Pharmacist Roles, Risks in Guiding AI-Enabled Medical Device Use

As artificial intelligence (AI) is built into more than a thousand medical devices, from blood pressure monitors to automated insulin delivery systems, pharmacists remain the critical link between the technology and the patients who use it.

According to Rita King, CEO and senior regulatory strategist with MethodSense, AI-enabled medical devices may offer patients more data and education than ever before, but they also carry risks of false reassurance and misuse that pharmacists are uniquely positioned to catch.

“The pharmacist is still the connecting piece,” she told Drug Topics®. “They connect the information that the [medical device] is providing to the patient.”

In this week’s episode of the Over the Counter podcast, King joined to discuss her extensive background in the medical device industry, how her organization is approaching AI’s integration in the space, and what this all could mean for pharmacies down the line.

Navigating Patient Safety and Device Limitations

Every medical device cleared by the FDA carries specific instructions for use that outline operational boundaries and patient population constraints. King emphasizes that pharmacists must actively evaluate these instructions to prevent patient misunderstanding, particularly when software applications accompany physical hardware.

Although algorithms provide supplementary metrics and trend analysis, false reassurance remains a substantial clinical risk if patients assume automated features eliminate operational errors. Simple human mistakes, including selecting an improper blood pressure cuff size or failing to follow proper sensor application techniques, can corrupt the underlying data stream.

When underlying data is flawed, downstream therapeutic evaluations conducted by clinicians or automated software become compromised. Regulators address these software risks by evaluating premarket authorizations and utilizing predetermined change control plans, which allow manufacturers to make bounded modifications without requiring entirely new clearing submissions.¹

Mapping Authorized Technologies and Practice Realities

The landscape of AI in medical devices spans over 1600 authorized products regulated by federal oversight agencies. A comprehensive review of FDA authorizations reveals that 84.4% of AI medical devices utilize imaging data, while 14.5% analyze physiological signals such as electrocardiograms.^1,2

Most current applications focus on patient assessment, but interventional tools such as automated insulin delivery systems demonstrate how software algorithms directly assist in active therapy management.²

Systematic reviews highlight that smart insulin pens can achieve over 95% accuracy in detecting proper injection sites, while smart pumps autonomously process glucose monitor trends to stabilize glycemic control.³

These technological advancements align with broader market expansion projections, which estimate the global AI health care sector will surpass $187 billion by 2030.

Despite this rapid expansion of automated devices, real-world adoption among pharmacy professionals remains cautious. A survey conducted among 122 pharmacists across New York hospital and specialty settings revealed that 61% reported moderate familiarity with AI tools.⁴

However, usage was predominantly restricted to administrative duties, including document proofreading at 50% and literature summarization at 44%, while only 3% utilized software for clinical decision support or order verification.

Although 55% of surveyed pharmacists agreed that AI could potentially reduce medication errors, 82% cited information accuracy as a major concern, 79% pointed to a lack of clinical judgment, and 61% raised data privacy risks.⁴

Strengthening Risk Feedback Loops and Future Integration

To bridge the gap between technological potential and clinical safety, pharmacists occupy a pivotal position in post-market risk management. As accessible health care providers, pharmacists receive direct feedback from patients regarding device alerts, interface difficulties, and operational confusion.

Reporting these recurring operational observations back to device manufacturers enables developers to refine instructions, resolve interface issues, and enhance overall safety profiles.

Looking ahead, the health care industry anticipates a rise in home monitoring technologies, personalized therapeutic software, and eventually, autonomous agentic systems once standardized testing protocols are established. Survey data indicates that 77% of practicing pharmacists are willing to adopt AI tools if validated institutionally, while 89% advocate for integrating AI education directly into professional curricula.⁴

Through structured training and active risk surveillance, pharmacists can safely guide patients through the expanding ecosystem of medical device technology.

Stay tuned for weekly podcast episodes of Over the Counter powered by Drug Topics. Check out our most recent episode with Melissa McGivney, PharmD, FAPhA, FCCP, who joined us to discuss the exciting events, observances, and happenings surrounding American Pharmacists Month.

REFERENCES

1. AI-enabled medical devices. FDA. September 22, 2026. Accessed October 21, 2026. https://www.fda.gov/medical-devices/digital-health-center-excellence/artificial-intelligence-enabled-medical-devices

2. Singh R, Bapna M, Diab AR, et al. How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations. NPJ Digit Med. 2025;8(1):388. doi:10.1038/s41746-025-01800-1

3. Ponnambalath Mohanadas H, Manikandan A, Ismail AF, et al. AI applications in medical devices for personalized health care solutions: systematic review. J Med Internet Res. 2026;28:e72410. 2026 Mar 4. doi:10.2196/72410

4. Abraham K, Doran CE, D’Anna S, et al. Pharmacists’ perceptions of AI in specialty, outpatient, and inpatient pharmacy practice in New York state. JAPhA Pract Innov. 2026;3(3):100114. doi:10.1016/j.japhpi.2026.100114