Better patient value for the poor in Africa

Better patient value for the poor in Africa: stepwise implementation of value-based health care in Kenya using mobile technology




Sub-Saharan Africa has the highest burden of disease worldwide, combined with very limited resources for healthcare. Within this setting, it is essential that funds are spent efficiently and effectively to achieve the highest patient value. However, data on the costs and the quality of care are lacking. This makes it impossible for patients to choose for quality care, impossible for payers to purchase care based on value and impossible for clinicians to get insight in the outcomes of their patients and engage in data driven learning. Our initiative aims to get insight in the value of care in Africa, on a large scale, by making use of the mobile platform M-TIBA.

M-TIBA is Africa’s mobile platform for inclusive healthcare: a people-centered health platform that directly connects patients, healthcare providers and healthcare payers, and exchanges money and data between them. From the patient perspective, M-TIBA is a wallet on a mobile phone containing entitlements for healthcare. Healthcare providers get direct payment for services through M-TIBA. In addition, the platform generates a wealth of data. Each individual transaction on the platform is visible and generates data on diagnosis, tests and procedures done, drugs prescribed and costs of care. M-TIBA launched in Kenya in June 2016 and is a collaboration between Dutch NGO PharmAccess, Kenyan enterprise CarePay and telecom provider Safaricom. So far, over 800,000 people and more than 450 healthcare providers have registered. A pilot to test the M-TIBA software in Nigeria has started, expansion to Tanzania is planned for 2018. Building on the opportunities the M-TIBA platform offers, we are developing value-based healthcare services that aim to increase insight in and improve patient value in a setting where currently hardly any health data exist.

Together with the Gertrude’s outreach clinics that serve the population in the slums of Nairobi, we developed optimal patient journeys for HIV and pregnancy care. We started tracking patient journeys and their outcomes, making use of the automatically generated data on the M-TIBA platform. We are testing different ways of feeding back these insights to clinicians and patients and evaluate whether this led to use of that data by doctors and patients, better quality data due to a shorter feedback loop, improvement in adherence to care plans and protocols, and improvement in patient outcomes. Together with a multidisciplinary staff at Gertrude’s, we developed a phone-based application that shows real-time insight in clinic performance for all HIV patients and pregnant women, and all individual patient journeys, deviation from guidelines, health outcomes and costs of care. In addition, we partnered with ICHOM to implement a localized outcome standard for pregnancy care, including patient reported outcomes, collected at very low costs through mobile phone surveys. Insights were discussed on a regular basis with all staff members that take care of the patient along the journey (e.g. doctors, nurses, pharmacy staff, and support staff). We were able to show that our mobile platform offers great opportunity to collect data on the value of care at scale. It requires no extra data entry for doctors and is scalable at very low costs. We showed that staff was highly motivated to engage in data driven learning and showed improvement in adherence to care protocols. Clinicians indicated that the PROM surveys gave them valuable insights in what happens to their patients outside the walls of the hospital. Our initiative strengthened IPUs: the regular feedback sessions were used by the multidisciplinary team to create solutions for improved patient value. Some of these solutions, such as automatic SMS reminders to patients for follow up visits are now being tested. Patients were motivated to participate in outcome surveys. They valued that they were asked for their opinion and were asked what happened to them after they left the clinic.

As a next step, we are starting to add value-based elements in our contracts with providers. We are also testing how we can give feedback to patients about value of care such that they can make informed decisions. In addition, we aim to enrich our data sets and expand in size and scope. We are currently building a data engine that can cope with large datasets and we are developing modelling tools for clinicians that can benchmark their performance against other clinics and allow them to predict which patients are at risk for a poor outcome. With the roll-out of M-TIBA at exponential pace, we can expand our target population to 3.5 million people in the coming 2 years. Expansion to a program covering 250,000 women in Tanzania is also planned. In addition, we are expanding the range of conditions for which we measure outcomes to hypertension and diabetes care, thereby covering the majority of chronic conditions of the population in Africa. We are partnering with quality assurance organization SafeCare to have a structural data driven learning approach for all M-TIBA clinics. But this is just the start, M-TIBA is planning to scale up to 100 million users by 2025. This offers an unprecedented opportunity to measure, monitor and improve the value of patient care in sub-Saharan Africa at very low costs.