Journal of evaluation in clinical practice
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In the United States chronic illnesses have become a way of life for multiple generations - they are the number one cause of death and disability (accounting for more than 70% of deaths), 60% of American adults have at least one chronic disease, and 40% have multiple chronic conditions. Although multiple factors contribute to the growth in chronic disease prevalence, a major factor has been overreliance on health care systems for promoting health and preventing disease. Large health care systems are ill equipped for this role since they are designed to detect, treat, and manage disease, not to promote health or address the underlying causes of disease. ⋯ The paper demonstrates means for integrating the social determinants of health into collaborative place-based approaches, for aligning community assets and reducing health disparities. It concludes by discussing how asset-based community development can promote social connectivity and improve health, and how our approach reflects the emerging national consensus on the importance of place-based population system change.
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Creating networked business models is one of the innovative approaches that have the ability and potential for meeting market needs. The purpose of this study is to provide a decision-making model for a fair profit sharing among the members of a diagnostic laboratory network while providing a distinctive value for the patients. ⋯ In conclusion, it is evident that the use of Shapely value may help managers in the process of sharing profits among network members in a fair way, thereby improving network performance. In this way, incentive strategies may be created for the members of the network, and long-term survival of the network may be achieved.
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The COVID-19 has posed a wide range of urgent questions: about the disease, testing, immunity, treatments, and outcomes. Extreme situations, such as pandemics, call for exceptional measures. However, this threatens the production and application of evidence. ⋯ In order to avoid fake facts and to provide sustainable solutions, we need to pay attention to the various kinds of uncertainty. Producing high-quality evidence is the solution, not the problem.
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Our purpose is to assess epidemiological agent-based models-or ABMs-of the SARS-CoV-2 pandemic methodologically. The rapid spread of the outbreak requires fast-paced decision-making regarding mitigation measures. However, the evidence for the efficacy of non-pharmaceutical interventions such as imposed social distancing and school or workplace closures is scarce: few observational studies use quasi-experimental research designs, and conducting randomized controlled trials seems infeasible. Additionally, evidence from the previous coronavirus outbreaks of SARS and MERS lacks external validity, given the significant differences in contagiousness of those pathogens relative to SARS-CoV-2. To address the pressing policy questions that have emerged as a result of COVID-19, epidemiologists have produced numerous models that range from simple compartmental models to highly advanced agent-based models. These models have been criticized for involving simplifications and lacking empirical support for their assumptions. ⋯ Given this, we claim that the best epidemiological ABMs are models of actual mechanisms and deliver both mechanistic and difference-making evidence. Consequently, they may also adequately describe the effects of possible interventions. Finally, we discuss the limitations of ABMs and put forward policy recommendations.
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In the United States, the reluctance of the federal government to impose a national stay-at-home policy in wake of COVID-19 pandemic has left the decision of how to achieve social distancing to individual state governors. We hypothesized that in the absence of formal guidelines, the decision to close a state reflects the classic Weber-Fechner law of psychophysics - the amount by which a stimulus (such as number of cases or deaths) must increase in order to be noticed as a fraction of the intensity of that stimulus. ⋯ when there are not clearly articulated rules to follow, decision-makers resort to simple heuristics, in this case one consistent with the Weber-Fechner law.