How vital are the vital signs? A multi-center observational study from emergency departments of Pakistan.

BACKGROUND: Vital signs play a critical role in prioritizing patients in emergency departments (EDs), and are the foundation of most triage methods and disposition decisions. This study was conducted to determine the frequency of vital signs documentation anytime during emergency department treatment and to explore if abnormal vital signs were associated with the likelihood of admission for a set of common presenting complaints. METHODS: Data were collected over a four-month period from the EDs of seven urban tertiary care hospitals in Pakistan. The variables included age, sex, hospital type (government run vs. private), presenting complaint, ED vital signs, and final disposition. Patients who were >12 years of age were included in the analysis. The data were analyzed to describe the proportion of patients with documented vitals signs, which was then crossed-tabulated with top the ten presenting complaints to identify high-acuity patients and correlation with their admission status. RESULTS: A total of 274,436 patients were captured in the Pakistan National Emergency Department Surveillance (Pak-NEDS), out of which 259,288 patients were included in our study. Vital signs information was available for 90,569 (34.9%) patients and the most commonly recorded vitals sign was pulse (25.7%). Important information such as level of consciousness was missing in the majority of patients with head injuries. Based on available information, only 13.3% with chest pain, 12.8% with fever and 12.8% patients with diarrhea could be classified as high-acuity. In addition, hospital admission rates were two- to four-times higher among patients with abnormal vital signs, compared with those with normal vital signs. CONCLUSION: Most patients seen in the EDs in Pakistan did not have any documented vital signs during their visit. Where available, the presence of abnormal vital signs were associated with higher chances of admission to the hospital for the most common presenting symptoms.

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.