Health Policy最新文献

In August 2024, the EU Artificial Intelligence Act (AI Act) entered into force. This legally binding instrument sets rules for the development, the placing on the market, the putting into service, and the use of AI systems in the European Union. As the world's first extensive legal framework on AI, it aims to boost innovation while protecting individuals against the harms of AI. Since healthcare is one of the top sectors for AI deployment, the new rules will significantly reform national policies and practices on health technology. In this article, we highlight the implications of the AI Act for the healthcare sector. We give a comprehensive overview of the new legal obligations for various healthcare stakeholders (tech developers; healthcare professionals; public health authorities). We conclude that, due to its horizontal approach, it is necessary to adopt further guidelines to address the unique needs of the healthcare sector. To this end, we make recommendations for the upcoming implementation and standardization phase.

Suicide is a global public health issue which has far-reaching impacts on individuals, families, and wider communities. Early intervention is a core pillar of policy on the prevention of suicide related deaths. However, limited mental health literacy, and negative attitudes regarding mental illness amongst the public are a barrier to early intervention. Past research has not explored mental health literacy and attitudes regarding suicide specifically. The aim of the current study was to examine mental health literacy and attitudes towards suicide in adults. 590 adults in Ireland aged 18-80 years (M = 43.24, SD = 12.6) took part in this online cross-sectional study, completing the Mental Health Literacy Scale and The Attitudes Towards Suicide Scale. Experience of suicide deaths was common among participants. Independent t-tests indicated that males had significantly lower levels of mental health literacy and more stigmatising attitudes towards suicide than females. Young adults also had lower ability to recognise mental health difficulties than older adults. Hierarchical Multiple Regressions found that mental health literacy significantly accounted for varied attitudes towards suicide in adults, particularly willingness to communicate about suicide, and beliefs that suicide is preventable. Findings are discussed in the context of informing policy-makers who are promoting early-intervention for suicide prevention.

Objectives

French dentists charge additional fees for dental prostheses. This paper aims to provide new information on the determinants of dental price setting and inform public decision-making in the context of the widespread rejection of prosthetic dental care for financial reasons. We focus on the competitive mechanism in the dental prosthetics market and measure the impact of the density of professionals and competitors' prices on the fees charged by dentists.

Methods

We use data merging from an administrative health insurance database and information from tax declarations of French dentists. We test the effect of competitor prices and competition on individual price-setting using instrumental variables. The database obtained included 29,220 dentists.

Results

Practitioners’ prices grow with competitors’ prices (+1€ in competitor prices entails an increase of + 0.37€ in the practitioner's price). Women set lower prices, and having a young child in the household predicts an increase in price of 6.8€ (p-value=0.014). Rural areas present lower fees than urban areas (+11.4€ (p value=0.000)).

Conclusion

Prosthetic prices are strategic complements that are compatible with the application of monopolistic competition in the dental care market. We encourage the regulator to develop competitive mechanisms, for example, through a public offer at moderate prices.

Introduction

A nationwide pay-for-performance (P4P) scheme was introduced in the Netherlands between 2018 and 2023 to incentivize appropriate prescribing in general practice. Appropriate prescribing was operationalised as adherence to prescription formularies and measured based on electronic health records (EHR) data. We evaluated this P4P scheme from a learning health systems perspective.

Methods

We conducted semi-structured interviews with 15 participants representing stakeholders of the scheme: general practitioners (GPs), health insurers, pharmacists, EHR suppliers and formulary committees. We used a thematic approach for data analysis.

Results

Using EHR data showed several benefits, but lack of uniformity of EHR systems hindered consistent measurements. Specific indicators were favoured over general indicators as they allow GPs to have more control over their performance. Most participants emphasized the need for GPs to jointly reflect on their performance. Communication to GPs appeared to be challenging. Partly because of these challenges, impact of the scheme on prescribing behaviour was perceived as limited. However, several unexpected positive effects of the scheme were mentioned, such as better EHR recording habits.

Conclusions

This study identified benefits and challenges useful for future P4P schemes in promoting appropriate care with EHR data. Enhancing uniformity in EHR systems is crucial for more consistent quality measurements. Future P4P schemes should focus on high-quality feedback, peer-to-peer learning and establish a single point of communication for healthcare providers.

The medical technology sector is characterised by a constant influx of innovations with the potential to revolutionise patient care. In France, there are several pathways for medical devices to enter the market, from diagnosis-related group tariffs to reimbursement lists. However, traditional regulatory pathways can delay market access for innovative technologies. In response, France has established Early Access Programs to expedite patient access to medical devices. This paper looks at three of these Early Access Programs for medical devices. Innovation Funding, introduced in its final version in 2015, provides temporary coverage for innovative devices and facilitates data collection for informed funding decisions. Transitional Coverage (PECT), established in 2021, targets CE-marked devices for rare or serious conditions. Transitional coverage for digital health applications (PECAN), introduced in 2022, covers digital medical devices, either therapeutic or for patient monitoring. Innovation funding has been granted to 16 technologies out of 35 applications (46%) since 2015. 6 technologies out of 11 (64%) applications benefit from PECT. PECAN, in its first year, has granted a telemonitoring solution with a favourable opinion. The French experience could provide valuable lessons for the development of a harmonised European framework to ensure that innovative medical technologies benefit those who need them, while maintaining high safety standards.

Most research on health care equity focuses on accessing services, with less attention given to how revenue is collected to pay for a country's health care bill. This article examines the progressivity of revenue collection among publicly funded sources: income taxes, social insurance (often in the form of payroll) taxes, and consumption taxes (e.g., value-added taxes). We develop methodology to derive a qualitative index that rates each of 29 high-income countries as to its progressivity or regressivity for each of the three sources of revenue. A variety of data sources are employed, some from secondary data sources and other from country representatives of the Health Systems and Policy Monitor of the European Observatory on Health Systems and Policies. We found that countries with more progressive income tax systems used more income-based tax brackets and had larger differences in marginal tax rates between the brackets. The more progressive social insurance revenue collection systems did not have an upper income cap and exempted poorer persons or reduced their contributions. The only pattern regarding consumption taxes was that countries that exhibited the fewest overall income inequalities tended to have least regressive consumption tax policies. The article also provides several examples from the sample of countries on ways to make public revenue financing of health care more progressive.

Background

Traditional approaches to monitoring health inequalities predominantly rely on headcount methods. However, these methods fail to reflect the non-linear health economic implications of changes in disease severity. Alternative, distribution-sensitive metrics are available which could more adequately inform financial planning and policy decision making.

Methods

We describe the design of the Foster-Greer-Thorbecke (FGT) index, and discuss its relative merits as a summary monitoring metric of health inequalities in the population, compared to the Erreygers concentration index. We illustrate the FGT index by conducting a comparative longitudinal analysis of adult excess inequalities in England using Health Survey for England data from 2009 to 2019.

Findings

Excess weight inequalities have steadily increased in the English adult population, especially over the last five years. Going beyond headcount, the FGT index analyses revealed that, unlike the rest of the population, the average overweight adult from the most socio-economically deprived group is either obese (30.3 BMI for females) or at the brink of obesity (29.1 BMI for males). These results underscore a deepening divide in obesity severity between communities, with the most socioeconomically deprived groups being increasingly and disproportionally affected. Conclusions: The FGT index can address some shortcomings of traditional approaches to inequality measurement and local governments should consider adopting it as an alternative population health metric. Future research should apply and develop more refined distribution-sensitive measures of health inequality.

This paper proposes a method to support population management by evaluating population needs using population stratification based on healthcare trajectories.

Reimbursed healthcare consumption data for the first semester of 2017 contained within the inter-mutualist database were analysed to create healthcare trajectories for a subset of the population aged between 60 and 79 (N = 22,832) to identify (1) the nature of health events, (2) key transitions between lines of care, (3) the relative duration of different events, and (4) the hierarchy of events. These factors were classified using a K-mers approach followed by multinomial mixture modelling.

Five population groups were identified using this healthcare trajectory approach: “low users”, “high intensity of nursing care”, “transitional care & nursing care”, “transitional care”, and “long time in hospital”.

This method could be used by loco-regional governing bodies to learn reflectively from the place where care is provided, taking a systems perspective rather than a disease perspective, and avoiding the one-size-fits-all definition. It invites decision makers to make better use of routinely collected data to guide continuous learning and adaptive management of population health needs.

Progress towards universal health coverage is monitored by the incidence of catastrophic spending. Two catastrophic spending indicators are commonly used in Europe: Sustainable Development Goal (SDG) indicator 3.8.2 and the WHO Regional Office for Europe (WHO/Europe) indicator. The use of different indicators can cause confusion, especially if they produce contradictory results and policy implications. We use harmonised household budget survey data from 27 European Union countries covering 505,217 households and estimate the risk of catastrophic spending, conditional on household characteristics and the design of medicines co-payments. We calculate the predicted probability of catastrophic spending for particular households, which we call LISAs, under combinations of medicines co-payment policies and compare predictions across the two indicators. Using the WHO/Europe indicator, any combination of two or more protective policies (i.e. low fixed co-payments instead of percentage co-payments, exemptions for low-income households and income-related caps on co-payments) is associated with a statistically significant lower risk of catastrophic spending. Using the SDG indicator, confidence intervals for every combination of protective policies overlap with those for no protective policies. Although out-of-pocket medicines spending is a strong predictor of catastrophic spending using both indicators, the WHO/Europe indicator is more sensitive to medicines co-payment policies than the SDG indicator, making it a better indicator to monitor health system equity and progress towards UHC in Europe.