- Politics
- Diversity, equity and inclusion
- Financial Decision Making
- Telehealth
- Patient Experience
- Leadership
- Point of Care Tools
- Product Solutions
- Management
- Technology
- Healthcare Transformation
- Data + Technology
- Safer Hospitals
- Business
- Providers in Practice
- Mergers and Acquisitions
- AI & Data Analytics
- Cybersecurity
- Interoperability & EHRs
- Medical Devices
- Pop Health Tech
- Precision Medicine
- Virtual Care
- Health equity
Setting Expectations Around AI in Healthcare
The lack of interoperability might be holding AI technology back.
There’s a lot of hype and promises to artificial intelligence (AI) in healthcare. But what can be done to reap the full benefits of this technology?
>> READ: What Is Being Done About Healthcare's Lack of Interoperability?
Michael Doyle, CEO of COTA, told Healthcare Analytics News™ that interoperability is a factor in how AI works. AI needs data to learn. The more data, the better the technology is. And with the lack of interoperability, the technology is missing out on data that can help it perform with higher accuracy.
While interoperability is a difficult problem to overcome, government organizations are working hard to advance it.
Doyle believes that with interoperability and human intervention, AI technology will work best and there will be a better result for the patient and the healthcare ecosystem as a whole.
With AI, natural language processing and machine learning, along with real-time evidence, the future of healthcare is poised for improved outcomes.
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Weighing the Benefits and Challenges of Interoperability
