A Prototype Knowledge Base and SMART App
to Facilitate Organization of Patient Medications by Clinical Problems
Allison B. McCoy, PhD1, Adam Wright, PhD2, Archana Laxmisan, MD, MA3,
Hardeep Singh, MD, MPH3, Dean F. Sittig, PhD1
1School of Biomedical Informatics, The University of Texas
Health Science Center at Houston (UTHealth), Houston, TX
2Brigham and Women’sHospital, Harvard Medical School, Boston, MA
3Houston VA Health Services Research and Development Center of Excellence,
Michael E. DeBakey Veterans Affairs Medical Center and Section of Health Services
Research, Department of Medicine, Baylor College of Medicine, Houston, TX
Abstract
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.
Introduction
In early electronic health record (EHR) and health information technology (HIT) adopter organizations, patients may
have over 10 years of clinical data covering all aspects of their care. These readily accessible, legible archives of
clinical notes, laboratory test results, radiographic images, and provider correspondence can inform clinical care (1),
but they also pose a challenge for time-pressured clinicians working in busy settings (2). As the number of clinicians
using EHRs and the number of health information exchanges (HIEs) capable of exchanging patient-level data
increases, the quantity of data those clinicians will need to review for safe and effective care increases exponentially
(3). In addition, clinicians must integrate these data with their existing knowledge and fast-changing external
scientific literature and guidelines, while still keeping in view the internal policies and procedures of their
institutions (4). HIT is likely to be critical to management of these data and information needs, and solutions will
require using explicit, unified, accurate, and comprehensive patient-centered models that reflect the true work
domain ontology (5). A preliminary step in creating such models is automated linking of a patient’s medications
with clinical indications, or problems. In this paper, we describe the generation of a clinical knowledge base and
development of a prototype SMART app to facilitate the organization of a patient’s medications according to their
clinical problems, which we believe is a better cognitive match for most tasks involving clinician review and
integration than an alphabetical or chronological view of medications.
Background
The Unified Medical Language System Metathesaurus
The Unified Medical Language System (UMLS) Metathesaurus (6), developed over the last 25 years by the United
States National Library of Medicine (NLM), is a large, integrated biomedical database of 158 source vocabularies
containing more than 2.3 million concepts, 8.5 million unique concept names, and over 12 million relationships
among concepts. The UMLS Metathesaurus is built from more than 100 source vocabularies, including RxNorm,
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A Prototype Knowledge Base and SMART App
to Facilitate Organization of Patient Medications by Clinical Problems
Allison B. McCoy, PhD1, Adam Wright, PhD2, Archana Laxmisan, MD, MA3,
Hardeep Singh, MD, MPH3, Dean F. Sittig, PhD1
1School of Biomedical Informatics, The University of Texas
Health Science Center at Houston (UTHealth), Houston, TX
2Brigham and Women’sHospital, Harvard Medical School, Boston, MA
3Houston VA Health Services Research and Development Center of Excellence,
Michael E. DeBakey Veterans Affairs Medical Center and Section of Health Services
Research, Department of Medicine, Baylor College of Medicine, Houston, TX
Abstract
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.
Introduction
In early electronic health record (EHR) and health information technology (HIT) adopter organizations, patients may
have over 10 years of clinical data covering all aspects of their care. These readily accessible, legible archives of
clinical notes, laboratory test results, radiographic images, and provider correspondence can inform clinical care (1),
but they also pose a challenge for time-pressured clinicians working in busy settings (2). As the number of clinicians
using EHRs and the number of health information exchanges (HIEs) capable of exchanging patient-level data
increases, the quantity of data those clinicians will need to review for safe and effective care increases exponentially
(3). In addition, clinicians must integrate these data with their existing knowledge and fast-changing external
scientific literature and guidelines, while still keeping in view the internal policies and procedures of their
institutions (4). HIT is likely to be critical to management of these data and information needs, and solutions will
require using explicit, unified, accurate, and comprehensive patient-centered models that reflect the true work
domain ontology (5). A preliminary step in creating such models is automated linking of a patient’s medications
with clinical indications, or problems. In this paper, we describe the generation of a clinical knowledge base and
development of a prototype SMART app to facilitate the organization of a patient’s medications according to their
clinical problems, which we believe is a better cognitive match for most tasks involving clinician review and
integration than an alphabetical or chronological view of medications.
Background
The Unified Medical Language System Metathesaurus
The Unified Medical Language System (UMLS) Metathesaurus (6), developed over the last 25 years by the United
States National Library of Medicine (NLM), is a large, integrated biomedical database of 158 source vocabularies
containing more than 2.3 million concepts, 8.5 million unique concept names, and over 12 million relationships
among concepts. The UMLS Metathesaurus is built from more than 100 source vocabularies, including RxNorm,
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