KOL (關鍵意見領袖) 的報酬:2016年
Global Key Opinion Leader Compensation 2016
|出版商||Cutting Edge Information||商品編碼||356825|
|出版日期||內容資訊||英文 75 Pages
|KOL (關鍵意見領袖) 的報酬:2016年 Global Key Opinion Leader Compensation 2016|
|出版日期: 2016年04月25日||內容資訊: 英文 75 Pages||
本報告提供KOL (關鍵意見領袖) 的報酬相關調查，主要的治療領域、每個地區的報酬比率。
The spotlight on the life sciences industry's monetary relationships with physicians continues to shine in the United States, Europe and the rest of the world and is growing ever brighter. In this new transparency environment norm, manufacturers must aggressively track changes in fair market value (FMV) compensation rates. While it's true that rates for some therapeutic area/country combinations remain relatively stable over time, others (such as neurology in the US) can change significantly year over year. Companies that fail to keep abreast of current FMV rates risk falling out of compliance with regulations or losing competitive advantage in thought leader recruitment.
This report will explore the most far-reaching year-over-year trends and highlight specific compensation rates in major therapeutic areas and regions. In the process, CEI will introduce its patent-pending methodology for analyzing and tracking FMV rates that is superior to the salary/economic indicator-based methodologies prevalent in other approaches. Finally, the report explores how companies manage their key opinion leader engagement activities and how thought leaders are being segmented across the life sciences industry.
For the research shown in this report, Cutting Edge Information surveyed life sciences industry leaders worldwide. We collected data from internal FMV stakeholders in compliance, medical affairs, commercial and operations functions, among others.
As seen in Figure E.1, 43% of those surveyed are from companies within PharmExec's Top 50 companies, with annual revenues over $2.1 billion. Small life science companies are also well represented in the data (55% of those surveyed). Besides company size, the research covers a wide geographic scope (Figure E.2). While 48% of survey respondents are based in the US, 26% operate in Europe, and 9% operate in the Asia-Pacific region.
Figure E.1: Company Type Cross-Section of 2016 FMV Survey Participants
Figure E.2: Regional Cross- Section of 2016 FMV Survey ParticipantLocation
While the breakdown of participants on a regional basis shows CEI's penetration worldwide, the regional breakdown at the data point level proves the global scope of our research. Of the 27,000 FMV rates collected, 84% of the data relate to countries outside of the United States, as shown in Figure E.3. Even more, 32% of our database covers emerging markets. No other data source can claim as vast a worldwide scope.
Figure E.3: Regional Cross- Section of 2016 FMV Survey Data
The CEI methodology - which is discussed in full detail in Chapter 1 - involves a carefully developed three-step data analytic process encompassing regression, outlier compression and balancing sample data with regression results through Bayes Theorem. The general idea is that FMV rates exist as a fabric. In other words, rates around the world, across different tiers and therapeutic areas, are interconnected; CEI's process looks for the patterns prevalent in the fabric to build accurate, defensible FMV rate profiles.
Analyzing the CEI methodology shows that its core regression has a predictive power of 47%, a truly impressive R-squared for any real-world data problem. Much of this stems from the size of our survey database, which we believe to be the largest of its kind in the life sciences industry. Finally, there is industry acceptance of the approach; in fact, 8 of the Top 10 pharma companies utilize our rates in their thought leader interactions.
The general framework of CEI's methodology appears in research spanning dozens of industries. One easily digestible example can be found in real estate appraisals. When a home buyer looks to purchase their dream house, an appraiser must determine its fair market value by looking at comparables, homes with similar characteristics - square footage, number of bedrooms and bathrooms, age, and school quality, for example. Most of the comparables will not match the target home's characteristic profile. So appraisers apply a regression-based process that identifies which of the characteristics truly influence a house's value and by how much. With that knowledge, the appraiser can determine the target house's fair market value.
In the case of physician compensation, the dimensions (groups of factors) of greatest importance are:
A simple regression would stop here, but CEI takes this process a step further by assessing how the dimensions interact in pairs to answer, for example, if there any unique differences in tier differentials by specialty. For instance, a cardiologist in the US is paid more than one would expect if only the US location and the cardiology specialty were considered. It is the process of finding these interactions that makes the CEI regression-based approach so effective and accurate. And that is only step one of the full methodology. (Chapter 1 explores the full methodology in detail.)
Cutting Edge Information analysts synthesized the following three key observations from this study's findings. These observations are designed to provide a snapshot of the most important takeaways from this report:
As previously discussed, the CEI methodology has a calculated predictive power of 47%. In comparison, a regression that only accounts for GDP and salary has a predictive power of just 11% - less than one quarter of the predictive power of the CEI methodology. But how does that factor into FMV rate determination?
Figure E.4 shows the difference between rates from the CEI methodology and rates that are generated via a simple regression that relies solely on physician salary and economic indicators such as a country's per capita GDP. In the US, comparing the two approaches results in a difference in compensation of $83 for adult cardiology and $102 for pediatric cardiology per hour - a greater than 20% difference for both therapeutic areas. Similar differences appear in specialist rates across the board.
A salary-driven methodology seriously undercuts the value of US physicians. Companies using this model would face push-back from physicians who will choose to work with other companies offering more reasonable rates. Rates in other countries, such as Brazil, face the opposite problem. The GDP + Salary model highly overvalues every specialty, opening companies to significant scrutiny by regulators and the public.
The results are clear: a GDP + Salary model will not accurately forecast the FMV payment landscape. Pharmaceutical and device companies cannot afford the compliance penalties or the competitive disadvantages that stem from utilizing such FMV rate determination methodologies.
Figure E.4: Hourly Compensation Rates for Tier 2 KOLs in the US: Comparing Simple Regression and CEI Methodology
As shown in Figure E.5, in 2016 the average pharmaceutical company signed contracts with Exceptional-level thought leaders 28.8% of the time, an increase of 2.1 percentage points from 2015. This highest tier of KOL is typically reserved for specialists with memberships in elite-level medical societies and extensive experience in conducting global-scale clinical trials.
Meanwhile, usage of Tier 3 thought leaders - those with local-level influence - declined year over year from 17.2% in 2015 to 15% in 2016.
CEI's research shows that Tier 3 thought leader usage is higher among large companies (those with over $2 billion in annual revenues) than small companies, which tend to engage more with Exceptional-level healthcare providers. In addition, US-based groups are driving the upward trend of upper-tier thought leader utilization; a full 70% of FMV contracts among surveyed companies in the US are with either Exceptional or Tier 1 thought leaders.
It is somewhat hard to pinpoint the cause in this upward shift. One possible explanation is that companies look to maximize program effectiveness. In many cases, maximizing effectiveness means recruiting a more influential KOL to lead the company's efforts. While this strategy seems solid, companies should beware losing sight of the benefits of working with local-level physicians who often have a clearer grasp of the patient perspective.
Another possible explanation is that this trend reflects some companies' attempts to circumvent internal guidelines for tier compensation limits. Artificial inflations in tier definitions could allow less qualified physicians to ascend to desired higher compensation levels without any defensible backing. Compliance teams should keep a close eye on KOL tier advancements within their company's thought leader programs as potential risk signs.
Figure E.5: Thought Leader Tier Utilization, All Companies: 2015 to 2016
The five major markets in Europe - Germany, the United Kingdom, France, Italy and Spain - have traditionally trended as a unit within the life sciences industry. Weakening economies during the economic collapse, however, created a wall between the strong economies in Germany, the United Kingdom and France and struggling Italy and Spain. But the economic upswing repaired the relationship, and the growth within the industry appeared to be shared by all - that is, until 2016.
As shown in Figure E.6, nearly every major therapeutic area saw significant drops in FMV rates for German physicians across the tiers. But the Big 5 region shows modest increases in FMV rates (see Figure E.7). For this to be true, the decreasing German rates have been countered by strong rate jumps within the other four countries. It is highly unusual to see such massive swings in rates within developed markets. However, they can occur, and companies operating in the Big 5 markets should prioritize rate reviews to reflect these changes.
E.6: 2015 to 2016 Changes in Pharmaceutical FMV Rates for Specialists in Germany, by Therapeutic Area: All Tiers
E.7: 2015 to 2016 Changes in Pharmaceutical FMV Rates for Specialists in the EU Big 5,* by Therapeutic Area: All Tiers