Linkage of Emergency Medical Services and Hospital Data: A Necessary Precursor to Improve Understanding of Outcomes of Prehospital Care.
Ian E BlanchardT S WilliamsonP RonksleyB HagelD NivenS DeanM N ShahE S LangC J DoigPublished in: Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors (2021)
Objective: Linking emergency medical services (EMS) data to hospital outcomes is important for quality assurance and research initiatives. However, non-linkage due to missing or incomplete patient information may increase the risk of bias and distort findings. The purpose of this study was to explore if an optimization strategy, in addition to an existing linkage process, improved the linkage rate and reduced selection and information bias.Methods: 4,150 transported patients in a metropolitan EMS system in Alberta, Canada from 2016/17 were linked to two Emergency Department (ED) databases by a standard strategy using a unique health care number, date/time of ED arrival, and hospital name. An optimized strategy added additional linkage steps incorporating last name, year of birth, and a manual search. The strategies were compared to assess the rate of linkage, and to describe event and patient-level characteristics of unlinked records.Results: The standard strategy resulted in 3,650 out of 4,150 (88.0%) linked records (95% CI 86.9%-88.9%). Of the 500 non-linked records, an additional 381 were linked by the optimized strategy (n = 4,031/4,150 [97.1%; 95% CI: 96.6%-97.6%]). There were no false positive linkages. The highest linkage failure was in 25 to 34 year-old patients (n = 93/478, 19.5%), males (n = 236/1975, 12.0%), Echo level events (n = 15/77, 19.5%), and emergency transport (45/231, 19.5%). The optimized strategy improved linkage in these groups by 68.8% (64/93), 79.2% (187/236), 40.0% (6/15), and 51.1% (23/45) respectively. For dispatch card, the highest linkage failure occurred in Card 24-Pregnancy/Childbirth/Miscarriage (n = 30/44, 68.2%), Card 27-Stab/Gunshot/Penetrating Trauma (n = 6/17, 35.3%), and Card 9-Cardiac/Respiratory Arrest/Death (n = 12/46, 26.1%). The optimized strategy improved linkage by 10.0% (3/30), 83.3% (5/6), and 41.7% (5/12) respectively. For the 119 unlinked records, 71 (59.7%) had sufficient information for linkage, but no appropriately matching records could be found.Conclusion: An optimized sequential deterministic strategy linking EMS data to ED outcomes improved the linkage rate without increasing the number of false positive links, and reduced the potential for bias. Even with adequate information, some records were not linked to their ED visit. This study underscores the importance of understanding how data are linked to hospital outcomes in EMS research and the potential for bias.
Keyphrases
- emergency medical
- emergency department
- healthcare
- genome wide
- hiv testing
- end stage renal disease
- men who have sex with men
- newly diagnosed
- ejection fraction
- chronic kidney disease
- big data
- primary care
- public health
- magnetic resonance
- dna methylation
- adipose tissue
- pregnant women
- computed tomography
- cardiac arrest
- health information
- peritoneal dialysis
- heart failure
- gene expression
- prognostic factors
- acute care
- adverse drug
- case report
- hepatitis c virus
- high density
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- cell proliferation
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- mental health
- atrial fibrillation
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- patient reported outcomes
- type diabetes