Is the trend of increasing use of patient‑reported outcome measures in medical device studies the sign of shift towards value‑based purchasing in Europe?

Background The recent update of the European Union’s (EU) regulation on public procurement has created new opportunity for progress in the purchasing of medical devices by shifting towards focus on value from one purely on price. Patientreported outcome measures (PROMs) may serve as additional tools for manufacturers to demonstrate value beyond traditional metrics of safety and performance and to diferentiate their products in a market of increasing competition. The aim of our study was to investigate the extent to which PROMs are included in registered device studies in the EU and interpret the results in the context of the purchasing of medical devices. Methods Twelve device groups were searched in clinical trial registries to determine the frequency distribution of PROMs in related studies. Results Results indicate that clinical studies of the selected device categories are done predominately in the western EU nations and are increasingly including PROMs. In the United Kingdom 121 (65%) study, out of 186 included PROMs, and in Germany, 92 (52%) out of 178 between 1998 and 2018. Few device studies were done in the Central and Eastern European region, and out of 76 studies 27 (35%) included PROMs. Since there is no requirement to include PROMs in device studies for regulatory purposes, it seems probable that their increasing use is driven by competitive market pressures. Conclusion The trend of increasing use of PROMs might be driven by the demand of purchasers to demonstrate value of devices, but is manifested at diferent levels in various regions of the EU

The impact of the recession on health care expenditure — How does the Czech Republic, Hungary, Poland and Slovakia compare to other OECD countries?

In the past few years, several papers have been published in the international literature on the impact of the economic crisis on health and health care. However, there is limited knowledge on this topic regarding the Central and Eastern European (CEE) countries. The main aims of this study are to examine the effect of the financial crisis on health care spending in four CEE countries (the Czech Republic, Hungary, Poland and Slovakia) in comparison with the OECD countries. In this paper we also revised the literature for economic crisis related impact on health and health care system in these countries. OECD data released in 2012 were used to examine the differences in growth rates before and after the financial crisis. We examined the ratio of the average yearly growth rates of health expenditure expressed in USD (PPP) between 2008–2010 and 2000–2008. The classification of the OECD countries regarding “development” and “relative growth” resulted in four clusters. A large diversity of “relative growth” was observed across the countries in austerity conditions, however the changes significantly correlate with the average drop of GDP from 2008 to 2010. To conclude, it is difficult to capture visible evidence regarding the impact of the recession on the health and health care systems in the CEE countries due to the absence of the necessary data. For the same reason, governments in this region might have a limited capability to minimize the possible negative effects of the recession on health and health care systems

Sociodemographic determinants of vaccination and willingness to pay for COVID-19 vaccines in Hungary, results of a cross-sectional online questionnaire

Background: Several different coronavirus disease (COVID-19) vaccines were authorized and distributed all over the world, including Hungary, but vaccination rates and acceptance of the different vaccines varied through 2021 and subsequent years. In Hungary Western vaccines and the Chinese and Russian vaccines were available in early 2021. Understanding preference and willingness to pay (WTP) for the COVID-19 vaccine could provide information for policy decision making to control the COVID-19 pandemic. We aimed to assess the socio-demographic factors influencing the COVID-19 vaccination and to analyse individual preferences for the available COVID-19 vaccines in Hungary. Methods: A cross-sectional online questionnaire survey was conducted between 25–05-2021 and 08–06-2021 exploring the vaccine acceptance and WTP for vaccination in the Hungarian general population. To assess the preferences towards the different vaccines available in Hungary at the time of the study, we used a multi-step WTP task. Results: Altogether 2,000 respondents filled out our survey, with the average age of 49.1 (SD = 15.3), out of whom 370 respondents (18.5%) stated that they already had a COVID-19 infection. Age above 65 years, male gender, higher level of education, higher income and residence in the capital or county seats were associated with a higher probability of vaccination. The average WTP ranged from 14.2 to 30.3 EUR for the different vaccine types. Conclusions: Males, respondents with higher education and income stated a higher WTP value for all vaccines. Better socioeconomic status increased both vaccination coverage and willingness to pay for vaccines

Productivity Loss in Patients With Chronic Diseases: A Pooled Economic Analysis of Hungarian Cost-of-Illness Studies

Objectives: To assess productivity loss (PL) variations across a set of chronic diseases and analyze significant PL drivers (demographics, health status, healthcare resource use) in Hungary. Methods: Data from 11 cost-of-illness studies (psoriasis, dementia, systemic sclerosis, multiple sclerosis, benign prostatic hyperplasia, Parkinson’s disease, psoriatic arthritis, rheumatoid arthritis, schizophrenia, epilepsy, and diabetes) were pooled, and patient-level data were analyzed. A weighted multiple linear regression analysis was run to identify significant PL indicators. All costs were adjusted to 2018 euro rates and PL was further presented as a proportion of gross domestic product/capita, facilitating results comparability and transferability. Results: The dataset comprised 1888 patients from 11 chronic diseases. The average indirect cost/(gross domestic product/ capita) ratio was highest in schizophrenia (72.4%) and rheumatoid arthritis (71.3%) and lowest in benign prostatic hyperplasia (1.6%). Correlation results infer that a higher EuroQol 5-dimension 3-level index score was significantly associated with lower PL. The number of hospital admissions was the main contributor toward increasing PL among resource use indicators. Age and sex showed inconsistent and insignificant correlations with PL. In regression analysis, a better EuroQol 5-dimension 3-level index score and higher education were consistently associated with decreasing PL in all models. Conclusions: This article will enable health decision makers to understand the importance of adopting a societal perspective for chronic disease reimbursement decisions. The correlation between PL and health status supports that timely started effective treatments may prevent patients from losing their workability

A Direct Comparison of the Measurement Properties of EQ-5D-5L, PROMIS-29+2 and PROMIS Global Health Instruments and EQ-5D-5L and PROPr Utilities in a General Population Sample

Objectives: We aimed to compare measurement properties of the 5-level version of EQ-5D (EQ-5D-5L) and 2 Patient-Reported Outcomes Measurement Information System (PROMIS) short forms, PROMIS-29+2 and PROMIS Global Health (PROMIS-GH-10), and of EQ-5D-5L and PROMIS-preference scoring system (PROPr) utilities. Methods: A cross-sectional survey was conducted in a general population sample in Hungary (N = 1631). We compared the following measurement properties at the level of items, domains, and utilities, the latter using corresponding US value sets: ceiling and floor, informativity (Shannon's indices), agreement, convergent, and known-group validity. For the analyses, PROMIS items/domains were matched to EQ-5D-5L domains that cover similar concepts of health. Results: The majority of PROMIS items showed enhanced distributional characteristics, including lower ceilings and higher informativity than the EQ-5D-5L. Good convergent validity was established between EQ-5D-5L and PROMIS domains capturing similar aspects of health. Mean EQ-5D-5L utilities were substantially higher than those of PROPr (0.864 vs 0.535). EQ-5D-5L utilities correlated moderately or strongly with PROPr (r = 0.61), PROMIS-GH-10 physical (r = 0.68), and mental health summary scores (r = 0.53). EQ-5D-5L utilities decreased with age, whereas PROPr utilities slightly increased with age. EQ-5D-5L utilities discriminated significantly better in 12/28 (ratio of F-statistics) and 18/26 (area under the receiver-operating characteristics curve ratio) known groups defined by age, self-perceived health status, and self-reported physician-diagnosed health conditions, including hypertension, diabetes, coronary heart disease, chronic kidney disease, and stroke. Conclusions: This study provides comparative evidence on the measurement properties of EQ-5D-5L, PROMIS-29+2, and PROMIS-GH-10 and informs decisions about the choice of instruments in population health surveys for assessment of patients’ health and for cost-utility analyses.</p

The impact of the recession on health care expenditure — How does the Czech Republic, Hungary, Poland and Slovakia compare to other OECD countries?

In the past few years, several papers have been published in the international literature on the impact of the economic crisis on health and health care. However, there is limited knowledge on this topic regarding the Central and Eastern European (CEE) countries. The main aims of this study are to examine the effect of the financial crisis on health care spending in four CEE countries (the Czech Republic, Hungary, Poland and Slovakia) in comparison with the OECD countries. In this paper we also revised the literature for economic crisis related impact on health and health care system in these countries. OECD data released in 2012 were used to examine the differences in growth rates before and after the financial crisis. We examined the ratio of the average yearly growth rates of health expenditure expressed in USD (PPP) between 2008–2010 and 2000–2008. The classification of the OECD countries regarding “development” and “relative growth” resulted in four clusters. A large diversity of “relative growth” was observed across the countries in austerity conditions, however the changes significantly correlate with the average drop of GDP from 2008 to 2010. To conclude, it is difficult to capture visible evidence regarding the impact of the recession on the health and health care systems in the CEE countries due to the absence of the necessary data. For the same reason, governments in this region might have a limited capability to minimize the possible negative effects of the recession on health and health care systems