Cargando…

Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England

OBJECTIVES: Evaluate the reliability of using diagnosis codes and prescription data to identify the timing of symptomatic onset, cognitive assessment and diagnosis of Alzheimer’s disease (AD) among patients diagnosed with AD. METHODS: This was a retrospective cohort study using the UK Clinical Pract...

Descripción completa

Detalles Bibliográficos
Autores principales: Dell’Agnello, Grazia, Desai, Urvi, Kirson, Noam Y, Wen, Jody, Meiselbach, Mark K, Reed, Catherine C, Belger, Mark, Lenox-Smith, Alan, Martinez, Carlos, Rasmussen, Jill
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875601/
https://www.ncbi.nlm.nih.gov/pubmed/29567847
http://dx.doi.org/10.1136/bmjopen-2017-019684
_version_ 1783310379239079936
author Dell’Agnello, Grazia
Desai, Urvi
Kirson, Noam Y
Wen, Jody
Meiselbach, Mark K
Reed, Catherine C
Belger, Mark
Lenox-Smith, Alan
Martinez, Carlos
Rasmussen, Jill
author_facet Dell’Agnello, Grazia
Desai, Urvi
Kirson, Noam Y
Wen, Jody
Meiselbach, Mark K
Reed, Catherine C
Belger, Mark
Lenox-Smith, Alan
Martinez, Carlos
Rasmussen, Jill
author_sort Dell’Agnello, Grazia
collection PubMed
description OBJECTIVES: Evaluate the reliability of using diagnosis codes and prescription data to identify the timing of symptomatic onset, cognitive assessment and diagnosis of Alzheimer’s disease (AD) among patients diagnosed with AD. METHODS: This was a retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD). The study cohort consisted of a random sample of 50 patients with first AD diagnosis in 2010–2013. Additionally, patients were required to have a valid text-field code and a hospital episode or a referral in the 3 years before the first AD diagnosis. The earliest indications of cognitive impairment, cognitive assessment and AD diagnosis were identified using two approaches: (1) using an algorithm based on diagnostic codes and prescription drug information and (2) using information compiled from manual review of both text-based and coded data. The reliability of the code-based algorithm for identifying the earliest dates of the three measures described earlier was evaluated relative to the comprehensive second approach. Additionally, common cognitive assessments (with and without results) were described for both approaches. RESULTS: The two approaches identified the same first dates of cognitive symptoms in 33 (66%) of the 50 patients, first cognitive assessment in 29 (58%) patients and first AD diagnosis in 43 (86%) patients. Allowing for the dates from the two approaches to be within 30 days, the code-based algorithm’s success rates increased to 74%, 70% and 94%, respectively. Mini-Mental State Examination was the most commonly observed cognitive assessment in both approaches; however, of the 53 tests performed, only 19 results were observed in the coded data. CONCLUSIONS: The code-based algorithm shows promise for identifying the first AD diagnosis. However, the reliability of using coded data to identify earliest indications of cognitive impairment and cognitive assessments is questionable. Additionally, CPRD is not a recommended data source to identify results of cognitive assessments.
format Online
Article
Text
id pubmed-5875601
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-58756012018-04-02 Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England Dell’Agnello, Grazia Desai, Urvi Kirson, Noam Y Wen, Jody Meiselbach, Mark K Reed, Catherine C Belger, Mark Lenox-Smith, Alan Martinez, Carlos Rasmussen, Jill BMJ Open Research Methods OBJECTIVES: Evaluate the reliability of using diagnosis codes and prescription data to identify the timing of symptomatic onset, cognitive assessment and diagnosis of Alzheimer’s disease (AD) among patients diagnosed with AD. METHODS: This was a retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD). The study cohort consisted of a random sample of 50 patients with first AD diagnosis in 2010–2013. Additionally, patients were required to have a valid text-field code and a hospital episode or a referral in the 3 years before the first AD diagnosis. The earliest indications of cognitive impairment, cognitive assessment and AD diagnosis were identified using two approaches: (1) using an algorithm based on diagnostic codes and prescription drug information and (2) using information compiled from manual review of both text-based and coded data. The reliability of the code-based algorithm for identifying the earliest dates of the three measures described earlier was evaluated relative to the comprehensive second approach. Additionally, common cognitive assessments (with and without results) were described for both approaches. RESULTS: The two approaches identified the same first dates of cognitive symptoms in 33 (66%) of the 50 patients, first cognitive assessment in 29 (58%) patients and first AD diagnosis in 43 (86%) patients. Allowing for the dates from the two approaches to be within 30 days, the code-based algorithm’s success rates increased to 74%, 70% and 94%, respectively. Mini-Mental State Examination was the most commonly observed cognitive assessment in both approaches; however, of the 53 tests performed, only 19 results were observed in the coded data. CONCLUSIONS: The code-based algorithm shows promise for identifying the first AD diagnosis. However, the reliability of using coded data to identify earliest indications of cognitive impairment and cognitive assessments is questionable. Additionally, CPRD is not a recommended data source to identify results of cognitive assessments. BMJ Publishing Group 2018-03-22 /pmc/articles/PMC5875601/ /pubmed/29567847 http://dx.doi.org/10.1136/bmjopen-2017-019684 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Research Methods
Dell’Agnello, Grazia
Desai, Urvi
Kirson, Noam Y
Wen, Jody
Meiselbach, Mark K
Reed, Catherine C
Belger, Mark
Lenox-Smith, Alan
Martinez, Carlos
Rasmussen, Jill
Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England
title Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England
title_full Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England
title_fullStr Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England
title_full_unstemmed Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England
title_short Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer’s disease diagnosis: a pilot study in England
title_sort reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and alzheimer’s disease diagnosis: a pilot study in england
topic Research Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875601/
https://www.ncbi.nlm.nih.gov/pubmed/29567847
http://dx.doi.org/10.1136/bmjopen-2017-019684
work_keys_str_mv AT dellagnellograzia reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT desaiurvi reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT kirsonnoamy reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT wenjody reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT meiselbachmarkk reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT reedcatherinec reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT belgermark reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT lenoxsmithalan reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT martinezcarlos reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland
AT rasmussenjill reliabilityofcodeddatatoidentifyearliestindicationsofcognitivedeclinecognitiveevaluationandalzheimersdiseasediagnosisapilotstudyinengland