Biomedical subjects

C G Chute

Publications and source records attributed to C G Chute.

At least 19 recordsLinked to original sources

PubMed2001

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.

Medical Informatics↗

PubMed2001

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.

Persons with Disabilities↗

PubMed2000

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.

Abstracting and Indexing↗

PubMed2000

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.

Humans↗

PubMed2000

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.

Health Status↗

PubMed2000

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.

Abstracting and Indexing↗

PubMed1999

Incremental costs of enrolling cancer patients in clinical trials: a population-based study.

BACKGROUND: Payment for care provided as part of clinical research has become less predictable as a result of managed care. Because little is known at present about how entry into cancer trials affects the cost of care for cancer patients, we conducted a matched case-control comparison of the incremental medical costs attributable to participation in cancer treatment trials. METHODS: Case patients were residents of Olmsted County, MN, who entered phase II or phase III cancer treatment trials at the Mayo Clinic from 1988 through 1994. Control patients were patients who did not enter trials but who were eligible on the basis of tumor registry matching and medical record review. Sixty-one matched pairs were followed for up to 5 years after the date of trial entry for case patients or from an equivalent date for control patients. Hospital, physician, and ancillary service costs were estimated from a population-based cost database developed at the Mayo Clinic. RESULTS: Trial enrollees incurred modestly (no more than 10%) higher costs over various follow-up periods. The mean cumulative 5-year cost in 1995 inflation-adjusted U.S. dollars among trial enrollees after adjustment for censoring was $46424 compared with $44 133 for control patients. After 1 year, trial enrollee costs were $24645 compared with $23 964 for control patients. CONCLUSIONS: This study suggests that cancer chemotherapy trials may not imply budget-breaking costs. Cancer itself is a high-cost illness. Clinical protocols may add relatively little to that cost.

Cancer Care Facilities↗

PubMed1999

Desiderata for a clinical terminology server.

Clinical terminology servers are distinguished from more broadly based terminology servers intended for nomenclature development or mediation across classifications. Focusing upon the consistent and comparable entry of clinical observations, findings, and events, key desiderata are enumerated and expanded. These include 1) word normalization, 2) word completion, 3) target terminology specification, 4) spelling correction, 5) lexical matching, 6) term completion, 7) semantic locality, 8) term composition and 9) decomposition. Comparisons of this functionality to previously published models and specifications are made. Experience with a clinical terminology server, Metaphrase, is described.

Abstracting and Indexing↗

PubMed1999

Detailed content and terminological properties of DSM-IV.

DSM-IV, the Diagnostic and Statistical Manual of Mental Disorders, is the internationally accepted standard for nomenclature and diagnosis in psychiatric practice. The objective of this project is to parse the rubric criteria of the DSM to extract the clinically detailed signs, symptoms, findings, and conditions that are present. These are a "latent terminology" implicit within the DSM, which is highly granular and clinically specific. This manuscript describes the content of these terms that heretofore existed sub rosa, though we recognize that during the authorship of the DSM such terms were constructed deliberately and systematically. Relevant characteristics of the classification system are briefly reviewed. Summary results of parsing the defining criteria for the 400 ICD-9 Codes enumerated in DSM-IV are presented.

Humans↗

PubMed1999

A randomized double-blind controlled trial of automated term dissection.

OBJECTIVE: To compare the accuracy of an automated mechanism for term dissection to represent the semantic dependencies within a compositional expression, with the accuracy of a practicing Internist to perform this same task. We also compare the results of four evaluators to determine the inter-observer variability and the variance between term sets, with respect to the accuracy of the mappings and the consistency of the failure analysis. METHODS: 500 terms, which required a compositional expression to effect an exact match, were randomly distributed into two sets of 250 terms (Set A and Set B). Set A was dissected using the Automated Term Dissection (ATD) Algorithm. A physician specializing in Internal Medicine dissected set B. He had no prior knowledge of the dissection algorithm or how it functioned. In this manuscript, the authors use Human Term Dissection (HTD) to refer to this method. Set A was randomized to two sets of 125 terms (Set A1 and Set A2). Set B was randomized to two sets of 125 terms (Set B1 and Set B2). A new set of 250 terms Set C was created from Set A1 and Set B2. A second new set of 250 terms Set D was created from Set A2 and Set B1. Two expert Indexers reviewed Set C and another two expert Indexers reviewed Set D. They were blinded to which terms were dissected by the clinician and which terms were dissected by the automated term dissection algorithm. The person providing the files for review to the Indexers was also unaware of which terms were dissected by ATD vs. the HTD method. The Indexers recorded whether or not the dissection was the best possible representation of the input concept. If not, a failure analysis was conducted. They recorded whether or not the dissection was in error and if so was a modifier not subsumed or was a Kernel concept subsumed when it should not have been. If a concept was missing, the Indexers recorded whether it was a Kernel concept, a modifier, a qualifier or a negative qualifier. RESULTS: The ATD method was judged to be accurate and readable in 265 out of the 424 terms with adequate content (62.7%). The HTD method was judged to be accurate in 272 out of 414 terms with adequate content (65.7%). There was no statistically significant difference between the rates of acceptability of the ATD and HTD methods (p = 0.33). There was a non-significant trend toward greater acceptability of the ATD method in the subgroup of terms with three or more compositional elements. ATD was acceptable in 53.6% of the terms where the HTD was only acceptable in 43.6% (p = 0.11). The failure analysis showed that both methods misrepresented kernel concepts and modifiers much more commonly than qualifiers (p < 0.001). CONCLUSIONS: There is no statistically significant difference in the accuracy and readability of terms dissected using the automated term dissection method when compared with human term dissection, as judged by four expert medical indexers. There is a non-significant trend toward improved performance of the ATD method in the subset of more complex terms. The authors submit that this may be due to a tendency for users to be less compulsive when the time to complete the task is long. Automated term dissection is a useful and perhaps preferable method for representing readable and accurate compound terminological expressions.

Abstracting and Indexing↗

PubMed1999

Barriers to the clinical implementation of compositionality.

BACKGROUND: Compositional mechanisms for the entry of clinically relevant controlled vocabularies have been suggested as a possible solution to providing adequate descriptive precision while keeping term vocabulary redundancy under control. As of yet, there are no widely accepted term navigators that allow physicians to enter problem lists utilizing controlled vocabularies with compositionality. METHODS: We report on the results of a usability trial of 5 physicians using our most recent attempt at developing the Mayo Problem List Manager. We tested the implementation of an automated term composition, and hierarchical term dissection. RESULTS: Participants found acceptable terms 96% of the time and found automated term composition helpful in 85% of the case scenarios. There was significant confusion about the terminology used to describe compositional elements (kernel concepts, modifiers, and qualifiers) however participants used the functions appropriately. Speed of entry was universally stated as the limiting factor. CONCLUSIONS: The variety of methods that our participants used to enter terms highlights the need for multiple ways to accomplish the task of data entry. Successful implementation of user directed compositionality could be accomplished with further improvement of the user interface and the underlying terminology.

Humans↗

PubMed1999

A large-scale evaluation of terminology integration characteristics.

OBJECTIVE: To describe terminology integration characteristics of local specialty specific and general vocabularies in order to facilitate the appropriate inclusion and mapping of these terms into a large-scale terminology. METHODS: We compared the sensitivity, specificity, positive predictive value, and positive likelihood ratios for Automated Term Composition to correctly map 9050 local specialty specific (dermatology) terms and 4994 local general terms to UMLS using Metaphrase. Results were systematically combined among exact matches, semantic type filtered matches, and non-filtered matches. For the general set, an analysis of semantic type filtering was performed. RESULTS: Dermatology exact matches defined a sensitivity of 51% (57% for general terms) and a specificity of 86% (92% general terms). Including semantic type filtered matches increased sensitivity (75% dermatology; 88% general); as did inclusion of non-filtered matches (98% and 99%). These inclusions correspondingly decreased specificity (filtered: 82% and 74%; non-filtered: 52% and 32%). Positive predictive values for exact matches (93.0% dermatology, 97.6% general) were improved by small but significant (p < 0.001) margins by including filtered matches (95.1% dermatology, 98.4% general) but decreased with non-filtered matches (89.2% dermatology, 87.8% general). Adding additional semantic types to the filtering algorithm failed to improve the positive predictive value or the positive likelihood ratio of term mapping, in spite of a 2.3% improvement in sensitivity. CONCLUSIONS: Automated methods for mapping local "colloquial" terminologies to large-scale controlled health vocabulary systems are practical (ppv 95% dermatology, 98% general). Semantic type filtering improves specificity without sacrificing sensitivity and yields high positive predictive values in every set analyzed.

Algorithms↗

PubMed1998

The role of compositionality in standardized problem list generation.

Compositionality is the ability of a Vocabulary System to record non-atomic strings. In this manuscript we define the types of composition, which can occur. We will then propose methods for both server based and client-based composition. We will differentiate the terms Pre-Coordination, Post-Coordination, and User-Directed Coordination. A simple grammar for the recording of terms with concept level identification will be presented, with examples from the Unified Medical Language System's (UMLS) Metathesaurus. We present an implementation of a Window's NT based client application and a remote Internet Based Vocabulary Server, which makes use of this method of compositionality. Finally we will suggest a research agenda which we believe is necessary to move forward toward a more complete understanding of compositionality. This work has the promise of paving the way toward a robust and complete Problem List Entry Tool.

Humans↗

PubMed1998

Secular changes in radical prostatectomy utilization rates in Olmsted County, Minnesota 1980 to 1995.

PURPOSE: We estimated the changes in utilization of radical prostatectomy for treatment of prostate cancer and describe the clinical characteristics of men undergoing radical prostatectomy in a population based setting. MATERIALS AND METHODS: The Rochester Epidemiology Project was used to identify all Olmsted County residents who underwent radical prostatectomy from 1980 to 1995. The community medical records of these men were reviewed to determine the clinical and pathological stage and grade at biopsy and following surgery. RESULTS: From 1980 to 1995, 311 radical prostatectomies were performed on Olmsted County men. From 1980 to 1987 prostatectomy rates ranged from 6.3 to 31.0/100,000 men but rates increased dramatically to 53.6/100,000 in 1988 and 106.2/100,000 in 1992. The rate after 1992 decreased to 53.0/100,000 and then increased slightly to 80.4/100,000. There was a shift to younger age in more recent times (mean patient age 65.4 years in 1980 to 1986 and 62.4 in 1993 to 1995, p = 0.02), a nonsignificant (p = 0.10) trend toward lower pathological stage in recent years (42% stage pT2 in 1980 to 1986 versus 55% in 1993 to 1995) and a significant decrease in the proportion of cases of disease up staged following surgery (53% in 1980 to 1986 versus 37% in 1993 to 1995, p = 0.03). There was no significant trend in pathological grade with time (63% Mayo grade I or II in 1980 to 1986 versus 52% in 1993 to 1995, p = 0.30). CONCLUSIONS: These findings demonstrate an increase in radical prostatectomy rates that coincided with increases in prostate cancer incidence. There was a decrease in population prostatectomy rates in 1993 which was followed by modest increases to levels lower than the peak in 1992. However, the clinical characteristics of patients during this period did not change dramatically, suggesting that in a population based setting the selection factors for patients undergoing surgical treatment may not have changed.

Adult↗

PubMed1998

Metaphrase: an aid to the clinical conceptualization and formalization of patient problems in healthcare enterprises.

Patient descriptors, or "problems," such as "brain metastases of melanoma" are an effective way for caregivers to describe patients. But most problems, e.g., "cubital tunnel syndrome" or "ulnar nerve compression," found in problem lists in an Electronic Medical Record (EMR) are not comparable computationally--in general, a computer cannot determine whether they describe the same or a related problem, or whether the user would have preferred "ulnar nerve compression syndrome." Metaphrase is a scalable, middleware component designed to be accessed from problem-manager applications in EMR systems. In response to caregivers' informal descriptors it suggests potentially equivalent, authoritative, and more formally comparable descriptors. Metaphrase contains a clinical subset of the 1997 UMLS Metathesaurus and some 10,000 "problems" from the Mayo Clinic and Harvard Beth Israel Hospital. Word and term completion, spelling correction, and semantic navigation, all combine to ease the burden of problem conceptualization, entry and formalization.

Humans↗

PubMed1998

Scalable methodologies for distributed development of logic-based convergent medical terminology.

As the size and complexity of medical terminologies increase, terminology modelers are increasingly hampered by lack of tools and methods to manage the development process. This paper presents our use and ongoing evaluation of a description-logic classifier to support cognitive scalability of the underlying terminology and our enhancements to that classifier to support concurrent development utilizing semantics-based concurrency control methods. Our enhancements, collectively referred to as the Gálapagos, consist of several applications that take locally-developed terminology enhancements from multiple sites, identify conflicting design decisions, support the modelers' reconciliation of the conflicting designs, and efficiently disseminate updates tailored for locally enhanced terminologies. We have tested our ideas through concurrent evolutionary enhancement of SNOMED International at three Kaiser Permanente regions and the Mayo Clinic. We have found that the underlying environment has met our design objectives, and supports semantic-based concurrency control, and identification and resolution of conflicting design decisions.

Artificial Intelligence↗

PubMed1998

The Copernican era of healthcare terminology: a re-centering of health information systems.

Health terminology and classifications have been an unseen backwater in healthcare practice and information systems development. Today however, the recognized need for comparable patient data is driving a new discovery about its strategic importance. Consistent patient descriptions and concept-centered data representations are crucial for efficient discovery of optimal treatments, best outcomes, and efficient practice patterns. The fabled linkage of knowledge sources at the time and place of care requires the conceptual intermediary of common terminology. A brief history overviewing the evolution of health classifications will provide the foundation for considering present and evolving health terminology developments. Their roles in health information systems will be characterized. Discussion will focus on the likely influences of the HIPAA legislation nationally and the new ISO Healthcare Informatics Technical Committee internationally, on terminology adaptation and incorporation.

Disease↗

PubMed1998

A randomized controlled trial of automated term composition.

OBJECTIVE: To compare the ability of an Automated Term Composition (ATC) algorithm with non-compositional mappings to provide coverage (exact mappings to a controlled vocabulary) for a randomly selected set of free text entries which were entered as headings to the Impression section of the clinical notes system at the Mayo Foundation. We also compare the results of four evaluators to determine the inter-observer variability and the variance between term sets, with respect to the accuracy of the mappings and the reliability of the failure analysis. METHODS: From a corpus of approximately 1,000,000 unique terms entered into the Impression/Report/Plan section of the clinical notes system in the calendar year 1997, we randomly selected 1,000 terms. We then further randomized these 1,000 terms into two groups of 500 (Sets A and B). We constructed two copies of the same term matching interface, one without ATC (alpha) and one with ATC (beta). We took four expert Indexers and assigned them to one of the following tasks. The first reviewer (R1) compared set A using the alpha program and then set B using the beta program (R1(Aalpha + Bbeta)). The second compared set A using the alpha program and then set B using the alpha program (R2(A + B) alpha). The third compared set B using the beta program and then set A using the beta program (R3(B + A) beta). The fourth compared set A using the beta program and then set B using the alpha program (R4(Abeta + Balpha)). RESULTS: The program with Automated Term Composition mapped 540 out of the 1,000 Concepts correctly (54.0%). The same program without ATC mapped only 276 out of the 1,000 Concepts correctly (27.6%). Therefore the program with ATC was significantly more effective at matching concepts in our problem lists than the same search engine without ATC (p < 0.0001; McNemar Method). These figures result from the comparison of the alpha program with the beta program by reviewers one and four. Failure analysis showed that with the alpha version 425 out of the 724 mismatches were because a base concept was missing from the retrieval set (58.7%) and 299 mismatches were from missing qualifiers or modifiers or both (41.3%). In the beta version of the program (with ATC) 340 out of the 460 mismatches were secondary to there being a missing base concept in the retrieval set (73.9%) and only 120 mismatches due to missing modifiers and or qualifiers (26.1%). CONCLUSIONS: Automated term composition provided significantly better coverage of a randomly chosen set of patient problems, diagnosed at the Mayo Clinic during the 1997 calendar year, when compared with the same information retrieval system without ATC. We believe that these results speak further to the excellent content coverage provided by the UMLS metathesaurus. These authors believe that increased structure, normalization of UMLS content and semantics, and better tools to make use of the currently available content such as automated term composition, are what is needed to leverage the production of commercially viable tools that provide access to controlled vocabularies for medicine.

Abstracting and Indexing↗