Many have argued that the COVID-19 pandemic is a “black swan”: a catastrophic event that can only be understood with the benefit of hindsight. While there is some appeal to this observation, the originator of the black swan theory, Naseem Taleb, strongly refutes this assertion. He counters that COVID-19 was a “white swan”—a predictable event with predictable consequences.
New federal data shows that Latinos and African Americans living in the US are three times as likely to become infected as their white neighbors. African Americans make up 13.4% of the population, but counties with higher Black populations account for more than half of all COVID-19 cases and almost 60% of deaths. Ultimately, the consequences of the virus are disproportionately borne by those otherwise marginalized in society—interestingly and disappointingly, this is no different than most other health outcomes. The reasons for this disparity have been speculated extensively, and it’s been attributed to a variety of factors from genetic to behavioral to access to health care. But there is something deeper at work, and it requires that we acknowledge the corrosive influence of history and the deep structural inequalities that drive these disparities.
Societally, there is a tremendous amount of work to be done to address the role that systemic racism plays in health disparities. But as healthcare technology leaders, what can we do in our work today to address socially determined risk amid COVID-19?
Design technology that builds trust
Organizations must examine the health system from the patient’s point of view. From the patient perspective, it is apparent for those with long-term conditions, amongst whom older Americans and African Americans are disproportionately represented, that there is a considerable amount of work required to make use of the healthcare that is available. Each visit requires follow-ups, medications, and tests, along with tracking symptoms and biometrics to determine which actions to take if their health deteriorates. It is left to patients to carry this burden, largely alone and alongside their other family responsibilities, all while grappling with structural factors that are systematically biased against them.
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It is unsurprising that, for many, healthcare is hard. A key opportunity for technology is to try to make it easier. A design principle that organizations can apply to help is to build trust with patients who have grown to mistrust the health system. This means that any technology that is deployed in healthcare should be deployed in the context of a relationship with a clinician where that relationship serves the purpose of building trust, and ultimately improving a patient’s autonomy. It may sound counterintuitive, but providing patients with more care actually helps them become more independent and empowered.
Fulfill AI’s promise to uncover needs and expand access
In spite of a cacophony of bold promises regarding its transformational potential, AI has delivered few results in the COVID-19 response thus far. One reason being that data science is dependent upon data, and the COVID-19 pandemic has exposed the fault lines of data availability. But there are many beacons of hope in this area. Firstly, research initiatives are underway to create an aggregated data set across ICUs in the spirit of the existing MIMIC initiative from MIT to support the development of AI algorithms in ICU. Second, there are states that have been successful in solving the data infrastructure problem—namely the state of Nebraska, symbolically in the heart of the country, which with the NEHII initiative has aggregated insurer, hospital, and clinic data into a central database and made it available, through visualizations, to the state governor who is able to view bed occupancy and testing rates in real-time.
The increasing adoption of digital health tools across demographics also affords healthcare organizations a unique opportunity: a large dataset that can offer a window into health trends among those most at risk from COVID-19. When applied to the novel datasets generated from digital health solutions, AI can inform advocacy and support. Using natural language processing algorithms, healthcare organizations can understand the needs of the most vulnerable in real-time and at scale. The technology can then extend clinicians’ ability to respond quickly to those needs with trusted support and education.
Key takeaways
COVID-19 has brought into focus the consequences of structural racism in our society as well as the understanding that a true solution involves social change as well as technological advances. Technology leaders can play a role by deploying solutions that can rebuild trust and enable real-time monitoring and response to the needs of the most vulnerable. The pieces of this solution are already in place, and never has there been a greater imperative to bring these fledgling initiatives together.
Source: Hit Consultant
