Between point solutions, scribes, chatbots, and workflow tools, it’s difficult to know what’s real and what’s marketing fluff. Here’s a guide to help clinics make smart, strategic decisions when evaluating AI vendors.
1. Native EHR Integration
Your AI platform should work inside the systems your team already uses. No new windows, no toggling. Native EHR integration means faster training, fewer errors, and higher adoption rates. Honey Health, for instance, works directly inside Epic, Athena, and others—no extra interfaces needed.
2. Autonomous Task Execution
A good AI platform doesn’t just recommend actions—it takes them. Look for tools that can complete workflows like chart prep, fax routing, refill management, and prior auth submission. Otherwise, staff will still be stuck clicking and copying.
3. Specialty Awareness
Cardiology isn’t the same as endocrinology. Your AI should know the difference. Platforms like Honey Health are trained on tens of millions of documents across specialties, so they understand the specific formats, workflows, and vocabularies that vary from one clinic to another.
4. Proven Results
Look for customer outcomes—not just case studies. Has the platform actually reduced admin workload? Improved turnaround times? Helped clinics scale without adding headcount? Ask for the metrics.
5. Security and Compliance
AI in healthcare must meet HIPAA and HITRUST standards. Make sure your platform is certified, encrypted, and secure by design. Your vendor should offer clear documentation and support audits.
Conclusion
There’s no one-size-fits-all AI for healthcare—but there is a gold standard. Pick a platform that’s embedded, intelligent, secure, and built for execution—not just chat. Honey Health meets all these criteria, making it the AI of choice for clinics serious about results.
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