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ARRA Investments in Enhanced Electronic Health Records
Public Health Burden
Assuring wide deployment and meaningful use of electronic health records is a goal of the Obama administration and an important aspect of the Health Information Technology (HITECH) component of the American Recovery and Reinvestment Act. At this time, most available commercial electronic health record systems do not easily integrate data from other systems, seldom contain complete records for a given patient, and do not provide routine access to decision support aids. Electronic health record systems can be enhanced to take advantage of sophisticated computer tools in ways that will help clinicians, patients and researchers.
Assistance for Health Care Decisions
Electronic health record systems rarely contain tools that allow physicians and other caregivers to see a high-level portrait of a patient’s total condition, draw data from a variety of sources to construct a fuller picture of therapeutic options, or predict problems before they occur. A variety of ARRA funded grants are developing approaches to helping health care providers and patients make informed decisions that lead to better health. These grants are undertaking projects that:
Provide guidelines for diagnosis and treatment of ADHD from within an electronic health record system to assist primary care physicians during a patient visit.
Create a comprehensive summary of information in a patient’s record, using computer intelligence. This summary would be especially helpful for physicians treating patients with chronic diseases, whose health records are long and complex.
Mine patient care data in order to provide the physician with a high-level view of a given patient as compared to other patients with similar characteristics. The focus of this work is diagnosis, management and treatment of critically-ill children.
Develop a reasoning system that can draw upon multiple sources of information to answer a physician’s questions about HIV drug treatment and drug resistance.
Support for Clinical Research
Electronic health record systems can be a source of potential participants for new clinical trials by alerting clinicians to current patients who meet eligibility criteria. Sophisticated information retrieval approaches can also be used to mine the data in electronic health records and biomedical literature, making them a source of ideas for new clinical trials. Some ARRA-funded research projects will:
Provide a mechanism in a personal health record that allows a researcher to contact a research subject, while protecting that subject’s anonymity, so that new information about the meaning of genetic tests or other trial outcomes can be communicated to the patient/subject.
Create a mechanism for managing informed consent and privacy authorizations for use in tracking an individual consumer’s preferences for involvement in research.
Create a library of standardized questions relevant to rare diseases that can be used for developing new patient registries for clinical research. Patient registries are an important step in understanding rare diseases and play a role in research that can improve patient outcomes.
Develop a point-of-care clinical alert that notifies a primary care physician that her patient meets eligibility requirements for a relevant clinical trial. Delivering the alerts in a timely way could increase recruitment into clinical trials.
Real-time Health Research
Electronic health record systems contain huge stores of data. Using health data standards, large clinical data warehouses can be constructed that support real-time health research about patterns of disease, medical errors, health outcomes and other important indicators of health care quality. Research supported by ARRA funds will:
Compare data mining methods for discovering unexpected acute drug-related adverse events in electronic health records. The research will mine data from three different health care locations, to assess the safety of commonly prescribed drugs.
Create a mechanism for linking patient records that are stored in multiple sites across a state, so that health records of a single individual could be linked together into longitudinal health histories, for purposes of research or care.
Develop techniques for gathering drug exposure and medical event data as they become available, for purposes of drug safety monitoring. This will improve current approaches to drug safety monitoring and will support creation of public alerts when a drug is found to be unsafe.
Build a national electronic research database of de-identified clinical information from 30,000,000 current and past members of Kaiser Permanente from eight regions of the US. This resource will employ standard terminologies based upon UMLS, and will use LOINC coding for clinical laboratory data. The resulting resource will support thousands of clinical, epidemiological and health services research studies.
-- Computer Decision Aid for ADHD Managements (CDAAM) -- Carroll, Aaron (IN)
-- An NLP Approach to Generating Patient Record Summaries -- Elhadad, Noemie(NY)
-- Advanced Computational Framework for Decision Support in Critically Ill Children -- Wetzel, Randolph (CA)
-- Intelligent Question Answering in the HIV Domain -- Waldinger, Richard J. (contact) (CA)
-- Presenting Genome Information in Patient Electronic Records: The Informed Cohort -- Mandl, Kenneth D. (contact) (MA)
-- An Open Source Research Permissions Framework for South Carolina -- Moskowitz, Jay (SC)
-- Library of Standardized Patient Registry Questions for Rare Diseases -- Richesson, Rachel (FL)
-- Evaluating HER-based, Point-of-Care Trial Recruitment Across Clinical Settings -- Embi, Peter (OH)
-- Data Mining Electronic Health Records for Drug Adverse Events -- Kuldorff, Martin (contact) (MA)
-- Development of a Statewide Master Person Index -- Narus, Scott (UT)
-- “Stopping Rules” for Drug Safety Monitoring Using Health Care Databases -- Schneeweiss, Sebastian (MA)
-- The Kaiser Permanente National Research Database -- Terdiman, Joseph (CA)
Office of Extramural Research
National Institutes of Health
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Version 1.5 Page Last Updated on April 01, 2013
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