1、From the Bench All the Way to Bedside Clinical Decision Support: The Role of Semantic Technologies in a Knowledge Management Infrastructure for Translational Medicine,Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management and Decision Support Clinical Informatics R&D Partners H
2、ealthcare System,Current State of Translational Medicine,17 year innovation adoption curve from discovery into accepted standards of practice Even if a standard is accepted, patients have a 50:50 chance of receiving appropriate care, a 5-10% probability of incurring a preventable, anticipatable adve
3、rse event The market is balking at healthcare inflation, new diagnostics and therapeutics will find increasing resistance for reimbursement,The Volume and Velocity of Knowledge Processing Required for Care Delivery,Medical literature doubling every 19 years Doubles every 22 months for AIDS care 2 Mi
4、llion facts needed to practice Genomics, Personalized Medicine will increase the problem exponentially Typical drug order today with decision support accounts for, at best, Age, Weight, Height, Labs, Other Active Meds, Allergies, Diagnoses Today, there are 3000+ molecular diagnostic tests on the mar
5、ket, typical HIT systems cannot support complex, multi-hierarchical chaining clinical decision support,Covell DG, Uman GC, Manning PR. Ann Intern Med. 1985 Oct;103(4):596-9,Todays Health IS Vendor Knowledge Management Capabilities:,Knowledge “hardwired” or structured in proprietary modes into applic
6、ations, not easily updated or shared Little or no standardization of HIT vendors on SNOMED, no shared interface terminologies for observation capture, no standard order catalogues Most EMRs have a task-interfering approach to decision support, sub-optimal usability Knowledge-engineering tools typica
7、lly edit into transaction, no support for provenance, versioning, life-cycle, propagation, discovery or maintenance Consequently, clinical systems implementations are under-resourced with adequate knowledge to meet current workflow and quality needs Labor of converting knowledge into Clinical Decisi
8、on Support is vastly underestimated Doesnt bode well for personalized medicine,Knowledge Management and Decision Support Intersection Points in Translational Medicine,Patient Encounter (direct care or clinical trial),Diagnostic Test ordering and documentation guidance,Therapeutic Intervention Orderi
9、ng and documentation guidance,Integrated Genotypic Phenotypic Databases,Personalized Medicine Decision Support Knowledge Repository,Tissue-bank,Clinical Trials Referral,Knowledge Discovery, Acquisition & Management,Structured Research Annotations,Bench R&D,Clinical Trials 1- 4,Pharmacovigilance,Stru
10、ctured Test Result Interpretations,Composite Decision Support Application: Diabetes Management,Guided Data Interpretation,Guided Observation Capture,Guided Ordering,What healthcare needs from Semantic Web Technologies,Reduce the cost, duration, risk of drug discovery Data integration, Knowledge inte
11、gration, Visualization Knowledge representation New Knowledge Discovery Reduce the cost/duration/risk of clinical trial management Patient identification and referral Trial design (ie to capture better safety surveillance) Data quality and clinical outcomes measurement Post-market surveillance Reduc
12、e the cost/duration/liability of knowledge acquisition and maintenance for clinical decision support and clinical performance measurement Knowledge provenance and representation Conversion of “discovery algorithms” into “clinical practice algorithms” Event-driven change management and propagation of
13、 change,KM for Translational Medicine: Functional/Business Architecture,PORTALS,R&D,CLINICAL TRIALS,DIAGNOSTIC Svs LABs,CLINICAL CARE,LIMS,EHR,ASSAYS ANNOTATIONS,DIAGNOSTIC TEST RESULTS ASSAY INTERPRETATIONS,ORDERS AND OBSERVATIONS,Genotypic,Phenotypic,Data Domains,Knowledge Domains,Logic/Policy Dom
14、ains,DATA REPOSITORIES AND SERVICES,KNOWLEDGE ACQUISITION AND DISCOVERY SERVICES,NCI Metathesaurus, UMLS, SNOMED CT, DxPlain, ETCother Knowledge Sources,Data Analysts and Collaborative Knowledge Engineers,Semantic Inferencing And Agent-based Discovery Services,KNOWLEDGE and WORKFLOW DELIVERY SERVICE
15、S FOR ALL PORTAL ROLES,Decision Support Services,Knowledge Asset Management and Repository Services,Collaboration Support Services,Workflow Support Services,State Management Services,APPLICATIONS,Meta- Knowledge,INFERENCING AND VOCABULARY ENGINES,Example: Diabetes,Epidemic, associated with obesity Q
16、uality measures drive reimbursement of hospitals and physicians Maintain HbA1c 7 (diet, oral agents and/or insulin) If Renal Disease and no contraindication, should be on ACE inhibitor or ARB If lipid disorder and no contraindication, should be on a Statin National problem of non-compliance with the
17、se standards of care compromised patient longevity, quality of life, ability to maintain employment CMS and employer financial risk,Renal disease = Chronic Renal Failure Nephropathy, chronic renal failure, end-stage renal disease, renal insufficiency, hemodialysis, peritoneal dialysis on Problem Lis
18、t (SNOMED) Creatinine 2 Calculated GFR 30 Diabetes Many variants on the problem list On Insulin or oral hypoglycemic drugContraindication to ACE inhibitor Allergy, Cough on ACE on adverse reaction list, or Hyperkalemia on problem list, Pregnant (20 sub rules to define this state) K test result 5,Ima
19、gine this CDS Rule: If Renal Disease and DM and no contraindication, should be on ACE inhibitor or ARB,Composite Decision Support Application: Diabetes Management,Guided Data Interpretation,Guided Observation Capture,Guided Ordering,The Maintenance and Propagation Challenge,These “complex” definitio
20、ns must be identical in rules (if that is how “recognition” is handled), documentation templates for structured data capture, and in reporting systems that drive payor reimbursement The rate of change for contraindication definition today is slow, yet clinical decision support systems are not keepin
21、g up When molecular diagnostics take off, this rate of change could be “daily” or “hourly” Further, when a patient has a molecular diagnostic test result in the EMR that is currently of “unknown significance” and later, with new knowledge, the interpretation of the former result is “contraindication
22、” to a drug, then this “interpretation” must be updated to ensure proper CDS functioning,Role of Semantic Technologies,Data/Knowledge Integration and Visualization Ontology based approaches Integration across multiple data sources: Genotypic/Phenotypic data from LIMS/HER Knowledge Repositories for d
23、ata interpretation Clinical Decision Support Inference engines - SWRL Description logics for “recognition” - OWL Knowledge representation Etc. Knowledge Acquisition, Maintenance and Evolution Ontology-based Definitions Management Versioning, life-cycle, propagation into “dependent” objects such as r
24、ules, templates orders/documentation, reporting systems Knowledge Provenance Reconciling knowledge representation among different stakeholders (care givers, payors, performance measurement, clinical trials, R&D),Market Drivers Will Make Semantic Web Technologies an Imperative for Translational Medic
25、ine,Genomics: personalized medicine will require decision support architectures that can proactively support complex decision making answering 1,000,000 of questions before run-time These systems will require self-adaptive, machine learning modes of knowledge acquisition, purely human dependent knowledge acquisition will not scale Pharma will need cooperative relationships with HIT vendors to make speed the translational medicine life-cycle,
