The data: Health systems are prioritizing digital health technologies focused on patient access, AI, and telehealth, per a recent December 2021 KLAS and Center for Connected Medicine survey.
The promise of AI in healthcare: AI’s ability to assist clinical diagnostics and absolve burnt out healthcare workforces of admin tasks has health execs ready to kick their AI investments into high gear.
AI-powered predictive tools can help map out disease progression, diagnoses, and help streamline providers’ clinical decision-making:
On the other hand, AI can help automate administrative drudgery (like prior authorizations and other insurance paperwork) so clinicians can better focus on providing quality care.
The challenge with healthcare AI: Many health professionals have been wary of the tech’s potential for errors and biases when it comes to diagnostic applications.
There’s uncertainty around the integrity and diversity of data that AI algorithms are modeled on—something that leads to inaccurate outputs and medical errors.
Plus, a bug in one AI system could affect thousands of patients, as opposed to a provider’s human error affecting just one. With an increasing number of cybersecurity attacks on healthcare, this could pose a significant risk.
What’s next? As more health systems secure a stronger footing in healthcare AI, the next step will be to make new AI capabilities mesh with both digital health technologies and existing healthcare processes.
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