Value sets and the problem of redundancy in value set repositories
Crafting high-quality value sets is time-consuming and requires a range of clinical, terminological, and informatics expertise. Despite widespread agreement on the importance of reusing value sets, value set repositories suffer from clutter and redundancy, greatly complicating efforts at reuse. When...
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| Veröffentlicht in: | PloS one 2024-12, Vol.19 (12), p.e0312289 |
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| creator | Gold, Sigfried Lehmann, Harold P Schilling, Lisa M Lutters, Wayne G |
| description | Crafting high-quality value sets is time-consuming and requires a range of clinical, terminological, and informatics expertise. Despite widespread agreement on the importance of reusing value sets, value set repositories suffer from clutter and redundancy, greatly complicating efforts at reuse. When users encounter multiple value sets with the same name or ostensibly representing the same clinical condition, it can be difficult to choose amongst them or determine if any differences among them are due to error or intentional decision.
This paper offers a view of value set development and reuse based on a field study of researchers and informaticists. The results emerge from an analysis of relevant literature, reflective practice, and the field research data.
Qualitative analysis of our study data, the relevant literature, and our own professional experience led us to three dichotomous concepts that frame an understanding of diverse practices and perspectives surrounding value set development: Permissible values versus analytic value sets;Prescriptive versus descriptive approaches to controlled medical vocabulary use; andSemantic and empirical types of value set development and evaluation practices and the data they rely on.This three-fold framework opens up the redundancy problem, explaining why multiple value sets may or may not be needed and advancing academic understanding of value set development.
In order for value set repositories to become more rather than less useful over time, software must channel user efforts into either improving existing value sets or making new ones only when absolutely necessary. This would require major, innovative changes to value set repository platforms. We believe the most direct path to giving value set developers the ability to leverage prior work is by encouraging them to compare existing value sets using advanced interfaces like VS-Hub, and by collecting and using metadata about code inclusion and exclusion decisions during the authoring process. |
| doi_str_mv | 10.1371/journal.pone.0312289 |
| format | Article |
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This paper offers a view of value set development and reuse based on a field study of researchers and informaticists. The results emerge from an analysis of relevant literature, reflective practice, and the field research data.
Qualitative analysis of our study data, the relevant literature, and our own professional experience led us to three dichotomous concepts that frame an understanding of diverse practices and perspectives surrounding value set development: Permissible values versus analytic value sets;Prescriptive versus descriptive approaches to controlled medical vocabulary use; andSemantic and empirical types of value set development and evaluation practices and the data they rely on.This three-fold framework opens up the redundancy problem, explaining why multiple value sets may or may not be needed and advancing academic understanding of value set development.
In order for value set repositories to become more rather than less useful over time, software must channel user efforts into either improving existing value sets or making new ones only when absolutely necessary. This would require major, innovative changes to value set repository platforms. We believe the most direct path to giving value set developers the ability to leverage prior work is by encouraging them to compare existing value sets using advanced interfaces like VS-Hub, and by collecting and using metadata about code inclusion and exclusion decisions during the authoring process.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0312289</identifier><identifier>PMID: 39652546</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Biology and Life Sciences ; Clutter ; Codes ; Computer and Information Sciences ; Computer supported cooperative work ; Data analysis ; Data collection ; Databases, Factual ; Electronic health records ; Engineering and Technology ; Error analysis ; Genotype & phenotype ; Humans ; Hypothesis testing ; Informatics ; Medicine and Health Sciences ; Observational studies ; Physical Sciences ; Qualitative analysis ; Redundancy ; Repositories ; Research and Analysis Methods ; Reuse ; Semantics ; Social Sciences ; Vocabulary, Controlled</subject><ispartof>PloS one, 2024-12, Vol.19 (12), p.e0312289</ispartof><rights>Copyright: © 2024 Gold et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>2024 Gold et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Gold et al 2024 Gold et al</rights><rights>2024 Gold et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c406t-b82e6ebf2e293e65e334a958876c93a1f71795ecd8f7e22f5634814b8e3037ef3</cites><orcidid>0000-0001-7853-6137 ; 0000-0003-4193-2114 ; 0000-0002-6878-189X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11627404/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11627404/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23865,27923,27924,53790,53792,79371,79372</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39652546$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Dey, Avanti</contributor><creatorcontrib>Gold, Sigfried</creatorcontrib><creatorcontrib>Lehmann, Harold P</creatorcontrib><creatorcontrib>Schilling, Lisa M</creatorcontrib><creatorcontrib>Lutters, Wayne G</creatorcontrib><title>Value sets and the problem of redundancy in value set repositories</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Crafting high-quality value sets is time-consuming and requires a range of clinical, terminological, and informatics expertise. Despite widespread agreement on the importance of reusing value sets, value set repositories suffer from clutter and redundancy, greatly complicating efforts at reuse. When users encounter multiple value sets with the same name or ostensibly representing the same clinical condition, it can be difficult to choose amongst them or determine if any differences among them are due to error or intentional decision.
This paper offers a view of value set development and reuse based on a field study of researchers and informaticists. The results emerge from an analysis of relevant literature, reflective practice, and the field research data.
Qualitative analysis of our study data, the relevant literature, and our own professional experience led us to three dichotomous concepts that frame an understanding of diverse practices and perspectives surrounding value set development: Permissible values versus analytic value sets;Prescriptive versus descriptive approaches to controlled medical vocabulary use; andSemantic and empirical types of value set development and evaluation practices and the data they rely on.This three-fold framework opens up the redundancy problem, explaining why multiple value sets may or may not be needed and advancing academic understanding of value set development.
In order for value set repositories to become more rather than less useful over time, software must channel user efforts into either improving existing value sets or making new ones only when absolutely necessary. This would require major, innovative changes to value set repository platforms. We believe the most direct path to giving value set developers the ability to leverage prior work is by encouraging them to compare existing value sets using advanced interfaces like VS-Hub, and by collecting and using metadata about code inclusion and exclusion decisions during the authoring process.</description><subject>Algorithms</subject><subject>Biology and Life Sciences</subject><subject>Clutter</subject><subject>Codes</subject><subject>Computer and Information Sciences</subject><subject>Computer supported cooperative work</subject><subject>Data analysis</subject><subject>Data collection</subject><subject>Databases, Factual</subject><subject>Electronic health records</subject><subject>Engineering and Technology</subject><subject>Error analysis</subject><subject>Genotype & phenotype</subject><subject>Humans</subject><subject>Hypothesis testing</subject><subject>Informatics</subject><subject>Medicine and Health Sciences</subject><subject>Observational 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informatics expertise. Despite widespread agreement on the importance of reusing value sets, value set repositories suffer from clutter and redundancy, greatly complicating efforts at reuse. When users encounter multiple value sets with the same name or ostensibly representing the same clinical condition, it can be difficult to choose amongst them or determine if any differences among them are due to error or intentional decision.
This paper offers a view of value set development and reuse based on a field study of researchers and informaticists. The results emerge from an analysis of relevant literature, reflective practice, and the field research data.
Qualitative analysis of our study data, the relevant literature, and our own professional experience led us to three dichotomous concepts that frame an understanding of diverse practices and perspectives surrounding value set development: Permissible values versus analytic value sets;Prescriptive versus descriptive approaches to controlled medical vocabulary use; andSemantic and empirical types of value set development and evaluation practices and the data they rely on.This three-fold framework opens up the redundancy problem, explaining why multiple value sets may or may not be needed and advancing academic understanding of value set development.
In order for value set repositories to become more rather than less useful over time, software must channel user efforts into either improving existing value sets or making new ones only when absolutely necessary. This would require major, innovative changes to value set repository platforms. We believe the most direct path to giving value set developers the ability to leverage prior work is by encouraging them to compare existing value sets using advanced interfaces like VS-Hub, and by collecting and using metadata about code inclusion and exclusion decisions during the authoring process.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39652546</pmid><doi>10.1371/journal.pone.0312289</doi><orcidid>https://orcid.org/0000-0001-7853-6137</orcidid><orcidid>https://orcid.org/0000-0003-4193-2114</orcidid><orcidid>https://orcid.org/0000-0002-6878-189X</orcidid><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Algorithms Biology and Life Sciences Clutter Codes Computer and Information Sciences Computer supported cooperative work Data analysis Data collection Databases, Factual Electronic health records Engineering and Technology Error analysis Genotype & phenotype Humans Hypothesis testing Informatics Medicine and Health Sciences Observational studies Physical Sciences Qualitative analysis Redundancy Repositories Research and Analysis Methods Reuse Semantics Social Sciences Vocabulary, Controlled |
| title | Value sets and the problem of redundancy in value set repositories |
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