Analysis of Waiting-Time Data in Health Services Research


Book Description

Why some patients wait longer than others remains an important question. This book is a reference for health services researchers looking for statistical tools with which to study waiting times. The book offers detailed coverage of statistical concepts and methods for the analysis and interpretation of waiting-time data. It provides analysis from health services research perspective, rather than operations management, and contains a collection of examples.




The Patient Satisfaction Questionnaire Short-form (PSQ-18)


Book Description

This article reports on the development and psychometric properties of a short-form version of the 50-item Patient Satisfaction Questionnaire III (PSQ-III). The short-form instrument, the PSQ-18, contains 18 items tapping each of the seven dimensions of satisfaction with medical care measured by the PSQ-III: general satisfaction, technical quality, interpersonal manner, communication, financial aspects, time spent with doctor, and accessibility and convenience. PSQ-18 subscale scores are substantially correlated with their full-scale counterparts and possess generally adequate internal consistency reliability. Moreover, both the magnitude of the correlation coefficients and the overall pattern of correlations among PSQ-18 subscales are highly similar to those observed for the PSQ-III. These preliminary analyses support the use of the PSQ-18 in situations where the need for brevity precludes administration of the full-length PSQ-III.




OECD Health Policy Studies Waiting Time Policies in the Health Sector What Works?


Book Description

This book provides a framework to understand why there are waiting lists for elective surgery in some OECD countries and not in others. It also describes how waiting times are measured in OECD countries and reviews different policy approaches to tackling excessive waiting times.




OECD Health Policy Studies Waiting Times for Health Services Next in Line


Book Description

The report reviews a range of policies that countries have used to tackle waiting times for different services, including elective surgery and primary care consultations, but also cancer care and mental health services, with a focus on identifying the most successful ones.




Artificial Intelligence and Data Mining in Healthcare


Book Description

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.




Heart Disease in Men


Book Description

Heart disease is an umbrella term for a number of different diseases affecting the heart. As of 2007, it is the leading cause of death in the United States, England, Canada and Wales, killing one person every 34 seconds in the United States alone.Heart disease is synonymous with cardiac disease but not with cardiovascular disease which is any disease of the heart or blood vessels. Among the many types of heart disease are, for example: Angina; Arrhythmia; Congenital heart disease; Coronary artery disease (CAD); Dilated cardiomyopathy; Heart attack (myocardial infarction); Heart failure; Hypertrophic cardiomyopathy; Mitral regurgitation; Mitral valve prolapse; and Pulmonary stenosis. This new book brings together important recent research on heart disease with a focus on men and heart disease.




Improving Diagnosis in Health Care


Book Description

Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.




Health Care Benchmarking and Performance Evaluation


Book Description

This new edition continues to emphasize the use of data envelopment analysis (DEA) to create optimization-based benchmarks within hospitals, physician group practices, health maintenance organizations, nursing homes and other health care delivery organizations. Suitable for graduate students learning DEA applications in health care as well as for practicing administrators, it is divided into two sections covering methods and applications. Section I considers efficiency evaluations using DEA; returns to scale; weight restricted (multiplier) models; non-oriented or slack-based models, including in this edition two versions of non-controllable variable models and categorical variable models; longitudinal (panel) evaluations and the effectiveness dimension of performance evaluation. A new chapter then looks at new and advanced models of DEA, including super-efficiency, congestion DEA, network DEA, and dynamic network models. Mathematical formulations of various DEA models are placed in end-of-chapter appendices. Section II then looks at health care applications within particular settings, chapter-by-chapter, including hospitals, physician practices, nursing homes and health maintenance organizations (HMOs). Other chapters then explore home health care and home health agencies; dialysis centers, community mental health centers, community-based your services, organ procurement organizations, aging agencies and dental providers; DEA models to evaluate provider performance for specific treatments, including stroke, mechanical ventilation and perioperative services. A new chapter then examines international-country-based applications of DEA in health care in 16 different countries, along with OECD and multi-country studies. Most of the existing chapters in this section were expanded with recent applications. Included with the book is online access to a learning version of DEA Solver software, written by Professor Kaoru Tone, which can solve up to 50 DMUs for various DEA models listed in the User’s Guide at the end of the book.




Finding What Works in Health Care


Book Description

Healthcare decision makers in search of reliable information that compares health interventions increasingly turn to systematic reviews for the best summary of the evidence. Systematic reviews identify, select, assess, and synthesize the findings of similar but separate studies, and can help clarify what is known and not known about the potential benefits and harms of drugs, devices, and other healthcare services. Systematic reviews can be helpful for clinicians who want to integrate research findings into their daily practices, for patients to make well-informed choices about their own care, for professional medical societies and other organizations that develop clinical practice guidelines. Too often systematic reviews are of uncertain or poor quality. There are no universally accepted standards for developing systematic reviews leading to variability in how conflicts of interest and biases are handled, how evidence is appraised, and the overall scientific rigor of the process. In Finding What Works in Health Care the Institute of Medicine (IOM) recommends 21 standards for developing high-quality systematic reviews of comparative effectiveness research. The standards address the entire systematic review process from the initial steps of formulating the topic and building the review team to producing a detailed final report that synthesizes what the evidence shows and where knowledge gaps remain. Finding What Works in Health Care also proposes a framework for improving the quality of the science underpinning systematic reviews. This book will serve as a vital resource for both sponsors and producers of systematic reviews of comparative effectiveness research.




Race, Ethnicity, and Language Data


Book Description

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.