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Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases
Background and objective: We previously built a weighted Depressive Health State Index (DHSI) based on 29 parameters routinely collected in an automated healthcare database (AHDB). We now propose a linear DHSI (L-DHSI) which is easier to use and to replicate across AHDBs. Methods: A historical cohor...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Routledge
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792044/ https://www.ncbi.nlm.nih.gov/pubmed/31656554 http://dx.doi.org/10.1080/20016689.2019.1674115 |
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author | Touya, Maëlys Lamy, François-Xavier Tanasescu, Adrian Saragoussi, Delphine François, Clément Wade, Alan G. Llorca, Pierre-Michel Lançon, Christophe Falissard, Bruno |
author_facet | Touya, Maëlys Lamy, François-Xavier Tanasescu, Adrian Saragoussi, Delphine François, Clément Wade, Alan G. Llorca, Pierre-Michel Lançon, Christophe Falissard, Bruno |
author_sort | Touya, Maëlys |
collection | PubMed |
description | Background and objective: We previously built a weighted Depressive Health State Index (DHSI) based on 29 parameters routinely collected in an automated healthcare database (AHDB). We now propose a linear DHSI (L-DHSI) which is easier to use and to replicate across AHDBs. Methods: A historical cohort of patients with ≥1 episode of depression was identified in the Clinical Practice Research Datalink (CPRD). The DHSI was calculated for each treated episode of depression. Validation was performed by using validated definitions of remission (proxy and Patient Health Questionnaire 9 or PHQ-9) and comparing the L-DHSI between subgroups. Reliability was assessed using Cronbach’s alpha. Results: Between 1 January 2006 and 31 December 2012, 309,279 episodes of depression were identified in the CPRD. Remission was observed in 5% of the patients with lowest L-DHSI scores and in 78% of the patients with highest L-DHSI scores. Although less sensitive than the weighted DHSI, the L-DHSI was reliable and relatively easy of use. The L-DHSI was highly correlated to the weighted DHSI (Spearman coefficient 0.790, p < 0.001). Conclusion: The L-DHSI represents a good balance between reliability, usability, and reproducibility. In addition, the linearity of this index allows for an easier interpretation than the original weighted DHSI. |
format | Online Article Text |
id | pubmed-6792044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Routledge |
record_format | MEDLINE/PubMed |
spelling | pubmed-67920442019-10-25 Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases Touya, Maëlys Lamy, François-Xavier Tanasescu, Adrian Saragoussi, Delphine François, Clément Wade, Alan G. Llorca, Pierre-Michel Lançon, Christophe Falissard, Bruno J Mark Access Health Policy Original Research Article Background and objective: We previously built a weighted Depressive Health State Index (DHSI) based on 29 parameters routinely collected in an automated healthcare database (AHDB). We now propose a linear DHSI (L-DHSI) which is easier to use and to replicate across AHDBs. Methods: A historical cohort of patients with ≥1 episode of depression was identified in the Clinical Practice Research Datalink (CPRD). The DHSI was calculated for each treated episode of depression. Validation was performed by using validated definitions of remission (proxy and Patient Health Questionnaire 9 or PHQ-9) and comparing the L-DHSI between subgroups. Reliability was assessed using Cronbach’s alpha. Results: Between 1 January 2006 and 31 December 2012, 309,279 episodes of depression were identified in the CPRD. Remission was observed in 5% of the patients with lowest L-DHSI scores and in 78% of the patients with highest L-DHSI scores. Although less sensitive than the weighted DHSI, the L-DHSI was reliable and relatively easy of use. The L-DHSI was highly correlated to the weighted DHSI (Spearman coefficient 0.790, p < 0.001). Conclusion: The L-DHSI represents a good balance between reliability, usability, and reproducibility. In addition, the linearity of this index allows for an easier interpretation than the original weighted DHSI. Routledge 2019-10-09 /pmc/articles/PMC6792044/ /pubmed/31656554 http://dx.doi.org/10.1080/20016689.2019.1674115 Text en © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Article Touya, Maëlys Lamy, François-Xavier Tanasescu, Adrian Saragoussi, Delphine François, Clément Wade, Alan G. Llorca, Pierre-Michel Lançon, Christophe Falissard, Bruno Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
title | Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
title_full | Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
title_fullStr | Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
title_full_unstemmed | Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
title_short | Creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
title_sort | creation and validation of a linear index to measure the health state of patients with depression in automated healthcare databases |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792044/ https://www.ncbi.nlm.nih.gov/pubmed/31656554 http://dx.doi.org/10.1080/20016689.2019.1674115 |
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