No abstract

The Greek health system does not yet offer universal coverage and has fragmented funding and delivery. Funding is regressive, with a reliance on informal payments, and there are inequities in access, supply and quality of services. Inefficiencies arise from an over reliance on relatively expensive inputs, as evidenced by the oversupply of specialists and under-supply of nurses. Resource allocation mechanisms are historical and political with no relation to performance or output, therefore providers have little incentive to improve productivity. Some options for future health system reform include focusing on coordinating funding by developing a monopsony purchaser with the aim of improving quality of services and efficiency in the health system and changing provider incentives to improve productivity.

Childhood disabilities entail a range of immediate and long-term economic costs that have important implications for the well-being of the child, the family, and society but that are difficult to measure. In an extensive research review, Mark Stabile and Sara Allin examine evidence about three kinds of costs—direct, out-of-pocket costs incurred as a result of the child's disability; indirect costs incurred by the family as it decides how best to cope with the disability; and long-term costs associated with the child's future economic performance. Not surprisingly, the evidence points to high direct costs for families with children with disabilities, though estimates vary considerably within these families. Out-of-pocket expenditures, particularly those for medical costs, for example, are higher among families with children with a special health care need. An important indirect cost for these families involves decisions about employment. Stabile and Allin examine several studies that, taken together, show that having a child with disabilities increases the likelihood that the mother (and less often the father) will either curtail hours of work or stop working altogether. Researchers also find that having a child with disabilities can affect a mother's own health and put substantial strains on the parents' relationship. In the longer term, disabilities also compromise a child's schooling and capacity to get and keep gainful employment as an adult, according to the studies Stabile and Allin review. Negative effects on future well-being appear to be much greater, on average, for children with mental health problems than for those with physical disabilities. Stabile and Allin calculate that the direct costs to families, indirect costs through reduced family labor supply, direct costs to disabled children as they age into the labor force, and the costs of safety net programs for children with disabilities average $30,500 a year per family with a disabled child. They note that the cost estimates on which they base their calculation vary widely depending on the methodology, jurisdiction, and data used. Because their calculations do not include all costs, notably medical costs covered through health insurance, they represent a lower bound. On that basis, Stabile and Allin argue that many expensive interventions to prevent and reduce childhood disability might well be justified by a cost-benefit calculation.

No abstract

We found some support for wealth as a more sensitive indicator of socioeconomic status among older adults than was income. Wealth may thus allow more accurate measurements of socioeconomic differences in use of health care services for this population.

The results of this study lend support to the hypothesis that physicians are motivated to perform CS for financial and convenience incentives. The recent commercialization of gynaecology services in Greece is discussed, along with its implications on physicians' decisions to perform CS.

Background Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. Objective The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users (“why”), content and data (“what”), and analyses and displays (“how” they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. Methods We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. Results A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are “close to home”; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. Conclusions COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.

In spite of the vast number of studies measuring economic efficiency in health care, there has been little take-up of this evidence by policy-makers to date. This study provides an illustration of how a system-level study drawing on best practice in empirical measurement of efficiency may be of practical use to health system decision makers and managers. We make use of the rich data available in Canada to undertake a robust two-stage data envelopment analysis to calculate efficiency at the regional (sub-provincial) level. Decisions about what the health system produces (the outcome to measure efficiency against) and what are the resources it has to produce that outcome were based on interviews and consultation with health system decision makers. Overall, we find large inefficiencies in the Canadian health care system, which could improve outcomes (here, measured as a reduction in treatable causes of death) by between 18 and 35% across our analyses. Also, we find that inefficiencies are the result of three main sets of factors that policy makers could pay attention to: management factors, such as hospital re-admissions; public health factors, such as obesity and smoking rates; and environmental factors such as the population's average income.