Roundtable on Value and Science-Driven Health Care – författare

Recent scientific and technological advances have accelerated our understanding of the causes of disease development and progression, and resulted in innovative treatments and therapies. Ongoing work to elucidate the effects of individual genetic variation on patient outcomes suggests the rapid pace of discovery in the biomedical sciences will only accelerate. However, these advances belie an important and increasing shortfall between the expansion in therapy and treatment options and knowledge about how these interventions might be applied appropriately to individual patients. The impressive gains made in Americans'' health over the past decades provide only a preview of what might be possible when data on treatment effects and patient outcomes are systematically captured and used to evaluate their effectiveness. Needed for progress are advances as dramatic as those experienced in biomedicine in our approach to assessing clinical effectiveness. In the emerging era of tailored treatments and rapidly evolving practice, ensuring the translation of scientific discovery into improved health outcomes requires a new approach to clinical evaluation. A paradigm that supports a continual learning process about what works best for individual patients will not only take advantage of the rigor of trials, but also incorporate other methods that might bring insights relevant to clinical care and endeavor to match the right method to the question at hand. The Institute of Medicine Roundtable on Value & Science-Driven Health Care''s vision for a learning healthcare system, in which evidence is applied and generated as a natural course of care, is premised on the development of a research capacity that is structured to provide timely and accurate evidence relevant to the clinical decisions faced by patients and providers. As part of the Roundtable''s Learning Healthcare System series of workshops, clinical researchers, academics, and policy makers gathered for the workshop Redesigning the Clinical Effectiveness Research Paradigm: Innovation and Practice-Based Approaches. Participants explored cutting-edge research designs and methods and discussed strategies for development of a research paradigm to better accommodate the diverse array of emerging data resources, study designs, tools, and techniques. Presentations and discussions are summarized in this volume.

Successful development of clinical data as an engine for knowledge generation has the potential to transform health and health care in America. As part of its Learning Health System Series, the Roundtable on Value & Science-Driven Health Care hosted a workshop to discuss expanding the access to and use of clinical data as a foundation for care improvement.

As past, current, or future patients, the public should be the health care system''s unwavering focus and serve as change agents in its care. Taking this into account, the quality of health care should be judged not only by whether clinical decisions are informed by the best available scientific evidence, but also by whether care is tailored to a patient''s individual needs and perspectives. However, too often it is provider preference and convenience, rather than those of the patient, that drive what care is delivered. As part of its Learning Health System series of workshops, the Roundtable on Value & Science-Driven Health Care hosted a workshop to assess the prospects for improving health and lowering costs by advancing patient involvement in the elements of a learning health system.

Like many other industries, health care is increasingly turning to digital information and the use of electronic resources. The Institute of Medicine''s Roundtable on Value & Science-Driven Health Care hosted three workshops to explore current efforts and opportunities to accelerate progress in improving health and health care with information technology systems.

Recent scientific and technological advances have accelerated our understanding of the causes of disease development and progression, and resulted in innovative treatments and therapies. Ongoing work to elucidate the effects of individual genetic variation on patient outcomes suggests the rapid pace of discovery in the biomedical sciences will only accelerate. However, these advances belie an important and increasing shortfall between the expansion in therapy and treatment options and knowledge about how these interventions might be applied appropriately to individual patients. The impressive gains made in Americans'' health over the past decades provide only a preview of what might be possible when data on treatment effects and patient outcomes are systematically captured and used to evaluate their effectiveness. Needed for progress are advances as dramatic as those experienced in biomedicine in our approach to assessing clinical effectiveness. In the emerging era of tailored treatments and rapidly evolving practice, ensuring the translation of scientific discovery into improved health outcomes requires a new approach to clinical evaluation. A paradigm that supports a continual learning process about what works best for individual patients will not only take advantage of the rigor of trials, but also incorporate other methods that might bring insights relevant to clinical care and endeavor to match the right method to the question at hand. The Institute of Medicine Roundtable on Value & Science-Driven Health Care''s vision for a learning healthcare system, in which evidence is applied and generated as a natural course of care, is premised on the development of a research capacity that is structured to provide timely and accurate evidence relevant to the clinical decisions faced by patients and providers. As part of the Roundtable''s Learning Healthcare System series of workshops, clinical researchers, academics, and policy makers gathered for the workshop Redesigning the Clinical Effectiveness Research Paradigm: Innovation and Practice-Based Approaches. Participants explored cutting-edge research designs and methods and discussed strategies for development of a research paradigm to better accommodate the diverse array of emerging data resources, study designs, tools, and techniques. Presentations and discussions are summarized in this volume.

Successful development of clinical data as an engine for knowledge generation has the potential to transform health and health care in America. As part of its Learning Health System Series, the Roundtable on Value & Science-Driven Health Care hosted a workshop to discuss expanding the access to and use of clinical data as a foundation for care improvement.

As past, current, or future patients, the public should be the health care system''s unwavering focus and serve as change agents in its care. Taking this into account, the quality of health care should be judged not only by whether clinical decisions are informed by the best available scientific evidence, but also by whether care is tailored to a patient''s individual needs and perspectives. However, too often it is provider preference and convenience, rather than those of the patient, that drive what care is delivered. As part of its Learning Health System series of workshops, the Roundtable on Value & Science-Driven Health Care hosted a workshop to assess the prospects for improving health and lowering costs by advancing patient involvement in the elements of a learning health system.

Like many other industries, health care is increasingly turning to digital information and the use of electronic resources. The Institute of Medicine''s Roundtable on Value & Science-Driven Health Care hosted three workshops to explore current efforts and opportunities to accelerate progress in improving health and health care with information technology systems.

Digital health data are the lifeblood of a continuous learning health system. A steady flow of reliable data is necessary to coordinate and monitor patient care, analyze and improve systems of care, conduct research to develop new products and approaches, assess the effectiveness of medical interventions, and advance population health. The totality of available health data is a crucial resource that should be considered an invaluable public asset in the pursuit of better care, improved health, and lower health care costs.

The ability to collect, share, and use digital health data is rapidly evolving. Increasing adoption of electronic health records (EHRs) is being driven by the implementation of the Health Information Technology for Economic and Clinical Health (HITECH) Act, which pays hospitals and individuals incentives if they can demonstrate that they use basic EHRs in 2011. Only a third had access to the basic features necessary to leverage this information for improvement, such as the ability to view laboratory results, maintain problem lists, or manage prescription ordering.

In addition to increased data collection, more organizations are sharing digital health data. Data collected to meet federal reporting requirements or for administrative purposes are becoming more accessible. Efforts such as Health.Data.gov provide access to government datasets for the development of insights and software applications with the goal of improving health. Within the private sector, at least one pharmaceutical company is actively exploring release of some of its clinical trial data for research by others. Digital Data Improvement Priorities for Continuous Learning in Health and Health Care: Workshop Summary summarizes discussions at the March 2012 Institute of Medicine (2012) workshop to identify and characterize the current deficiencies in the reliability, availability, and usability of digital health data and consider strategies, priorities, and responsibilities to address such deficiencies.

Health care quality and its affordability have become very pressing issues in the United States. All sectors of the country are attempting to push forward initiatives that will improve the health care system as well as the health of the American population in general. Despite the economical dedication to health care, about 1/5, the system remains uneven and fragmented, patient harm is quite common, care is often uncoordinated, and many more mishaps occur. There exists many obstacles to improve the nation''s health care system; these include the capacity to reliably and consistently measure progress. In 2006 the Institute of Medicine (IOM) established the Roundtable on Value & Science-Driven Health Care which has since accelerated the development of a learning health system- one in which science, informatics, incentives, and culture are aligned to create a continuous learning loop. This learning loop would thus help make the health care system better.

In response, the IOM organized a 2-day workshop to explore in depth the core measurement needs for population health, health care quality, and health care costs. The workshop hoped to gain a full understanding of how to improve the nation''s measurement capacity to track progress in the health care system. Having this knowledge would help the nation get one step closer to the creation of an efficient learning loop.

The workshop was divided into a series of sessions that focused on different aspects of measurement. Core Measurement Needs for Better Care, Better Health, and Lower Costs: Counting What Counts: Workshop Summary includes explanations and key details for these sessions: Vision, Current Measurement Capabilities, Specifying the Shape of a Core Metric Set, and Implementation. The report also features common themes within these areas, the workshop agenda, and information about those involved.

The Institute of Medicine\''s Roundtable on Value & Science-Driven Health Care held a workshop, titled Partnering with Patients to Drive Shared Decisions, Better Value, and Care Improvement, on February 25 and 26, 2013. The workshop, supported by the Gordon and Betty Moore Foundation and the Blue Shield of California Foundation, focused on identifying and exploring issues, attitudes, and approaches to increasing patient engagement in and demand for the following: shared decision making and better communication about the evidence in support of testing and treatment options; the best value from the health care they receive; and the use of data generated in the course of their care experience for care improvement.

The workshop hoped to build awareness and demand from patients and families for better care at lower costs and to create a health care system that continuously learns and improves. Participants included members of the medical, clinical research, health care services research, regulatory, health care economics, behavioral economics, health care delivery, payer, and patient communities. Partnering with Patients to Drive Shared Decisions, Better Value, and Care Improvement Workshop Proceedings offers a summary of the 2-day workshop including the workshop agenda and biographies of speakers.

Randomized clinical trials (RCTs) are often referred to as the "gold standard" of clinical research. However, in its current state, the U.S. clinical trials enterprise faces substantial challenges to the efficient and effective conduct of research. Streamlined approaches to RCTs, such as large simple trials (LSTs), may provide opportunities for progress on these challenges. Clinical trials support the development of new medical products and the evaluation of existing products by generating knowledge about safety and efficacy in pre- and post-marketing settings and serve to inform medical decision making and medical product development. Although well-designed and -implemented clinical trials can provide robust evidence, a gap exists between the evidence needs of a continuously learning health system, in which all medical decisions are based on the best available evidence, and the reality, in which the generation of timely and practical evidence faces significant barriers.

Large Simple Trials and Knowledge Generation in a Learning Health System is the summary of a workshop convened by the Institute of Medicine''s Roundtable on Value & Science-Driven Health Care and the Forum on Drug Discovery, Development, and Translation. Experts from a wide range of disciplines—including health information technology, research funding, clinical research methods, statistics, patients, product development, medical product regulation, and clinical outcomes research—met to marshal a better understanding of the issues, options, and approaches to accelerating the use of LSTs. This publication summarizes discussions on the potential of LSTs to improve the speed and practicality of knowledge generation for medical decision making and medical product development, including efficacy and effectiveness assessments, in a continuously learning health system.

Large Simple Trials and Knowledge Generation in a Learning Health System explores acceleration of the use of LSTs to improve the speed and practicality of knowledge generation for medical decision making and medical product development; considers the concepts of LST design, examples of successful LSTs, the relative advantages of LSTs, and the infrastructure needed to build LST capacity as a routine function of care; identifies structural, cultural, and regulatory barriers hindering the development of an enhanced LST capacity; discusses needs and strategies in building public demand for and participation in LSTs; and considers near-term strategies for accelerating progress in the uptake of LSTs in the United States.

Clinical research strains to keep up with the rapid and iterative evolution of medical interventions, clinical practice innovation, and the increasing demand for information on the clinical effectiveness of these advancements. In response to the growing availability of archived and real-time digital health data and the opportunities this data provides for research, as well as the increasing number of studies using prospectively collected clinical data, the Institute of Medicine\''s Roundtable on Value & Science-Driven Health Care convened a workshop on Observational Studies in a Learning Health System. Participants, including experts from a wide range of disciplines - clinical researchers, statisticians, biostatisticians, epidemiologists, health care informaticians, health care analytics, research funders, health products industry, clinicians, payers, and regulators - explored leading edge approaches to observational studies, charted a course for the use of the growing health data utility, and identified opportunities to advance progress. Workshop speakers and individual participants strove to identify stakeholder needs and barriers to the broader application of observational studies.

Observational Studies in a Learning Health Systemis the summary of the workshop. This report explores the role of observational studies in the generation of evidence to guide clinical and health policy decisions. The report discusses concepts of rigorous observational study design and analysis, emerging statistical methods, and opportunities and challenges of observational studies to complement evidence from experimental methods, treatment heterogeneity, and effectiveness estimates tailored toward individual patients.