Browsing by Subject "electronic health record"

Now showing 1 - 4 of 4
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    Creating Domain Specific Resources For Building Semantic Role Labling System For Operative Notes
    (2015-07) Wang, Yan
    Operative notes contain rich information about techniques, instruments, and materials used in surgeries. With widespread electronic health record (EHR) system adoption throughout healthcare, operative reports are increasingly accessible in electronic format and are potential information sources which may be valuable for a wide variety of secondary functions including new medical knowledge development, decision support, and clinical research. But manual review of large number of reports is time consuming and limits our ability to provide timely evidence-based guide in clinical environment. Automatic extraction of techniques, instruments, materials, and other factors surrounding operative procedures from operative notes can provide an efficient way for physicians to acquire valuable information distilled from diverse experiences reported by clinicians and decide optimal technique approach for patients. To automate the representation and extraction of the rich information from operative notes, the goal of this research is to create domain specific resources needed for creating a semantic role labeling (SRL) system to extract information from operative notes. The coverage of existing domain-specific resources and general English resources for building a SRL system for operative notes were evaluated on a corpus obtained from the Fairview Health Services and the sublanguage used to describe surgical actions in operative notes was investigated. The results from the study show that general English resources are not adequate for building a SRL system for clinical text. Also the study shows some sublanguage characters of operative notes that can be used for parser adaption. Next, an existing unlexicalized probabilistic context-free grammar (PCFG) parser, the Stanford PCFG parser, was adapted to clinical text for better syntactic parsing performance. Finally, domain specific predicate structure (PAS) frames were created for operative notes, as existing semantic frames for general English are not enough for operative notes. The domain specific resource created in this research can be used to build a SRL system for automatically extracting detailed information from operative notes.
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    Evaluation of an Electronic Health Record Intervention to Decrease Over-screening in Women Beyond the Screening Age Limits or Post-hysterectomy
    (2018-03) Teoh, Deanna
    Objectives: 1) To assess healthcare provider adherence to the 2012 cervical cancer screening guidelines beyond screening age limits and post-hysterectomy; 2) To evaluate effects of electronic health record clinical decision support to decrease non-indicated screening. Methods: A retrospective chart review determined cervical cancer screening practices from 2012-2014 in women <21 or >65 years of age or post-hysterectomy. Tests were designated as indicated/non-indicated per 2012 guidelines. To test the effect of clinical decision support, the proportion of non-indicated tests were compared before and after implementation of decision support. Results: Tests were indicated in 51%, 40%, and 29% of women <21 years, >65 years, and post-hysterectomy, respectively. Implementation of clinical decision support did not change the proportion of non-indicated Pap tests (OR 1.08, 95% CI 0.77-1.52). Conclusions: 35% of Pap tests in women beyond the screening age limits or post-hysterectomy were not indicated. A clinical decision support alert did not change practices.
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    Leveraging Electronic Health Record Data For Whole-Person Knowledge Discovery
    (2018-04) Gao, Grace
    This dissertation presents strengths data capture in electronic health record (EHR) documentation, risk assessment and management using a strengths-based data capture model, and a strengths-based research study within a wellbeing context using de-identified EHR data and a data-driven model. It starts with the description of the current state of documentation of problems and strengths in the EHRs. There exists a gap of strengths data in EHRs that predominantly follow problem-based infrastructure in the healthcare information system, and there are also emerging new data sources that include strengths data in EHRs. Following this trend, this dissertation examines the potential of leveraging the use of a proposed Strengths-based Data Capture Model in health risk assessment and management. This model adds a whole-person perspective including the purposeful use of strengths data as health assets in data capture, aggregation, and person-driven application throughout the process of risk assessment and management. It concludes by a strengths-based research in older adults using a data-driven model to aid data-mining discovery of associations among older adults’ strengths, problems, planned nursing interventions, and baseline Knowledge, Behavior, and Status scores using EHR data captured by the Omaha System. By integrating strengths-based documentation, data capture model, and research, this dissertation introduces a cutting-edge data capture model, and creates a platform for continued research and application of a strength-based ontology in clinical practice and electronic system of documentation.
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    A Scoping Review of Interventions Increasing Screening and Diagnosis of Familial Hypercholesterolemia
    (Elsevier, 2022) Polanski, Amanda; Wolin, Ellory; Kocher, Megan; Zierhut, Heather
    Purpose Familial Hypercholesterolemia (FH) is one of the most common genetic conditions, with a prevalence of ~1/250 individuals. If left untreated, FH greatly increases risk for cardiovascular disease and premature death. Currently, FH is largely underdiagnosed, and interventions are needed to increase identification. The purpose of this study was to identify effective interventions aimed at increasing FH diagnosis. Methods A scoping review of the literature addressing interventions to increase FH detection was conducted. Included studies detailed interventions which increased screening and detection of FH globally. Studies were characterized by intervention type and analyzed for themes using the Consolidated Framework for Implementation Research. Results A total of 46 studies were included in the review across 32 countries. All studies were effective in increasing FH detection. Twelve different intervention types were extracted with the most used being cascade and electronic medical record screening-based interventions. Conclusions Given the versatility of effective interventions in this review, efforts could explore approaches that maximize identification through a combination of interventions. Our results support one such strategy that uses electronic medical records to screen for index cases and a two-step indirect and direct contact method of index cases’ relatives.