Improving Population Health Using Electronic Health Records

Electronic health records (EHRs) have become commonplace in the medical profession. Health data are readily captured and permanently stored in a digital fashion, and consequently, are increasingly being utilized in health research. The quality of this research depends upon the investigator’s ability to obtain the correct data to answer the correct question. It is easy to churn out poor quality research from the EHR; it is much harder to produce meaningful results that influence the population’s health. Improving Population Health Using Electronic Health Records takes the reader through the process of conducting meaningful research from data in the EHR. It de-mystifies the entire research process, from how to ask the right kind of research questions, to obtaining data with particular emphasis on data management and manipulation, to performing a valid statistical analyses, and interpreting and presenting the results in a clear, concise fashion that has the potential to improve population health. This book can be used as a hands-on how-to guide of performing research from EHR data in either a piece-meal fashion, selecting only the topics of greatest interest, or a complete guide to the entire research process. Readers will benefit from the intuitive presentation of complex methods with a multitude of examples. It is invaluable reading for researchers and clinicians who are not otherwise familiar with the complexities of working with large data sets.

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.

Commissioned by the Department of Health and Human Services, Key Capabilities of an Electronic Health Record System provides guidance on the most significant care delivery-related capabilities of electronic health record (EHR) systems. There is a great deal of interest in both the public and private sectors in encouraging all health care providers to migrate from paper-based health records to a system that stores health information electronically and employs computer-aided decision support systems. In part, this interest is due to a growing recognition that a stronger information technology infrastructure is integral to addressing national concerns such as the need to improve the safety and the quality of health care, rising health care costs, and matters of homeland security related to the health sector. Key Capabilities of an Electronic Health Record System provides a set of basic functionalities that an EHR system must employ to promote patient safety, including detailed patient data (e.g., diagnoses, allergies, laboratory results), as well as decision-support capabilities (e.g., the ability to alert providers to potential drug-drug interactions). The book examines care delivery functions, such as database management and the use of health care data standards to better advance the safety, quality, and efficiency of health care in the United States.

Determinants of health - like physical activity levels and living conditions - have traditionally been the concern of public health and have not been linked closely to clinical practice. However, if standardized social and behavioral data can be incorporated into patient electronic health records (EHRs), those data can provide crucial information about factors that influence health and the effectiveness of treatment. Such information is useful for diagnosis, treatment choices, policy, health care system design, and innovations to improve health outcomes and reduce health care costs. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2 identifies domains and measures that capture the social determinants of health to inform the development of recommendations for the meaningful use of EHRs. This report is the second part of a two-part study. The Phase 1 report identified 17 domains for inclusion in EHRs. This report pinpoints 12 measures related to 11 of the initial domains and considers the implications of incorporating them into all EHRs. This book includes three chapters from the Phase 1 report in addition to the new Phase 2 material. Standardized use of EHRs that include social and behavioral domains could provide better patient care, improve population health, and enable more informative research. The recommendations of Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2 will provide valuable information on which to base problem identification, clinical diagnoses, patient treatment, outcomes assessment, and population health measurement.

Substantial empirical evidence of the contribution of social and behavioral factors to functional status and the onset and progression of disease has accumulated over the past few decades. Electronic health records (EHRs) provide crucial information to providers treating individual patients, to health systems, including public health officials, about the health of populations, and to researchers about the determinants of health and the effectiveness of treatment. Inclusion of social and behavioral health domains in EHRs is vital to all three uses. The Health Information Technology for Economic and Clinical Health Act and the Patient Protection and Affordable Care Act place new importance on the widespread adoption and meaningful use of EHRs. "Meaningful use" in a health information technology context refers to the use of EHRs and related technology within a health care organization to achieve specified objectives. Achieving meaningful use also helps determine whether an organization can receive payments from the Medicare EHR Incentive Program or the Medicaid EHR Incentive Program. Capturing Social and Behavioral Domains in Electronic Health Records is the first phase of a two-phase study to identify domains and measures that capture the social determinants of health to inform the development of recommendations for meaningful use of EHRs. This report identifies specific domains to be considered by the Office of the National Coordinator, specifies criteria that should be used in deciding which domains should be included, identifies core social and behavioral domains to be included in all EHRs, and identifies any domains that should be included for specific populations or settings defined by age, socioeconomic status, race/ethnicity, disease, or other characteristics.

Electronic Health Record (EHR) systems today provide increasing levels of clinical decision support and are the fulcrum for change for value-based healthcare delivery. Billions of dollars of government and insurer payments are dependent on evidence-based workflow design and quality report. In this context, quality measurement is no longer a retrospective exercise, but an essential prospective process embedded in clinical operations. Population health tools in the EHR enhance the efficiency and effectiveness of interventions thus improving the quality of care at lower cost. Population health methods are effective in ensuring that the right patient receives the right care at the right time. This book provides a clear framework for design, implementation, and monitoring of innovative population health tools to accelerate measurable improvements in care delivery. Key benefits for readers include conceptual framework, team approach, and technical insights that result in improved patient care, improved performance on quality measures and increased revenue from quality performance incentives and risk-based contracts. This is also a practice guide to the healthcare professionals many roles who are eager to build or improve population health programs with the goal of delivering high quality value-based care.

Each year in the United States, more than 4,000 occupational fatalities and more than 3 million occupational injuries occur along with more than 160,000 cases of occupational illnesses. Incorporating patients' occupational information into electronic health records (EHRs) could lead to more informed clinical diagnosis and treatment plans as well as more effective policies, interventions, and prevention strategies to improve the overall health of the working population. At the request of the National Institute for Occupational Safety and Health, the IOM appointed a committee to examine the rationale and feasibility of incorporating occupational information in patients' EHRs. The IOM concluded that three data elements - occupation, industry, and work-relatedness - were ready for immediate focus, and made recommendations on moving forward efforts to incorporate these elements into EHRs.

v. 1. Research findings -- v. 2. Concepts and methodology -- v. 3. Implementation issues -- v. 4. Programs, tools and products.