Electronic health record interoperability across transport medicine
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Author/Creator ORCID
Date
2014-02-28
Type of Work
Department
Towson University. Department of Computer and Information Sciences
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Citation of Original Publication
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Copyright protected, all rights reserved.
There are no restrictions on access to this document. An internet release form signed by the author to display this document online is on file with Towson University Special Collections and Archives.
There are no restrictions on access to this document. An internet release form signed by the author to display this document online is on file with Towson University Special Collections and Archives.
Subjects
Abstract
There is an expectation that when a patient is transferred between two different medical institutions, their medical records will follow them. While this is becoming true for the majority of the patient population, there is a gap for those who must be medically transported by either ambulance, helicopter or fixed wing. Developing this type of IT architecture, our research will focus on properly aligning the concept of electronic health record interoperability across the transport medicine environment in a seamless fashion as well as address the contribution, expectations and promises associated with a universal electronic health record as defined by the Health Information Technology Standards Panel (HITSP). In August of 2006 the US Government passed an executive order to implement electronic health records by 2014. We developed an Integrating the Healthcare Enterprise (IHE) profile for Transport Medicine, to facilitate interoperability between various healthcare facilities and the transport environment utilizing distributed computing technologies such as SOAP envelopes for ebXML over mobile networks. Current Enterprise Architecture (EA) models provide little guidance, if any, for implementing interoperability in healthcare organizations. We developed an EA interoperability method that leverages current EA models and business IT. Our EA interoperability method refocuses a healthcare organization's principles and IT to include external entities that current EA models ignore for competitive reasons. Our approach shows the advantage of considering these external relationships between competitors and synergistic third parties. Advantages include increased patient satisfaction, meaningful data exchange and integrated transport solutions that support high-level business processes. We developed an algorithm which searches for available documents that are relevant to the patients' current conditions based on medical coding within these documents, clinical document architecture (CDA) documents, using HL7 message exchange mechanism in SOAP envelopes. These CDA documents are then consolidated into a single transport record summary (TRS) document to filter out redundancies and provide destination medical service provider with the most pertinent information that is readily accessible to both human and machine. In a time critical environment, access to multiple documents from difference sources is not likely feasible. For this reason, we developed a CDA document consolidation tool, the TRS Constructor, which creates a TRS by querying and analyzing patient's multiple CDA documents. The new TRS will be registered into the Health Information Exchange (HIE) environment for cross-reference across healthcare facilities and other providers. The need to support transport clinicians with the most valid pertinent information about each patient is the main focus to our research. We built a medical ontology around transport medicine protocols which associated multiple diseases and their associated symptoms. We developed semantic queries using the patient's current symptoms as input and the query result is analyzed by our algorithm to derive probable diseases. The algorithm uses types of associated symptoms based on the ontology to quantify a confidence level for each possible disease. If the disease ruled in, we presented this information to the clinician as part of a decision support system. We used this output to query the patient's existing EHR for relevant medical history regarding the current disease process. We provide both the probable diagnoses along with the patient's relevant history in a single XML resource document.