AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
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AMIA Annu Symp Proc · Jan 2018
Interoperability Progress and Remaining Data Quality Barriers of Certified Health Information Technologies.
The Consolidated Clinical Document Architecture (C-CDA) is the primary standard for clinical document exchange in the United States. While document exchange is prevalent today, prior research has documented challenges to high quality, effective interoperability using this standard. Many electronic health records (EHRs) have recently been certified to a new version of the C-CDA standard as part of federal programs for EHR adoption. ⋯ This research applies automated tooling and manual inspection to evaluate conformance and data quality of these testing artifacts. It catalogs interoperability progress as well as remaining barriers to effective data exchange. Its findings underscore the importance of programs that evaluate data quality beyond schematron conformance to enable the high quality and safe exchange of clinical data.
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HL7 Fast Healthcare Information Resources (FHIR) is rapidly becoming the de-facto standard for the exchange of clinical and healthcare related information. Major EHR vendors and healthcare providers are actively developing transformations between existing EHR databases and their corresponding FHIR representation. ⋯ Considerable cost savings could be realized and overall quality could be improved were it possible to transformation primary FHIR EHR data directly into an IDR. We developed a FHIR to i2b2 transformation toolkit and evaluated the viability of such an approach.
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AMIA Annu Symp Proc · Jan 2018
Social Responsibility Practices of EHR Vendors: An Analysis of Disclosures in Annual Corporate Reports and Websites.
Socially desirable outcomes within healthcare IT depend not only on the ethical behavior of individuals, but also on the actions and policies of large corporations. It is therefore important to have public accountability mechanisms that can be applied to corporations. ⋯ The SASB standards and methodology were used to assess disclosures in the annual shareholder reports and websites of the top EHR vendors. The results showed a very low rate of meaningful disclosure.
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AMIA Annu Symp Proc · Jan 2018
A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning performs better than a traditional keyword model for ARDS identification. Linguistic pre-processing of reports was performed and text features were inputs to machine learning classifiers tuned using 10-fold cross-validation on 80% of the sample size and tested in the remaining 20%. ⋯ The traditional model had an accuracy of 67.3% (95% CI: 58.3-76.3) with a positive predictive value (PPV) of 41.7% (95% CI: 27.7-55.6). The best NLP model had an accuracy of 83.0% (95% CI: 75.9-90.2) with a PPV of 71.4% (95% CI: 52.1-90.8). A computable phenotype for ARDS with NLP may identify more cases than the traditional model.
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AMIA Annu Symp Proc · Jan 2018
Systematic Literature Review of Prescription Drug Monitoring Programs.
Prescription opioid abuse has become a serious national problem. To respond to the opioid epidemic, states have implemented prescription drug monitoring programs (PDMPs) to monitor and reduce opioid abuse. We conducted a systematic literature review to better understand the PDMP impact on reducing opioid abuse, improving prescriber practices, and how EHR integration has impacted PDMP usability. Lessons learned can help guide federal and state-based efforts to better respond to the opioid crisis.