Does the 10,000-Hours Rule Apply to Clinical Trials?

Author: Nicole Latimer, Medrio CEO

When I read Malcolm Gladwell’s Outliers in 2009, I first learned that to perform at the highest levels, you need to devote ten years or 10,000 hours to practice. Since then, the concept has been embraced[1] (just ask any parent of an athlete on a youth travel team), refined[2] (we meant 10,000 hours of practice with a gifted instructor), and debunked[3] (10,000 hours was the average; you really have to look at the range).

Regardless of where you stand on the 10,000 hours, there is no question that performance excellence stems from experience. There is also no question that performance excellence is valued. We search for performance excellence and are willing to pay more to receive it.

The latest research from Industry Standard Research (ISR) shows that the clinical trials industry is no different. In both its phase I and phase II/III contract research organization (CRO) benchmarking reports, ISR reports that sponsors evaluate and choose CROs based on operational (or performance) excellence and its close corollary, expectations for data quality.[4] When engaging CROs, sponsors expect high-quality data from clinical trials that are delivered with reliability and efficacy.

But how do you define clinical trial expertise and how can you identify providers who are experts? In this article, we will look at the signs of clinical trial expertise and explain why those elements are critical to clinical trial success.

The Customization Expectation

Delivering increasingly high quality with predictable speed, in almost every other industry, is tackled with strict application of W. Edwards Deming’s total quality management practices and continuous improvement cycles. The conundrum for clinical trials is that the product, the study data, and the process, as well as how the study is conducted, differ not only from study to study but also from phase to phase. Protocol amendments and other mid-study changes are frequent, averaging from 1.7 modifications in phase I studies to 3.0 modifications in phase III studies.[5]

To address the uniqueness of each study as well as the likely complexity of changes being introduced during the study, the clinical trials industry has always embraced customization. Bespoke databases, data management plans, and training are all routine elements of clinical trials to ensure accurate data. This customization, however, also increases the cost and time required for each study.

With double-digit inflation and shrinking access to capital, the industry is starting to question whether there are more efficient ways to provide high-quality data apart from the total customization typically used in each study. At Medrio, we looked at some of our most successful customers and discovered an abundant use of EDC templates driving study efficiencies.

Efficiency Through Templates

The concept of using templates for electronic data capture (EDC) databases within clinical trials may seem antithetical. Each EDC, after all, is built to match the unique data needs of a specific study protocol. In practice, however, Medrio’s CRO and Sponsor customers recognize that a significant number of identical patient data fields are required in nearly every study. Instead of rebuilding electronic case report forms (eCRFs) from scratch for every new study, these customers create libraries of eCRF and study templates that are used repeatedly.

To examine the impact of using eCRF and study templates, Medrio examined the data from more than 2,800 studies, spanning pharmaceutical, biotech, medical device, and diagnostics. The studies examined were completed across the last five years by more than 150 CROs or sponsors. Studies using EDC templates were defined as those studies that requested a complete copy of a previous study when initiating an EDC build.

Anticipating efficiencies across the study process, we examined build times, the total number of queries, and close times. We defined those parameters as follows:

  • Build times: the period between the date the EDC build was initiated and the date of the First-Patient-In (FPI) data was entered.
  • Total number of queries: all queries initiated throughout the course of the study.
  • Close times: the period from the date of the last data entry in the study to the study completion date.

Reduced Study Build Times

Overall, 48 percent of the more than 2,800 studies used a template study to initiate their EDC build. On average, using a study template shortened the build time by 17 percent, which translated into reducing the build time by 10 days. All phases across drug and medical device and technology (MedTech) studies benefited from using study templates when building studies. The study phases that realized the greatest efficiencies from using study templates included phase I and phase II for drug studies and pilot and pivotal phases for MedTech studies.

One of the most straightforward uses of a template is when an EDC database from an earlier phase is copied as the basis for the next phase’s EDC. Medrio’s CRO and sponsor customers leveraged earlier phases’ EDCs and realized build efficiencies. Phase II studies, with the ability to use the EDC from phase I as a template, reduced study build times, on average, by 32 percent. Similarly, pivotal MedTech studies, using their pilot studies as templates, reduced EDC build times by 38 percent.

Our data, however, also showed efficiencies for initial phases when CROs and sponsors did not have the ability to copy EDCs from earlier phases but still introduced a template for electronic data capture. Phase I studies reduced study build times by 63 percent and pivotal MedTech studies reduced study build times by 27 percent, on average, when using an EDC template. Although the number of Phase I or pilot studies that an organization conducted was positively correlated with reduced study build times, volume alone did not drive efficient initial phase builds using templates. Sponsors and CROs that only copied one study to facilitate a phase I or pilot study also realized shorter build times.

While not as significant as those realized by earlier stage studies, build efficiencies were also experienced in phase III and IV drug studies as well as in post-marketing MedTech studies when study templates were used. Within drug studies, phase III and phase IV studies realized 7 percent and 5 percent decreases in build times, respectively. Even post-marketing MedTech studies saw a benefit; those that used a template saw a 1 percent decrease in build times.

Reduced Number of Queries

Build times were not the only efficiency realized through the use of study templates. Across the more than 2,800 studies, those that used study templates, on average, opened 26 percent fewer queries than the studies built from scratch.

The phases that showed the steepest declines in the number of queries were phase IV for drug studies and pivotal for MedTech studies. These phases realized a greater than 50% decrease in queries when they used study templates.

Overall, in nearly all phases of studies, whether pharmaceutical, biotech, medical device or diagnostics studies, the use of templates demonstrated fewer queries when compared to studies that did not use templates. Only pilot MedTech studies saw an increase in queries (of 4 percent) when using study templates.

The table below shows the query reduction by phase when using study templates.

Study PhasePercent Reduction in Queries when Using Study Templates
Pharmaceutical/Biotech Studies 
Phase I39%
Phase II29%
Phase III24%
Phase IV63%
Medical Device/Diagnostics Studies 

The reduction in queries seen in templated studies underscores the importance of the EDC database build. To capture high-quality data, EDC builders incorporate logic, such as edit checks and form rules, that trigger queries when entered data fall outside anticipated ranges. Underusing logic may result in unexplained variances in certain variables and difficulty drawing conclusions from the study data. Overusing logic may result in an excessive number of queries that slow the progress of the study as each query is investigated.

The correlation between the frequency of study template use with a reduction in queries suggests that some CROs and sponsors have found the Goldilocks application of logic in their eCRFs. Likely through re-use and continuous improvement, CROs and sponsors that use study templates frequently better understand certain data parameters and have fine-tuned their logic to minimize unnecessary queries.

Another hypothesis related to query reduction from the use of study templates considers site familiarity with the eCRFs. To the extent that CROs and sponsors are not only using study templates but also deploying those templated EDCs to the same sites, investigators and other clinicians learn to collect similar data in a consistent manner. Sites, seeing the same eCRFs in multiple studies, may become more comfortable with the data variables required as well as the entry of those data. The consistency of data capture, in turn, may increase accuracy and decrease the number of queries.

Reduced Study Close-Out Times

For many studies, the least predictable period of time is from the date of the final data entry to study completion, which is also referred to as study close-out. How quickly a study can be closed is dependent on the accuracy of the data captured. Higher-quality data generates fewer queries and requires less data cleansing, which shortens the close-out period. Data that results in a large number of queries may require significant data cleansing, delaying the ability to close out the study. Given the reduction in queries seen from the use of study templates, it is not surprising to see that study close-out times across some phases were also reduced when templates were used.

The phases that realized shorter close-out times when using study templates were phase III and phase IV drug studies as well as post-marketing MedTech studies. Phase IV studies saw the greatest difference in close-out times, showing a 93 percent reduction when using study templates. Phase III drug studies and post-marketing MedTech studies experienced more modest improvements, reducing the close-out time by 11 percent and 10 percent, respectively, when templates were used.

The reduction in close-out times in late-phase studies may stem from how study templates facilitate the use of additional templates. Studies that have similar structures, such as multiple post-marketing studies measuring the real-world efficacy of a device, may leverage existing study processes and existing SAS programs to evaluate study results. Since the data captured through study templates is delivered in a common format, these study processes and SAS programs can be used as is or with minor modifications rather than building processes and programs from scratch.

The 10,000-hour Takeaway

To achieve clinical trial success in today’s environment, sponsors and CROs should both seek trusted partners who are true experts in quality data capture and management. This expertise and guidance is especially critical when facing tight timelines, navigating geographic barriers, or anticipating mid-study changes that require additional flexibility. 

For sponsors that have in-house clinical data management departments, they will want to evaluate clinical trial technology, especially EDC, from the perspective of their product and program portfolio. If a sponsor plans to run multiple studies in the same therapeutic area or engage the same sites, selecting an EDC that facilitates building a library of templates will provide efficiencies across the entire portfolio. The EDC should allow copying not only of individual eCRFs but also of entire studies to realize the greatest benefits of applying study templates.

Sponsors that use CROs often perceive that clinical trial technology selection, including EDC, is the realm of the CRO. Most CROs, however, declare themselves as technology agnostic and often expect the sponsor to mandate the technologies to be used. This is the opportunity for the sponsor to suggest to the CRO an EDC that permits intuitive template building and copying. In addition, sponsors, if intending to work with a CRO from phase to phase or across a broad portfolio of studies, should ensure that the CRO embraces the concept of study templates, builds them, and uses them to maximize efficiencies.

Request a demo today to see for yourself what makes Medrio’s EDC different. Our platform is flexible, easy-to-use, and integrated – and our teams have far more than 10,000 hours of practice with electronic data capture.

Experience what it means to work with an EDC expert. Experience Medrio.


[1] Ericsson, K.A., Prietula, M.J. & Cokely, E.T. (2007). The Making of an Expert. Harvard Business Review (July-August 2007). Retrieved 7 Nov 2022.

[2] Young, J. R. (2020, May 5). Researcher Behind ‘10,000-Hour Rule’ Says Good Teaching Matters, Not Just Practice. EdSurge. Retrieved 7 Nov 2022.

[3] Manfred, T. (2013, Aug 12). Author Of A New Book About Genetics Destroys Malcolm Gladwell’s ‘10,000-Hour Rule’. Business Insider. Retrieved 7 Nov 2022.

[4] Industry Standard Research, 2022

[5] Tufts CSDD 2020

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