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A review of measurement practice in studies of clinical decision support systems 1998–2017

OBJECTIVE: To assess measurement practice in clinical decision support evaluation studies. MATERIALS AND METHODS: We identified empirical studies evaluating clinical decision support systems published from 1998 to 2017. We reviewed titles, abstracts, and full paper contents for evidence of attention...

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Autores principales: Scott, Philip J, Brown, Angela W, Adedeji, Taiwo, Wyatt, Jeremy C, Georgiou, Andrew, Eisenstein, Eric L, Friedman, Charles P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748820/
https://www.ncbi.nlm.nih.gov/pubmed/30990522
http://dx.doi.org/10.1093/jamia/ocz035
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author Scott, Philip J
Brown, Angela W
Adedeji, Taiwo
Wyatt, Jeremy C
Georgiou, Andrew
Eisenstein, Eric L
Friedman, Charles P
author_facet Scott, Philip J
Brown, Angela W
Adedeji, Taiwo
Wyatt, Jeremy C
Georgiou, Andrew
Eisenstein, Eric L
Friedman, Charles P
author_sort Scott, Philip J
collection PubMed
description OBJECTIVE: To assess measurement practice in clinical decision support evaluation studies. MATERIALS AND METHODS: We identified empirical studies evaluating clinical decision support systems published from 1998 to 2017. We reviewed titles, abstracts, and full paper contents for evidence of attention to measurement validity, reliability, or reuse. We used Friedman and Wyatt’s typology to categorize the studies. RESULTS: There were 391 studies that met the inclusion criteria. Study types in this cohort were primarily field user effect studies (n = 210) or problem impact studies (n = 150). Of those, 280 studies (72%) had no evidence of attention to measurement methodology, and 111 (28%) had some evidence with 33 (8%) offering validity evidence; 45 (12%) offering reliability evidence; and 61 (16%) reporting measurement artefact reuse. DISCUSSION: Only 5 studies offered validity assessment within the study. Valid measures were predominantly observed in problem impact studies with the majority of measures being clinical or patient reported outcomes with validity measured elsewhere. CONCLUSION: Measurement methodology is frequently ignored in empirical studies of clinical decision support systems and particularly so in field user effect studies. Authors may in fact be attending to measurement considerations and not reporting this or employing methods of unknown validity and reliability in their studies. In the latter case, reported study results may be biased and effect sizes misleading. We argue that replication studies to strengthen the evidence base require greater attention to measurement practice in health informatics research.
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spelling pubmed-67488202019-09-23 A review of measurement practice in studies of clinical decision support systems 1998–2017 Scott, Philip J Brown, Angela W Adedeji, Taiwo Wyatt, Jeremy C Georgiou, Andrew Eisenstein, Eric L Friedman, Charles P J Am Med Inform Assoc Reviews OBJECTIVE: To assess measurement practice in clinical decision support evaluation studies. MATERIALS AND METHODS: We identified empirical studies evaluating clinical decision support systems published from 1998 to 2017. We reviewed titles, abstracts, and full paper contents for evidence of attention to measurement validity, reliability, or reuse. We used Friedman and Wyatt’s typology to categorize the studies. RESULTS: There were 391 studies that met the inclusion criteria. Study types in this cohort were primarily field user effect studies (n = 210) or problem impact studies (n = 150). Of those, 280 studies (72%) had no evidence of attention to measurement methodology, and 111 (28%) had some evidence with 33 (8%) offering validity evidence; 45 (12%) offering reliability evidence; and 61 (16%) reporting measurement artefact reuse. DISCUSSION: Only 5 studies offered validity assessment within the study. Valid measures were predominantly observed in problem impact studies with the majority of measures being clinical or patient reported outcomes with validity measured elsewhere. CONCLUSION: Measurement methodology is frequently ignored in empirical studies of clinical decision support systems and particularly so in field user effect studies. Authors may in fact be attending to measurement considerations and not reporting this or employing methods of unknown validity and reliability in their studies. In the latter case, reported study results may be biased and effect sizes misleading. We argue that replication studies to strengthen the evidence base require greater attention to measurement practice in health informatics research. Oxford University Press 2019-04-17 /pmc/articles/PMC6748820/ /pubmed/30990522 http://dx.doi.org/10.1093/jamia/ocz035 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Reviews
Scott, Philip J
Brown, Angela W
Adedeji, Taiwo
Wyatt, Jeremy C
Georgiou, Andrew
Eisenstein, Eric L
Friedman, Charles P
A review of measurement practice in studies of clinical decision support systems 1998–2017
title A review of measurement practice in studies of clinical decision support systems 1998–2017
title_full A review of measurement practice in studies of clinical decision support systems 1998–2017
title_fullStr A review of measurement practice in studies of clinical decision support systems 1998–2017
title_full_unstemmed A review of measurement practice in studies of clinical decision support systems 1998–2017
title_short A review of measurement practice in studies of clinical decision support systems 1998–2017
title_sort review of measurement practice in studies of clinical decision support systems 1998–2017
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748820/
https://www.ncbi.nlm.nih.gov/pubmed/30990522
http://dx.doi.org/10.1093/jamia/ocz035
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