Learning from the crowd while mapping to LOINC

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Objective To describe the perspectives of Regenstrief LOINC Mapping Assistant (RELMA) users before and after the deployment of Community Mapping features, characterize the usage of these new features, and analyze the quality of mappings submitted to the community mapping repository. Methods We evaluated Logical Observation Identifiers Names and Codes (LOINC) community members' perceptions about new "wisdom of the crowd" information and how they used the new RELMA features. We conducted a pre-launch survey to capture users' perceptions of the proposed functionality of these new features; monitored how the new features and data available via those features were accessed; conducted a follow-up survey about the use of RELMA with the Community Mapping features; and analyzed community mappings using automated methods to detect potential errors. Results Despite general satisfaction with RELMA, nearly 80% of 155 respondents to our pre-launch survey indicated that having information on how often other users had mapped to a particular LOINC term would be helpful. During the study period, 200 participants logged into the RELMA Community Mapping features an average of 610 times per month and viewed the mapping detail pages a total of 6686 times. Fifty respondents (25%) completed our post-launch survey, and those who accessed the Community Mapping features unanimously indicated that they were useful. Overall, 95.3% of the submitted mappings passed our automated validation checks. Conclusion When information about other institutions' mappings was made available, study participants who accessed it agreed that it was useful and informed their mapping choices. Our findings suggest that a crowd-sourced repository of mappings is valuable to users who are mapping local terms to LOINC terms.

Original languageEnglish (US)
Pages (from-to)1205-1211
Number of pages7
JournalJournal of the American Medical Informatics Association
Volume22
Issue number6
DOIs
StatePublished - 2015

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Logical Observation Identifiers Names and Codes
Learning
Surveys and Questionnaires

Keywords

  • Clinical laboratory information systems
  • Controlled
  • LOINC
  • Medical record systems
  • Vocabulary

ASJC Scopus subject areas

  • Health Informatics

Cite this

Learning from the crowd while mapping to LOINC. / Vreeman, Daniel; Hook, John; Dixon, Brian.

In: Journal of the American Medical Informatics Association, Vol. 22, No. 6, 2015, p. 1205-1211.

Research output: Contribution to journalArticle

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abstract = "Objective To describe the perspectives of Regenstrief LOINC Mapping Assistant (RELMA) users before and after the deployment of Community Mapping features, characterize the usage of these new features, and analyze the quality of mappings submitted to the community mapping repository. Methods We evaluated Logical Observation Identifiers Names and Codes (LOINC) community members' perceptions about new {"}wisdom of the crowd{"} information and how they used the new RELMA features. We conducted a pre-launch survey to capture users' perceptions of the proposed functionality of these new features; monitored how the new features and data available via those features were accessed; conducted a follow-up survey about the use of RELMA with the Community Mapping features; and analyzed community mappings using automated methods to detect potential errors. Results Despite general satisfaction with RELMA, nearly 80{\%} of 155 respondents to our pre-launch survey indicated that having information on how often other users had mapped to a particular LOINC term would be helpful. During the study period, 200 participants logged into the RELMA Community Mapping features an average of 610 times per month and viewed the mapping detail pages a total of 6686 times. Fifty respondents (25{\%}) completed our post-launch survey, and those who accessed the Community Mapping features unanimously indicated that they were useful. Overall, 95.3{\%} of the submitted mappings passed our automated validation checks. Conclusion When information about other institutions' mappings was made available, study participants who accessed it agreed that it was useful and informed their mapping choices. Our findings suggest that a crowd-sourced repository of mappings is valuable to users who are mapping local terms to LOINC terms.",
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