Pharmacy of the Future: Pharmacy Practice and the AI Revolution
The pace of technological progress and innovations has powered the rapid development of artificial intelligence. The healthcare industry is no exception to the transformative power of AI. Where can AI play a role in pharmacy? How could AI reshape the landscape of the practice? What implications does the integration of AI hold for the healthcare system?
The Fusion of Pharmacy Practice and Artificial Intelligence (AI)
With advancements in medical knowledge and testing diagnostics, the delivery of healthcare has only increased in complexity. To manage the demands of the system, pharmacy has grown outside of the traditional role of medication dispensing with pharmacists providing more clinical services such as medication therapy management, adverse event monitoring, and management of chronic diseases. With an increased focus on clinical work, AI could reduce the burden on pharmacists by automating dispensing tasks like inventory control, prescription verification, and review of drug interactions (1). Adding upon that, an AI-powered system would eliminate human error thereby reducing the risk of errors while also freeing up pharmacists' time to focus on more patient-centric tasks.
In addition to lowering the workload on pharmacy personnel, AI-powered systems can introduce novel solutions to address nonadherence to medications. For example, AI is being used in smartphone apps, sensors, and machine learning algorithms to ensure patients adhere to their prescribed medication regimens. In a study aiming to reduce nonadherence in anticoagulation therapy, an AI system successfully improved adherence by providing reminders to patients and visually confirming ingestion of the medication (2). By reminding patients to take their medications and tracking their medication usage, AI can empower patients to meet their goals of therapy.
Unlocking the Potentials: AI's Positive Impact on Pharmacy Practice
Data suggests that incorporating AI into pharmacy practice and PBM (Pharmacy Benefit Manager) workflows, patient outcomes are improved, efficiency is maximized, and cost is minimized. As previously mentioned, AI can be used to improve poor adherence. The estimated annual adjusted disease-specific economic cost of nonadherence has been estimated to be between $949 to $44,190 per person (3). By increasing a patient’s compliance with drug therapy, improved health outcomes are seen. Adding upon that, the financial burden of poor adherence can be minimized. In addition, AI can automate routine tasks a clinical pharmacist completes while eliminating the risk of human errors, thereby driving efficiency. Ultimately, AI may be the innovative solution to long-standing problems currently impacting cost and outcomes in pharmacy.
Hurdles and Reflections
While AI holds immense promise, the technology also presents several challenges that should be addressed. At its core, AI is an information processing system; therefore, the collection and analysis of patient data raises concerns surrounding privacy and data security. PBMs, payers and pharmacies must ensure that AI systems comply with relevant regulations. Additionally, staff training is needed to be on how to effectively use AI tools and understand the technology's limitations. Integrating AI systems into existing workflows can be complex and may require significant investments in infrastructure and training.
As AI continues to evolve, it is crucial for key stakeholders to stay informed about the latest developments and collaborate to harness the full potential of AI in pharmacy.. The journey towards a more AI-enhanced pharmacy practice promises a healthier, more efficient, and patient-centric future for all.
By Jasmine Zaidi, PharmD Candidate
For questions, e-mail pharmd@prodigyrx.com
Citations
Milenkovich, N. "The Rise of AI in Pharmacy Practice Presents Benefits and Challenges." Pharmacy Times (2023) 89: 7.
Labovitz DL, Shafner L, Reyes Gil M, Virmani D, Hanina A. Using artificial intelligence to reduce the risk of nonadherence in patients on anticoagulation therapy. Stroke. (2017) 48:1416–9. doi: 10.1161/STROKEAHA.116.016281
Cutler RL, Fernandez-Llimos F, Frommer M, Benrimoj C, Garcia-Cardenas V. Economic impact of medication non-adherence by disease groups: a systematic review. BMJ Open. (2018) 8:e016982. doi: 10.1136/bmjopen-2017-016982