This blog is the second in a series that shares our vision for a unified access platform. As co-founder and EVP of Product and Strategy for IntegriChain, most of my waking hours — and probably even my sleep — is dedicated to ensuring that IntegriChain delivers value for a market gap. This is where I began to sort out the business dynamics of Market Access as the world moves to specialty and precision medicine.

In my last post, I introduced our work to codify, if you will, the key goals of Market Access teams as they look to the future with the advent of speciality and precision medicine and how achieving these goals has been stymied by siloed data and processes. When a team needs data from across these silos, too often the projects become mired in vendor data requests, manual data wrangling, and other sources of toil and delay. The Market Access function of the future cannot remain handcuffed by siloed data and processes; it must be expansive and integrated.

We began the blog series by examining the commercial goals of Market Access; today, we deep dive into the financial goals.

Market Access Financial Goals: Data-Driven Decisioning

Imagine greater visibility into brand performance, increased predictability around net prices, and the ability to quickly and accurately model potential contracting and pricing changes. This financial nirvana would require integrated channel mix, payer mix, and patient service utilization data together with an understanding of the interdependencies between net prices and channel/service/payer strategy. Let’s take a run through three primary financial goals of Market Access.

GTN & Pricing Visibility

Gross-to-net (GTN) and government pricing “what if” analyses require the integration of everything plus the kitchen sink. Analysts might need to model a change in contract terms, a change in channel strategy, or increases or decreases in patient support programs. For this, they require access to data for nearly any fee and price concession including channel service fees, patient support program utilization, and any rebate or administrative fee. For any manufacturer, the data exists – somewhere – but is often not accessible or usable due to fragmented platforms and a lack of integrated master data. Forgoing these analyses or relying only on high level data, however, can result in bad decisioning with unintended consequences. Streamlining the process of GTN and government price modeling is critical for specialty drugs that are entertaining new channel designs or facing increased pressure to contract. Manufacturers need to cut out the data middle men and eliminate the manual work that holds back this type of analysis today.

Contract Modeling & Performance Management

The key to modern contracting success is data-driven decisioning. For Market Access teams, this means the ability to understand a payer’s level of control not just through formulary tier but rather through the impact of their policy restrictions. Not all policy restrictions are created equal, and not all payers are imposing the same level of barrier on patient access to specialty therapies. For two decades, manufacturers have utilized combinations of formulary, claims, and rebate data to assess the potential impact of contracting decisions on demand: does the rebate agreement open up true new demand or not? Does it cannibalize existing demand and merely pay out a higher rebate? But now for specialty and precision medicines, manufacturers need to be able to leverage hub and specialty pharmacy data sets alongside those legacy data assets to fully understand how policy restrictions are impacting patient initiation and adherence and also to validate that contracting decisions solve the patient hurdle.

GTN Digitalization

No Market Access processes face as many challenges from data silos as gross-to-net forecasting and accrual management. Gross-to-net requires everything from rebates, chargebacks, and government prices to channel inventories, shipments, specialty dispensing, and co-pay program utilization. Too often, highly valuable Gross-to-Net team members are bogged down in data chasing, data wrangling, and other toil directly caused by the disconnect between revenue management systems, channel data aggregation, and the forecasting process. Manufacturers must free up these highly knowledgeable resources so that they can spend more time executing or supporting the “what if” analysis and contract models that can actually move the business forward. After years of evaluation and proof of concepts, the industry is finally pushing ahead with automation of gross-to-net. But without a more unified data backbone, these projects are proving very challenging and costly.  

There’s more to share on the operational goals of Market Access in my next post.