Published spend transparency data requirements were introduced via the Open Payments program, as mandated in the Affordable Care Act[1], to raise awareness of the financial influence that drug and device manufacturers have on the so-called covered recipients (physicians and a defined set of teaching hospitals). The intent was to place higher scrutiny on how, and how much, life sciences companies, or any company marketing a prescription brand, are spending to develop, promote and sell branded prescription products in the United States. The underlying premise of this omnibus legislation was to highlight factors driving increased healthcare costs, expand healthcare access and reduce aggregate healthcare costs.
Providing visibility into the nature and purpose of the relationships and transactions among the applicable manufacturers and the physicians and institutions that would potentially prescribe or administer them is primarily intended to benefit consumers. While the effect of the legislation is not precisely quantifiable, open access to the detailed spend data appears to be changing the industry culture and behavior of healthcare practitioners. Consumers and media-based consumer watch groups look for outlier connections and activities in the reported data that may indicate inappropriate business relationships.
Thus, we can conclude that published transparency data can be used to benefit the consumer – but can this data also be used to benefit the product manufacturers and the companies promoting the products? In other words, can the companies reporting the data, use the data to extract intelligence to drive better informed business decisions?
Spoiler alert… Yes.
Understanding how published transparency data can be used to benefit the industry also requires understanding of data limitations. There is a subjective nature to the way the data is reported – not all companies interpret the rules of reporting the same way. For example, Company A may spend $100 on lunch for Dr. Smith’s office, an amount that is required to be reported. However, it turns out that three out of the four staff members at lunch are not licensed practitioners and, therefore, not considered “covered recipients” by the letter of the rule. Company A calculates that only 25%, or $25 needs to be reported. Interpretive differences and varying levels of creative reporting tactics can make the data very subjective and render it unreliable for making certain types of highly specific conclusions. One example of this would be answering the question: What are the true promotional expenditures associated with the covered recipient for that transfer of value (TOV) event? The manufacturer may have reported $25 for Dr. Smith but spent at least $100, or four times, the amount reported. And if there were nine staffers partaking in the lunch, 90% of the promotional spend would go unreported.
Nevertheless, there are general types of analytics that can provide objective data and help confirm and reveal certain industry themes and qualitative trends. These key types of published transparency data include:
- Manufacturer making the TOV
- Covered recipient accepting the TOV
- Spend type, i.e. a consulting fee, speaker fee, honoraria, food and beverage, development, promotional spend, investment and ownership
- Transaction amount and date
Additionally, applicable manufacturers must report:
- Types of payment: Manufacturers are required to categorize how the recipient received the payment (such as cash or cash equivalent, in-kind items or services, or stock, stock option(s), or any other ownership interest, dividend, profit, or other return on investment).
- Indirect payments – through a third party (such as a hospital, research organization, or travel agency on behalf on the manufacturer)
- Research payments – investigators on research supported by manufacturers
- Ownership interests – held by physicians and their immediate family members (outside of publicly traded securities)
Proper analysis of this data, which is made easy by readily accessible data technology, can provide industry insights for benchmarking and answer some important questions. For example:
- How much time and money is being spent to develop new products?
- How much money is being spent to promote certain products or product classes?
- What combination of promotional tactics are being used in conjunction with a single physician or physician type?
- Which market areas are seeing growth in promotional activity and what are the results of those activities?
To achieve the maximum benefit of published transparency data, it should be considered a single metric that can be valued in the context of other metrics to gain an even deeper insight. Recognizing, for example, the correlation between market-available claims data, readily accessible internal factory sales and product development data can reveal trends and insights about what is happening in particular markets and therapeutic areas.
Armed with this data, product manufacturers and promoters have another set of data points to validate and adjust three to five year forecasts on a regular basis and make proactive, strategic choices about where to invest time, money and effort. Whether a company wants to take on a role of the innovator, early adopter, or late adopter, published transparency data is an excellent resource for acquiring a comprehensive view and clear understanding of the market. This is especially true when the transparency data is used in conjunction with other data resources such as internal sales and properly aggregated adjudicated claims data. Companies that are not leveraging the visibility and intelligence contained within published transparency or value data are missing a powerful opportunity to make better strategic decisions and, predictably, place themselves at a decided disadvantage.
[1] Section 6002 of the Affordable Care Act requires the establishment of a transparency program, now known as “Open Payments.”
Contributed by: Darryl Williams, head of Global MDM and Platform Solutions, Health Care, LexisNexis® Risk Solutions. He has over twenty years of experience architecting, implementing, and managing integration, optimization, and strategy programs for initiatives in the life sciences and healthcare industries. Darryl focuses on applying Agile Data Management principles and enterprise information management capabilities to a diverse array of business solutions across healthcare verticals using rich toolsets available via HPCC, the LexisNexis Big Data platform for information management and solutions enablement.
Speak Your Mind