There is no denying that the role of Artificial Intelligence (AI) in healthcare has caused a major positive change in various fields, such as prescription drug management. Since AI has the capability to process huge amounts of data in little to no time, as well as generate insights in just a snap of a finger, AI has revolutionized the way medications are prescribed, managed, and monitored. Because of this, there have been significant benefits for healthcare professionals, pharmacists, and patients since efficiency, accuracy, and personalization in drug therapies have improved significantly.
One area where AI has proved invaluable is in improving pharmacy benefit manager technology or PBM technology. PBMs act as intermediaries between insurers, pharmaceutical companies, and drug manufacturers. They are focused on negotiating drug prices, managing formularies, and guaranteeing access to medications for patients. AI has played a huge role in enabling PBMs to simplify a lot of these processes which have led to improved patient care and more efficient drug management.
AI-Driven Prescription Decision Support
One of the major areas where AI has made a huge impact is in prescription decisions. AI has the capacity to provide healthcare professionals with relevant data and recommendations based on a given set of information gathered from a patient’s records.
For example, AI can easily analyze a patient’s medical history, what medications they are taking currently, and genetic data that would then enable AI to make recommendations to make sure the patient receives the most effective and safest drug therapies. This reduces the risk of medication errors, as well as helps reduce the risk of adverse drug interactions. Overprescribing is also prevented, and AI helps make sure that patients get the medications that are tailored to their specific needs.
AI can also help detect potential cost savings for patients. By analyzing data on drug prices and insurance coverage, AI has the power to recommend alternative medications or generics that are as effective as more expensive brands.
Enhancing Formulary Management with AI
Formulary management is the process of determining which drugs will be covered by insurance and at what cost. It is a complex data-heavy task; one that requires no errors in data presentation. Since AI is very accurate and efficient, this task can now be completed without taking up a lot of time, even when analyzing huge amounts of data. AI has the power to make evidence-based decisions about which medications should be included and excluded. This helps guarantee that patients receive the right medications at a lower cost.
AI also has the capability of predictive analytics that gives a forecast on drug demand based on historical data. This helps PBMs guarantee an adequate supply of medications while minimizing waste.
Improving Medication Adherence
Medication adherence is very important since it helps make sure that patients follow through on their prescriptions. Non-adherence has become very common, and it leads to poor health outcomes, increased hospitalizations, and drug resistance. AI helps in this area by developing personalized reminders and interventions to make sure that patients never forget to adhere to their prescriptions at all costs.
There are mobile apps and smart pill dispensers that can help with this. These apps can also monitor patient adherence and can also alert healthcare providers once this happens. Plus, AI can also detect whether a patient is at a high-risk of non-adherence and informs healthcare providers about this possibility so that it can be prevented.
The Future of AI in Prescription Management
As of today, the role of AI in streamlining prescription drug management has been a huge success. But there is no doubt that AI will still improve and grow to make processes even simpler and more efficient. PBM technology is benefiting from these advancements by becoming more efficient and effective in managing drug therapies and guaranteeing that patients have access to the medications they need at all times.
