The United States currently ranks highest in healthcare spending among developed nations accounting for 18% (about $3.5 trillion) of gross domestic product (GDP). It spends twice as much on healthcare as any other industrialized nation but with the lowest outcomes. Healthcare costs are projected to increase by 5.5% annually to consume 20% of GDP by 2026. This outpaces the expected growth of the overall economy and strains the budget for the government, business, and consumers. It also diverts money away from education, infrastructure, and other vital investments.
The U.S. healthcare system is unique among other advanced industrialized countries. It does not have a uniform health system, or universal healthcare coverage. There are no major plans for a public policy fix in sight, to reduce growing healthcare costs. To mitigate rising insurance premium costs, the insured population is opting for high-deductible healthcare plans. As a result, there is a gap in access to healthcare for not only the uninsured and poor but the insured as well, with both groups often postponing otherwise treatable ailments only to receive care when the issue becomes acute, costing more to the overall system.
A trio of titan firms, Amazon, J.P. Morgan, and Berkshire Hathaway, have opted out of this system and teamed up to create a healthcare company with a focus on technology solutions to provide high-quality healthcare for their employees at a reasonable cost. There is a race among the tech giants to capitalize on medical technology and the health data mining market. However, the attendant risk of using legacy technology for health care, where it is necessary to access data in real time, is systemic cyber threats and ransomware attacks, that can expose patient information and cripple entire hospital systems. Introduction of blockchain technology can ensure that patient records are not altered or accessed by unauthorized intruders.
Artificial Intelligence (AI) can lead the transformation to value-based healthcare. AI can improve medical equipment, imaging and reducing turnaround time for lab results while making examinations more precise. Data, analyzed with AI, can facilitate collaboration between medical specialties, and provide personalized, targeted patient care. In the next five to ten years, AI is likely to transform diagnostic imaging. This will by no means replace radiologists or doctors, but rather help meet rising demand for imaging examinations, prevent diagnostic errors, and enable sustained productivity increases.
AI can lead to targeted diagnosis and therapy, reducing the cost of healthcare while improving outcomes, it is a positive solution for all parties: the patient, the insurer, and the healthcare system. Naturally, for any of this to work, there must be an improvement in public policy imposing oversight for pricing and services, establishing a national standard of care.