality in government health expenditures within African regional economic communities

BACKGROUND

The unequal distribution of government health spending within African regional economic groupings is a significant barrier to achieving Universal Health Coverage and reaching health-related Sustainable Development targets. It also hampers the progress toward achieving the African Union's vision of an integrated and prosperous Africa, free of its heavy disease burden. Based on panel data from 36 countries nested into eight Regional Economic Communities (RECs), this study probes the effects of countries' macro-level factors on government health expenditure disparities within eight regional economic communities from 2000 to 2019.

METHOD

We use the multilevel linear mixed-effect method to show whether countries' trade gains, life expectancy at birth, poverty, urbanization, information and communication technology, and population aging worsen or reduce the differences for two government health expenditure indicators.

RESULTS

The insignificant effect of GDP per capita suggests that in most regional economic groupings, the health sector is still not considered a high-priority sector regarding overall government expenditures. Countries' poverty levels and urbanization increase the domestic general government health expenditure disparities as a percentage of general government expenditure within the regional groupings. However, trade gains and ICT diffusion reduce these disparities. Furthermore, the results reveal that external health expenditure per capita and life expectancy at birth positively impact within-regional inequalities in the domestic general government health expenditure per capita. In contrast, GDP per capita and trade gains tend to reduce them.

CONCLUSIONS

This study enriches the research on the determinants of government health expenditure inequality in Africa. Policies that can spur growth in trade and ICT access should be encouraged. Countries should also make more efforts to reduce poverty. Governments should also develop policies promoting economic growth and planned urbanization.

Public preferences for the allocation of societal resources over different healthcare purposes

OBJECTIVE

Increasing healthcare expenditures require governments to make difficult prioritization decisions. Considering public preferences can help raise citizens' support. Previous research has predominantly elicited preferences for the allocation of public resources towards specific treatments or patient groups and principles for resource allocation. This study contributes by examining public preferences for budget allocation over various healthcare purposes in the Netherlands.

METHODS

We conducted a Participatory Value Evaluation (PVE) choice experiment in which 1408 respondents were asked to allocate a hypothetical budget over eight healthcare purposes: general practice and other easily accessible healthcare, hospital care, elderly care, disability care, mental healthcare, preventive care by encouragement, preventive care by discouragement, and new and better medicines. A default expenditure was set for each healthcare purpose, based on current expenditures. Respondents could adjust these default expenditures using sliders and were presented with the implications of their adjustments on health and well-being outcomes, the economy, and the healthcare premium. As a constraint, the maximum increase in the mandatory healthcare premium for adult citizens was €600 per year. The data were analysed using descriptive statistics and a Latent Class Cluster Analysis (LCCA).

RESULTS

On average, respondents preferred to increase total expenditures on all healthcare purposes, but especially on elderly care, new and better medicines, and mental healthcare. Three preference clusters were identified. The largest cluster preferred modest increases in expenditures, the second a much higher increase of expenditures, and the smallest favouring a substantial reduction of the healthcare premium by decreasing the expenditure on all healthcare purposes. The analyses also demonstrated substantial preference heterogeneity between clusters for budget allocation over different healthcare purposes.

CONCLUSIONS

The results of this choice experiment show that most citizens in the Netherlands support increasing healthcare expenditures. However, substantial heterogeneity was identified in preferences for healthcare purposes to prioritize. Considering these preferences may increase public support for prioritization decisions.

Health care expenditure and income in Canada: Evidence from panel data

This paper investigates the long-run relationship between health care expenditures (HCE) and income using Canadian provincial data spanning a period of 40 years from 1981 to 2020. We study the non-stationary and cointegration properties of HCE and income and estimate the long-run income elasticities of HCE. Using heterogeneous panel models that incorporate cross-section dependence via unobserved common correlated factors to capture global shocks, we estimate long-run income elasticities that lie in the 0.11-0.16 range. Our results indicate that health care is a necessity good for Canada. These elasticity estimates are much smaller than those estimated in other studies for Canada. We find that HCE and income in Canada are cointegrated and that short-run changes in federal transfers significantly and positively affect HCE.

Factors Associated with Out-of-Pocket Health Expenditure in Polish Regions

Out-of-pocket (OOP) payments are perceived as the most regressive means of health financing. Using the panel-data approach and region-aggregated data from Statistics Poland, this research investigated associations between socio-economic factors and OOP health spending in 16 Polish regions for the period 1999–2019. The dependent variable was real (inflation-adjusted) monthly OOP health expenditure per person in Polish households. Potential independent variables included economic, labour, demographic, educational, health, environmental, and lifestyle measures based on previous research. A set of panel-data estimators was used in regression models. The factors that were positively associated with OOP health spending were disposable income, the proportions of children (aged 0–9) and elderly (70+ years) in the population, healthcare supply (proxied by physicians’ density), air pollution, and tobacco and alcohol expenditure. On the other hand, the increased unemployment rate, life expectancy at age 65, mortality rate, and higher sports participation were all related to lower OOP health spending. The results may guide national strategies to improve health-care allocations and offer additional financial protection for vulnerable groups, such as households with children and elderly members.

Does Economic Policy Uncertainty Matter for Healthcare Expenditure in China? A Spatial Econometric Analysis

A growing body of research has documented the determinants of healthcare expenditure, but no known empirical research has focused on investigating the spatial effects between economic policy uncertainty (EPU) and healthcare expenditure. This study aims to explore the spatial effects of EPU on healthcare expenditure using the panel data of 29 regions in China from 2007 to 2017. Our findings show that healthcare expenditure in China has the characteristics of spatial clustering and spatial spillover effects. Our study also shows that EPU has positive spatial spillover effects on healthcare expenditure in China; that is, EPU affects not only local healthcare expenditure but also that in other geographically close or economically connected regions. Our study further indicates that the spatial spillover effects of EPU on healthcare expenditure only exist in the eastern area. The findings of this research provide some key implications for policymakers in emerging markets.

On the Network Transmission Mechanisms of Disease-Specific Healthcare Expenditure Spillovers: Evidence from the Connectedness Network Analyses

Previous studies investigating factors influencing healthcare expenditure growth ignored the network transmission mechanisms of disease-specific healthcare expenditure spillovers and regarded the processes culminating in healthcare expenditure growth as a black box. In this study, we investigated factors influencing the network transmission mechanisms underlying the determinants of healthcare expenditure growth through the dynamic connectedness network and the robust least square regression analyses. Our results indicate that demographic transition and business cycles are key factors increasing interconnectedness of different disease-specific healthcare expenditures, and that promotion of primary care utilization would reduce total healthcare expenditure spillovers. In order to reduce diffusion of disease-specific healthcare expenditures, health promotion activities should focus on those clinical diagnosis-related groups of diseases classified as pure net transmitters of spillover, and preventive interventions targeting different diseases should be activated in different phrases of the business cycle.

Health Care Utilization and Costs of Patients With Prostate Cancer in China Based on National Health Insurance Database From 2015 to 2017

BACKGROUND

In terms of medical costs, prostate cancer is on the increase as one of the most costly cancers, posing a tremendous economic burden, but evidence on the health care utilization and medical expenditure of prostate cancer has been absent in China.

OBJECTIVE

This study aimed to analyze health care utilization and direct medical costs of patients with prostate cancer in China.

METHODS

Health care service data with a national representative sample of basic medical insurance beneficiaries between 2015 and 2017 were obtained from the China Health Insurance Association database. We conducted descriptive and statistical analyses of health care utilization, annual direct medical costs, and composition based on cancer-related medical records. Health care utilization was measured by the number of hospital visits and the length of stay.

RESULTS

A total of 3,936 patients with prostate cancer and 24,686 cancer-related visits between 2015 and 2017 were identified in the database. The number of annual outpatient and inpatient visits per patient differed significantly from 2015 to 2017. There was no obvious change in length of stay and annual direct medical costs from 2015 to 2017. The number of annual visits per patient (outpatient: 3.0 vs. 4.0, P < 0.01; inpatient: 1.5 vs. 2.0, P < 0.001) and the annual medical direct costs per patient (US$2,300.1 vs. US$3,543.3, P < 0.001) of patients covered by the Urban Rural Resident Basic Medical Insurance (URRBMI) were both lower than those of patients covered by the Urban Employee Basic Medical Insurance (UEBMI), and the median out-of-pocket expense of URRBMI was higher than that of UEBMI (US$926.6 vs. US$594.0, P < 0.001). The annual direct medical costs of patients with prostate cancer in Western regions were significantly lower than those of patients in Eastern and Central regions (East: US$4011.9; Central: US$3458.6; West: US$2115.5) (P < 0.001).

CONCLUSIONS

There was an imbalanced distribution of health care utilization among regions in China. The direct medical costs of Chinese patients with prostate cancer remained stable, but the gap in health care utilization and medical costs between two different insurance schemes and among regions still needed to be further addressed.

Exploring healthcare professionals' understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review

BACKGROUND

The integration of artificial intelligence (AI) into our digital healthcare system is seen as a significant strategy to contain Australia's rising healthcare costs, support clinical decision making, manage chronic disease burden and support our ageing population. With the increasing roll-out of 'digital hospitals', electronic medical records, new data capture and analysis technologies, as well as a digitally enabled health consumer, the Australian healthcare workforce is required to become digitally literate to manage the significant changes in the healthcare landscape. To ensure that new innovations such as AI are inclusive of clinicians, an understanding of how the technology will impact the healthcare professions is imperative.

METHOD

In order to explore the complex phenomenon of healthcare professionals' understanding and experiences of AI use in the delivery of healthcare, an integrative review inclusive of quantitative and qualitative studies was undertaken in June 2018.

RESULTS

One study met all inclusion criteria. This study was an observational study which used a questionnaire to measure healthcare professional's intrinsic motivation in adoption behaviour when using an artificially intelligent medical diagnosis support system (AIMDSS).

DISCUSSION

The study found that healthcare professionals were less likely to use AI in the delivery of healthcare if they did not trust the technology or understand how it was used to improve patient outcomes or the delivery of care which is specific to the healthcare setting. The perception that AI would replace them in the healthcare setting was not evident. This may be due to the fact that AI is not yet at the forefront of technology use in healthcare setting. More research is needed to examine the experiences and perceptions of healthcare professionals using AI in the delivery of healthcare.