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Validation of US CDC National Death Index mortality data, focusing on differences in race and ethnicity
by
Basra, Sundeep S
, Horberg, Michael A
, Ter-Minassian, Monica
, Watson, Eric S
, Derus, Alphonse J
in
Algorithms
/ Centers for Disease Control and Prevention, U.S
/ Data Management
/ Databases, Factual
/ Electronic Health Records
/ Ethnicity
/ Female
/ Healthcare
/ Hispanic people
/ Humans
/ Information Systems
/ Marital status
/ Medical Record Linkage
/ Mortality
/ Original Research
/ Outcome Assessment
/ Pacific Islander people
/ Population
/ Public Health
/ Quality control
/ Self report
/ Social security numbers
/ United States - epidemiology
2023
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Validation of US CDC National Death Index mortality data, focusing on differences in race and ethnicity
by
Basra, Sundeep S
, Horberg, Michael A
, Ter-Minassian, Monica
, Watson, Eric S
, Derus, Alphonse J
in
Algorithms
/ Centers for Disease Control and Prevention, U.S
/ Data Management
/ Databases, Factual
/ Electronic Health Records
/ Ethnicity
/ Female
/ Healthcare
/ Hispanic people
/ Humans
/ Information Systems
/ Marital status
/ Medical Record Linkage
/ Mortality
/ Original Research
/ Outcome Assessment
/ Pacific Islander people
/ Population
/ Public Health
/ Quality control
/ Self report
/ Social security numbers
/ United States - epidemiology
2023
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Validation of US CDC National Death Index mortality data, focusing on differences in race and ethnicity
by
Basra, Sundeep S
, Horberg, Michael A
, Ter-Minassian, Monica
, Watson, Eric S
, Derus, Alphonse J
in
Algorithms
/ Centers for Disease Control and Prevention, U.S
/ Data Management
/ Databases, Factual
/ Electronic Health Records
/ Ethnicity
/ Female
/ Healthcare
/ Hispanic people
/ Humans
/ Information Systems
/ Marital status
/ Medical Record Linkage
/ Mortality
/ Original Research
/ Outcome Assessment
/ Pacific Islander people
/ Population
/ Public Health
/ Quality control
/ Self report
/ Social security numbers
/ United States - epidemiology
2023
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Validation of US CDC National Death Index mortality data, focusing on differences in race and ethnicity
Journal Article
Validation of US CDC National Death Index mortality data, focusing on differences in race and ethnicity
2023
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Overview
ObjectivesThe US Center for Disease Control and Prevention’s National Death Index (NDI) is a gold standard for mortality data, yet matching patients to the database depends on accurate and available key identifiers. Our objective was to evaluate NDI data for future healthcare research studies with mortality outcomes.MethodsWe used a Kaiser Permanente Mid-Atlantic States’ Virtual Data Warehouse (KPMAS-VDW) sourced from the Social Security Administration and electronic health records on members enrolled between 1 January 2005 to 31 December 2017. We submitted data to NDI on 1 036 449 members. We compared results from the NDI best match algorithm to the KPMAS-VDW for vital status and death date. We compared probabilistic scores by sex and race and ethnicity.ResultsNDI returned 372 865 (36%) unique possible matches, 663 061 (64%) records not matched to the NDI database and 522 (<1%) rejected records. The NDI algorithm resulted in 38 862 records, presumed dead, with a lower percentage of women, and Asian/Pacific Islander and Hispanic people than presumed alive. There were 27 306 presumed dead members whose death dates matched exactly between the NDI results and VDW, but 1539 did not have an exact match. There were 10 017 additional deaths from NDI results that were not present in the VDW death data.ConclusionsNDI data can substantially improve the overall capture of deaths. However, further quality control measures were needed to ensure the accuracy of the NDI best match algorithm.
Publisher
BMJ Publishing Group Ltd,BMJ Publishing Group LTD,BMJ Publishing Group
Subject
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