Increasing use of electronic health records requires comprehensive patient-centered views of clinical data. We describe a prototype knowledge base and SMART app that facilitates organization of patient medications by clinical problems, comprising a preliminary step in building such patient-centered views. The knowledge base includes 7,164,444 distinct problem-medication links, generated from RxNorm, SNOMED CT, and NDF-RT within the UMLS Metathesaurus. In an evaluation of the knowledge base applied to 5000 de-identified patient records, 22.4% of medications linked to an entry in the patient’s active problem list, compared to 32.6% of medications manually linked by providers; 46.5% of total links were unique to the knowledge base, not added by providers. Expert review of a random patient subset estimated a sensitivity of 37.1% and specificity of 98.9%. The SMART API successfully utilized the knowledge base to generate problem-medication links for test patients. Future work is necessary to improve knowledge base sensitivity and efficiency.

1. A Prototype Knowledge Base and
SMART App to Facilitate
Organization of Patient
Medications by Clinical Problems
Allison B. McCoy, PhD
Adam Wright, PhD, Archana Laxmisan, MD, MA
Hardeep Singh, MD, MPH, Dean F. Sittig, PhD

2. Summarization Aims
• Develop methodologies that:
– Model and summarize complex, chronically-ill
patients’ EHR data
– Enhance decision making with context-
appropriate, evidence-based
recommendations
• To improve clinician decision-making
under information overload and time
pressure
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3. Research Focus
• Develop a knowledge base for linking
medications and problems
• Evaluate the knowledge base with real
patient data
• Implement a prototype app that utilizes the
knowledge base to summarize patient
data
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4. Ontology-Based Summarization
• The Unified Medical Language System
Metathesaurus (UMLS)
– RxNorm, SNOMED CT, NDF-RT
NDF-RT “may_treat” NDF-RT SNOMED CT
RxNorm CUI
Preparation Disease Concept
“isa”
SNOMED CT
Concept
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5. Ontology-Based Summarization
• Generated over 7 million problem–
medication links
RxCUI Medication SNOMED Code Problem
198211 SIMVASTATIN 40 MG Oral (systemic) tablet 13644009 Hypercholesterolaemia
198211 SIMVASTATIN 40 MG Oral (systemic) tablet 302870006 Hypertriglyceridaemia
198211 SIMVASTATIN 40 MG Oral (systemic) tablet 3744001 Hyperlipoproteinaemia
198211 SIMVASTATIN 40 MG Oral (systemic) tablet 129589009 Endogenous hyperlipaemia
… … … …
200345 SIMVASTATIN 80 MG Oral (systemic) tablet 13644009 Hypercholesterolaemia
200345 SIMVASTATIN 80 MG Oral (systemic) tablet 302870006 Hypertriglyceridaemia
200345 SIMVASTATIN 80 MG Oral (systemic) tablet 3744001 Hyperlipoproteinaemia
200345 SIMVASTATIN 80 MG Oral (systemic) tablet 129589009 Endogenous hyperlipaemia
… … … …
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6. Evaluation Setting
• Large, multi-specialty ambulatory
academic practice for adults, adolescents
and children
• Electronic health record utilization
• Manual links enabled between a
medication and a diagnosis within the
patient’s clinical problem list
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7. Evaluation Population
• 5000 randomly selected patients
• At least one outpatient encounter during
July 1, 2010-December 31, 2010
– At least one active, coded clinical problem
and medication
– Included only problems and medications
mapped to SNOMED CT and RxNorm
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8. Knowledge Base Utility
• Knowledge base linked 5,251 medications
to problems
– 10,738 total links with manual provider links
– 4,763 medications not previously linked by
providers (47% of total links)
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9. Knowledge Base Accuracy
• Expert review of 25 patients with ≥ 3
problems and ≥ 5 medications
• 82.1% positive predictive value
– Ex. Linking Prednisone 20 MG Tablet to
Hypertrophic Scar – false due to wrong route
• 37.1% sensitivity
– Ex. Difference in precision of medication and problem
entries in EHR compared to KB
– Ex. Relationships within UMLS are incomplete
– Ex. Incomplete medication and problem mappings in
EHR to standards
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10. SMART Architecture
• Substitutable Medical Apps, Reusable
Technologies
• Allows “iPhone-like” substitutability for
medical apps
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11. SMART App Development
• SMART Javascript Library
• Developed and tested in the SMART
Reference EMR
– 50 test patients
– Medications mapped to RxNorm
– Problems mapped to SNOMED CT
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12. SMART App Demonstration
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16. Future Directions
• Expand knowledge base to include medications
with “isa” relationship
• Improve local mapping to standardized
terminologies
• Compare accuracy with knowledge bases
developed using data mining and other methods
• Expand knowledge base to include other data
types (e.g., lab values)
• Implement knowledge base into live EHR
• Evaluate use of summarization and knowledge
base on clinical practice
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17. Summary
• Ontology-based summarization knowledge
base can assist problem-medication
linking
• SMART app effectively utilizes knowledge
base to display problem-oriented
medication list
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18. Acknowledgments
• Funding
– National Center for Cognitive Informatics and Decision
Making in Healthcare SHARP Program Award
(Grant No. 10510949)
– Houston VA HSR&D Center of Excellence (HFP90-020)
– NCRR Grant (3UL1RR024148)
– UT Houston-Memorial Hermann Center for Healthcare
Quality and Safety
• Collaborators
– SHARP-C Project 3 Members
– UTHealth CDW Team
– UTHealth SBMI IT Support
– SMART Team
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19. Thank You
Email: allison.b.mccoy@uth.tmc.edu
Twitter: allisonbmccoy
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