Accuracy of EMS-Recorded Patient Demographic Data

Abstract

Objective. Emergency medical services (EMS) research is frequently dependent on data recorded by prehospital personnel. Linking EMS information with hospital outcome depends on essential identifying data. We sought to determine the accuracy of these data in patients who activated EMS for chest pain and to describe the types of errors committed. Methods. We performed a retrospective, consecutive case series study of all prehospital records for patients transported by the City of Pittsburgh Bureau of EMS (annual call volume, 60,000) for chest pain to three area hospitals during a three-month interval. Demographic data, including name, date of birth (DOB), and Social Security number (SSN), for each patient were extracted from the EMS record. These were compared to the definitive information in the hospital records. Results. 360 prehospital records were examined, with 341 matches to hospital records. The correct patient name was recorded in 301 records (83.6%), the correct DOB was recorded 284 times (78.9%), and the correct SSN was recorded 120 times (33.3%). The overall error rate of demographic data recorded on EMS records was 73.9% (266/360). If SSN is not included as a demographic variable, then the overall error rate was 25.3% (91/360). Conclusion. The use of EMS-generated demographic data demonstrates moderate agreement and linkage with hospital records. Name and DOB are more reliable data elements for matching than SSN. Future research should examine the impact of electronic medical records and EMS identification numbers on data reliability.

A Qualitative Assessment of Factors That Influence Emergency Medical Services Partnerships in Prehospital Research

“…Individual EMS investigators have raised concerns about human subjects protections, including availability of institutional review boards, informed consent in the emergency setting, preservation of patient confidentiality, and safe transfer of patient data 14–16 . They have also raised methodologic concerns such as lack of standardized data definitions, lack of reliable patient randomization techniques, and lack of focus on system‐based research 12–22 . While these challenges are clearly important and were mentioned by individual subjects in our study, they were not as pronounced, suggesting that they are not as strong an influence on research participation at the agency and provider levels.…”

“…Limited attention, however, was paid to the obstacles faced at the agency and provider levels, which may be more amenable to change by individual investigators. EMS researchers have independently outlined the obstacles that they faced while conducting prehospital research 10–22 . While these experiences provide important insights into the potential challenges faced by the EMS researcher, they only provide one side of the story.…”

Accuracy of Emergency Medical Services–Reported Last Known Normal Times in Patients Suspected With Acute Stroke

“…One study evaluated the accuracy of EMS-collected demographic information including name, date of birth, and social security number for all-comers to a single emergency department. 7 The overall accuracy in data collected was 74%; varying from 33% for social security number to 83% for patient name. The accuracy of pediatric weight estimates by EMS was evaluated in children needing prehospital medication administration en-route, demonstrating 82% accuracy for EMS weight estimates (within 20% of actual weights).…”

Analysis of Patient Forms of Prehospital Emergency Medical Services

“…Brice ve ark. yaptıkları çalışmada Acil Mobil Sistem kayıtları ile hastane kayıtlarını karşılaştırdıkları çalışmalarında %5 veriyi kullanamadıklarını bildirmişlerdir(6). Downing ve ark.…”

“…Brice ve ark. Acil Mobil Sistem kayıtlarına dayanan demografik verilerin makul ölçüde doğru olduğunu, hasta adının, doğum tarihini takip eden en güvenli bilgiyi sağladığını, sosyal güvenlik numarasının ise seyrek kaydedilen son derece güvenilmez bir veri olduğunu düşündüklerini bildirmişlerdir(6). Bizim çalışmamızda da hasta adı en sık kaydedilen demografik veri iken (%63.8) sosyal güvenlik bilgileri enaz kaydedilen bilgi idi (%11.1).…”