Utilizing E-coded data for nonfatal injury surveillance in the pediatric emergency department setting: a literature review and recommendations

Children's injury database: development of an injury surveillance system in a pediatric emergency department

BACKGROUND

Injuries are the leading cause of death in children and are also a leading cause of all emergency department (ED) visits for children. Obtaining epidemiologic data to define the wide range of childhood injuries for individual communities is challenging. The Children's Injury Database (CID) is an injury surveillance system developed to collect data from injury-related visits to our tertiary care pediatric emergency department.

RESULTS

During 2021, a total of 15,168 injury visits were analyzed representing 22% of total ED visits (68,834). A total of 2053 injury visits (13.5%) resulted in hospital admission. The 10 leading injury types included: falls, poisonings, motor vehicle collision (MVC), assault, dog bite, burns, sports, pedestrian, bicycle, and all-terrain vehicle (ATV). Admission rates varied by age group with children ages 13 years and older having the highest rate of admission (18.4%). The median length of stay (LOS) for all injured children requiring admission was 2 days while the median LOS for preschoolers was 1 day, the median LOS for school-age children was 2 days, and the median LOS for teenagers was 3 days. While MVCs were the most common cause of vehicle-related injuries, ATV-related injuries had the highest rate of admission (51%).

CONCLUSIONS

In this study, teenagers had significantly higher admission rates, lengths of stay, and hospital charges. Black and Hispanic children were under-represented in the number of visits for injuries compared to all ED visits. Further research should focus on disparities in injury-related visits based on race as well as gender. CID has demonstrated that injury surveillance systems can assist with reporting new injury patterns while also acting as a stimulus for new research ideas, planning interventions targeting the most at-risk populations, and evaluating the effectiveness of injury prevention interventions.

The Pakistan National Emergency Department Surveillance Study (Pak-NEDS): Introducing a pilot surveillance

BACKGROUND

Evidence-based decision making is essential for appropriate prioritization and service provision by healthcare systems. Despite higher demands, data needs for this practice are not met in many cases in low- and middle-income countries because of underdeveloped sources, among other reasons. Emergency departments (EDs) provide an important channel for such information because of their strategic position within healthcare systems. This paper describes the design and pilot test of a national ED based surveillance system suitable for the Pakistani context.

METHODS

The Pakistan National Emergency Department Surveillance Study (Pak-NEDS) was pilot tested in the emergency departments of seven major tertiary healthcare centres across the country. The Aga Khan University, Karachi, served as the coordinating centre. Key stakeholders and experts from all study institutes were involved in outlining data needs, development of the study questionnaire, and identification of appropriate surveillance mechanisms such as methods for data collection, monitoring, and quality assurance procedures. The surveillance system was operational between November 2010 and March 2011. Active surveillance was done 24 hours a day by data collectors hired and trained specifically for the study. All patients presenting to the study EDs were eligible participants. Over 270,000 cases were registered in the surveillance system over a period of four months. Coverage levels in the final month ranged from 91-100% and were highest in centres with the least volume of patients. Overall the coverage for the four months was 79% and crude operational costs were less than $0.20 per patient.

CONCLUSIONS

Pak-NEDS is the first multi-centre ED based surveillance system successfully piloted in a sample of major EDs having some of the highest patient volumes in Pakistan. Despite the challenges identified, our pilot shows that the system is flexible and scalable, and could potentially be adapted for many other low- and middle-income settings.