Active Semantic Electronic Medical Recordsan Application of Active Semantic Documents in Health Care Amit Sheth , S. Agrawal, J. Lathem, N. Oldham, H. Wingate, P. Yadav, K.Gallagher

Athens Heart Center & LSDIS Lab, University of Georgiahttp://lsdis.cs.uga.edu

Semantic Web application in useIn daily use at Athens Heart Center28 person staffInterventional CardiologistsElectrophysiology CardiologistsDeployed since January 200640-60 patients seen daily3000+ active patientsServes a population of 250,000 people

Information OverloadNew drugs added to marketAdds interactions with current drugsChanges possible procedures to treat an illnessInsurance Coverage's ChangeInsurance may pay for drug X but not drug Y even though drug X and Y are equivalentPatient may need a certain diagnosis before some expensive test are runPhysicians need a system to keep track of ever changing landscape

System though out the practice

System though out the practice

System though out the practice

System though out the practice

Active Semantic Document (ASD)A document (typically in XML) with the following features:

Semantic annotationsLinking entities found in a document to ontologyLinking terms to a specialized lexicon

Actionable informationRules over semantic annotationsViolated rules can modify the appearance of the document (Show an alert)

Active Semantic Patient RecordAn application of ASDThree OntologiesPracticeInformation about practice such as patient/physician data DrugInformation about drugs, interaction, formularies, etc.ICD/CPTDescribes the relationships between CPT and ICD codesMedical Records in XML created from database

Practice Ontology Hierarchy (showing is-a relationships)

Drug Ontology Hierarchy (showing is-a relationships)interaction_ with_non_ drug_reactant

Drug Ontology showing neighborhood of PrescriptionDrug concept

Part of Procedure/Diagnosis/ICD9/CPT Ontologyspecificitydiagnosisproceduremaps_to_diagnosismaps_to_procedure

Extraction and Annotation using an ontology

Local Medical Review Policy (LMRP) supportExample a partial list of ICD9CM codes that support medical necessity for an EKG (CPT 93000)Data extracted from the Centers for Medicare and Medicaid Services

ICD9CMDiagnosis Name244.9Hypothyrodism250.00Diabetes mellitus Type II250.01Diabetes Mellitus Type I272.2Mixed Hyperlipidemia414.01CAD Native780.2-780.4Syncope and Collapse Dizziness and Giddiness780.79Other Malaise and Fatigue785.0-785.3Tachycardia Unspecified - Other Abnormal Heart Sounds786.50-786.51Unspecified Chest Pain Precordial786.59Other Chest Pain

Technology - nowSemantic Web: OWL, RDF/RDQL, JenaOWL (constraints useful for data consistency), RDFRules are expressed as RDQLREST Based Web Services: from server sideWeb 2.0: client makes AJAX calls to ontology, also auto complete Problem:Jena main memory- large memory footprint, future scalability challengeUsing Jenas persistent model (MySQL) noticeably slower

Design and Implementation IssuesSchema designPopulation (knowledge sources)FreshnessScalability though client side processingRules: Starting at instance A is it possible to get to instance B going through these certain relationships, if so what are the properties of the relationship (e.g., Does nitrates or a super class of nitrates interact with Viagra or one of its super classes, if so what is the interaction level )

Architecture & Technology

DemoOn-line demo of Active Semantic Electronic Medical Record

deployed and in use at Athens Heart Center

Evaluation and ROIGiven that this work was done in a live, operational environment, it is nearly impossible to evaluate this system in a clean room fashion, with completely controlled environment no doctors office has resources or inclination to subject to such an intrusive, controlled and multistage trial. Evaluation of an operational system also presents many complexities, such as perturbations due to change in medical personnel and associated training.

Athens Heart Center Practice Growth

Chart Completion before the preliminary deployment of the ASMER

Chart Completion after the preliminary deployment of the ASMER

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Benefits of current systemError prevention (drug interactions, allergy)Patient careinsuranceDecision Support (formulary, billing)Patient satisfactionReimbursementEfficiency/timeReal-time chart completionsemantic and automated linking with billing

Benefits of current systemBiggest benefit is that decisions are now in the hands of physicians not insurance companies or coders.

Technology - FutureBRAHMS (with SPARQL support and path computation*) for high performance main memory based computationSWRL for better rule representationSupport for example user specified rules, possibly for integration with clinical pathways:If patients blood pressure is > than 150/70 prescribe this medicine automatically. If patients weight is > 350 disallow a nuclear scan in the office because our scanning bed cannot handle such weight.If patient has diagnoses X alert, the user to suggest a doctor to refer patient to Y. * Semantic Discovery http://lsdis.cs.uga.edu/projects/semdis/

Value propositions & Next stepsIncreasing the value of content, and content in context highly customized using one of the ontologies (not just CTP/ICD9, but also specialty specific), at the point of use; no separate search, no wading through delivered contentActionable rulesPossible trial involving alert services: When a physician scrolls down on the list of drugs and clicks on the drug that he wants to prescribe, any study / clinical trial / news item about the drug and other related drugs in the same category will be displayed.

Comments on EvaluationQuestions?

More? See Active Semantic Document Project (http://lsdis.cs.uga.edu/projects/asdoc/) at the LSDIS lab

Or resources (example ontologies, Web services, tools, applications):Google: LSDIS resources, orhttp://lsdis.cs.uga.edu/library/resources/

Active Semantic Doc with 3 OntologiesAnnotate ICD9sAnnotate DoctorsLexical AnnotationLevel 3 Drug InteractionInsurance FormularyDrug Allergy

Explore neighborhood for drug Tasmar

Explore: Drug Tasmar

Explore neighborhood for drug Tasmar

belongs to groupbelongs to groupbrand / genericclassificationclassificationclassificationinteractionSemantic browsing and querying-- perform decision support (how many patients are using this class of drug, )

This ontology is was not designed with the idea of capturing a general practice domain but was designed to be a specific to the practice, reflecting there terms and internal data schemasMove this slideKnowledge base changes often freshness is thus hard, rx hub, Metion erarly Complete solution web base bc we want e a service model and easy intergration with others, novelSemantics dont slow you down, speeds you up, better product (fewer mistakes), patient load going up with clinical load going upProves efficancy wise is ok, allso adds validation of data, rules prevent errorsDiscisons make at right place, physcian not insuracne making diagnosisTop two complexes, external content revlivent to pt