TY - JOUR
T1 - Building A Longitudinal Cohort From 9-1-1 to 1-Year Using Existing Data Sources, Probabilistic Linkage, and Multiple Imputation
T2 - A Validation Study
AU - Newgard, Craig D.
AU - Malveau, Susan
AU - Zive, Dana
AU - Lupton, Joshua
AU - Lin, Amber
N1 - Funding Information:
From the Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University (CDN, SM, DZ, JL, AL), Portland, OR. Received April 6, 2018; revision received June 18, 2018; accepted June 20, 2018. This project was supported by grant R01HS023796 from the Agency for Healthcare Research and Quality (AHRQ). The content is solely the responsibility of the authors and does not necessarily represent the official views of AHRQ. The authors have no potential conflicts to disclose. Author Contributions: CDN conceived of and designed the study and obtained research funding; CDN, SM, AL, and DZ assisted with data acquisition; SM performed all probabilistic linkage; AL and SM performed database management and creation of variables from the linked data; CDN developed the multiple imputation models; JL performed the independent linkage validation; AL conducted all statistical analyses; All authors helped interpret the data; CDN drafted the manuscript and all authors contributed substantially to manuscript revisions; and CDN takes responsibility for the paper as a whole. Supervising Editor: Manish N. Shah, MD, MPH. Address for correspondence and reprints: Craig D. Newgard, MD, MPH; e-mail: newgardc@ohsu.edu. ACADEMIC EMERGENCY MEDICINE 2018;25:1268–1283.
Publisher Copyright:
© 2018 by the Society for Academic Emergency Medicine
PY - 2018/11
Y1 - 2018/11
N2 - 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.
AB - 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.
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U2 - 10.1111/acem.13512
DO - 10.1111/acem.13512
M3 - Article
C2 - 29969840
AN - SCOPUS:85051077202
SN - 1069-6563
VL - 25
SP - 1268
EP - 1283
JO - Academic Emergency Medicine
JF - Academic Emergency Medicine
IS - 11
ER -