"THE DOCTORS TALK LIKE WE DON’T KNOW WHAT WE ARE DOING”: Could new technologies like Artificial Intelligence (AI) help erase this sentiment in sub-Saharan Africa?
The world’s foremost authority on healthcare issued a 150-page guidance on Artificial Intelligence for Healthcare, and that can be taken as a sign that officially, the healthcare world has begun to take AI seriously [1]. The consensus seems to be that despite the challenges to be overcome in implementing AI effectively and safely, its potential for improving healthcare delivery cannot be denied. In 2020, the American Medical Association shared an article on 10 ways AI could transform primary care [2]. 8/10 out of about 1000 physicians recently surveyed in the United States agree [3].
In the Ghanaian Health System, there are principally, four main levels of care: Community-based Health Planning and Services (CHPS) Zones, Health Centres/Polyclinics, District Hospitals and Regional Hospitals [4]. These are arranged in order of complexity and thus clinical cases that cannot be well-managed at a lower-level facility are referred to a higher-level facility along that chain. I have had the opportunity to work for a while in a health centre (one level above a CHPS compound) with one clinician at the helm. He was the primary clinician, administrator and supervisor all-in-one . This health centre was the only one in the capital town of a district, and one in 10 serving that district of 90,000+ inhabitants in Ghana. Under-resourced and overworked, he would complain bitterly about getting unpleasant feedback on how some conditions were managed from doctors in higher-level facilities when he referred patients. He felt it was unfair not to be given due appreciation about the efforts he and his little team put in. In his words: “The doctors talk like we don’t know what we are doing, meanwhile we are the ones taking care of these communities”.
I have also been on the other side, at a district-level hospital which is a referral centre for health centres, and observed how the staff would be frustrated by how conditions were managed prior to referral. There is frustration on both sides and ultimately it is the patient who suffers. This is just one of the many everyday problems faced in healthcare delivery in sub-Saharan Africa that a technology like AI might help reduce.
This has been one of the big topics of discussion for the team at SnooCODERED – improving healthcare in resource-constrained settings, for emergencies and for public health. We drew inspiration from interactions we had a year ago at the African Conference for Emergency Medicine, where some visitors to our booth commended our work with the SnooCODERED Control Centre system, and asked if it could help with a few first-aid tips for less educated paramedics once it directed them to the emergency scene. We realised that with AI, even non-professional first responders could receive first-aid and triage instructions before a victim is transported to a health facility. We thought about how such a system could help in primary healthcare as well, where ultimately, patients could ask a mobile device questions and get access to sound medical advice and even virtual consultations with a healthcare provider. The primary clinician at the CHPS compound or the polyclinic could also use the AI-powered tool to better diagnose and triage patients, reducing the stress on doctors at higher-level facilities.
We brainstormed on how to measure the benefits, or otherwise, of such a tool in a rural setting in sub-Sahara Africa. One suggestion was to set up a study with a pre-test-post-test experimental design where inhabitants are asked about how often they would wish to access quality healthcare annually, how often they actually do, and the ease of access, before and after the device is installed, and their responses compared. What do you think are effective ways to assess the benefits of an AI tool in primary healthcare settings in resource-constrained settings?
–DR. PAULINA MENSAH, SnooCODE TECHNOLOGIST (DATA SCIENCE)
REFERENCES
1. Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: World Health Organization; 2021. Licence: CC BY-NC-SA 3.0 IGO.
2. American Medical Association. (n.d.). 10 ways health care AI could transform primary care. AMA. Retrieved February 23, 2024, from https://www.ama-assn.org/practice-management/digital/10-ways-health-care-ai-could-transform-primary-care
3. athenahealth. (n.d.). US physicians surveyed feel burned out on a regular basis. athenahealth. Retrieved February 23, 2024, from https://www.athenahealth.com/press-releases/us-physicians-surveyed-feel-burned-out-on-a-regular-basis.
4. Ghana Health Service. (n.d.). Organization Of GHS. Retrieved March 4, 2024, from https://ghs.gov.gh/organization-of-ghs%EF%BF%BC/.