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Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study

BACKGROUND: Administrative databases that capture diagnostic codes are increasingly being used worldwide for research because they can save time and reduce costs. However, assessing validity is necessary before defining diseases using only diagnostic codes in research applications. OBJECTIVE: Our ob...

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Autores principales: Peterson, Brett J., Rocca, Walter A., Bower, James H., Savica, Rodolfo, Mielke, Michelle M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218579/
https://www.ncbi.nlm.nih.gov/pubmed/34164614
http://dx.doi.org/10.1016/j.prdoa.2020.100061
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author Peterson, Brett J.
Rocca, Walter A.
Bower, James H.
Savica, Rodolfo
Mielke, Michelle M.
author_facet Peterson, Brett J.
Rocca, Walter A.
Bower, James H.
Savica, Rodolfo
Mielke, Michelle M.
author_sort Peterson, Brett J.
collection PubMed
description BACKGROUND: Administrative databases that capture diagnostic codes are increasingly being used worldwide for research because they can save time and reduce costs. However, assessing validity is necessary before defining diseases using only diagnostic codes in research applications. OBJECTIVE: Our objective was to assess the validity of using diagnostic codes to identify incident Parkinson's disease (PD) cases in Olmsted County, Minnesota using an established standard for comparison (1976–2005). METHODS: Cases were identified solely using computer programs applied to administrative diagnostic code indexes from the Rochester Epidemiology Project (REP). Two codes >30 days apart or one code on the death certificate constituted PD. The standard was a clinical diagnosis by movement disorders specialists based on medical record review. Validity was assessed using positive predictive value (PPV) and sensitivity. Numbers of incident cases and incidence rates were compared between the two ascertainment methods by sex. RESULTS: The codes only method over-counted the number of incident PD cases by 73% (804 versus 464), and this over-counting generally increased with calendar year. Sensitivity was 80% (95% CI [76%, 84%]) and PPV was 46% (95% CI [34%, 50%]). Disease status misclassification accounted for two-thirds of falsely identified cases, where individuals were found to not have PD (43%) or even parkinsonism (23%) after medical record review. The codes only method also over-estimated the incidence rate time trend for men and women by approximately two-fold. CONCLUSION: In our context, using administrative diagnostic codes only to identify incident PD cases is not recommended unless more accurate algorithms are developed.
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spelling pubmed-82185792021-06-22 Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study Peterson, Brett J. Rocca, Walter A. Bower, James H. Savica, Rodolfo Mielke, Michelle M. Clin Park Relat Disord Original Article BACKGROUND: Administrative databases that capture diagnostic codes are increasingly being used worldwide for research because they can save time and reduce costs. However, assessing validity is necessary before defining diseases using only diagnostic codes in research applications. OBJECTIVE: Our objective was to assess the validity of using diagnostic codes to identify incident Parkinson's disease (PD) cases in Olmsted County, Minnesota using an established standard for comparison (1976–2005). METHODS: Cases were identified solely using computer programs applied to administrative diagnostic code indexes from the Rochester Epidemiology Project (REP). Two codes >30 days apart or one code on the death certificate constituted PD. The standard was a clinical diagnosis by movement disorders specialists based on medical record review. Validity was assessed using positive predictive value (PPV) and sensitivity. Numbers of incident cases and incidence rates were compared between the two ascertainment methods by sex. RESULTS: The codes only method over-counted the number of incident PD cases by 73% (804 versus 464), and this over-counting generally increased with calendar year. Sensitivity was 80% (95% CI [76%, 84%]) and PPV was 46% (95% CI [34%, 50%]). Disease status misclassification accounted for two-thirds of falsely identified cases, where individuals were found to not have PD (43%) or even parkinsonism (23%) after medical record review. The codes only method also over-estimated the incidence rate time trend for men and women by approximately two-fold. CONCLUSION: In our context, using administrative diagnostic codes only to identify incident PD cases is not recommended unless more accurate algorithms are developed. Elsevier 2020-06-02 /pmc/articles/PMC8218579/ /pubmed/34164614 http://dx.doi.org/10.1016/j.prdoa.2020.100061 Text en © 2020 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Peterson, Brett J.
Rocca, Walter A.
Bower, James H.
Savica, Rodolfo
Mielke, Michelle M.
Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
title Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
title_full Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
title_fullStr Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
title_full_unstemmed Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
title_short Identifying incident Parkinson's disease using administrative diagnostic codes: a validation study
title_sort identifying incident parkinson's disease using administrative diagnostic codes: a validation study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218579/
https://www.ncbi.nlm.nih.gov/pubmed/34164614
http://dx.doi.org/10.1016/j.prdoa.2020.100061
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