Breaking healthcare’s iron triangle
May 29, 2019
Access, affordability and effectiveness no longer need to be competing priorities.
The challenges faced by current and future healthcare systems are no secret. Healthcare costs increase faster than GDP grows, and healthcare is the most labor-intensive industry of our times. It faces a globally growing, aging, population increasingly suffering multiple chronic conditions and consuming excessive amounts of resources.
Three of healthcare systems' top priorities—access, affordability and effectiveness—have traditionally formed an “iron triangle” of dependence, unable to be improved simultaneously. Whenever access was improved, affordability was necessarily reduced. Whenever effectiveness was improved costs, similarly, rose. Conversely, when costs were lowered, access and/or effectiveness were necessarily disadvantaged.
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The rise of digital health, and especially Artificial Intelligence (AI), has given us the first real opportunity to break the triangle and allow all three dimensions to improve simultaneously. As a result, I believe the care system of the future will look very different to the one we have today. Not just because of the science, but because of our ability to provide care without requiring a physical interaction with the caregiver.
More important than my view is the real-world fact that AI is being embraced enthusiastically by healthcare executives across the world. Some leaders have already implemented AI in their organisations, and an encouragingly high number are planning and piloting AI adoption, according to the Accenture Executive Survey on AI in Healthcare. At the same time, executives are being appropriately selective about the types of AI applications they are planning to implement.
The popular narrative around the benefit of AI in healthcare has been about making better and smarter decisions for doctors, and helping to enable better clinical care. That’s all contained in the effectiveness category of the Iron Triangle.
The reality is that healthcare organisations are, for now, focused more on operational benefits and cost. When we hear back from healthcare leaders about how they use AI, they tell us they mostly use AI in their back offices. For example, they use it to make their systems safe from cyberattacks and for supporting mundane administrative tasks like admissions, prescriptions, and regular vital-sign testing.
The move towards AI is not due to easier application or less risk to patient lives. When executives look at AI's potential they told us that AI’s real transformative power in the next few years lies in applications that lead to affordability. Only a small group said so for the AI applications that focus on greater care effectiveness.
AI will make its way into the front office, though, at some point later. It will push healthcare work to patients and/or smart machines, and lower physician workloads. We estimate that ~30 percent of the workload can be done by a smart machine, or patients themselves, i.e., 10-15 percent of the workload is about care documentation/EMR data capture, so data input to EMRs is another strong candidate for AI utilization.
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AI investments should also increase over the next few years; 40 percent of health executives are quite or highly focused on increasing the use of AI-assisted applications, while another 53 percent are moderately focused. While the application of AI is clustered in the back office for now, patient-facing applications are expected to follow and to show substantial benefits in the future.
Part of the reason that healthcare has not benefited from the productivity gains of IT as other parts of society have is that much of the work of healthcare is non-routine work both physical and cognitive.
AI and ability for machines to learn and change without explicit human programming means that they can now begin to do non-routine work. So AI even more that just IT is the key to breaking open the iron triangle
I am thrilled about these developments being driven by today´s healthcare leaders, and we are proud to be part of the global health movement to a meaningful, measured approach to AI usage in healthcare.