In the wake of the Covid-19 pandemic, pharmaceutical companies have accelerated their uptake of healthcare technology in their bid to develop better testing protocols and vaccines. As a result, major growth and rapid demand for artificial intelligence (AI) and machine learning is expected in healthcare this year, with Accenture predicting the market value of health AI to reach $6.6 billion in 2021.
Digitization is no longer an academic endeavor; hospitals have recently taken advantage of AI and ML to improve diagnoses, boost patient outcomes and increase revenue. Some hospitals use AI technology to predict which patients are at risk of contracting cancer, osteoporosis and cardiovascular disease.
Nearly every hospital in America plans to use AI across the entire revenue cycle in the next few years.
Nearly two-thirds of those who responded cite limited use of AI in parts of the revenue cycle. By 2023 98% of healthcare leaders hope to use AI in RCM in some form. Advances in implementation are likely to increase in this time. Currently only 12 percent consider their AI implementation to be mature, with 35 percent anticipating maturity by 2023.
AI empowers widespread improvements, however the approach is tactical, and not end-to-end.
Hospitals that use AI in RCM are doing so with the view to improve patient and payer payments (83%) and cash flow (80%). AI functionality is most typically used for eligibility and benefits verification (72%) and patient payment estimation (64%). Prior authorization (68%), payment value and timing estimation (62%), and denials management (61%) are expected to emerge as the top AI-powered functions in revenue cycle management by 2023.
Since 2020 the world has turned more and more to AI to develop predictive models that would show how Covid-19 would spread, and when herd immunity would be reached. Predictive tools and machine learning has helped immunologists make new discoveries and develop Covid-19 vaccines.
The Current Challenges Faced by Revenue Cycle Managers
Over and above the pharma industry’s science and research and development aspect, they, like all businesses, face operational and financial challenges.
Challenges such as cost-to-collect, denials, underpayments, and patient collections are at the top of the list, along with A/R management and staffing. Revenue cycle managers are turning to AI solutions to drive improvements quickly and efficiently in all of these areas.
Barriers to AI Adoption
The operational benefits that AI technology brings to a business are well documented. According to a recent study by Engine of IT, financial, c-suite, and the hospital’s revenue cycle leaders and health systems, they are actively seeking ways to deploy modern technologies to address complex business problems.
However, the findings showed that trust, budgetary constraints, and security concerns are holding most pharma back from rapidly adopting AI technologies into their operations.
Outdated thinking and processes at an executive level are also a challenge. Many pharma still believe that the “science sells” and have yet to define the ROI for marketing or demonstrate ROI on basic services. Additionally, they have yet to extract meaningful insights from their data as the main portion of their investment has not been in innovative commercial capabilities.
More than that, a complete shift in marketing and sales thinking would be required. For pharma to utilize AI to simplify, automate, and gain deeper insights, they will need to move away from the traditional “sales rep and physician” dynamic they have relied on for decades.
This is happening now quite simply because the commercial side of Life Sciences has to evolve in order to drive innovation actively and achieve outcomes sustainably.
Goals like delivering hyper-personalized customer experiences, exploring new avenues of growth, and achieving greater levels of efficiency are only possible when AI technology is radically embraced.
The reason for this is, on the whole, that AI tools like SEDGE take the operational burden out of the system, freeing up the organization to focus on their reaching business goals. AI makes it possible for pharma to continue delivering products and supporting services that help patients and healthcare providers improve health outcomes in more economically sustainable ways.
How AI Solves these Challenges
There are many ways that Life Sciences companies can improve commercial operations and significantly accelerate growth, profitability and sustainability through utilizing AI.
Over 80 percent of revenue cycle leaders consider the improved reimbursement management that comes with AI well worth the initial capital outlay, while those outside of the revenue cycle are less inclined to invest (IT: 46% and corporate: 44%). Therefore, the first, most important step is to identify when and where AI can be most effective from a commercial standpoint.
Here are some ways that AI can support the revenue cycle
AI’s ability to quickly identify patterns in vast volumes of data, learn from it, and then make accurate predictions about the likelihood of similar patterns taking place again in the future makes it an ideal tool in supporting the revenue cycle.
AI tools help to Optimize:
Patient and payer payments
Eligibility / benefits verification
Patient payment forecasting
Payment amount/timing forecasting
Additionally, AI eases operational burdens and improves profitability in the following areas:
Intelligent automation of admin-heavy, time-intensive mundane tasks to drive increased productivity and profitability.
Enhanced decision-making which augments leadership’s decisions, provides business intelligence that increases growth velocity, reduces risk, and improves sustainability.
Enhanced customer interaction through intuitive personalization's and real-time content.
Intelligent product creation to accelerate growth through innovative therapeutics and discovering new value propositions for payers.
Embrace AI in an Affordable, Easy-to-Use Platform for Immediate Results
SEDGE is a powerful AI tool that processes masses of data quickly and efficiently. SEDGE gives decision-makers insights and unbiased forecasts that are data-driven, ensuring your business utilizes the full value of your customer, supplier, market, and R&D data.