When discussing the role of AI in Pharma with a Pharma executive recently, one executive said:
“It doesn’t have one, does it? The biggest challenges the industry faces are reimbursement and access and compliance and concordance. But can AI address these problems?”
– EU Commercial Vice President —
A primary focus for many governments and other payers in both developed and emerging markets is to minimize Pharmaceutical spend growth by enacting pricing and reimbursement legislation. This has been partially brought about by the increasing aging population which, in turn, will increase drug expenditure because the average elderly person consumes 3-5 times more healthcare resources than a younger person.
While reference-pricing systems have already brought prices down in many countries, they have not stopped healthcare payers from pushing for even greater savings. The governments in both Sweden and the UK have secured pricing deals with drug manufacturers on top of other efforts to drive down costs. Such policies can be controversial, leading to reversals in some markets. Germany, for example, is under pressure to revise its value-based pricing scheme for Pharmaceuticals
Healthcare policy-makers and payers are increasingly mandating, or influencing, what doctors can prescribe. As treatment protocols replace individual physician prescribing decisions, Pharma’s target audience is also becoming more consolidated and more powerful, with profound implications for its sales and marketing model. The industry will have to work much harder for its dollars, collaborate with healthcare payers and providers, and improve patient compliance.
A Shift to A Value-Based Healthcare System
A basic tenet of healthcare reform is the quest for improved quality and reduced cost. In turn, this is driving a dramatic rethinking of the traditional fee-for-service reimbursement system to one in which reimbursement is based on value (defined as quality/cost) as it applies to the health of not just individual patients but populations.
One result of this is changing formulary management strategies. In 2013 in the US, nearly half of all health plans had moved to formularies based on clinical outcomes, while another 20% planned to implement such formularies in 2014; 40% had created formularies based on value, while 16% planned to do so in 2014; a third were using big data (analytics) to influence formulary decisions and clinical guideline development, while 24% planned to do so in 2014. We are seeing a move to clinical-based formularies throughout the developed world, with increasing emphasis on the value of Pharmaceuticals. In 2014 alone, the National Institute for Health and Care Excellence in the United Kingdom 11 high-priced drugs declined (or recommended that the drugs be declined), citing cost compared to efficacy.
Health plans, and employers, are increasingly looking for head-to-head and comparative effectiveness studies as well as real-world evidence in making any formulary decisions. As the authors of a report on value-based reimbursement and the Pharmaceutical industry noted: “Value attributes (e.g. outcome or performance variables of interest) must be collected, measured, valued, aggregated and converted (using a decision rule) to evaluate whether the value metric was achieved. Also, there must be a consensus program of data collection, typically initiated early in the commercial lifecycle.”
Pushback on Specialty Drugs
Specialty drugs have been one of the bright spots in the Pharma industry, accounting for nearly 30% of total pharmacy spend on the commercial side in 2013, despite accounting for less than 1% of all US prescriptions. Spending on specialty drugs increased 14.1% that year, 17.8% in 2015 and is expected to increase between six and eight percent annually between 2016 and 2018. This is driven, in part, by high-priced hepatitis C (HCV) drugs entering the market. At the same time, spending on 6 of the top 10 traditional therapy classes dropped, primarily because of lower unit costs.
However, state systems and commercial insurers globally are pushing back against these high-cost drugs. Plans are designing special formularies for specialty drugs, implementing Oncology pathways to rein in costs, and shifting coverage from the medical benefit to the pharmacy benefit, which may put greater financial responsibility on patients. Indeed, 61% of commercial plans (75% of covered lives), and 87% of Medicare Advantage and prescription drug plans charged a co-insurance rather than co-pay for specialty drugs in 2013. In late 2014, state Medicaid directors sent an eight-page letter to Congress urging “an immediate federal solution” to the cost of specialty drugs.
Providers are also pushing back. In April 2013, an international coalition of Cancer experts released a call to action, decrying the “astronomical” cost of certain drugs. The letter followed the actions of Oncologists at New York’s Memorial Sloan-Kettering Cancer Center in 2012 who publically refused to prescribed the drug Zaltrap (zivaflibercept) for Colon Cancer because it was twice as expensive as similar therapies. Their outcry eventually led the drug’s manufacturer to slash the price in half. These efforts are having an effect; Sanofi and Gilead Sciences Inc., which make the high-priced hepatitis drug Sovaldi, reported lower-than-expected sales in the third quarter of 2014. Add the threat of biosimilars for many specialty drugs, and it is clear that this lucrative arena is under attack.
To combat the risk of significant revenue loss from these drugs, manufacturers need to determine pricing and marketing based on more than just recouping research investment and hitting profit goals. Analytics must include the effect of pricing on increasingly cost-conscious private and public payers, as well as the true value of the product. For instance, cost-benefit analyses of Solvadi find it is more cost-effective than current treatments for HCV. But how do manufacturers get that message to their customers in the most effective way? That’s where predictive analytics comes in.
Changing Delivery Models
Today, more providers are salaried employees, bound by their organization’s prescribing policies which often limits sales rep access to providers and restricts them to organizational formularies. In addition, the growth of accountable care organizations (ACOs), which share risk for the health of populations and the cost of care, is also altering prescribing behavior. This, in turn, requires that Pharmaceutical companies identify innovative ways to market in this new environment. Such changes require greater use of data to meet the needs of individual customers.
Pay-For-Performance Is on the Rise
A growing number of healthcare payers are measuring the pharmacoeconomic performance of different medicines. Widespread adoption of electronic medical records will give them the outcomes data they need to determine best medical practice, discontinue products that are more expensive or less effective than comparable therapies, and pay for treatments based on the outcomes they deliver.
Pharma will have to prove that its medicines really work, provide value for money and are better than alternative forms of intervention.
How Artificial Intelligence Can Help
Pre-AI, pricing in Pharma was all focused on the clinical attributes of a drug versus its competitors. This focus will not get a drug approved and reimbursed by payers anymore. With the shifts in this space, Eularis have been working on Artificial Intelligence powered pricing analytics that utilize real-world data on patient populations and analyze the clinical trial data alongside this to deliver a value-based price designed to appeal to more payers than the competitors due to the increased value to them, and also weighed up to provide maximum profit to the company.
So, to answer the question, “The biggest challenges the industry faces are reimbursement and access. But can AI address these problems?” …. Yes, it can!
For any information on this use of Artificial Intelligence and how Eularis work in this space, please contact the author at Eularis: https://www.eularis.com
