Global surgery broadly refers to a rapidly expanding multidisciplinary field concerned with providing better and equitable surgical care across international health systems. Global surgery initiatives primarily focus on capacity building, advocacy, education, research, and policy development in low-and middle-income countries (LMICs). The inadequate surgical, anesthetic, and obstetric care currently contributes to 18 million preventable deaths each year. Hence, there is a growing interest in the rapid growth of artificial intelligence (AI) that provides a distinctive opportunity to enhance surgical services in LMICs. AI modalities have been used for personalizing surgical education, automating administrative tasks, and developing realistic and cost-effective simulation-training programs with provisions for people with special needs. Furthermore, AI may assist with providing insights for governance, infrastructure development, and monitoring/predicting stock take or logistics failure that can help in strengthening global surgery pillars. Numerous AI-assisted telemedicine-based platforms have allowed healthcare professionals to virtually assist in complex surgeries that may help to improve surgical accessibility across LMICs. Challenges in implementing AI technology include the misrepresentation of minority populations in the datasets leading to discriminatory bias. Human hesitancy, employment uncertainty, automation bias, and role of confounding factors need to be further studied for equitable utilization of AI. With a focused and evidence-based approach, AI could help several LMICs overcome bureaucratic inefficiency and develop more efficient surgical systems.
AimsWithin healthcare, several measures are used to quantify and compare the severity of health conditions. Two common measures are disability weight (DW), a context-independent value representing severity of a health state, and utility weight (UW), a context-dependent measure of health-related quality of life. Neither of these measures have previously been determined for developmental dysplasia of the hip (DDH). The aim of this study is to determine the DW and country-specific UWs for DDH.MethodsA survey was created using three different methods to estimate the DW: a preference ranking exercise, time trade-off exercise, and visual analogue scale (VAS). Participants were fully licensed orthopaedic surgeons who were contacted through national and international orthopaedic organizations. A global DW was calculated using a random effects model through an inverse-variance approach. A UW was calculated for each country as one minus the country-specific DW composed of the time trade-off exercise and VAS.ResultsOver a four-month period, 181 surgeons participated in the survey, with 116 surgeons included in the final analysis. The global DW calculated to be 0.18 (0.11 to 0.24), and the country-specific UWs ranged from 0.26 to 0.89.ConclusionThis is the first time that a global disability weight and country-specific utility weights have been estimated for DDH, which should assist in economic evaluations and the development of health policy. The methodology may be applied to other orthopaedic conditions.Cite this article: Bone Jt Open 2023;4(3):120–128.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.