The economic evaluation of healthcare interventions requires an assessment of whether the improvement in health outcomes they offer exceeds the improvement in health that would have been possible if the additional resources required had, instead, been made available for other healthcare activities. Therefore, some assessment of these health opportunity costs is required if the best use is to be made of the resources available for healthcare. This paper provides a framework for generating country-specific estimates of cost per disability-adjusted life year (DALY) averted ‘thresholds’ that reflect health opportunity costs. We apply estimated elasticities on mortality, survival, morbidity and a generic measure of health, DALYs, that take account of measures of a country’s infrastructure and changes in donor funding to country-specific data on health expenditure, epidemiology and demographics to determine the likely DALYs averted from a 1% change in expenditure on health. The resulting range of cost per DALY averted ‘threshold’ estimates for each country that represent likely health opportunity costs tend to fall below the range previously suggested by WHO of 1–3× gross domestic product (GDP) per capita. The 1–3× GDP range and many other previous and existing recommendations about which interventions are cost-effective are not based on an empirical assessment of the likely health opportunity costs, and as a consequence, the health effects of changes in health expenditure have tended to be underestimated, and there is a risk that interventions regarded as cost-effective reduce rather than improve health outcomes overall.
Background: Cost-effectiveness analysis is an important tool for informing treatment coverage and pricing decisions, yet no consensus exists about what threshold for the incremental cost-effectiveness ratio (ICER) in dollars per quality-adjusted life year gained (QALY) indicates whether treatments are likely to be cost-effective in the United States (US).Objective: To estimate a US cost-effectiveness threshold based on health opportunity costs.Design: Simulation of short-term mortality and morbidity attributable to individuals dropping health insurance due to increased healthcare expenditures passed though as premium increases. Model inputs came from demographic data and the literature; 95% uncertainty intervals (UI) were constructed.
Online games can serve as research instruments to explore the effects of game design elements on motivation and learning. In our research, we manipulated the design of an online math game to investigate the effect of challenge on player motivation and learning. To test the "Inverted-U Hypothesis", which predicts that maximum game engagement will occur with moderate challenge, we produced two large-scale (10K and 70K subjects), multifactor (2x3 and 2x9x8x4x25) online experiments. We found that, in almost all cases, subjects were more engaged and played longer when the game was easier, which seems to contradict the generality of the Inverted-U Hypothesis. Troublingly, we also found that the most engaging design conditions produced the slowest rates of learning. Based on our findings, we describe several design implications that may increase challenge-seeking in games, such as providing feedforward about the anticipated degree of challenge.
Energy feedback systems, particularly residential energy feedback systems (REFS), have emerged as a key area for HCI and interaction design. However, we argue that HCI researchers, designers and others concerned with the design and evaluation of interactive systems should more strongly consider the ineffectiveness of such systems, including not only potential limitations of specific types of REFS or REFS in general but also potentially counterproductive or harmful effects of REFS. In this paper we outline research questions and issues for future work based on critical gaps in REFS research identified from (i) a review of REFS literature and (ii) findings from two qualitative studies of commercial home energy monitors.
BackgroundCognitive behavioral therapy is an efficacious treatment for child anxiety disorders. Although efficacious, many children (40%-50%) do not show a significant reduction in symptoms or full recovery from primary anxiety diagnoses. One possibility is that they are unwilling to learn and practice cognitive behavioral therapy skills beyond therapy sessions. This can occur for a variety of reasons, including a lack of motivation, forgetfulness, and a lack of cognitive behavioral therapy skills understanding. Mobile health (mHealth) gamification provides a potential solution to improve cognitive behavioral therapy efficacy by delivering more engaging and interactive strategies to facilitate cognitive behavioral therapy skills practice in everyday lives (in vivo).ObjectiveThe goal of this project was to redesign an existing mHealth system called SmartCAT (Smartphone-enhanced Child Anxiety Treatment) so as to increase user engagement, retention, and learning facilitation by integrating gamification techniques and interactive features. Furthermore, this project assessed the effectiveness of gamification in improving user engagement and retention throughout posttreatment.MethodsWe redesigned and implemented the SmartCAT system consisting of a smartphone app for children and an integrated clinician portal. The gamified app contains (1) a series of interactive games and activities to reinforce skill understanding, (2) an in vivo skills coach that cues the participant to use cognitive behavioral therapy skills during real-world emotional experiences, (3) a home challenge module to encourage home-based exposure tasks, (4) a digital reward system that contains digital points and trophies, and (5) a therapist-patient messaging interface. Therapists used a secure Web-based portal connected to the app to set up required activities for each session, receive or send messages, manage participant rewards and challenges, and view data and figures summarizing the app usage. The system was implemented as an adjunctive component to brief cognitive behavioral therapy in an open clinical trial. To evaluate the effectiveness of gamification, we compared the app usage data at posttreatment with the earlier version of SmartCAT without gamification.ResultsGamified SmartCAT was used frequently throughout treatment. On average, patients spent 35.59 min on the app (SD 64.18) completing 13.00 activities between each therapy session (SD 12.61). At the 0.10 significance level, the app usage of the gamified system (median 68.00) was higher than that of the earlier, nongamified SmartCAT version (median 37.00, U=76.00, P<.01). The amount of time spent on the gamified system (median 173.15) was significantly different from that of the earlier version (median 120.73, U=173.00, P=.06).ConclusionsThe gamified system showed good acceptability, usefulness, and engagement among anxious children receiving brief cognitive behavioral therapy treatment. Integrating an mHealth gamification platform within treatment for anxious children seems to increase in...
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