Measuring Mortality Information in Clinical Data Warehouses
The ability to track and report long-term outcomes, especially mortality, is essential for advancing clinical research. The purpose of this study was to present a framework for assessing the quality of mortality information in clinical research databases. Using the clinical data warehouse (CDW) at C...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Informatics Association
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525266/ https://www.ncbi.nlm.nih.gov/pubmed/26306284 |
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author | Jones, Barrett Vawdrey, David K. |
author_facet | Jones, Barrett Vawdrey, David K. |
author_sort | Jones, Barrett |
collection | PubMed |
description | The ability to track and report long-term outcomes, especially mortality, is essential for advancing clinical research. The purpose of this study was to present a framework for assessing the quality of mortality information in clinical research databases. Using the clinical data warehouse (CDW) at Columbia University Medical Center as a case study, we measured: 1) agreement in vital status between our institution’s patient registration system and the U.S. Social Security Administration’s Death Master File (DMF), 2) the proportion of patients marked as deceased according to the DMF records who had subsequent visits to our institution, and 3) the proportion of patients still living according to Columbia’s CDW who were over 100 and 120 years of age. Of 33,295 deaths recorded in our institution’s patient registration system, 13,167 (39.5%) did not exist in the DMF. Of 315,037 patients in our CDW who marked as deceased according to the DMF, 2.1% had a subsequent clinical encounter at our institution. The proportion of patients still living according to Columbia’s CDW who were over 100 and 120 years of age was 43.6% and 43.1%, respectively. These measures may be useful to other clinical research investigators seeking to assess the quality of mortality data (1–4). |
format | Online Article Text |
id | pubmed-4525266 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | American Medical Informatics Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-45252662015-08-24 Measuring Mortality Information in Clinical Data Warehouses Jones, Barrett Vawdrey, David K. AMIA Jt Summits Transl Sci Proc Articles The ability to track and report long-term outcomes, especially mortality, is essential for advancing clinical research. The purpose of this study was to present a framework for assessing the quality of mortality information in clinical research databases. Using the clinical data warehouse (CDW) at Columbia University Medical Center as a case study, we measured: 1) agreement in vital status between our institution’s patient registration system and the U.S. Social Security Administration’s Death Master File (DMF), 2) the proportion of patients marked as deceased according to the DMF records who had subsequent visits to our institution, and 3) the proportion of patients still living according to Columbia’s CDW who were over 100 and 120 years of age. Of 33,295 deaths recorded in our institution’s patient registration system, 13,167 (39.5%) did not exist in the DMF. Of 315,037 patients in our CDW who marked as deceased according to the DMF, 2.1% had a subsequent clinical encounter at our institution. The proportion of patients still living according to Columbia’s CDW who were over 100 and 120 years of age was 43.6% and 43.1%, respectively. These measures may be useful to other clinical research investigators seeking to assess the quality of mortality data (1–4). American Medical Informatics Association 2015-03-25 /pmc/articles/PMC4525266/ /pubmed/26306284 Text en ©2015 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose |
spellingShingle | Articles Jones, Barrett Vawdrey, David K. Measuring Mortality Information in Clinical Data Warehouses |
title | Measuring Mortality Information in Clinical Data Warehouses |
title_full | Measuring Mortality Information in Clinical Data Warehouses |
title_fullStr | Measuring Mortality Information in Clinical Data Warehouses |
title_full_unstemmed | Measuring Mortality Information in Clinical Data Warehouses |
title_short | Measuring Mortality Information in Clinical Data Warehouses |
title_sort | measuring mortality information in clinical data warehouses |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525266/ https://www.ncbi.nlm.nih.gov/pubmed/26306284 |
work_keys_str_mv | AT jonesbarrett measuringmortalityinformationinclinicaldatawarehouses AT vawdreydavidk measuringmortalityinformationinclinicaldatawarehouses |