Public health and medical care for the world's factory: China's Pearl River Delta Region

While the growth of urbanization, worldwide, has improved the lives of migrants from the hinterland, it also raises health risks related to population density, concentrated poverty and the transmission of infectious disease. Will megacity regions evolve into socially infected breeding grounds for the rapid transmission of disease, or can they become critical spatial entities for the protection and promotion of population health? We address this question for the Pearl River Delta Region (PRD) based on recent data from Chinese sources, and on the experience of how New York, Greater London, Tokyo and Paris have grappled with the challenges of protecting population health and providing their populations with access to health care services. In some respects, there are some important lessons from comparative experience for PRD, notably the importance of covering the entire population for health care services and targeting special programs for those at highest risk for disease. In other respects, PRD's growth rate and sheer scale make it a unique megacity region that already faces new challenges and will require new solutions

Health Care Consumers: Choices and Constraints

This article summarizes the research and data currently available on different dimensions of consumer choice. These dimensions include not only whether to participate in a health care plan and which plan to select if given a choice but also the decisions that lead to having a choice and the implications of making the choice. Data are presented on what choices consumers face, how many are given what kinds of choices, what constraints they face, what we know about how they make these choices, and what information they are given and what they use. The majority of Americans are offered some kind of health insurance plan either through their place of employment or as a dependent on someone else’s employer-sponsored health plan. About half of those offered health insurance are offered a choice, usually of only two or three plans. The majority elect to participate in one of those plans.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68465/2/10.1177_107755879905600102.pd

Healthcare trajectories and costs in the last year of life: a retrospective primary care and hospital analysis

Objectives To analyse healthcare utilisation and costs in the last year of life in England, and to study variation by cause of death, region of patient residence and socioeconomic status. Methods This is a retrospective cohort study. Individuals aged 60 years and over (N=108 510) who died in England between 2010 and 2017 were included in the study. Results Healthcare utilisation and costs in the last year of life increased with proximity to death, particularly in the last month of life. The mean total costs were higher among males (£8089) compared with females (£6898) and declined with age at death (£9164 at age 60–69 to £5228 at age 90+) with inpatient care accounting for over 60% of total costs. Costs decline with age at death (0.92, 95% CI 0.88 to 0.95, p<0.0001 for age group 90+ compared with to the reference category age group 60–69) and were lower among females (0.91, 95% CI 0.90 to 0.92, p<0.0001 compared with males). Costs were higher (1.09, 95% CI 1.01 to 1.14, p<0.0001) in London compared with other regions. Conclusions Healthcare utilisation and costs in the last year of life increase with proximity to death, particularly in the last month of life. Finer geographical data and information on healthcare supply would allow further investigating whether people receiving more planned care by primary care and or specialist palliative care towards the end of life require less acute care

Unwanted pregnancy, mental health and abortion: untangling the evidence

Abortion policy is still contentious in many parts of the world, and periodically it emerges to dominate health policy debates. This paper examines one such debate in Australia centering on research findings by a New Zealand research group, Fergusson, Horwood & Ridder, published in early 2006. The debate highlighted the difficulty for researchers when their work is released in a heightened political context. We argue that the authors made a logical error in constructing their analysis and interpreting their data, and are therefore not justified in making policy claims for their work. The paper received significant public attention, and may have influenced the public policy position of a major professional body. Deeply held views on all sides of the abortion debate are unlikely to be reconciled, but if policy is to be informed by research, findings must be based on sound science

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

<p>Abstract</p> <p>Background</p> <p>Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process.</p> <p>Discussion</p> <p>We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence.</p> <p>Summary</p> <p>In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.</p