Inclusive tech for public health

June 23, 2019
How smartphones and data can support equitable access to limited resources.

Southeast Asia faces an extreme range of public health challenges: from deadly air pollution in over-populated cities, high rates of maternal mortality in remote areas, vitamin A deficiencies that can stunt growth in poor regions, to obesity epidemics where access to fast food has rapidly transformed diets.

Many health professionals are looking to data and artificial intelligence for solutions. Among them is Beth Ann Lopez, Director of Public Affairs for mClinica, a social enterprise creating digital networks of pharmacies to tackle public health problems across Southeast Asia. But for Lopez, new possibilities come with new risks.

“There’s a lot of interest from physicians and health workers in using artificial intelligence to mine electronic health records,” she says, “and create personalized medicines, analyze genomes, identify risk factors, and so on. My concern is that this focus on personalization could lead to increasing inequality. I’d like to see it used to support public health outcomes.”

With access to care being a crucial problem in the region, Lopez is looking for ways that AI can reduce inefficiencies so people can get the right help at the right time. “There are many routine tasks that AI could help to perform at clinics to reduce waiting times, such as taking vital signs such as blood pressure and pulling up patients’ health records. All these basic things could be automated.”

This is already a major trend in more developed markets such as China and Singapore. For instance, Chinese start-up WeDoctor uses AI to see what level of healthcare a patient needs: you don’t need to see a top specialist if you have a cold—WeDoctor can direct someone to a facility that’s tailored to their needs.

In a region where access to effective medicine is thwarted not only by inadequate supply but by counterfeits and parallel imports, smartphones can literally be lifesavers.

“It’s not about replacing health practitioners, but enabling them to focus”, says Lopez.

Beyond AI, how can data support equal access to healthcare in Southeast Asia? One challenge is the availability of modern tech: wearables and watches are only available to a small subset in Southeast Asia. On the other hand, mobile connectivity is around 140%, with multiple sims and phones per person. This proved a crucial resource in the aftermath of Typhoon Haiyan, Lopez explains.

“When Haiyan hit, people didn’t know if medicines were available or not. Some needed critical medicines but there was no information on where to find them. Some of those medicines were available in towns nearby but those in need didn’t know, and so were forced to go without them.”

In response, mClinica created a mobile data system called SnapRx or the Electronic Drug Safety System. SnapRx is an app that generates health data from prescriptions in real time. Every time a pharmacist issues a prescribed drug, they simply snap a photo of the prescription with the app, using their mobile phone camera. The app uses artificial intelligence to digitize the information, which is sent in real time to a cloud database. This can then be used to create national health surveillance, monitoring supply, and also to predict and detect epidemics. For instance, as more pharmacists snap pictures of flu medicine, we can spot an outbreak, identify where it is, and plan a response.”

In a region where access to effective medicine is thwarted not only by inadequate supply but by counterfeits and parallel imports, smartphones can literally be lifesavers.

This article was produced by MIT Technology Review Insights in association with TM One and first appeared on on June 5, 2019.