Health Systems Balance AI for Patients and Providers
Robert Havasy, senior director of informatics strategy at HIMSS, is tracking how health systems deploy AI across the entire care journey - from patient engagement to clinical decision support - while simultaneously addressing provider burnout and workflow challenges.
The dual focus reflects a shift in how healthcare organizations think about AI implementation. Rather than treating patient-facing and provider-facing applications as separate initiatives, leading health systems are designing AI tools that benefit both simultaneously.
Havasy's interest centers on practical deployments. Health systems are using AI to guide patients through scheduling, pre-visit preparation, and post-discharge follow-up. At the same time, these same systems reduce administrative burden on clinicians and nurses by automating documentation, flagging critical information, and prioritizing alerts.
The stakes are high. Provider burnout directly affects patient care quality. When AI reduces time spent on paperwork and data entry, clinicians have more capacity for direct patient interaction.
AI for Healthcare implementations that succeed tend to address both sides of this equation. Tools that only benefit administrators or only benefit patients often face adoption resistance.
Health systems exploring this space are discovering that the best use cases tend to cluster around three areas: patient communication and navigation, clinical documentation and decision support, and operational workflow optimization. The most mature implementations connect all three.
For healthcare professionals evaluating AI tools or planning implementations, the key question is straightforward: Does this improve both the patient experience and the provider experience, or does it optimize for one at the expense of the other?
Learn more about Patient Engagement strategies in healthcare settings.
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