M'Care AI

With a global acute shortage of healthcare professionals at 100 times less than the ideal, it will take us 800 years to match the ideal ratio of physicians to patients (1:600) as recommended by the World Health Organization (WHO). This acute shortage of healthcare professionals disproportionately affects patients with rare and complicated diseases who require a team of specialists and caregivers to monitor and ultimately halt disease progression for an improved quality of life. Yet, 300m people living with 6,000 identified rare diseases, 70% starting at childhood, there are simply not enough specialised care teams to support every patient, monitor and eventually contribute their clinical and scientific insights to accelerate the development of therapeutic agents. 

African patients with rare diseases, living in rural communities are worse off. They live far away from hospitals and healthcare professionals hence with no access to a specialised care team for diagnosis and disease management; they are mostly low income and lack health insurance hence the onset of rare diseases at childhood typically tips families into abject poverty. It is therefore no surprise that Sub-Saharan Africa has the highest under 5-year mortality rate according to UNICEF as most children with rare diseases die before they reach the age of 5 in Africa. The WHO alludes to this, identifying pre-term birth complications and congenital anomalies as 1 of the top 7 leading causes of death for children under 5 years.

M'Care AI is an artificial intelligence decision support solution providing decision support for community health workers to triage, diagnose, treat, manage cases, referrals and coordinated response to primary and complex diseases with local health authorities. Using advanced analytics and machine learning, M'Care also predicts disease progression for complex diseases and prescribes actions to healthcare teams that could mitigate and alleviate symptoms. The information is relayed to health authorities for coordinated responses as precise cases are identified and prioritised for coordinated support. The precise guidance received through M'Care AI's provides insights for the right course of action for clinicians; maximising scarce healthcare resources while incorporating families and community health workers as caregivers in disease management to limit dependence on unavailable healthcare professionals. 

M'Care AI is available to registered community health workers in rural communities with no doctors. Most patients seeking care from the community health workers live on less than $2 a day and have no health insurance.

M'Care AI connects rural communities to the overall healthcare system to ensure government managed health funds are targeted to indigent patients who need care, particularly children under 5 years with rare diseases; allocating scarce healthcare resources judiciously.

Hence, M'Care helps identify, accelerate access to specialised care and treatment for patients with rare diseases who will otherwise not have access to care teams and the financial capability to manage a rare disease.

Our team represents a diverse range of skills in Behavioural science, Medical Science and Public health, Pharmacy and Supply Chain management, Software engineering, data science, AI/ML, epidemiology, finance and linguists. The broad range gives us a healthy balance of skills for design thinking to uncover ethnographic insights, technology adaptation and business modelling. 

With over 350 community health workers embedded and living in the communities we serve, we have first insights on patient's lived experience and care journey.

Opeoluwa Ashimi, the CEO and Founder is a Digital Health Specialist, a Pharmacist and former community health worker with an MBA (UK). A United Nations Equals Fellows and USAID  Mandela Washington fellow, She has 15 years of experience working within multidisciplinary, multi-stakeholder systems in public private partnerships including in WHO, World Bank and UNICEF programs. She leads the 60-member team of AI engineers and Data scientists, Medical professionals, M&E specialists, behavioural scientists and financial managers, ensuring a sustainable balance of skill sets that will deliver impact for patients and enable a healthy scaling economics for the organisation. 

The Horizon Prize will provide us with access to experts across the world working on rare disease as we contribute to the data repository on managing rare diseases in the African Child. By contributing to the diversity in clinical insights and access to treatment and care options for our patients through the resources provided by the Horizon Prize we will better serve our patients.

M'Care, an integrated production system with knowledge represented in rules (including an explanation system and inference engine) offers 5 core functionalities which allows contextualization, scalability and adaptability to different geographies and users. They are: 

1) a mobile library of decision support content for community health workers; negating the need for in-person training on use of M'Care's AI. It unlocks access to M'Care AI the expert system for detecting, diagnosing, treating and managing complex/rare diseases to verified Community health workers.

2) a compass which is the geo-location or coordinate-enabled tracking feature of patient requests, workflows and treatments in every community with timestamps. The compass allows each index case of a disease to be detected and transmitted to the right specialised health care team for coordinated response and management.

3) the medication tracker which is a record of all medications administered by a community health worker. It is useful for planning restocking especially because last mile logistics of medicines is a huge challenge for rural communities.

4) a user interface now available both offline and online on fixed devices making it hyper relevant for poor internet settings.

5) an editable knowledge base which allows feedback loops to continuously monitor patient's symptoms, and improve its AI's effectiveness in predicting disease progression for coordinated care and action for patients, caregivers, community health workers and assigned healthcare professionals.

Hence, one platform allows specialised care coordination with personalised care tips necessary for rare diseases management in a cost-efficient manner.

In one year we aim to double the population we serve and in 5 years make our solution accessible nationwide including 2 other African countries to provide more patients with rare diseases with access to fast diagnosis, coordinated care team and treatment options that extend and improve their quality of life.  

Number of community health workers or trained and using M'Care AI  SDG 9c

Percentage of community health workers or volunteer using M'Care AI without prior digital skills SDG 9c

Daily usage rate by case requests per community health worker (SDG 3.4; 3.8) 

Percentage change in number of out-of-stock request for medicines using M'Care supply chain planning (SDG 3.4, 3.8, 3b)

Number of cases detected; reported and responded to within 12hrs, 24hrs and 72hrs (SDG 3.3, 3d)

Number of communities using M’Care AI as its main health system directly contributes to SDG 9.4.

Number of partnering organizations supporting M'Care's deployment in developing countries (SDG 17)

ACTIVITIES: M'Care core activities includes M'Care AI context of use identification and exploration; Stakeholder engagement and partnership enlisting; Development of contextualized M'Care AI; verification and equipping of community health workers with M'Care AI

 OUTPUT: Community health workers use M'Care AI for case detection, diagnosis, treatment, referral and coordinated case management including supply chain options for essential medicines.

OUTCOME: Identification and tracking of cases, effective clinical and emergency management of rare diseases, coordinated mitigation of symptom progression, access to essential medicines to address clinical case management and early treatment of identified cases.

IMPACT: Pro-actively limit disease progression, extend life expectancy and improve quality of life of patients with rare diseases living in remote communities at a lower and more affordable cost with access to government health funds and subsidies for treatments. Empower patients and caregivers to proactively manage care journeys.

1) AI DECISION SUPPORT SYSTEM with a ML FEEDBACK LOOP from patients symptoms reporting and tracking to predict disease progression. Similar solution has been designed by IBM Watson.

2) GEO-LOCATION TO IDENTIFY INDEX CASES: Geo-location is an existing technology that is already being used in existing software solutions for field workers in different industries; an example in the development space includes KoboToolBox. 

3) INTEGRATED ALERT SYSTEMS : Alert systems leveraging omnichannels (emails, SMS or Interactive voice responses) across multiple devices allows quick dissemination of high priority information (index case coordinates and coordinated response for symptom management or emergency support including monitoring)  adaptable to the context of concern. Examples of existing technology is Magpi

We employ 100% local teams and commit to 50% of our work force being female. We accommodate and encourage differently abled persons to be part of our team. We commit to equal pay for similar work done.

Our business model is conscious of its low income clients and caps screening fees for diagnostics services per user annually. We currently subsidise the referral and case management cost through cost sharing using governments' health funds who also provide and pay for community health workers; medication grants and B2B paid health promotions further support indigent rural patients across our growing network.

Long term, we plan to establish a health ID for rural citizens to have full health insurance from the government which will reimburse the cost of services. As of May 2022, the bill for the national health insurance authority was signed into law by the president. We expected this to be supplemented by our community health fund which covers other services that rare disease patients may need that are exempted from the national health fund.

Furthermore, we plan to partner with genomics and pharmaceutical companies to ensure anonymised data on rare diseases can guide therapies development and ensure targeted distribution of medicines get to the patients that need them the most through consensual grants for named patients with rare diseases.

As an organization, we broke even in 2020 and we are now raising venture capital and grants including service contract fees to ensure our financial sustainability.

Grant Funding sources: Tony Elumelu Foundation; Standard Chartered Foundation; European Commission H2020 Grant; Microsoft for Startups Grants, UN Equals/UNDP, MIT Solve and SAFEEM/WE4A.  

SEEDSTARS investment.

2021 Revenue was approximately $750,000.