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Software Engineering

Computational Complexity: Health Tech

On Tuesday, at the behest of an alumnus, I spent the afternoon at HIMSS, a large health tech conference being held at the big convention center in Chicago. When I think of Health Tech, I imagine fancy medical devices, but most of the exhibitors were focused on software solutions.

Cybersecurity had the biggest theme area, no surprise given the devasting role ransomware has had on some hospital chains. The second largest theme area focused on Interoperability. Just a few years ago, the vast majority of medical data is transferred via fax. A few companies, like Epic Systems, dominate the electronic health records space and don’t share nicely. There’s a relatively new standard, FHIR, for transferring medical data, making it easily accessible via APIs while keeping it secure. Hopefully, we can finally kill off the fax machines in doctors offices. Patient Engagement was the other big theme area.

Of course the big discussion topics are about how AI will change health care. For example, the advances in electronic records have led to doctors spending far too much time entering data instead of seeing patients. AI could make data entry quick, easier or perhaps even unnecessary. Also AI could help provide functionality for triage and initial diagnoses, helping to extend the capabilities in a staff-limited environment and help bring down health-care costs. Many of the exhibited software systems boasted about using AI but it won’t be until next year’s meeting that we see the true integration of large-language models into health care technology.

Many of the challenges of technology in health care carry over to higher education. We don’t generally use faxes, but why do we send transcripts by PDFs? Health and student data share similar privacy and security challenges, why can’t we develop a FHIR-like system for higher education? Cybersecurity and Patient Student Engagement challenges loom large for universities as well. 

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