Addressing global inequities in surgery with the FAIR and CARE principles

Surgical training and integrated service delivery often struggles to deliver on the principles of distributive justice, which aims to distribute resources fairly.Distributive justice concentrates on outcomes and aims to identify inequalities in resources and to deliver equity.Globally there are huge disparities in access to surgical expertise.The Lancet-commissioned review on Global Surgery 2030 1 concluded that nearly five billion people do not have access to surgical care.Approximately 94% of individuals in high-income countries have access to surgery compared to only 14.9% in low-and middle-income countries (LMIC).It is estimated that the cost to train the identified shortfall of 2.2 million surgeons and anaesthetists required for LMIC to have parity would be a staggering $350 billion 1 .However, the loss to income in LMIC from premature death and chronic illness related to this lack of surgical intervention is estimated at $12.3 trillion 1 .The Commission's findings indicate that the human and economic consequences of untreated surgical conditions in LMIC are the number one issue in healthcare, with a greater negative socioeconomic impact than malaria, TB, and HIV combined 1 .However, disparities are not limited to LMIC and an increasing focus on quality performance reporting following surgery has highlighted disparities in the quality-of-care patients receive in the USA 2 .Research on surgical disparities has identified elements such as race/ethnicity, socioeconomic status, and other demographic factors which correlate with adverse patient outcomes after surgery 3 .As surgical quality improvement programmes proliferate, we must return to one of the central tenets of the National Institute of Health-American College of Surgeons Symposium on Surgical Disparities Research: 'No quality without access'.Access to surgical expertise requires awareness of the need to train more surgeons to benchmarked skill levels, agreement on what those benchmarks are and how they are set.Another key element is decision-making in diagnosis, patient selection, treatment, and recovery.Do you have 'the right patient, for the right surgeon, at the right time in their learning curve'?One of the goals of surgical data science is to use data normalization to standardize metrics of surgical performance to better understand performance and evaluate decision-making 4 .Given the disparities linked to geography and socioeconomic status the challenge then becomes how to make these metrics and training materials accessible, applicable, and affordable to all.Sharing knowledge and objectively defining skills has the added