Health Concept and Knowledge Management: Twenty-five Years of Evolution.

OBJECTIVES: The fields of health terminology, classification, ontology, and related information models have evolved dramatically over the past 25 years. Our objective was to review notable trends, described emerging or enabling technologies, and highlight major terminology systems during the interval. METHODS: We review the progression in health terminology systems informed by our own experiences as part of the community involved in this work, reinforced with literature review and citation. RESULTS: The transformation in size, scope, complexity, and adoption of health terminological systems and information models has been tremendous, on the scale of orders of magnitude. CONCLUSION: The present "big science" era of inference and discovery in biomedicine would not have been possible or scalable absent the growth and maturation of health terminology systems and information models over the past 25 years.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE-PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of "precision medicine." The February 2015 eMERGE-PGx data release includes sequence-derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation-Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

A genome-wide association study identifies variants in KCNIP4 associated with ACE inhibitor-induced cough.

The most common side effect of angiotensin-converting enzyme inhibitor (ACEi) drugs is cough. We conducted a genome-wide association study (GWAS) of ACEi-induced cough among 7080 subjects of diverse ancestries in the Electronic Medical Records and Genomics (eMERGE) network. Cases were subjects diagnosed with ACEi-induced cough. Controls were subjects with at least 6 months of ACEi use and no cough. A GWAS (1595 cases and 5485 controls) identified associations on chromosome 4 in an intron of KCNIP4. The strongest association was at rs145489027 (minor allele frequency=0.33, odds ratio (OR)=1.3 (95% confidence interval (CI): 1.2-1.4), P=1.0 × 10(-8)). Replication for six single-nucleotide polymorphisms (SNPs) in KCNIP4 was tested in a second eMERGE population (n=926) and in the Genetics of Diabetes Audit and Research in Tayside, Scotland (GoDARTS) cohort (n=4309). Replication was observed at rs7675300 (OR=1.32 (1.01-1.70), P=0.04) in eMERGE and at rs16870989 and rs1495509 (OR=1.15 (1.01-1.30), P=0.03 for both) in GoDARTS. The combined association at rs1495509 was significant (OR=1.23 (1.15-1.32), P=1.9 × 10(-9)). These results indicate that SNPs in KCNIP4 may modulate ACEi-induced cough risk.

Harmonization of detailed clinical models with clinical study data standards.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". BACKGROUND: Data sharing and integration between the clinical research data management system and the electronic health record system remains a challenging issue. To approach the issue, there is emerging interest in utilizing the Detailed Clinical Model (DCM) approach across a variety of contexts. The Intermountain Healthcare Clinical Element Models (CEMs) have been adopted by the Office of the National Coordinator awarded Strategic Health IT Advanced Research Projects for normalization (SHARPn) project for normalizing patient data from the electronic health records (EHR). OBJECTIVE: The objective of the present study is to describe our preliminary efforts toward harmonization of the SHARPn CEMs with CDISC (Clinical Data Interchange Standards Consortium) clinical study data standards. METHODS: We were focused on three generic domains: demographics, lab tests, and medications. We performed a panel review on each data element extracted from the CDISC templates and SHARPn CEMs. RESULTS: We have identified a set of data elements that are common to the context of both clinical study and broad secondary use of EHR data and discussed outstanding harmonization issues. CONCLUSIONS: We consider that the outcomes would be useful for defining new requirements for the DCM modeling community and ultimately facilitating the semantic interoperability between systems for both clinical study and broad secondary use domains.

Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems.

We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1- to 3-year time frame across several clinical sites; (ii) to integrate well-established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to managing incidental findings, and patient and clinician education methods.

Effectiveness of lexico-syntactic pattern matching for ontology enrichment with clinical documents.

OBJECTIVE: To evaluate the effectiveness of a lexico-syntactic pattern (LSP) matching method for ontology enrichment using clinical documents. METHODS: Two domains were separately studied using the same methodology. We used radiology documents to enrich RadLex and pathology documents to enrich National Cancer Institute Thesaurus (NCIT). Several known LSPs were used for semantic knowledge extraction. We first retrieved all sentences that contained LSPs across two large clinical repositories, and examined the frequency of the LSPs. From this set, we randomly sampled LSP instances which were examined by human judges. We used a two-step method to determine the utility of these patterns for enrichment. In the first step, domain experts annotated medically meaningful terms (MMTs) from each sentence within the LSP. In the second step, RadLex and NCIT curators evaluated how many of these MMTs could be added to the resource. To quantify the utility of this LSP method, we defined two evaluation metrics: suggestion rate (SR) and acceptance rate (AR). We used these measures to estimate the yield of concepts and relationships, for each of the two domains. RESULTS: For NCIT, the concept SR was 24%, and the relationship SR was 65%. The concept AR was 21%, and the relationship AR was 14%. For RadLex, the concept SR was 37%, and the relationship SR was 55%. The concept AR was 11%, and the relationship AR was 44%. CONCLUSION: The LSP matching method is an effective method for concept and concept relationship discovery in biomedical domains.

Distributed biomedical terminology development: from experiments to open process.

OBJECTIVE: Can social computing efforts materially alter the distributed creation and maintenance of complex biomedical terminologies and ontologies; a review of distributed authoring history and status. BACKGROUND: Social computing projects, such as Wikipedia, have dramatically altered the perception and reality of large-scale content projects and the labor required to create and maintain them. Health terminologies have become large, complex, interdependent content artifacts of increasing importance to biomedical research and the communities understanding of biology, medicine, and optimal healthcare practices. The question naturally arises as to whether social computing models and distributed authoring platforms can be applied to the voluntary, distributed authoring of high-quality terminologies and ontologies. METHODS: An historical review of distributed authoring developments. RESULTS: The trajectory of description logic-driven authoring tools, group process, and web-based platforms suggests that public distributed authoring is likely feasible and practical; however, no compelling example on the order of Wikipedia is yet extant. Nevertheless, several projects, including the Gene Ontology and the new revision of the International Classification of Disease (ICD-11) hold promise.

Designing and testing computer based screening engine for severe sepsis/septic shock.

This study addresses the role of a sepsis "sniffer", an automatic screening tool for the timely identification of patients with severe sepsis/septic shock, based electronic medical records. During the two months prospective implementation in a medical intensive care unit, 37 of 320 consecutive patients developed severe sepsis/septic shock. The sniffer demonstrated a sensitivity of 48% and specificity of 86%, and positive predictive value 32%. Further improvements are needed prior to the implementation of sepsis sniffer in clinical practice and research.

Rule base system for identification of patients with specific critical care syndromes: The "sniffer" for acute lung injury.

Early detection of specific critical care syndromes, such as sepsis or acute lung injury (ALI)is essential for timely implementation of evidence based therapies. Using a near-real time copy of the electronic medical records ("ICU data mart") we developed and validated custom electronic alert (ALI"sniffer") in a cohort of 485 critically ill medical patients. Compared with the gold standard of prospective screening, ALI "sniffer" demonstrated good sensitivity, 93% (95% CI 90 to 95) and specificity, 90% (95% CI 87 to 92). It is not known if the bedside implementation of ALI "sniffer" will improve the adherence to evidence-based therapies and outcome of patients with ALI.

Frame semantics and the domain of functioning, disability and health.

We explore the use of FrameNet (FN) frames and their frame elements to represent content from the International Classification of Functioning, Disability and Health (ICF) Self-Care chapter. Terms were extracted from the ICF and mapped to FN frames. The mappings were validated by an expert. FN provided relevant and nearly complete coverage of ICF terms, suggesting FN may be an important resource to leverage for semantic language processing and knowledge representation in this domain.

Human cytosolic sulfotransferase database mining: identification of seven novel genes and pseudogenes.

A total of 10 SULT genes are presently known to be expressed in human tissues. We performed a comprehensive genome-wide search for novel SULT genes using two different but complementary approaches, and developed a novel graphical display to aid in the annotation of the hits. Seven novel human SULT genes were identified, five of which were predicted to be pseudogenes, including two processed pseudogenes and three pseudogenes that contained introns. Those five pseudogenes represent the first unambiguous SULT pseudogenes described in any species. Expression-profiling studies were conducted for one novel gene, SULT6B1, and a series of alternatively spliced transcripts were identified in the human testis. SULT6B1 was also present in chimpanzee and gorilla, differing at only seven encoded amino-acid residues among the three species. The results of these database mining studies will aid in studies of the regulation of these SULT genes, provide insights into the evolution of this gene family in humans, and serve as a starting point for comparative genomic studies of SULT genes.

Integrating pharmacokinetics knowledge into a drug ontology: as an extension to support pharmacogenomics.

The newly developed U.S. Common Medication Information Infrastructure was used as a basis to capture and formally express the properties of drugs relevant to research and the clinical application of pharmacogenomics. Two associated taxonomies within the model, Mechanism of Action and Physiologic Effect, were enriched to accommodate pharmacogenomic use-cases; the 4,000 active ingredients in the VA NDF-RT drug file were related to the enhanced taxonomies. Pharmacokinetics were independently modeled for pharmacogenomics and tested against thirty-one high-profile drugs to demonstrate our approach.

Guideline for health informatics: controlled health vocabularies--vocabulary structure and high-level indicators.

Developers and purchasers of controlled health terminologies require valid mechanisms for comparing terminological systems. By Controlled Health Vocabularies we refer to terminologies and terminological systems designed to represent clinical data at a granularity consistent with the practice of today's healthcare delivery. Comprehensive criterion for the evaluation of such systems are lacking and the known criteria are inconsistently applied. Although there are many papers, which describe specific desirable features of a controlled health vocabulary, to date there is not a consistent guide for evaluators of terminologies to reference, which will help them compare implementations of terminological systems on an equal footing 1,2 This guideline serves to fill the gap between academic enumeration of desirable terminological characteristics and the practical implementation or rigorous evaluations which will yield comparable data regarding the quality of one or more controlled health vocabularies.

Expression of a domain ontology model in unified modeling language for the World Health Organization International classification of impairment, disability, and handicap, version 2.

The International Classification of Impairment, Disability, and Handicap Version 2(ICIDH-2), an anticipated addition to the World Health Organization suite of terminologies, has been put forth as a means for standardized representation of generic health and/or functional status data. In an attempt to make explicit the ontology upon which ICIDH-2 is based the authors derived a concept model expressed as a Unified Modeling Language static class diagram through abstraction of concept-terms in the documentation provided with the Full Version Pre-Final Draft of ICIDH-2 (December 2000). ICIDH-2's semantic structure is analyzed and evaluated for its semantic consistency. Discussion is presented on the utility of domain ontology models in terminology development and potential roles ICIDH-2 might play, as it undergoes refinement towards a representational standard. It is intended that the proposed UML rendering will stimulate domain discourse and consensus that will lead to enhancement of conceptual clarity in the ICIDH-2 ontological hierarchy and further enable its study and development as a healthcare classification.

A randomized controlled trial of concept based indexing of Web page content.

OBJECTIVE: Medical information is increasingly being presented in a web-enabled format. Medical journals, guidelines, and textbooks are all accessible in a web-based format. It would be desirable to link these reference sources to the electronic medical record to provide education, to facilitate guideline implementation and usage and for decision support. In order for these rich information sources to be accessed via the medical record they will need to be indexed by a single comparable underlying reference terminology. METHODS: We took a random sample of 100 web pages out of the 6,000 web pages on the Mayo Clinic's Health Oasis web site. The web pages were divided into four datasets each containing 25 pages. These were humanly reviewed by four clinicians to identify all of the health concepts present (R1DA, R2DB, R3DC, R4DD). The web pages were simultaneously indexed using the SNOMED-RT beta release. The indexing engine has been previously described and validated. A new clinician reviewed the indexed web pages to determine the accuracy of the automated mappings as compared with the human identified concepts (R4DA, R3DB, R2DC, R1DD). RESULTS: This review found 13,220 health concepts. Of these 10,383 concepts were identified by the initial human review (78.5% +/- 3.6%). The automated process identified 10,083 concepts correctly (76.3% +/- 4.0%) from within this corpus. The computer identified 2,420 concepts, which were not identified by the clinician's review but were upon further consideration important to include as health concepts. There was on average a 17.1% +/- 3.5% variability in the human reviewers ability to identify the important health concepts within web page content. Concept Based Indexing provided a positive predictive value (PPV) of finding a health concept of 79.3% as compared with keyword indexing which only has a PPV of 33.7% (p < 0.001). CONCLUSION: SNOMED-RT is a reasonable ontology for web page indexing. Concept based indexing provides a significantly greater accuracy in identifying health concepts when compared with keyword indexing.

The content coverage and organizational structure of terminologies: the example of postoperative pain.

Concepts such as symptoms present specific representational challenges in the EMR. This is because concepts without clear boundaries and external referents such as physical objects can only be examined against other terminology-based concept representation systems. The truth and falsity of such concept representation is therefore relative to the terminology-based systems. Using the concept of acute postoperative pain as an example, we examined three terminology based approaches to representing the concept. Widely varying coverage across existing clinical terminologies was evident, although the common clinical approach to reporting attributes of symptoms provided a useful organizational structure and should be examined in relation to developing terminology and information models.

Representation by standard terminologies of health status concepts contained in two health status assessment instruments used in rheumatic disease management.

Health and functional status data have been shown to have clinical utility in predicting outcome. Various metadata registries in the form of patient self-administered health assessment questionnaires have been incorporated into routine clinical care and clinical research of patients with rheumatic disease. Examples of such health assessment instruments are the Clinical Health Assessment Questionnaire (CLINHAQ) and the Modified Health Assessment Questionnaire (MHAQ). These instruments contain concepts that are an integral part of the health and functional status domain. Using an automated indexing tool we examined the clinical content coverage by SNOMED RT and the Unified Medical Language System (UMLS) Metathesaurus for health and functional status concepts identified in the MHAQ and CLINHAQ. Significant differences existed between the overall representational ability of SNOMED and UMLS for concepts identified in the MHAQ (49%, vs. 77% respectively, p < .005) and for concepts identified in the CLINHAQ (30% vs. 64% respectively p < .005). Representational capability by SNOMED-RT and UMLS for concepts in a given health assessment instrument was carried across four semantic classes of "attitudes", "symptoms", "activities", and "social attributes". The conceptual content coverage of health status assessment concepts contained in the MHAQ and CLINHAQ by SNOMED-RT and UMLS was incomplete but better for UMLS with its panoply of vocabulary sources. This observed overall improved representation by UMLS appeared to be due to better representation of concepts in "activities" and "social attributes" semantic classes. Representation of health or functional status concepts in a computerized medical record should be founded on a universally agreed concept model of that domain. Established functional and health status metadata registries can serve as important sources for concepts and candidate classes within that domain.

A formal approach to integrating synonyms with a reference terminology.

Medical terminologies continue to grow in scope, completeness and detail. The emerging generation of terminology systems define concepts in terms of their position within a categorical structure. It is still necessary, however, to access and represent the concepts using everyday spoken and written language, which introduces both lexical and semantic ambiguity. This ambiguity can have a negative impact on both selectivity and recall when it comes to associating free-form textual phrases with their coded equivalent. Lexical ambiguity issues can often be addressed algorithmically, but semantic ambiguity presents a more difficult problem. A common solution to the semantic problem is to associate many different representational permutations with a given target concept. This approach has several drawbacks. An alternate solution is to build separate synonym tables that can serve as permuted indices into the terms representing the underlying concepts. A potential shortcoming of this approach, however, is a further reduction in the lookup selectivity. One possible source of loss of selectivity could be "meaning drift"--the gradual change in meaning that can be introduced when following a chain of nearly synonymous words. We posited that organizing synonyms into separate "meaning clusters" might reduce this loss in precision, but the results of this study did not bear that out.