Digital Data Improvement Priorities for Continuous Learning in Health and Health Care Workshop Summary (2013) / Chapter Skim
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1 Introduction
1 Introduction
Pages 1-8
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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 (IOM, 2012)
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Increasing collection, sharing, and aggregation of data are being matched by advances in methods for learning from these data. Clinical and administrative data can be used for studies to assess the effectiveness of health care interventions; identify product safety issues; detect emerging epidemics; and measure health care utilization and value.
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This challenge is magnified by the lack of lessons and best practices for how to approach data quality assurances needed to support the multiple facets of a learning health system. To address these issues and gain a better understanding of the types, sources, applications, limitations, appropriate uses, and quality improvement needs for digital health data, the IOM's Roundtable on Value & Science-Driven Health Care convened a meeting on March 23, 2012, titled Digital Data Priorities for Continuous Learning in Health and Health Care.
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In addition to traditional clinical trials, registries for quality activities, research, or postmarketing surveillance are a parallel source of enriched clinical data. Employers, as the purchasers of health insurance for much of the population, often possess data on employees' health care utilization, basic health status, and associated expenses which can be used for knowledge development.
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WORKSHOP SCOPE AND OBJECTIVES Workshop participants included experts from across medicine, public health, informatics, health information technology, health care services research, health care quality reporting, biomedical research, clinical research, statistics, medical product manufacturing, health care payment and financing, and patient advocacy. Content was structured to explore the data quality challenges and opportunities in a learning health system, highlighting the opportunities and priorities beyond care coordination such as population and care process management, clinical research, translational informatics, and public health support at the national and state level.
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ORGANIZATION OF THE SUMMARY This publication summarizes the proceedings of the workshop on Digital Data Priorities for Continuous Learning in Health and Health Care, the 12th in the Learning Health System Series of publications by the Roundtable
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Chapter 2 addresses data quality challenges and opportunities in a learning health system, including explorations of data heterogeneity and the importance of focusing on data of value to the patient. Chapter 3 focuses on the many uses of the digital health data utility, covering the management of patient populations, clinical research, translational informatics, and both national and local public health efforts.
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