At the dawn of COVID-19, Trust CoLab, an online platform initiated by the Massachusetts Institute of Technology’s (MIT) Center of Collective Intelligence and United States Pharmacopeia (USP) requested more than 100 global academia and physicians including experts affiliated to the American Association of Pharmacy, Bill and Melinda Gates Foundation, Harvard Medical School, and the US Food and Drug Administration (FDA) to imagine and pen down their thoughts on the state of medicine and healthcare over the next 20 years and our trust towards them.

The responses collated over the course of four weeks were put into a report – “Trust or Consequences 2040: Will innovations in health and medicine deliver” and was released recently. Overall, experts involved in the report believe there will be an increase in global health crises in the coming years and they will lead to large scale disturbances. This forces healthcare leaders and the medical community to collaborate and deliver solutions that have extensive impact. Specifically, four potential future scenarios were detailed.

Scaling the tried and true

As major health crises unfold, healthcare leaders will need to work with policymakers across the board to design, develop and deliver solutions that have global impact and make them widely accessible to all. Although artificial intelligence (AI) and big data had contributed to some advances, these evolutions tend to occur gradually and only benefit certain groups of people. As such, low-cost medication and preventive measures become the core and innovations around them have to be adopted quickly. All these will rely on trust and a successful cooperation model.

Dangerous uncertainty

AI and big data may lead to unforeseen and devastating healthcare failures. Unequal distribution of new technologies suggests health disparities may continue. The rich will probably enjoy exclusive access to certain advanced treatments; the middleclass may turn to traditional and modest solutions offered by their local caregivers while the poor may have to go after food-based cures or even folk medicine. Therefore, efficacy and safety of science-based medicine remain questionable and trust in healthcare system is still fragmented.

A world of difference

On the other hand, if AI and big data are utilized successfully, there will be rapid advances in personalized medicine, early diagnoses and interventions. Again, not everyone will have access and be able to enjoy the fruits of these innovations because not every region has the mean to surrender genetic information and other details to support AI and big data. These differences will perpetuate a “have” versus “have not” dynamic. Individuals’ trust in the healthcare system will also be shaped by where they are on the economic ladder and whether they can afford treatments driven by cutting-edge technologies.

Solving tomorrow’s problems

Diseases become more predictable as new insights and new treatments emerged with innovations. We become more informed about why certain illnesses occur and healthcare is not just tending to the sick but also evolved to emphasis on prevention. Nevertheless, the explosion of knowledge may complicate the kind of decisions one ought to make for their health. Constant sharing of one’s genetic and health information to fuel the development of AI and big data also threatens one’s privacy. A globally accepted standard for handling of health data and setting boundaries on when certain interventions should occur become critical and trust between key stakeholders, governments, providers and patients will be the cornerstone of the future.

Trust CoLab said these scenarios are not prediction but they are a set of narratives depicting what could happen in medicine and healthcare of the future to open up the public’s minds for more opportunities and take the chance to reflect on present decision making. The full report is made available here.


Author Bio

Hazel Tang A science writer with data background and an interest in the current affair, culture, and arts; a no-med from an (almost) all-med family. Follow on Twitter.