10093711AI-driven inclusive remote primary care triaging and clinical decision support system to tackle healthcare access inequality.ClosedInvestment AcceleratorInnovate UKThis project aims to deliver an inclusive AI-driven remote primary care triaging and clinical decision support system, The National Institute for Health and Care Excellence (NICE) reported that in England alone treating illness and disease arising from health inequalities cost the NHS an estimated £5.5 billion each year \[ Marmot Review report, 2010; NHS Inequalities Resource, Sep 2018\]. Several studies have also highlighted how the COVID-19 pandemic has widened and amplified the inherent inequalities of gender and race. Language, culture, legal, inadequate race-specific medical training biases among clinicians, and accessibility to a health professional (average 10 days of waiting time for routine GP appointment ) are some of the key barriers contributing to these inequalities \[COVID-19 and disparities affecting ethnic minorities, [Ali][0] S N & Morales D R, Lancet, 2021; \]. Alleviating these inequalities using an AI system often fails to meet the need, because the existing medical data itself is racially biased and incomplete. The developed triaging and decision support solution will be part of the MedAi digital healthcare platform. The platform has several components such as a voice-interactive multilingual symptom checker to enable ethnic Bengalis to report their symptoms in their preferred language and request medical appointments. The AI-powered clinical decision support system will offer provisional diagnosis to healthcare providers by combining patients' symptoms, medical history, and insights from the disease prevalence of similar patients for faster diagnosis. This data-driven way of communication and ability to communicate in their own language will empower patients, especially female patients from ethnic minority groups, to better express their concerns to their healthcare providers. Electronic consultation requests with a provisional diagnosis will help the administration staff manage appointment requests faster and allocate their time to serve more vulnerable patients. This will make the primary care service more accessible, and inclusive and reduce the inequality-driven illness and the cost of treating them. The solution will be first rolled out to community pharmacies and general practices with a high ethnic South Asian population before being gradually rolled out nationwide. [0]: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)00949-1/fulltext