. Diagnosis related groups in Europe: moving towards transparency, efficiency, and quality in hospitals?. BMJ (Clinical research ed.), 347 (7916), 1-7.
This review is the first to have focused on costs in different stages of dementia. The stage is an important determinant of costs. However, characteristics of individual studies need to be considered, when making use of their results.
Hospital readmissions receive increasing interest from policy makers because reducing unnecessary readmissions has the potential to simultaneously improve quality and save costs. This paper reviews readmission policies in Denmark, England, Germany and the United States (Medicare system). The suggested roadmap enables researchers and policy makers to systematically compare and analyse readmission policies. We find considerable differences across countries. In Germany, the readmission policy aims to avoid unintended consequences of the introduction of DRG-based payment; it focuses on readmissions of individual patients and hospitals receive only one DRG-based payment for both the initial and the re-admission. In Denmark, England and the US readmission policies aim at quality improvement and focus on readmission rates. In Denmark, readmission rates are publicly reported but payments are not adjusted in relation to readmissions. In England and the US, financial incentives penalise hospitals with readmission rates above a certain benchmark. In England, this benchmark is defined through local clinical review, while it is based on the risk-adjusted national average in the US. At present, not enough evidence exists to give recommendations on the optimal design of readmission policies. The roadmap can be a tool for systematically assessing how elements of other countries' readmission policies can potentially be adopted to improve national policies.
Generous short-term payment instruments to promote technological innovation should be applied carefully as they may imply rapidly increasing health-care expenditures. In general, they should be granted only if rigorous analyses have demonstrated their benefits. If the evidence remains uncertain, coverage with evidence development frameworks or frequent updates of the DRG-based hospital systems may provide policy alternatives. Once the data and evidence base is substantially improved, future research should empirically investigate how different policy arrangements affect the adoption and use of technological innovation and health-care expenditures.
BackgroundThe prevalence of non-communicable diseases (NCDs) is increasing in sub-Saharan Africa. At the same time, the use of mobile phones is rising, expanding the opportunities for the implementation of mobile phone-based health (mHealth) interventions. This review aims to understand how, why, for whom, and in what circumstances mHealth interventions against NCDs improve treatment and care in sub-Saharan Africa.MethodsFour main databases (PubMed, Cochrane Library, Web of Science, and Google Scholar) and references of included articles were searched for studies reporting effects of mHealth interventions on patients with NCDs in sub-Saharan Africa. All studies published up until May 2015 were included in the review. Following a realist review approach, middle-range theories were identified and integrated into a Framework for Understanding the Contribution of mHealth Interventions to Improved Access to Care for patients with NCDs in sub-Saharan Africa. The main indicators of the framework consist of predisposing characteristics, needs, enabling resources, perceived usefulness, and perceived ease of use. Studies were analyzed in depth to populate the framework.ResultsThe search identified 6137 titles for screening, of which 20 were retained for the realist synthesis. The contribution of mHealth interventions to improved treatment and care is that they facilitate (remote) access to previously unavailable (specialized) services. Three contextual factors (predisposing characteristics, needs, and enabling resources) influence if patients and providers believe that mHealth interventions are useful and easy to use. Only if they believe mHealth to be useful and easy to use, will mHealth ultimately contribute to improved access to care. The analysis of included studies showed that the most important predisposing characteristics are a positive attitude and a common language of communication. The most relevant needs are a high burden of disease and a lack of capacity of first-contact providers. Essential enabling resources are the availability of a stable communications network, accessible maintenance services, and regulatory policies.ConclusionsPolicy makers and program managers should consider predisposing characteristics and needs of patients and providers as well as the necessary enabling resources prior to the introduction of an mHealth intervention. Researchers would benefit from placing greater attention on the context in which mHealth interventions are being implemented instead of focusing (too strongly) on the technical aspects of these interventions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0782-z) contains supplementary material, which is available to authorized users.
BackgroundThe reasons of deaths in developing countries are shifting from communicable diseases towards non-communicable diseases (NCDs). At the same time the number of health care interventions using mobile phones (mHealth interventions) is growing rapidly. We review studies assessing the health-related impacts of mHealth on NCDs in low- and middle-income countries (LAMICs).MethodsA systematic literature search of three major databases was performed in order to identify randomized controlled trials (RCTs) of mHealth interventions. Identified studies were reviewed concerning key characteristics of the trial and the intervention; and the relationship between intervention characteristics and outcomes was qualitatively assessed.ResultsThe search algorithms retrieved 994 titles. 8 RCTs were included in the review, including a total of 4375 participants. Trials took place mostly in urban areas, tested different interventions (ranging from health promotion over appointment reminders and medication adjustments to clinical decision support systems), and included patients with different diseases (diabetes, asthma, hypertension). Except for one study all showed rather positive effects of mHealth interventions on reported outcome measures.Furthermore, our results suggest that particular types of mHealth interventions that were found to have positive effects on patients with communicable diseases and for improving maternal care are likely to be effective also for NCDs.ConclusionsDespite rather positive results of included RCTs, a firm conclusion about the effectiveness of mHealth interventions against NCDs is not yet possible because of the limited number of studies, the heterogeneity of evaluated mHealth interventions and the wide variety of reported outcome measures. More research is needed to better understand the specific effects of different types of mHealth interventions on different types of patients with NCDs in LaMICs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3226-3) contains supplementary material, which is available to authorized users.
BackgroundCountries rely on out-of-pocket (OOP) spending to different degrees and employ varying techniques. The article examines trends in OOP spending in ten high-income countries since 2000, and analyzes their relationship to self-assessed barriers to accessing health care services. The countries are Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States.MethodsData from three sources are employed: OECD statistics, the Commonwealth Fund survey of individuals in each of ten countries, and country-specific documents on health care policies. Based on trends in OOP spending, we divide the ten countries into three groups and analyze both trends and access barriers accordingly. As part of this effort, we propose a conceptual model for understanding the key components of OOP spending.ResultsThere is a great deal of variation in aggregate OOP spending per capita spending but there has been convergence over time, with the lowest-spending countries continuing to show growth and the highest spending countries showing stability. Both the level of aggregate OOP spending and changes in spending affect perceived access barriers, although there is not a perfect correspondence between the two.ConclusionsThere is a need for better understanding the root causes of OOP spending. This will require data collection that is broken down into OOP resulting from cost sharing and OOP resulting from direct payments (due to underinsurance and lacking benefits). Moreover, data should be disaggregated by consumer groups (e.g. income-level or health status). Only then can we better link the data to specific policies and suggest effective solutions to policy makers.
Assessing and improving quality of care presupposes an understanding of what it does and does not entail. Different definitions often specify relatively long lists of various attributes that they recognize as part of quality. Effectiveness, patient safety, and responsiveness/patient-centeredness seem to have become universally accepted as core dimensions of quality of care. The inclusion of a list of additional elements is confusing and often blurs the line between quality of care and overall health system performance. This presentation provides an in-depth look at this interplay, recognizing that the definition of quality changes depending on the level at which it is assessed. At the level of health services, there seems to be an emerging consensus that quality of care is the degree to which health services for individuals and populations are effective, safe, and people-centered. On the other hand, a health care system as a whole is of high quality when it achieves the overall goals of improved health, responsiveness, financial protection, and efficiency; here, there seems to be an international trend towards using the term health system performance. The workshop looks at different strategies to assure or improve the quality of health care. To understand, analyze, compare and ultimately prioritize or align different quality strategies, this presentation will introduce a comprehensive framework, which includes the following lenses: i) the three core dimensions of quality: safety, effectiveness, and patient-centeredness; ii) the four functions of health care: primary prevention, acute care, chronic care, and palliative care; iii) the three main activities of quality strategies: setting standards, monitoring, and assuring improvements; iv) Donabedian’s triad: structures, processes, and outcomes; v) the five main targets of quality strategies: health professionals, technologies, provider organizations, patients, and payers.
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