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The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder
BACKGROUND: We have previously demonstrated that routinely collected primary care data can be used to identify potential participants for trials in depression [1]. Here we demonstrate how patients with psychotic disorders can be identified from primary care records for potential inclusion in a cohor...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296666/ https://www.ncbi.nlm.nih.gov/pubmed/22333117 http://dx.doi.org/10.1186/1756-0500-5-95 |
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author | Economou, Alexis Grey, Michelle McGregor, Joanna Craddock, Nick Lyons, Ronan A Owen, Michael J Price, Vaughn Thomson, Sue Walters, James TR Lloyd, Keith |
author_facet | Economou, Alexis Grey, Michelle McGregor, Joanna Craddock, Nick Lyons, Ronan A Owen, Michael J Price, Vaughn Thomson, Sue Walters, James TR Lloyd, Keith |
author_sort | Economou, Alexis |
collection | PubMed |
description | BACKGROUND: We have previously demonstrated that routinely collected primary care data can be used to identify potential participants for trials in depression [1]. Here we demonstrate how patients with psychotic disorders can be identified from primary care records for potential inclusion in a cohort study. We discuss the strengths and limitations of this approach; assess its potential value and report challenges encountered. METHODS: We designed an algorithm with which we searched for patients with a lifetime diagnosis of psychotic disorders within the Secure Anonymised Information Linkage (SAIL) database of routinely collected health data. The algorithm was validated against the "gold standard" of a well established operational criteria checklist for psychotic and affective illness (OPCRIT). Case notes of 100 patients from a community mental health team (CMHT) in Swansea were studied of whom 80 had matched GP records. RESULTS: The algorithm had favourable test characteristics, with a very good ability to detect patients with psychotic disorders (sensitivity > 0.7) and an excellent ability not to falsely identify patients with psychotic disorders (specificity > 0.9). CONCLUSIONS: With certain limitations our algorithm can be used to search the general practice data and reliably identify patients with psychotic disorders. This may be useful in identifying candidates for potential inclusion in cohort studies. |
format | Online Article Text |
id | pubmed-3296666 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32966662012-03-08 The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder Economou, Alexis Grey, Michelle McGregor, Joanna Craddock, Nick Lyons, Ronan A Owen, Michael J Price, Vaughn Thomson, Sue Walters, James TR Lloyd, Keith BMC Res Notes Research Article BACKGROUND: We have previously demonstrated that routinely collected primary care data can be used to identify potential participants for trials in depression [1]. Here we demonstrate how patients with psychotic disorders can be identified from primary care records for potential inclusion in a cohort study. We discuss the strengths and limitations of this approach; assess its potential value and report challenges encountered. METHODS: We designed an algorithm with which we searched for patients with a lifetime diagnosis of psychotic disorders within the Secure Anonymised Information Linkage (SAIL) database of routinely collected health data. The algorithm was validated against the "gold standard" of a well established operational criteria checklist for psychotic and affective illness (OPCRIT). Case notes of 100 patients from a community mental health team (CMHT) in Swansea were studied of whom 80 had matched GP records. RESULTS: The algorithm had favourable test characteristics, with a very good ability to detect patients with psychotic disorders (sensitivity > 0.7) and an excellent ability not to falsely identify patients with psychotic disorders (specificity > 0.9). CONCLUSIONS: With certain limitations our algorithm can be used to search the general practice data and reliably identify patients with psychotic disorders. This may be useful in identifying candidates for potential inclusion in cohort studies. BioMed Central 2012-02-14 /pmc/articles/PMC3296666/ /pubmed/22333117 http://dx.doi.org/10.1186/1756-0500-5-95 Text en Copyright ©2012 Economou et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Economou, Alexis Grey, Michelle McGregor, Joanna Craddock, Nick Lyons, Ronan A Owen, Michael J Price, Vaughn Thomson, Sue Walters, James TR Lloyd, Keith The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
title | The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
title_full | The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
title_fullStr | The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
title_full_unstemmed | The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
title_short | The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
title_sort | health informatics cohort enhancement project (hice): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296666/ https://www.ncbi.nlm.nih.gov/pubmed/22333117 http://dx.doi.org/10.1186/1756-0500-5-95 |
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