Decision-making strategies: ignored to the detriment of healthcare training and delivery?

Context: People do not always make health-related decisions which reflect their best interest – best interest being defined as the decision they would make if they carefully considered the options and fully understood the information available. A substantial literature has developed in behavioral economics and social psychology that seeks to elucidate the patterns in individual decision-making. While this is particularly relevant to healthcare, the insights from these fields have only been applied in a limited way. To address the health challenges of the twenty-first century, healthcare providers and healthcare systems designers need to more fully understand how individuals are making decisions. Methods:: We provide an overview of the theories of behavioral economics and social psychology that relate to how individuals make health-related decisions. The concentration on health-related decisions leads to a focus on three topics: (1) mental shortcuts and motivated reasoning; (2) implications of time; and (3) implications of affect. The first topic is relevant because health-related decisions are often made in a hurry without a full appreciation of the implications and the deliberation they warrant. The second topic is included because the link between a decision and its health-related outcomes can involve a significant time lag. The final topic is included because health and affect are so often linked. Findings:: The literature reviewed has implications for healthcare training and delivery. Selection for medical training must consider the skills necessary to understand and adapt to how patients make decisions. Training on the insights garnered from behavioral economics and social psychology would better prepare healthcare providers to effectively support their clients to lead healthy lives. Healthcare delivery should be structured to respond to the way in which decisions are made. Conclusions:: These patterns in decision-making call into question basic assumptions our healthcare system makes about the best way to treat patients and deliver care. This literature has implications for the way we train physicians and deliver care

A Practical Guide to Selecting Models for Exploration, Inference, and Prediction in Ecology

Selecting among competing statistical models is a core challenge in science. However, the many possible approaches and techniques for model selection, and the conflicting recommendations for their use, can be confusing. We contend that much confusion surrounding statistical model selection results from failing to first clearly specify the purpose of the analysis. We argue that there are three distinct goals for statistical modeling in ecology: data exploration, inference, and prediction. Once the modeling goal is clearly articulated, an appropriate model selection procedure is easier to identify. We review model selection approaches and highlight their strengths and weaknesses relative to each of the three modeling goals. We then present examples of modeling for exploration, inference, and prediction using a time series of butterfly population counts. These show how a model selection approach flows naturally from the modeling goal, leading to different models selected for different purposes, even with exactly the same data set. This review illustrates best practices for ecologists and should serve as a reminder that statistical recipes cannot substitute for critical thinking or for the use of independent data to test hypotheses and validate predictions

From scaling up to sustainability in HIV: potential lessons for moving forward

Background: In 30 years of experience in responding to the HIV epidemic, critical decisions and program characteristics for successful scale-up have been studied. Now leaders face a new challenge: sustaining large-scale HIV prevention programs. Implementers, funders, and the communities served need to assess what strategies and practices of scaling up are also relevant for sustaining delivery at scale. Methods: We reviewed white and gray literature to identify domains central to scaling-up programs and reviewed HIV case studies to identify how these domains might relate to sustaining delivery at scale. Results: We found 10 domains identified as important for successfully scaling up programs that have potential relevance for sustaining delivery at scale: fiscal support; political support; community involvement, integration, buy-in, and depth; partnerships; balancing flexibility/adaptability and standardization; supportive policy, regulatory, and legal environment; building and sustaining strong organizational capacity; transferring ownership; decentralization; and ongoing focus on sustainability. We identified one additional potential domain important for programs sustaining delivery at scale: emphasizing equity. Conclusions: Today, the public and private sector are examining their ability to generate value for populations. All stakeholders are aiming to stem the tide of the HIV epidemic. Implementers need a framework to guide the evolution of their strategies and management practices. Greater research is needed to refine the domains for policy and program implementers working to sustain HIV program delivery at scale

Integrated care as a means to improve primary care delivery for adults and adolescents in the developing world: a critical analysis of Integrated Management of Adolescent and Adult Illness (IMAI)

Background: More than three decades after the 1978 Declaration of Alma-Ata enshrined the goal of ‘health for all’, high-quality primary care services remain undelivered to the great majority of the world’s poor. This failure to effectively reach the most vulnerable populations has been, in part, a failure to develop and implement appropriate and effective primary care delivery models. This paper examines a root cause of these failures, namely that the inability to achieve clear and practical consensus around the scope and aims of primary care may be contributing to ongoing operational inertia. The present work also examines integrated models of care as a strategy to move beyond conceptual dissonance in primary care and toward implementation. Finally, this paper examines the strengths and weaknesses of a particular model, the World Health Organization’s Integrated Management of Adolescent and Adult Illness (IMAI), and its potential as a guidepost toward improving the quality of primary care delivery in poor settings. Discussion Integration and integrated care may be an important approach in establishing a new paradigm of primary care delivery, though overall, current evidence is mixed. However, a number of successful specific examples illustrate the potential for clinical and service integration to positively impact patient care in primary care settings. One example deserving of further examination is the IMAI, developed by the World Health Organization as an operational model that integrates discrete vertical interventions into a comprehensive delivery system encompassing triage and screening, basic acute and chronic disease care, basic prevention and treatment services, and follow-up and referral guidelines. IMAI is an integrated model delivered at a single point-of-care using a standard approach to each patient based on the universal patient history and physical examination. The evidence base on IMAI is currently weak, but whether or not IMAI itself ultimately proves useful in advancing primary care delivery, it is these principles that should serve as the basis for developing a standard of integrated primary care delivery for adults and adolescents that can serve as the foundation for ongoing quality improvement. Summary As integrated primary care is the standard of care in the developed world, so too must we move toward implementing integrated models of primary care delivery in poorer settings. Models such as IMAI are an important first step in this evolution. A robust and sustained commitment to innovation, research and quality improvement will be required if integrated primary care delivery is to become a reality in developing world

Closing the Feedback Loop: A 12 Month Evaluation of ASTA, a Self-tracking Application for ASHAs

Accredited Social Health Activists (ASHAs) have been shown to have a positive impact on health outcomes of the households they visit, particularly in maternal and neonatal health. As the first line of the public health system in many countries, they are a critical link to the broader public health infrastructure for community members. Yet they do this all with minimal training and limited support infrastructure. To a pregnant woman, an ASHA is a trusted ally in navigating the health system---information gathered is returned by appropriate advice and counseling. To the health system, the ASHA is a key channel of valuable householdlevel information for the public health system, yet she generally receives minimal guidance in return. In this paper we present ASTA---the ASHA Self-Tracking Application---a system that provides ASHAs with timely, on-demand information regarding their own performance compared to their peers. Using ASTA, ASHAs access comparative performance data through both a web-based and voice-based interface on demand. We evaluated ASTA through a 12-month deployment with 142 ASHAs in Uttar Pradesh, India, assessing the impact of providing feedback on ASHA performance. We find that ASHAs with access to the ASTA system made significantly more client visits, with average monthly visits 21.5% higher than ASHAs who had access to a control system. In addition, higher ASHA performance was correlated with increased usage of ASTA. However, the performance improvement was front-loaded, with the impact of the system decreasing toward the end of the study period. Taken together, our findings provide promising evidence that studying and incorporating tools like ASTA could be cost effective and impactful for ASHA programs

Readiness, Availability and Utilization of Rural Vietnamese Health Facilities for Community Based Primary Care of Non-communicable Diseases: A Cross-Sectional Survey of 3 Provinces in Northern Vietnam

Background: Vietnam’s network of commune health centers (CHCs) have historically managed acute infectious diseases and implemented national disease-specific vertical programs. Vietnam has undergone an epidemiological transition towards non-communicable diseases (NCDs). Limited data exist on Vietnamese CHC capacity to prevent, diagnose, and treat NCDs. In this paper, we assess NCD service readiness, availability, and utilization at rural CHCs in 3 provinces in northern Vietnam. Methods: Between January 2014 and April 2014, we conducted a cross-sectional survey of a representative sample of 89 rural CHCs from 3 provinces. Our study outcomes included service readiness, availability of equipment and medications, and utilization for five NCD conditions: hypertension, diabetes, chronic pulmonary diseases, cancer, and mental illnesses.Results: NCD service availability was limited, except for mental health. Only 25% of CHCs indicated that they conducted activities focused on NCD prevention. Patient utilization of CHCs was approximately 223 visits per month or 8 visits per day. We found a statistically significant difference (P < .05) for NCD service availability, medication availability and CHC utilization among the 3 provinces studied. Conclusion: This is the first multi-site study on NCD service availability in Vietnam and the first study in a mountainous region consisting predominately of ethnic minorities. Despite strong government support for NCD prevention and control, Vietnam’s current network of CHCs has limited NCD service capacity

Disease dynamics in wild populations: modeling and estimation: a review

Abstract Models of infectious disease dynamics focus on describing the temporal and spatial variations in disease prevalence, and on understanding the factors that affect how many cases will occur in each time period and which individuals are likely to become infected. Classical methods for selecting and fitting models, mostly motivated by human diseases, are almost always based solely on raw counts of infected and uninfected individuals. We begin by reviewing the main classical approaches to parameter estimation, and some of their applications. We then review recently developed methods which enable representation of component processes such as infection and recovery, with observation models that acknowledge the complexities of the sampling and detection processes. We demonstrate the need to account for detectability in modeling disease dynamics, and explore a number of mark-recapture and occupancy study designs for estimating disease parameters while simultaneously accounting for variation in detectability. We highlight the utility of different modeling approaches and also consider the typically strong assumptions that may actually serve to limit their utility in general application to the study of disease dynamics (e.g., assignment of individuals to discrete disease states when underlying state space is more generally continuous; transitions assumed to be simple firstorder Markov; temporal separation of hazard and transition events)

Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

We consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual's covariates on their behavior or other measurable responses. We show that, generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular we demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects, and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual's enduring traits and their choices, even when there is no intrinsic affinity between them. We also suggest some possible constructive responses to these results.Comment: 27 pages, 9 figures. V2: Revised in response to referees. V3: Ditt