Browsing by Subject "Electronic Medical Records"

Now showing 1 - 5 of 5
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    Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records
    (2018) Patel, Jay; Mowery, Danielle; Krishnan, Anand; Thyvalikakath, Thankam
    Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it’s unclear to what extent patient-reported CVD information is accurately captured in Electronic Dental Records (EDRs). In this pilot study, we aimed to measure the reliability of patient-reported CVD conditions in EDRs. We assessed information congruence by comparing patients’ self-reported dental histories to their original diagnosis assigned by their medical providers in the Electronic Medical Record (EMR). To enable this comparison, we encoded patients CVD information from the free-text data of EDRs into a structured format using natural language processing (NLP). Overall, our NLP approach achieved promising performance extracting patients’ CVD-related information. We observed disagreement between self-reported EDR data and physician-diagnosed EMR data.
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    From Paper to Purgatory: The History of Electronic Medical Records and Their Impact on Healthcare
    (2023-04-05) Tierney, William M.
    Presentation slides for lecture delivered by Bill Tierney, MD (Clinical Professor and Associate Dean of Population Health and Health Outcomes, Richard M. Fairbanks School of Public Health, IUPUI) on April 5, 2023. Dr. Tierney’s research focuses on improving health care delivery and its outcomes through developing and implementing electronic health record systems and health information exchanges in hospital and outpatient venues in Indiana and in East Africa. Presentation recording available online: https://purl.dlib.indiana.edu/iudl/media/z40k81rq7f
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    Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits
    (Biomed Central, 2019-07-25) Glicksberg, Benjamin S.; Amadori, Letizia; Akers, Nicholas K.; Sukhavasi, Katyayani; Franzén, Oscar; Li, Li; Belbin, Gillian M.; Akers, Kristin L.; Shameer, Khader; Badgeley, Marcus A.; Johnson, Kipp W.; Readhead, Ben; Darrow, Bruce J.; Kenny, Eimear E.; Betsholtz, Christer; Ermel, Raili; Skogsberg, Josefin; Ruusalepp, Arno; Schadt, Eric E.; Dudley, Joel T.; Ren, Hongxia; Kovacic, Jason C.; Giannarelli, Chiara; Li, Shuyu D.; Björkegren, Johan L. M.; Chen, Rong; Pediatrics, IU School of Medicine
    BACKGROUND: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. RESULTS: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. CONCLUSION: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.
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    Mapping the rules: conceptual and logical relationships in a system for pediatric clinical decision support
    (2013-10-07) Ralston, Rick K.; Odell, Jere D.; Whipple, Elizabeth C.; Liu, Gilbert C.
    The Child Health Improvement through Computer Automation (CHICA) system uses evidence-based guidelines and information collected in the clinic and stored in an electronic medical record (EMR) to inform physician and patient decision making. CHICA helps physicians to identify and select relevant screenings and also provides personalized, just-in-time information for patients. This system relies on a database of Medical Logic Modules (MLMS) written in the Arden Rules syntax. These MLMs store observations (StorObs) during the clinical encounter which trigger potential screenings and preventive health interventions for discussion with the patient or for follow up at the next visit. This poster shows how informationists worked with the CHICA team to describe the MLMs using standard vocabularies, including Medical Subject Headings (MeSH) and Logical Observation Identifiers Names and Codes (LOINC). After assigning keywords to the database of MLMs, the informationists used visualization tools to generate maps. These maps show how rules are related by logic (shared StorObs) and by concept (shared vocabulary). The CHICA team will use these maps to identify gaps in the clinical decision support database and (if needed) to develop rules which bridge related but currently isolated concepts.
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    Short-Term Medical Costs of a VHA Health Information Exchange: A CHEERS-Compliant Article.
    (Wolters Kluwer Health, 2016-01) French, Dustin D.; Dixon, Brian E.; Perkins, Susan M.; Myers, Laura J.; Weiner, Michael; Zillich, Allan J.; Haggstrom, David A.; Department of Epidemiology, Richard M. Fairbanks School of Public Health
    The Virtual Lifetime Electronic Record (VLER) Health program provides the Veterans Health Administration (VHA) a framework whereby VHA providers can access the veterans’ electronic health record information to coordinate healthcare across multiple sites of care. As an early adopter of VLER, the Indianapolis VHA and Regenstrief Institute implemented a regional demonstration program involving bi-directional health information exchange (HIE) between VHA and non-VHA providers.The aim of the study is to determine whether implementation of VLER HIE reduces 1 year VHA medical costs.A cohort evaluation with a concurrent control group compared VHA healthcare costs using propensity score adjustment. A CHEERs compliant checklist was used to conduct the cost evaluation.Patients were enrolled in the VLER program onsite at the Indianapolis VHA in outpatient clinics or through the release-of-information office.VHA cost data (in 2014 dollars) were obtained for both enrolled and nonenrolled (control) patients for 1 year prior to, and 1 year after, the index date of patient enrollment.There were 6104 patients enrolled in VLER and 45,700 patients in the control group. The annual adjusted total cost difference per patient was associated with a higher cost for VLER enrollees $1152 (95% CI: $807–1433) (P < 0.01) (in 2014 dollars) than VLER nonenrollees.Short-term evaluation of this demonstration project did not show immediate reductions in healthcare cost as might be expected if HIE decreased redundant medical tests and treatments. Cost reductions from shared health information may be realized with longer time horizons.