Autonomous pharmacies: Are AI and medications a good combination?

• Author:
• Author name

  Quantumrun Foresight
• November 8, 2023

Insight summary

Pharmacies are increasingly using artificial intelligence (AI) to automate tasks like pill counting and inventory management, freeing pharmacists to focus on patient care and reducing medication errors. Regulatory and cybersecurity concerns are rising alongside these advances, prompting the creation of AI risk packages and data safety solutions. Automation in pharmacies also paves the way for new health apps, the Internet of Things (IoT) in healthcare, and a shift towards more patient-centered care by pharmacists.

Autonomous pharmacies context

Automating manual tasks is one of the primary ways pharmacies use artificial intelligence (AI), including counting pills or capsules, compounding, inventory management, and contacting physicians for refills or clarifications. Automating tasks allows pharmacists to focus on other work, such as identifying potentially dangerous medication interactions; this is particularly important because 7,000 to 9,000 individuals die each year in the United States due to medication errors. Additionally, the cost of emotional and physical trauma caused by medication errors exceeds $40 billion USD each year. 

A report released by the Department of Health and Social Care in England estimated 237 million medication errors in 2018. Even if 72 percent carry little or no potential for harm, the number is still troubling. According to the report, adverse drug reactions significantly cause medication errors, resulting in 712 deaths yearly in the UK. Extreme accuracy is needed to ensure patient safety, which may be attainable with self-learning machines. 

AI-powered tools and automation may support pharmacists in their decision-making. For example, AI-powered tools can help identify patterns in data that may not be detectable by humans. Identifying and analyzing data may assist pharmacists in making more informed decisions about prescribing medications and help notice potential problems with medication distribution.

Disruptive impact

Many tech companies are developing automation solutions for pharmacies and health centers. For example, Israel-based MedAware uses big data analytics and machine learning to dissect thousands of Electronic Medical Records (EMRs) to understand how physicians treat patients in real-world situations. MedAware flags unusual prescriptions as a possible error, prompting the doctor to double-check when a new drug does not follow the typical treatment pattern. Another example is US-based MedEye, a medication safety system that uses artificial intelligence to help nurses prevent medication errors. The system uses scanners for pills and capsules and cameras to identify other medications. The software compares the drugs against hospital information systems to ensure accuracy.

Meanwhile, biotech firm PerceptiMed applies AI to check medicines during dispensing and administration. This technology reduces medication errors while enhancing patient safety and satisfaction by identifying the dosage of each drug in real time while ensuring delivery to the correct patient. Automation allows healthcare facilities and pharmacies to balance and distribute workloads while maintaining compliance, adherence, and efficiency. 

Implications of autonomous pharmacies

Wider implications of autonomous pharmacies may include: 

• Health departments creating regulations on who will be accountable for AI risks and liabilities for misdiagnoses and medication errors. 
• Insurance providers developing AI risk packages for healthcare institutions using automation.
• Cybersecurity firms creating solutions for pharmacy health data safety. 
• More smartphone apps can help patients track and compare their medications and prescriptions. 
• Increasing use of the Internet of Things (IoT) to connect scanners, cameras, and sensors to ensure accurate diagnoses and prescriptions.
• Pharmacists focusing on patient-centered care as machines manage the distribution and direction of medicines.

Questions to comment on

• How else do you think automation can change pharmacies?
• What are the possible reviews to ensure that pharmacy automation is performing adequately? 
• Who is at fault for AI and automation failure in a healthcare setting?