Artificial Intelligence in Pharmacy: Improving Patient Outcomes

Artificial Intelligence (AI) in pharmacy refers to automated algorithms that perform tasks traditionally completed by human intelligence.


62% of healthcare companies plan on investing in AI, with around 50% of those fully utilizing the technology by 2025.



With its unique set of challenges, the pharmacy industry is already benefiting from AI-powered technology; research and development, prescribing decisions, treatment efficacy, adherence, and fraud, waste, and abuse detection are already being improved by AI.


This technology is not replacing humans in the pharmacy process. Rather it is providing stakeholders, from manufacturers to patients, the tools they need to improve outcomes.


AI + Drug Research and Development

According to an MIT study, only 13.8% of drug trials gain FDA approval. Drug manufacturers can expect to pay between $161 million and $2 billion for any drug that does complete the entire process.


86% of trials fail due to recruitment issues.


AI is key to improving the efficiency of drug research, development, and production.


By extracting thousands of clinical data points to create robust patient profiles, AI provides researchers and referring physicians the data they need to identify and enroll trial participants much faster than possible using manual research-based processes.


Likewise, AI reduces drug shortages and minimizes recalls. The potential to pinpoint precisely where disruption or contamination occurs in the supply chain allows manufacturers to correct or mitigate issues quickly. Faster identification of issues leads to faster notification of providers and patients, which improves health outcomes.


AI also speeds up the discovery of new drugs. By collecting, grouping, and testing digital information more efficiently than human analysis, AI-powered analysis increases the likelihood that new treatments for complex diseases like ALS and Alzheimer's can become a reality.


AI + Prescribing

In the early months of the COVID-19 pandemic, one company put AI to work by developing a product that identifies the drug and dose of individual pills in real-time while ensuring delivery of the medication to the correct patient.


Developed to streamline the pharmacy process so providers could spend more time administering vaccines, AI also reduces medication errors. Approximately 7,000 to 9,000 patient deaths in the United States are attributed to medication errors each year. The financial cost of these errors exceeds $40 billion annually.


AI eliminates human error, allowing pharmacists to take an active role in patient care, shifting to a safer, value-added model.


AI + Treatment

AI significantly improves a physician's diagnostic capabilities by providing data-driven patient categorizations that assist in earlier disease detection.


Complex algorithms employed to analyze a patient's health history, prescribed drugs, and individual needs support doctors in selecting the ideal treatment.


AI also significantly improves the use of specialty drugs.


The complexities of specialty treatment make it expensive for payers and patients.


AI gathers valuable data from providers and specialty pharmacies and applies it across the industry to help manufacturers perfect medications, doctors make more informed decisions, and patients achieve better outcomes.



AI + Adherence and Dosing

Adherence and dosing are essential in the development stages of the pharmacy pipeline.


To prove the success of a drug trial, pharmaceutical companies rely on voluntary participants to follow trial rules and guidelines. AI has been used to improve drug adherence.


The results of one study showed that when utilizing a facial recognition AI system, participant adherence rose from 71.9% to 89.7%.


Another AI technology continuously identifies the optimal dose of a cancer drug, allowing patients to see positive outcomes sooner.


Adherence and dosing tools are applicable beyond clinical trials. AI is valuable to insurers, plan sponsors, and patients in everyday prescribing and treatment as they search for ways to contain drug costs and improve health outcomes.


AI + Fraud, Waste, and Abuse

The National Care Anti-Fraud Association estimates that fraud, waste, and abuse (FWA) cost health care organizations $70 billion to $230 billion annually. However, the precise amount is unknowable because only 10% of fraud is ever detected.


With AI technology, increased insight into prescribing habits, the chain of custody, and patient behavior allows organizations to better investigate and confirm suspicious, costly behavior.


A major hurdle to monitoring for FWA is the disconnect between pharmacy and medical claims. Organizations rarely see a patient's full pharmacy and medical activity in one report, making it challenging to identify FWA.


With AI, organizations can aggregate and define large amounts of data, providing a more holistic view of prescribing habits and more accurate predictive models.


One FWA detection AI-powered detection program saved its health plan clients $279 million in the first year alone.


The application of AI in the pharmacy industry is far-reaching and could fill gaps that have long plagued the industry.


However, time, money, human resources, and resistance to change are barriers to effective implementation across the pharmacy pipeline.


Ultimately, AI technology will improve research and development, prescribing, treatment, adherence, and FWA detection, which will significantly enhance the pharmacy experience for the patient.

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