Geoffrey A Anderson1, Lenka Ilcisin2, Joseph Ngonzi3, Stephen Ttendo4, Deus Twesigye5, Noralis Portal Benitez6, Paul Firth7, Deepika Nehra8. 1. Department of Surgery, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02144, USA. 2. Department of Surgery, Brigham and Women's Hospital, 75 Francis St, ASB II L1, Boston, MA, 02115, USA. 3. Department of Obstetrics and Gynecology, Mbarara University of Science and Technology, PO Box 1410, Mbarara, Uganda. 4. Department of Anesthesia and Critical Care, Mbarara University of Science and Technology, PO Box 1410, Mbarara, Uganda. 5. Department of Surgery, Mbarara Regional Referral Hospital, Mbarara, Uganda. 6. Department of Surgery, Mbarara University of Science and Technology, PO Box 1410, Mbarara, Uganda. 7. Department of Anesthesia, Critical Care and Pain Management, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02144, USA. 8. Department of Surgery, Brigham and Women's Hospital, 75 Francis St, ASB II L1, Boston, MA, 02115, USA. dnehra@bwh.harvard.edu.
Abstract
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.
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.
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