In today’s rapidly evolving healthcare system, we see artificial intelligence (AI) as a vital part in this transformation. Across various areas of the healthcare industry, AI is continuously being integrated to streamline operations, improve medication adherence, optimize treatment outcomes, and improve patient care. With this advancement of AI, there are many ways that it could be incorporated in pharmacy settings. Let’s explore ways where this new technology is beneficial.

We have seen many healthcare organizations using AI to enhance patient care and outcomes. Chatbots are used to answer straightforward, factual questions to provide patients with immediate answers to avoid the often-delayed conversation with a provider. AI is used in the notification of adverse reactions. In the case of a patient experiencing high blood pressure, an alert can be sent to their healthcare provider comparing the patient’s vitals to baseline values pulled from datasets. Artificial intelligence is also commonly integrated into electronic health records to aid in medication reconciliation, medical history updates, identifying potential medication discrepancies, and ultimately saving healthcare providers’ time.

Within the pharmacy, AI is being integrated in the dispensing process for visual dispensing accuracy and verification of medication, dose, and quantity. AI is also being leveraged to expand same-day delivery services. Streamlining patient support through AI-powered communications helps to reduce the pharmacy staff workload and focus efforts on the communications that require human intervention. There is so much data available within a pharmacy practice management system that AI could be expanded to many aspects of profile review, intervention identification, scheduling assistance, discussion preparation, and clinical documentation support.

Pharmacies are not the only stakeholders benefiting from AI, as it has also been increasingly incorporated into payer and pharmacy benefit manager (PBM) systems to flag claim errors, streamline benefit contract reviews, and prevent fraud, waste and abuse. HealthPlan Data Solutions developed a model that can identify contract specifics (such as specialty, generic and brand pricing) and provide these details in a “single hub” for all contracts and amendments, eliminating searching through extensive folders and documents. These models have been effective in identifying claim errors, specifically regarding insulin copay limits. They also allowed HealthPlan Data Solutions to correct the claims and reimburse members who had been overcharged. In an initiative to implement NADAC-based reimbursement for independent pharmacies, HealthPlan Data Solutions worked with CareSource on an AI model to identify reimbursement discrepancies. The model ended up flagging claims with incorrect setup for 340B reimbursement and avoided about $1 million that either would have been absorbed by the company or recouped from the pharmacies.

AI can be seen in the prior authorization process for Health Care Service Corporation, which operates BCBS affiliates in Illinois, Texas, Oklahoma, Montana, and New Mexico.  Their system made prior authorization 1,400 times faster and expanded its access to inpatient acute care, long-term acute care, inpatient rehabilitation, skilled nursing care, outpatient and inpatient hospice care, home health, and outpatient services.

AI is being used by pharmaceutical manufacturers and supply chain vendors. Supply chain providers can use AI to help companies predict process bottlenecks, identify quality control issues, and proactively suggest corrective actions.  AI is also used in inventory management to predict future medication demands based on previous purchases. For example, an AI company created software for a German online and catalog retailer, Otto Group; the software can predict what the retailer will sell in 30 days with 95% accuracy. This system allows for direct delivery from the supplier to the consumer without having to pass through the warehouse.  AI allows for better drug discovery by cross-referencing several sources of published literature and data for R&D, reducing cycle times and costs to improve clinical development.

With all these advancements and improvements in pharmacies, incorporating AI still has its challenges. Pharmacies will need to ensure these systems are accurate, trustworthy, HIPAA compliant, and secure enough that all patient information is protected. Pharmacies may be liable for any mistakes or errors that occur with the new AI systems, and pharmacists must be trained to use them properly and remain up to date on any laws or regulations. Finally, lack of general trust in AI along with the question of patient consent can raise issues. In what areas of healthcare are you currently using AI? How will healthcare be impacted by AI in the future?