Browsing by Author "Kasthurirathne, Suranga Nath"

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    Evaluating Methods for Identifying Cancer in Free-Text Pathology Reports Using Various Machine Learning and Data Preprocessing Approaches
    (IOS, 2015) Kasthurirathne, Suranga Nath; Dixon, Brian E.; Grannis, Shaun J.; Department of BioHealth Informatics, School of Informatics and Computing
    Automated detection methods can address delays and incompleteness in cancer case reporting. Existing automated efforts are largely dependent on complex dictionaries and coded data. Using a gold standard of manually reviewed pathology reports, we evaluated the performance of alternative input formats and decision models on a convenience sample of free-text pathology reports. Results showed that the input format significantly impacted performance, and specific algorithms yielded better results for presicion, recall and accuracy. We conclude that our approach is sufficiently accurate for practical purposes and represents a generalized process.
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    Towards Standardized Patient Data Exchange: Integrating a FHIR Based API for the Open Medical Record System
    (IOS, 2015) Kasthurirathne, Suranga Nath; Mamlin, Burke; Grieve, Grahame; Biondich, Paul; Department of BioHealth Informatics, School of Informatics and Computing
    Interoperability is essential to address limitations caused by the ad hoc implementation of clinical information systems and the distributed nature of modern medical care. The HL7 V2 and V3 standards have played a significant role in ensuring interoperability for healthcare. FHIR is a next generation standard created to address fundamental limitations in HL7 V2 and V3. FHIR is particularly relevant to OpenMRS, an Open Source Medical Record System widely used across emerging economies. FHIR has the potential to allow OpenMRS to move away from a bespoke, application specific API to a standards based API. We describe efforts to design and implement a FHIR based API for the OpenMRS platform. Lessons learned from this effort were used to define long term plans to transition from the legacy OpenMRS API to a FHIR based API that greatly reduces the learning curve for developers and helps enhance adhernce to standards.