Avoiding the Pitfalls of Normative Databases in Healthcare Research

A long-standing debate on the utility of normative databases exists in the market research industry—how helpful are they really? In the dynamic field of market research, the use of normative databases has become increasingly prevalent, and for a few of our clients, an imperative when it comes to certain types of studies. Normative databases serve as benchmarks, providing researchers with reference points that enable them to interpret their findings within the context of broader market trends. In theory, they are a powerful tool offering comparative context and trending, enhanced validity and reliability, time and cost efficiencies, and improved targeting and personalization. However, like any tool, normative databases come with their own set of limitations that are not often fully acknowledged or recognized.

At Escalent, we’ve helped clients avoid a false sense of confidence gained by normative databases, especially with our Life Sciences clients. Here’s what everyone should keep in mind:

Normative Databases and the Potential for Misinterpretation

One of the major drawbacks of normative databases is the potential for misinterpretation. Norms are averages and may not accurately represent all segments of the market, which becomes very important when we are getting specific about our patient and physician audiences. Over-reliance on these averages can lead to incorrect conclusions and strategies that do not cater to our very specific patients or diverse physician specialists that our clients work to serve.

Example: A normative database that shows an average satisfaction score for a new diabetes treatment will mask significant differences in satisfaction between younger patients and older patients. This will lead to a strategy that fails to address the distinct needs of these different age groups.

The Effect of Outdated Normative Databases on Trends

The relevance of normative data depends on how frequently it is updated. Market dynamics can change rapidly, and outdated norms won’t reflect current trends. Relying on stale data can result in strategies that are out of sync with the current market reality, and we know how rapidly things can change as new therapies come to market. Normative database providers will argue that their databases include recent data and so serve as moving averages. However, in a fast-moving market, these moving averages are significantly different from the current situation.

Example: Normative databases did not immediately capture the surge in telemedicine usage that occurred during the COVID-19 pandemic, leading to strategies that overlooked this significant shift in how healthcare services are delivered.

Lack of Specificity with Normative Databases

Normative databases provide a general overview but often lack specificity. They may not capture the nuances of particular markets, regions, or demographic groups in healthcare. This can limit the applicability of the data for highly targeted or specialized research, which makes up most of the work we do with our life sciences clients.

Example: Normative databases with average data for cancer treatments across the country will not reflect the unique needs and behaviors of patients in rural areas versus urban areas, leading to healthcare strategies that are not tailored to these specific populations.

Bias and Homogeneity in Normative Databases Can Be a Barrier to Inclusive Insights

Normative data can introduce bias, especially if the database predominantly represents certain populations or regions. This homogeneity can skew the norms, leading to biased benchmarks that do not accurately reflect diverse markets and targets. This is a big problem as the industry works harder than ever to reduce bias and improve inclusivity in the way manufacturers care for, communicate, and more relevantly connect with all their customers.

Example: Normative databases that are heavily weighted towards data from Western countries will not accurately reflect the healthcare needs and preferences of patients in Asian or African countries, leading to strategies that are not inclusive or effective globally.

Historic Normative Data Does Not Always Translate to the Future

While historical data is valuable, over-reliance on it can be problematic. The past is not always a perfect predictor of the future, especially in fast-evolving industries like life sciences. Researchers need to balance normative data with forward-looking insights in healthcare to avoid being blindsided by new innovations that can change beliefs and behaviors of patients and physicians quickly.

Example: The introduction of a groundbreaking gene therapy could drastically change treatment paradigms and patient expectations, making historical normative data on traditional therapies less relevant or even obsolete.

Normative databases can be very useful for market research, but there are inherent dangers to look out for when it comes to potential for misinterpretation, outdated data, lack of specificity, bias and homogeneity, and over-reliance on historical data.

Healthcare experts at Escalent are available to discuss the utility of normative databases for your organization. We have deep experience in benchmarking and strategies to help assess how you stack up against the competition both now and in the future. Contact us.

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