That is a sizable number, but achievable according to McKinsey and Harvard researchers if AI/ML technology is adopted more broadly across the healthcare industry.
The National Health Expenditure (NHE) is expected to hit $4.5 trillion, in 2022. Which means if AI/ML is injected more widely into the healthcare system, that could save up to 10% of the NHE.
Even if the savings are not fully realized, such potential certainly seems worth the investment, right? Then why is the healthcare industry slow to embrace AI/ML compared to other industries?
Some reasons include:
1️⃣ Data privacy concerns
2️⃣ Disparate, siloed data throughout the healthcare system
3️⃣ Lack of trust in new technology (algorithms) versus human knowledge
4️⃣ Reimbursement structure that rewards quantity over quality
5️⃣ Regulatory barriers - although, this is starting to change
6️⃣ Ethical/bias concerns
AI/ML adoption needs to include all players in the healthcare continuum, as each group will benefit not only in cost savings, but also from deeper learnings and insights, predictive analytics and advances in precision care.
Benefits by the primary constituents include:
✅ Hospitals: improved quality of care, medical imaging, enhanced patient experience, risk prediction.
✅ Physicians: better insights into patient’s continuity of care and identification of diagnoses and diseases.
✅ Health Plans: automating claims payment integrity and prior authorization, HEDIS and STAR measures.
There is growing evidence that supports the benefits of implementing AI/ML technology throughout the healthcare system.
Recently, even the FDA cleared 520 AI/ML medical algorithms and approved 350 AI/ML-enabled medical devices, further reducing barriers for entry.
Now, the game-changing technology of ChatGPT is adding a whole new level to AI/ML. Many experts believe, with the advent of ChatGPT, that 2023 will be an inflection point for AI/ML in the healthcare industry.
Will this be the year your organization fully embraces AI/ML? Have you had discussions about ChatGPT?
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