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Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study

BACKGROUND: When medically unexplained physical symptoms (MUPS) become persistent, it may have major implications for the patient, the general practitioner (GP) and for society. Early identification of patients with MUPS in electronic medical records (EMRs) might contribute to prevention of persiste...

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Autores principales: den Boeft, Madelon, van der Wouden, Johannes C, Rydell-Lexmond, Trudie R, de Wit, Niek J, van der Horst, Henriëtte E, Numans, Mattijs E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052805/
https://www.ncbi.nlm.nih.gov/pubmed/24903850
http://dx.doi.org/10.1186/1471-2296-15-109
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author den Boeft, Madelon
van der Wouden, Johannes C
Rydell-Lexmond, Trudie R
de Wit, Niek J
van der Horst, Henriëtte E
Numans, Mattijs E
author_facet den Boeft, Madelon
van der Wouden, Johannes C
Rydell-Lexmond, Trudie R
de Wit, Niek J
van der Horst, Henriëtte E
Numans, Mattijs E
author_sort den Boeft, Madelon
collection PubMed
description BACKGROUND: When medically unexplained physical symptoms (MUPS) become persistent, it may have major implications for the patient, the general practitioner (GP) and for society. Early identification of patients with MUPS in electronic medical records (EMRs) might contribute to prevention of persistent MUPS by creating awareness among GPs and providing an opportunity to start stepped care management. However, procedures for identification of patients with MUPS in EMRs are not well established yet. In this validation study we explore the test characteristics of an EMR screening method to identify patients with MUPS. METHODS: The EMR screening method consists of three steps. First, all patients ≥18 years were included when they had five or more contacts in the last 12 months. Second, patients with known chronic conditions were excluded. Finally, patients were included with a MUPS syndrome or when they had three or more complaints suggestive for MUPS. We compared the results of the EMR screening method with scores on the Patient Health Questionnaire-15 (PHQ-15), which we used as reference test. We calculated test characteristics for various cut-off points. RESULTS: From the 1223 patients in our dataset who completed the PHQ-15, 609 (49/8%) scored ≥5 on the PHQ-15. The EMR screening method detected 131/1223 (10.7%) as patients with MUPS. Of those, 102 (77.9%) scored ≥5 on the PHQ-15 and 53 (40.5%) scored ≥10. When compared with the PHQ-15 cut-off point ≥10, sensitivity and specificity were 0.30 and 0.93 and positive and negative predictive values were 0.40 and 0.89, respectively. CONCLUSIONS: The EMR screening method to identify patients with MUPS has a high specificity. However, many potential MUPS patients will be missed. Before using this method as a screening instrument for selecting patients who might benefit from structured care, its sensitivity needs to be improved while maintaining its specificity.
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spelling pubmed-40528052014-06-12 Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study den Boeft, Madelon van der Wouden, Johannes C Rydell-Lexmond, Trudie R de Wit, Niek J van der Horst, Henriëtte E Numans, Mattijs E BMC Fam Pract Research Article BACKGROUND: When medically unexplained physical symptoms (MUPS) become persistent, it may have major implications for the patient, the general practitioner (GP) and for society. Early identification of patients with MUPS in electronic medical records (EMRs) might contribute to prevention of persistent MUPS by creating awareness among GPs and providing an opportunity to start stepped care management. However, procedures for identification of patients with MUPS in EMRs are not well established yet. In this validation study we explore the test characteristics of an EMR screening method to identify patients with MUPS. METHODS: The EMR screening method consists of three steps. First, all patients ≥18 years were included when they had five or more contacts in the last 12 months. Second, patients with known chronic conditions were excluded. Finally, patients were included with a MUPS syndrome or when they had three or more complaints suggestive for MUPS. We compared the results of the EMR screening method with scores on the Patient Health Questionnaire-15 (PHQ-15), which we used as reference test. We calculated test characteristics for various cut-off points. RESULTS: From the 1223 patients in our dataset who completed the PHQ-15, 609 (49/8%) scored ≥5 on the PHQ-15. The EMR screening method detected 131/1223 (10.7%) as patients with MUPS. Of those, 102 (77.9%) scored ≥5 on the PHQ-15 and 53 (40.5%) scored ≥10. When compared with the PHQ-15 cut-off point ≥10, sensitivity and specificity were 0.30 and 0.93 and positive and negative predictive values were 0.40 and 0.89, respectively. CONCLUSIONS: The EMR screening method to identify patients with MUPS has a high specificity. However, many potential MUPS patients will be missed. Before using this method as a screening instrument for selecting patients who might benefit from structured care, its sensitivity needs to be improved while maintaining its specificity. BioMed Central 2014-06-05 /pmc/articles/PMC4052805/ /pubmed/24903850 http://dx.doi.org/10.1186/1471-2296-15-109 Text en Copyright © 2014 den Boeft et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
den Boeft, Madelon
van der Wouden, Johannes C
Rydell-Lexmond, Trudie R
de Wit, Niek J
van der Horst, Henriëtte E
Numans, Mattijs E
Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
title Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
title_full Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
title_fullStr Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
title_full_unstemmed Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
title_short Identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
title_sort identifying patients with medically unexplained physical symptoms in electronic medical records in primary care: a validation study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052805/
https://www.ncbi.nlm.nih.gov/pubmed/24903850
http://dx.doi.org/10.1186/1471-2296-15-109
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