Utilizing AI for Medication Management

Drug Topics JournalDrug Topics July/August 2023
Volume 167
Issue 07

Pharmacists can utilize AI for medication management and to prevent medication errors.

Artificial intelligence (AI) is giving more time back to pharmacists and pharmacy technicians by eliminating the manual workflows that have traditionally bottlenecked operations like data entry, new facility onboarding, claims reconciliation, 340B auditing, patient support, communication, engagement and more.

One area it in which AI has begun to make a huge impact is in pharmacists utilizing AI for medication management and preventing medication errors.

As polypharmacy continues to increase, the burden on pharmacists to ensure that new prescriptions don’t result in adverse drug responses or drug-drug interactions has grown dramatically. AI can be a powerful ally to pharmacists and clinical teams, identifying potentially harmful drug interactions: Not only can AI sift through massive amounts of published data, but machine learning-based prediction algorithms can accurately determine both potential efficacy compromise and toxicity risks.

For medication management and preventing medication errors, AI can cross-verify patient data, prescription data, and pharmacy inventory. It can help identify potential issues such as incorrect dosages, drug-drug interactions, drug-disease contraindications, and duplicate therapies.

Pharmacist Abbas Kanani, MRPharmS, noted AI can provide real-time guidance to pharmacists during medication prescribing, dispensing, and administration processes, flagging duplicate prescriptions, potential drug interactions, allergies, or contraindications. “This can assist pharmacists so they can then intervene and rectify any errors before they reach the patient,” he said. “Personalized dosing recommendations may also reduce the likelihood of errors.”

AI-powered medication reminder apps can also aid patients in adhering to their medication regimen, improving outcomes and reducing hospital readmissions.

Gretchen Brummel, PharmD, BCPS, pharmacy executive director at Vizient and host of VerifiedRx, a podcast series focused on insight for pharmacists, noted that 1 good example would be to utilize AI to cross reference reported pediatric weights against CDC growth charts as a quality assurance step to ensure the weight provided is consistent with weight for age and height.

“Using the correct pediatric weight when dispensing medications is critical to preventing medication errors,” she said. “AI can be used to identify patients at the greatest need for comprehensive medication management. Most pharmacies currently use some form of clinical decision support to screen for duplicate medication and drug interactions. There is potential to expand to drug-disease state interactions and also include more pharmacogenomic information to customize patient care.”

The Institute for Safe Medication Practices (ISMP) recently released a set of best practices, “Targeted Medication Safety Best Practices for Community Pharmacy,” which includes several recommendations that can be supported using AI technology.

“This has direct patient care implications at the local pharmacy setting,” Brummel said. “Leveraging AI for innovative and comprehensive clinical decision support recommendations as well as to facilitate best practices in medication safety can facilitate individualized medication management practices for patients in the community pharmacy setting.”

Leslie Lotano-Saba, RPh, vice president of pharmacy solutions at global management and technology consulting firm AArete, noted by using physician prescribing patterns as well as patient medical and drug history and drug-use patterns, AI can identify drugs or dosages that look like an outlier for a specific patient.

“Leveraging information from over-the-counter purchases can provide an early warning of a patient’s condition worsening or an event being triggered by drug therapy issue,” she said. “For example, the purchase of first-aid products may indicate a fall in an elderly patient.”

What’s more, AI can also support the development of personalized medication plans by using patient data to predict individual responses to different treatments.

Jason Julianois a director within Eisner Advisory Group LLC, who counsels businesses on AI, noted AI solutions can automate drug administration and inventory management, freeing up pharmacists’ time to focus on pharmaceutical treatment management, medication adherence counseling, and answering any issues or inquiries.

“We actually helped some clients with these already, creating AI digital assistance that helps pharmacists and [health care providers] with drug information based on common questions,” he said, which include queries such as What is the right dose? What are the side effects? How can I store my medications? And What if I miss a dose? “Some of the data we used is public data sources from the FDA’s drug approvals and databases.”

Hayley Burgess, PharmD, chief clinical officer at VigiLanz, an EHR clinical surveillance company believes the use of AI for medication management and preventing errors is truly transformative.

“It creates smart, actionable information that reduces the noise burden,” she said. “Potential errors or inconsistencies in prescriptions can be flagged, triggering pharmacists to intervene sooner to avoid adverse drug events.”

And when it comes to applying clinical data with prescription management systems, the opportunities are endless. Understanding the patient’s adherence and fill history, along with pertinent lab, vitals, and microbiology reports, can create dynamic and impactful clinical outcomes.

“Pharmacists are ideal clinicians with their unique access to patients on a regular basis and their trust in the community,” Burgess said.

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