Using an electronic medical record system to describe injury epidemiology and health care utilization at an inner-city hospital in Indiana.
Injuries are a major public health problem worldwide. In the USA, injuries cause 146, 400 deaths annually, with 31 million non-fatal injury visits to emergency departments (EDs). EDs thus represent an important source of injury data. The primary objective of the current study was to describe the epidemiology of injury-related ED visits and assess injury-related utilization of health care resources in an inner-city hospital in Indiana, using data stored in a computerized medical record system. It involved a retrospective review of the records for injury visits to EDs and injury admissions over a 3-year period. The variables extracted and analysed included patients' demographics, external cause of injury, diagnosis, length of stay, ED and hospital charges. A total of 60,470 injury-related ED visits were made, the majority of patients were male (61.6%), uninsured (63.1%), treated in ED and discharged (98.4%). The leading causes of injury were falls (18.8%), motor vehicle crashes (18.4%), assaults (17.6%), being struck (11.2%) and overexertion (10.6). Firearms caused most injury deaths (32.4%; n = 314); motor vehicle crashes were the leading cause of hospitalization (26.6%; n = 642) and also the most expensive to treat as inpatients (mean charge $19,190). The mean charge per patient treated and discharged was $150 compared to $11,116 for patients admitted. These findings demonstrate the value of computerized medical records in capturing and storing E-coded injury data. The system generates data that can be used for epidemiological surveillance and injury prevention at the local level, and for assessment of impact of specific injuries on health care resources.
Odero
Wilson W
WW
Regenstrief Institute for Health Care, Indianapolis, IN, USA.
Tierney
William M
WM
Einterz
Robert M
RM
Mungai
Simon
S
D000058:Accidental Falls / Q000706:statistics & numerical data; D000063:Accidents, Traffic / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data*; D017722:Hospital Charges / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D007196:Indiana / Q000453:epidemiology; D007223:Infant; D007231:Infant, Newborn; D007348:Insurance, Health / Q000706:statistics & numerical data; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D012044:Regression Analysis; D017678:Sex Distribution; D014754:Violence / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000453:epidemiology*