Providing Anesthesia Care in Resource-limited Settings: A 6-year Analysis of Anesthesia Services Provided at Médecins Sans Frontières Facilities.

BACKGROUND: Anesthesia is integral to improving surgical care in low-resource settings. Anesthesia providers who work in these areas should be familiar with the particularities associated with providing care in these settings, including the types and outcomes of commonly performed anesthetic procedures. METHODS: The authors conducted a retrospective analysis of anesthetic procedures performed at Médecins Sans Frontières facilities from July 2008 to June 2014. The authors collected data on patient demographics, procedural characteristics, and patient outcome. The factors associated with perioperative mortality were analyzed. RESULTS: Over the 6-yr period, 75,536 anesthetics were provided to adult patients. The most common anesthesia techniques were spinal anesthesia (45.56%) and general anesthesia without intubation (33.85%). Overall perioperative mortality was 0.25%. Emergent procedures (0.41%; adjusted odds ratio [AOR], 15.86; 95% CI, 2.14 to 115.58), specialized surgeries (2.74%; AOR, 3.82; 95% CI, 1.27 to 11.47), and surgical duration more than 6 h (9.76%; AOR, 4.02; 95% CI, 1.09 to 14.88) were associated with higher odds of mortality than elective surgeries, minor surgeries, and surgical duration less than 1 h, respectively. Compared with general anesthesia with intubation, spinal anesthesia, regional anesthesia, and general anesthesia without intubation were associated with lower perioperative mortality rates of 0.04% (AOR, 0.10; 95% CI, 0.05 to 0.18), 0.06% (AOR, 0.26; 95% CI, 0.08 to 0.92), and 0.14% (AOR, 0.29; 95% CI, 0.18 to 0.45), respectively. CONCLUSIONS: A wide range of anesthetics can be carried out safely in resource-limited settings. Providers need to be aware of the potential risks and the outcomes associated with anesthesia administration in these settings.

Open Source Software For Patient Data Management In Critical Care.

We have previously developed a Patient Data Management System for Intensive Care based on Open Source Software. The aim of this work was to adapt this software to use in Emergency Departments in low resource environments. The new software includes facilities for utilization of the South African Triage Scale and prediction of mortality based on independent predictive factors derived from data from the Tabarre Emergency Trauma Center in Port au Prince, Haiti.