Literature DB >> 29969840

Building A Longitudinal Cohort From 9-1-1 to 1-Year Using Existing Data Sources, Probabilistic Linkage, and Multiple Imputation: A Validation Study.

Craig D Newgard1, Susan Malveau1, Dana Zive1, Joshua Lupton1, Amber Lin1.   

Abstract

OBJECTIVE: The objective was to describe and validate construction of a population-based, longitudinal cohort of injured older adults from 9-1-1 call to 1-year follow-up using existing data sources, probabilistic linkage, and multiple imputation.
METHODS: This was a descriptive cohort study conducted in seven counties in Oregon and Washington from January 1, 2011, through December 31, 2011, with follow-up through December 31, 2012. The primary cohort included all injured adults ≥ 65 years served by 44 emergency medical services (EMS) agencies. We used nine existing databases to assemble the cohort, including EMS data, two state trauma registries, two state discharge databases, two state vital statistics databases, the Oregon Physician Order for Life-Sustaining Treatment registry, and Medicare claims data. We matched data files using probabilistic linkage and handled missing values with multiple imputation. We independently validated data processes using 1,350 randomly sampled records for probabilistic linkage and 3,140 randomly sampled records for variables created from existing data sources.
RESULTS: There were 15,649 injured older adults in the primary cohort, with 13,661 (87.3%) total matched records and 9,337 (59.7%) matches to the index ED/hospital visit. The sensitivity of linkage was 99.9% (95% confidence interval [CI] = 99.3%-100%) for any match and 98.3% (95% CI = 96.2%-99.4%) for index event matches. The specificity of linkage was 95.7% (95% CI = 93.7%-97.2%) for any match and 100% (95% CI = 99.2%-100%) for index event matches. Name, date of birth, home zip code, age, and hospital had the highest yield for linkage. Patients with matched records tended to be higher acuity than unmatched patients, suggesting selection bias if unmatched patients were excluded. Compared to hand-abstracted values, the sensitivity of electronically derived variables ranged from 18.2% (abdominal-pelvic Abbreviated Injury Scale score ≥ 3) to 97.4% (in-hospital mortality), with specificity of 88.0% to 99.8%.
CONCLUSIONS: A population-based emergency care cohort with long-term outcomes can be constructed from existing data sources with high accuracy and reasonable validity of resulting variables.
© 2018 by the Society for Academic Emergency Medicine.

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Mesh:

Year:  2018        PMID: 29969840     DOI: 10.1111/acem.13512

Source DB:  PubMed          Journal:  Acad Emerg Med        ISSN: 1069-6563            Impact factor:   3.451


  4 in total

1.  Comorbidities, anticoagulants, and geriatric-specific physiology for the field triage of injured older adults.

Authors:  Craig D Newgard; Amber Lin; Elizabeth Eckstrom; Aaron Caughey; Susan Malveau; Denise Griffiths; Dana Zive; Eileen Bulger
Journal:  J Trauma Acute Care Surg       Date:  2019-05       Impact factor: 3.313

2.  Comparison of Injured Older Adults Included in vs Excluded From Trauma Registries With 1-Year Follow-up.

Authors:  Craig D Newgard; Aaron Caughey; K John McConnell; Amber Lin; Elizabeth Eckstrom; Denise Griffiths; Susan Malveau; Eileen Bulger
Journal:  JAMA Surg       Date:  2019-09-18       Impact factor: 14.766

3.  Application of the Whole Optimization of Emergency Nursing Model United and Its Influence on Patients' Stress Response and Nursing Satisfaction.

Authors:  Dannan Ai; Sumin Xu
Journal:  Appl Bionics Biomech       Date:  2022-05-28       Impact factor: 1.664

4.  Enhancing Human Biomonitoring Studies through Linkage to Administrative Registers-Status in Europe.

Authors:  Helle Margrete Meltzer; Tina Kold Jensen; Ondřej Májek; Hanns Moshammer; Maria Wennberg; Agneta Åkesson; Hanna Tolonen
Journal:  Int J Environ Res Public Health       Date:  2022-05-06       Impact factor: 3.390

  4 in total

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