Drug Discount Programs Poised to Change with New Tech, Pharma Execs Survey Finds

Pharmaceutical executives firmly believe that technology is poised to transform drug discount management, but they’re less-than-satisfied with the tools currently available to do it.

Sudhakar Velamoor

That was among the major takeaways from an online survey of 100 pharma executives that demonstrated how the practice of drug discounting is at an inflection point.

Specifically, the survey found that 99% of survey respondents agree that emerging technologies are poised to transform drug discount management for their organizations, while 58% reported that they’re not satisfied with the technologies and tools they currently are using for drug discount management.

To remedy the situation, pharmaceutical executives expect technologies such as data analytics platforms, artificial intelligence (AI), and machine learning will increasingly be used to improve drug discount processes over the coming years, the survey found.

The current approach: Too many manual processes

The survey data is unclear about whether executives feel greater dissatisfaction about their own drug discount management technologies or other, third-party solutions. However, it is clear that most have adopted a variety of tools to assist in the process.

For example, nearly one-half of executives said their organizations have implemented two major tools for drug discount management: data analytics platforms (48%) and revenue/gross-to-net reporting management platforms (47%).

These two popular solutions are joined by several other tools, the survey revealed, including:

• Manual data entry into spreadsheets (35%)
• Third-party managed services (34%)
• AI and machine learning solutions (30%)
• Bot technologies that scrub discount program lists (24%)

It is somewhat mind-boggling in 2024 that more than one-third of pharma organizations still rely on manual entry of data into Excel spreadsheets to track duplicate discounts that can cost millions of dollars a year in lost revenue if not identified and recovered. But that’s what the numbers revealed.

The problem with manual entry is that drug discount programs based on the method are extremely difficult to scale as drug discount programs such as the Medicaid Drug Rebate Program (MDRP) and 340B are growing rapidly. Inevitably, companies that employ these error-prone processes will experience inefficiencies that create unnecessary costs and sap revenues.

The following comments from pharmaceutical executives who responded to the survey illustrate the futility of depending on manual tools for drug discount programs:

• “Relying on manual processes and other tools that we use makes our drug discount management difficult and does not fulfill our needs.”
• “Because of manual input, the process of drug management has become very tedious, and there are chances of error.”
• “It is difficult working with our current tools and technologies as the management of drug discounts requires many considerations and data from various sources.”

More automation, greater transformation

For pharmaceutical companies, it is no longer tenable to run underperforming drug discount programs amidst fierce global competition and economic uncertainty. Pharmaceutical executives understand this. For example, the survey found that 39% of executives predict their organizations will use AI tools in their drug discount programs within the next five years, an increase from the 30% currently using AI. Similarly, 52% of executives expect their organizations to deploy data analytics for drug discounts within five years, up from the current 48%.

At the same time, thankfully, the days of manual processes to manage drug discounts may be coming to an end. The survey revealed that the use of manual data entry into spreadsheets is expected to drop by more than one-half over the next five years to 17% from 35%, a strong sign that executives recognize that their programs are being constrained by manual processes.

Drug discount programs are expanding, and pharmaceutical companies that manage these programs can no longer support them with manual processes and legacy technologies. Advanced technologies, such as cloud native data lakes, data pipelines that enhance quality, data analytics, and AI, are poised to change the industry, driving more transparency and enabling greater scale.

Sudhakar Velmamoor is chief technology officer for Kalderos.