As more people live longer, the need for quality long-term care for the elderly will increase dramatically. This volume examines the current system of nursing home regulations, and proposes an overhaul to better provide for those confined to such facilities. It determines the need for regulations, and concludes that the present regulatory system is inadequate, stating that what is needed is not more regulation, but better regulation. This long-anticipated study provides a wealth of useful background information, in-depth study, and discussion for nursing home administrators, students, and teachers in the health care field; professionals involved in caring for the elderly; and geriatric specialists.
The nation's health care system has changed dramatically and the country is debating further significant changes. Comprehensive information is needed to guide policymakers in understanding and evaluating the current problems and in formulating federal health care policy. This book contains an evaluation of the plan developed by the National Center for Health Statistics for restructuring its existing provider surveys. It identifies current and future data needed by researchers and policymakers to assess the effect of changes in financing, organization, and delivery of health care on access, quality, costs, and outcomes of care and determines the extent to which the design and content of the proposed survey can meet these data needs. The book goes beyond a simple review and recommends a design framework to develop a coordinated and integrated data system to gather information about people and their illness over time and to link this information to costs and health care outcomes.
Health facility surveys come in various guises. One dimension in which they vary is their motivation. Some seek to understand better links between households and providers. Others seek to understand better provider behavior and performance. Still others seek to understand the interrelationships between providers, while yet others seek to shed light on the linkages between government and providers. Health facility surveys differ too in the data they collect, in part due to the different motivations. Surveys also vary in the way they collect data, some relying on direct observation, some on record review, and some on interview. Some quality data are collected through clinical vignettes. Facility data have been put to a variety of uses, including planning and budgeting; monitoring, evaluation, and promoting accountability; and research. Lindel and Wagstaff review some of the literature under each heading and offer some conclusions regarding the current state of health facility surveys.
The goal of eliminating disparities in health care in the United States remains elusive. Even as quality improves on specific measures, disparities often persist. Addressing these disparities must begin with the fundamental step of bringing the nature of the disparities and the groups at risk for those disparities to light by collecting health care quality information stratified by race, ethnicity and language data. Then attention can be focused on where interventions might be best applied, and on planning and evaluating those efforts to inform the development of policy and the application of resources. A lack of standardization of categories for race, ethnicity, and language data has been suggested as one obstacle to achieving more widespread collection and utilization of these data. Race, Ethnicity, and Language Data identifies current models for collecting and coding race, ethnicity, and language data; reviews challenges involved in obtaining these data, and makes recommendations for a nationally standardized approach for use in health care quality improvement.
This third global survey of the WHO Global Observatory for eHealth (GOe) investigated how eHealth can support universal health coverage(UHC) in Member States. A total of 125 countries participated in the survey ? a clear reflection of the growing interest in this area. The report considers eHealth foundations built through policy development funding approaches and capacity building in eHealth through the training of students and professionals. It then observes specific eHealth applications such as mHealth telehealth electronic health records systems and eLearning and how these contribute to the goals of UHC. Of interest is the extent to which legal frameworks protect patient privacy in EHRs as health care systems move towards to delivering safer more efficient and more accessible health care. Finally the rapidly emerging areas of social media for health care as well as big data for research and planning are reported.
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
Have gaps in health outcomes between the poor and better off grown? Are they larger in one country than another? Are health sector subsidies more equally distributed in some countries than others? Are health care payments more progressive in one health care financing system than another? What are catastrophic payments and how can they be measured? How far do health care payments impoverish households? Answering questions such as these requires quantitative analysis. This in turn depends on a clear understanding of how to measure key variables in the analysis, such as health outcomes, health expenditures, need, and living standards. It also requires set quantitative methods for measuring inequality and inequity, progressivity, catastrophic expenditures, poverty impact, and so on. This book provides an overview of the key issues that arise in the measurement of health variables and living standards, outlines and explains essential tools and methods for distributional analysis, and, using worked examples, shows how these tools and methods can be applied in the health sector. The book seeks to provide the reader with both a solid grasp of the principles underpinning distributional analysis, while at the same time offering hands-on guidance on how to move from principles to practice.
