Pharma Focus Asia
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5 Proven Ways to Take PBM’s to the Future ‘Today’ with Conversational AI

Ravi Iyer, Senior Director - IT, Elevance Health

Narasimha, Result-driven Leader

Today, engaging patients by merely sending emails, messages, phone calls, or through mobile apps is completely outdated. The journey involves: enhancing the user experience by boosting efficiency, speed, accuracy, and strategy. The acceleration of AI-powered self-service tools in the PBM industry, especially during COVID-19, has created overwhelming demand-led innovation to help patients collaborate seamlessly with their payers, providers, and pharmacies.

artificial intelligence

Gone are those if you’re still thinking of keeping your customers engaged with your brand by merely sending emails, messages, phone calls, or mobile apps! They are expecting way beyond that today. It begs the question: Is the rapid evolution of self-service tools creating the need to expect more and more...

To be right on the button, when we say self-service tools, the first thing that comes to our mind is applications powered by artificial intelligence (AI). In a nutshell, the emergence of AI in almost every gamut of the industry has upgraded the standards of delivering services– rapidly within our fingertips.

Out of all the industries that exist today, healthcare is the one that plays an important role in people's lives to help and provide better patient care at all times. However, the industry is constantly plagued by the world's biggest challenge of “providing on-par patient care using high-end technologies and helping patients collaborate seamlessly with their payers, providers, and pharmacies."

Approaching the Challenges by Capturing the Scope

The COVID-19 pandemic unleashed new opportunities across industries in both vertical and horizontal dimensions and created overwhelming demand-led innovation in the PBM space. Let's take one step back to revisit the time when the pandemic hit and the pressure the health systems had to take to adapt to new ways in order to improve patient care. (Discussed in our previous article )

While PBMs continuously strive to reduce drug costs and improve member experience, it's a wheel within a wheel when the exchange of information and seamless workflow process decides the value of the patient care journey. Agree?

Approaching the Challenges by Capturing the Scope

Conversational AI: The Zenith for the PBM Industry to Enhance Member Experience

Creating wonders in the PBM pace is not only about boosting efficiency, speed, accuracy, and strategy; the journey involves elevating and enhancing the end-user experience. This is where conversational AIs come into the picture.

As per a recent cross-industry study , nearly 69 per cent of consumers think interacting with businesses using chatbots is the best option to address straightforward queries. The statistics also reveal that the paradigm shift to a mobile approach has gone up to 90 per cent and above across significant segments, including adults with lower incomes and people over 65.

Conversational AI , such as virtual assistants and chatbots, is estimated to grow into a US$15.7 billion market by 2024.

Every single year, nearly half a trillion dollars are spent on medications in the US, including prescription drugs, supply chain management, pharmacy benefit managers (PBMs), pharmacies, distributors, and providers dispensing and administering the medications. Did you know that one out of every seven dollars spent on healthcare is associated with medicine?

Many use cases have proved that AI is enabling communication and is getting better with each passing day, especially in the PBM industry and health plans, including its presence in analytics, insights, and the decision-making process.

Here’s a list of use cases that show how AI can help PBMs seize opportunities while lowering their investment strategies: A chance for pharmacy benefit managers to focus on consumer transparency.

Automated Prescription Management

Automated Prescription Management: Prescription Refills and Information

If a patient is prescribed a new drug, they spend a lot of time online understanding the drug on various platforms, including websites, apps, and much more.

Providers, pharmacies, payers, and other stakeholders can automate prescription data and include business analytics such as a patient's current medication brand names, the amount they are taking, how many refills are still available, and the name(s) of generic substitutes.The application can be integrated with other AI applications to place medication refill orders, provide prescription status and requests, and even send proactive messages to let patients know when their prescriptions are available for pickup.

IVAs (Virtual Assistants) have the power to provide specific information to the patient, such as drug interactions, the composition of the drug, recommendations, and dosage based on age and other criteria. The plus factor is that IVAs are budget-friendly and are a great networking tool between manufacturers and pharmacies.

Increasing Efficiency and Improving the Patient Experience

NLP in EMR

An Electronic Medical Record (EMR) is a virtual tool that contains humungous amounts of unstructured data, mainly used by physicians to record patients' information. One can find tons of information about patient interactions with their physicians, both previous and current.

Important information such as significant risk factor and a patient's active status can be easily accessed.EMR has already taken center stage in the healthcare continuum. What we are witnessing today was once an opportunity – a mere transformation of a volume-based model to a value-based model. Today, EMR has become paramount to gathering information and insights into patient health and enhancing patient-centric engagement at every step.

The Opportunity:

When physicians record patient information, they collate specific information about a patient under one section of the EMR and spend nearly twice as much time feeding data into the system. And there could be a possibility of losing some information in the entire process. This unstructured information must be mapped back into the EMR and applied with analytics to extract insights.

AI-powered tools have benefited physicians in augmenting care provision, providing appropriate recommendations and critical insights at the point of care while reducing data entry time. When these tools are integrated with an EHR, it identifies key aspects such as specific patient information, potential diagnosis, drug therapies, risk factors, and the physicians' decision-making process.

Robotics in Pharmacies

Robotics in Pharmacies

Pharmacy automation  is rapidly expanding, with a US$7.8 billion market expected by 2024, growing at an 8.6 per cent CAGR. There is no doubt that pharmacists are dedicated experts at dispensing drugs. At the end of the day, they are humans. There could be a chance of occasional medication dispensing errors, and when people rely on daily medication, accuracy, and precision matter the most.

The Opportunity:

By leveraging robots, pharmacies can fill prescriptions and automate the manual process to enhance efficiency and accuracy in drug delivery while improving patient safety. A robotic pharmacy accepts prescriptions, fills them, and then delivers medications to nurses' stations. Spending less time filling orders WITHOUT ERROR means pharmacists can focus on other responsibilities that require human supervision, such as patient counseling and doctor consultations.

According to the NIH , medication errors harm an estimated 1.5 million people annually, costing at least US$3.5 billion annually in the US. It is also estimated that ADEs (adverse drug events) affect approximately 2 million hospital stays annually and prolong the stay by 1.7–4.6 days.

Pharmacies are now getting robot-powered and automated to modernise the roles of pharmacists and the traditional drug dispensing model. The robot pods have the capability to dispense over900 different medications and can be paired with a patient’s other medications, such as a 90-day medication supply – labeled, filled, and packed accordingly with ZERO CHANCE of human error. This move can automate 80 per cent of the pharmacy’s drug dispensing requirements with accuracy and provide more drug safety.

Transforming Care and Lowering Physicians’ Workload

While we continue to reap the fruits of innovations accelerated by the COVID-19 pandemic, conversational AI has been distinctive in helping health providers understand and act spontaneously when a patient is critical. Telemedicine bots, to be precise, help providers diagnose, treat and deliver clinical services remotely, and communicate the procedures or instructions that a patient’s family must follow until aid arrives.

Providing answers to patients’ queries is the key to keeping them engaged and connected with the brand. Voice-activated chatbots powered by AI can simplify complex questions and provide adverse effects, addressing complaints and non-compliance with a humanised approach. Powerful next-generation bots can converse like humans and properly engage in multi-rooted conversations. Furthermore, insights can be drawn to predict unforeseen side effects or adverse impacts besides providing key details for decision-making.

Unlocking Potential Opportunities with AI in Real-Time

Unlocking Potential Opportunities with AI in Real-Time

Improve Member Engagement and Healthcare Spending

To improve and customise member engagement, PBMs are focusing on healthcare spending through AI. The AI-enabled chatbots linked with cloud applications fetch agents, employers, and plan members' precise information on benefits, costs, and providers, besides predicting medical expenses by lowering members' spending.

Outcome-based Contracting (OBC) & Value-based Programs

PBMs are leveraging AI platforms to explore and analyse unstructured patient data to provide payers and providers information on quality metrics and feedback on services for value-based care reimbursement after structuring this data. The key accelerators for value-based programs can be predicted by identifying patient populations, therapy effectiveness, disease and treatment options, and metrics to assess treatment outcomes.

Predicting Barriers for Field Reimbursement Managers (FRMs)

A pharma-based company has implemented AI and ML to improve risk score models and enable field reimbursement managers (FRMs) and stakeholders. The AI-ML-enabled solution prioritises interventions for patients by identifying potential roadblocks before they occur. Additionally, patients can request details on insurance benefits, channels, diagnosis codes, and out-of-pocket expenses and bridge patient status data to other relevant datasets such as dispensing, copay, and population data.

Estimate the best pricing and reimbursement

Similarly, an analytics platform developed a drug pricing measure to demonstrate how predictive analytics optimises Maximum Allowable Cost (MAC) by tracking actual acquisition costs and proven concepts from other sectors and applying the power of predictive analytics to drug pricing.

Identifying fraud, waste, and abuse (FWA)

It is crucial for carriers to discover and cut incorrect billing practices and streamline the reimbursement process. PBMs can utilise AI in this area to determine possible issues with prescription claim data, decrease erroneous claim payments, and ease the manual efforts frequently needed for a claim review - ultimately identifying potential fraud and misuse.

Thoughts

AI may not be a well-oiled machine today. However, businesses are euphoric to take a big leap to discover more potential ways of leveraging AI to automate various activities by leveraging modern machine learning algorithms and deep neural networks. The future of AI looks promising as it has the potential to transform healthcare into connected healthcare while making an impact on pharma revenues. Tetrasoft’s PBM experts believe that joining ML and AI forces can benefit health insurers by creating better health plans, optimising distribution activities, and managing claims while delivering proactive and personalised engagement.

1. https://www.pharmafocusasia.com/articles/how-pbms-transformed-to-provide-easy-access-to-prescription-drugs-post-covid-19
2. https://www.chatbot.com/blog/chatbot-statistics/
3. https://www.businesswire.com/news/home/20190328005384/en/15.7-Bn-Conversational-AI-IVA-and-Chatbots-Market---Global-Forecast-to-2024---ResearchAndMarkets.com
4. https://asianroboticsreview.com/home340-html
5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016741/#:~:text=Economic per cent20impact per cent20(United per cent20States)&text=Medication per cent20errors per cent20harm per cent20an per cent20estimated,(3) per cent20(N).

Ravi Iyer

Ravi Iyer is a visionary and innovative executive with diverse experience in leading and managing product delivery, client implementation, customer service, and operations with direct responsibility for multimillion-dollar budgets. He has extensive experience delivering across multiple disciplines, including Data Management, Data Governance, Cloud Architecture, Advanced Analytics, Master Data Management, Digital Products, and Digital Transformation. Excellent communicator who works collaboratively to deliver technology strategies and value added solutions that meet the needs of all business functions. Ravi is currently the technology executive and Senior Director at Elevance Health Inc.

Narasimha

Narasimha is result driven leader with vast experience in executing various PBM, Health care, Financial, and securities trading applications. Technical expertise in Big data, Cloud, Analytics, Mainframe, BPM, testing, and Data warehouse projects at esteemed organisations like Anthem, Tetrasoft, DST, HCL, Deutsche bank, and Atos Origin. He currently works as Solution Architect at Tetrasoft Inc. Narasimha has vast experience in Pre-sales, Project management, effective customer communication, Architect, Technical Lead, On-site coordinator, and business Analyst roles for various complex assignments across the globe.

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