Surgical, Obstetric, and Anesthetic Mortality Measurement at a Ugandan Secondary Referral Hospital.

BACKGROUND: The health care systems of low-income countries have severely limited capacity to treat surgical diseases and conditions. There is limited information about which hospital mortality outcomes are suitable metrics in these settings. METHODS: We did a 1-year observational cohort study of patient admissions to the Surgery and the Obstetrics and Gynecology departments and of newborns delivered at a Ugandan secondary referral hospital. We examined the proportion of deaths captured by standardized metrics of mortality. RESULTS: There were 17,015 admissions and 9612 deliveries. A total of 847 deaths were documented: 385 (45.5%) admission deaths and 462 (54.5%) perinatal deaths. Less than one-third of admission deaths occurred during or after an operation (n = 126/385, 32.7%). Trauma and maternal mortality combined with perioperative mortality produced 79.2% (n = 305/385) of admission deaths. Of 462 perinatal deaths, 412 (90.1%) were stillborn, and 50 (10.9%) were early neonatal deaths. The combined metrics of the trauma mortality rate, maternal mortality ratio, thirty-day perioperative mortality rate, and perinatal mortality rate captured 89.8% (n = 761/847) of all deaths documented at the hospital. CONCLUSIONS: The combination of perinatal, maternal, trauma, and perioperative mortality metrics captured most deaths documented at a Ugandan referral hospital.

Validation of an Electronic Surgical Outcomes Database at Mbarara Regional Referral Hospital, Uganda.

BACKGROUND: Accurate, complete and sustainable methods of tracking patients and outcomes in low-resource settings are imperative as we launch efforts to improve surgical care globally. The Surgical services QUality Assessment Database (SQUAD) at the Mbarara Regional Referral Hospital in Uganda is one of very few electronic surgical databases in a low-resource setting. We evaluated the completeness and accuracy of SQUAD. METHODS: Data were prospectively collected on 20 of the most clinically relevant variables captured by SQUAD for all general surgery patients admitted to MRRH over a two-week period. Patients were followed until discharge, death or hospital day 30; whichever occurred first. These data were compared to that in SQUAD for the same time period for completeness and accuracy. RESULTS: Of 186 unique patients seen over the two-week period, 172 (92.5%) were captured by SQUAD. The capture rate was greater than 86% for each of the 20 variables evaluated, except American Society of Anesthesiologists score, which had a 69% capture rate. Regarding accuracy, there was almost perfect agreement for 16/20 variables (all k > 0.81), substantial agreement for 2/20 variables (k 0.63, 0.73) and moderate agreement for the remaining 2/20 variables (k 0.43, 0.48) between SQUAD and the prospectively collected data. CONCLUSION: SQUAD is an electronic surgical database that has been implemented and sustained in a low-resource setting. For the 20 variables evaluated, the data within SQUAD are highly complete and accurate. This database may serve as a model for the development of additional surgical databases in low-resource environments.