Literature DB >> 11604954

Adding value to clinical data by linkage to a public death registry.

R D Pates1, K W Scully, J S Einbinder, R L Merkel, G J Stukenborg, T A Spraggins, C Reynolds, R Hyman, B P Dembling.   

Abstract

We describe the methodology and impact of merging detailed statewide mortality data into the master patient index tables of the clinical data repository (CDR) of the University of Virginia Health System (UVAHS). We employ three broadly inclusive linkage passes (designed to result in large numbers of false positives) to match the patients in the CDR to those in the statewide files using the following criteria: a) Social Security Number; b) Patient Last Name and Birth Date; c) Patient Last Name and Patient First Name. The results from these initial matches are refined by calculation and assignment of a total score comprised of partial scores depending on the quality of matching between the various identifiers. In order to validate our scoring algorithm, we used those patients known to have died at UVAHS over the eight year period as an internal control. We conclude that we are able to update our CDR with 97% of the deaths from the state source using this scheme. We illustrate the potential of the resulting system to assist caregivers in identification of at-risk patient groups by description of those patients in the CDR who were found to have committed suicide. We suggest that our approach represents an efficient and inexpensive way to enrich hospital data with important outcomes information.

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Year:  2001        PMID: 11604954

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  7 in total

1.  Analysis of identifier performance using a deterministic linkage algorithm.

Authors:  Shaun J Grannis; J Marc Overhage; Clement J McDonald
Journal:  Proc AMIA Symp       Date:  2002

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Authors:  Shaun J Grannis; J Marc Overhage; Siu Hui; Clement J McDonald
Journal:  AMIA Annu Symp Proc       Date:  2003

3.  An empiric modification to the probabilistic record linkage algorithm using frequency-based weight scaling.

Authors:  Vivienne J Zhu; Marc J Overhage; James Egg; Stephen M Downs; Shaun J Grannis
Journal:  J Am Med Inform Assoc       Date:  2009-06-30       Impact factor: 4.497

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Authors:  Patrick G Northup; Michael M Abecassis; Michael J Englesbe; Jean C Emond; Vanessa D Lee; George J Stukenborg; Lan Tong; Carl L Berg
Journal:  Liver Transpl       Date:  2009-02       Impact factor: 5.799

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Authors:  Charles Frey; Hong Zhou; Danielle Harvey; Richard H White
Journal:  J Gastrointest Surg       Date:  2007-06       Impact factor: 3.452

6.  Sharing and Reuse of Sensitive Data and Samples: Supporting Researchers in Identifying Ethical and Legal Requirements.

Authors:  Murat Sariyar; Irene Schluender; Carol Smee; Stephanie Suhr
Journal:  Biopreserv Biobank       Date:  2015-07-17       Impact factor: 2.300

7.  Development of South Australian-Victorian Prostate Cancer Health Outcomes Research Dataset.

Authors:  Rasa Ruseckaite; Kerri Beckmann; Michael O'Callaghan; David Roder; Kim Moretti; John Zalcberg; Jeremy Millar; Sue Evans
Journal:  BMC Res Notes       Date:  2016-01-22
  7 in total

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