Expertise-based trials

Expertise-Based Randomized Controlled Trials (EBRCTs)

An expertise-based randomized controlled trial (EBRCT) is a trial design where participants are randomized to treatment groups based on the expertise of the clinician delivering the intervention. Unlike traditional RCTs—where the same clinicians may deliver multiple treatments—EBRCTs assign participants to clinicians who specialize in only one of the interventions. This approach is particularly useful in contexts where treatment outcomes are highly dependent on the provider’s skill, such as surgery, psychotherapy, or other hands-on procedures.

1. Justification for the Expertise-Based Design

The expertise-based design should be considered when a standard RCT would introduce bias due to variability in clinician skill. If the intervention requires specialized experience to be delivered effectively, using the same clinicians for both arms may lead to suboptimal treatment and performance bias. For example, in a trial comparing surgical and non-surgical treatments for back pain, outcomes may be more valid if surgeons and physiotherapists deliver their respective treatments.

2. Participant Randomization

Participants should be randomized to treatment groups before being assigned a clinician. This maintains the integrity of randomization and reduces selection bias. Once randomized, participants are referred to a provider who has expertise in the assigned intervention. For instance, a participant randomized to the surgical arm would then be referred to a qualified surgeon.

3. Clinician Selection and Training

Clinicians participating in an EBRCT must have demonstrated expertise in their respective treatment. Minimum qualifications—such as number of procedures performed or years of experience—should be specified. All clinicians should receive standardized training to ensure consistent application of treatment protocols and adherence to the study protocol.

4. Standardization of Interventions

Even though clinicians are experts, it is essential to standardize the interventions to minimize variability. Protocols should be detailed and supported with manuals, checklists, or structured guides. For example, psychotherapists might follow a predefined 12-session cognitive-behavioral therapy plan.

5. Blinding and Bias Reduction

Blinding participants in an expertise-based design is often not feasible, especially when different types of providers are involved. However, outcome assessors should be blinded whenever possible to reduce detection bias. Objective outcome measures and careful monitoring of performance can help mitigate performance bias.

6. Outcome Measures

Objective outcomes such as lab results or imaging studies should be prioritized, as they are less subject to bias. When subjective outcomes like pain or satisfaction are used, validated tools and blinded assessment methods should be employed.

7. Sample Size Calculation

Sample size estimates must account for variability between clinicians and possible clustering effects, especially if each clinician treats multiple participants. If feasible, randomization can be stratified by clinician or center. Intraclass correlation coefficients (ICC) should be used to adjust the sample size accordingly.

8. Feasibility and Recruitment

Successful implementation of an EBRCT depends on recruiting a sufficient number of qualified clinicians in each treatment arm. Additionally, participants should be informed that they will be treated by experts specific to the intervention they are randomized to.

9. Monitoring and Quality Assurance

Regular monitoring and quality assurance activities should be conducted to ensure that the interventions are delivered according to protocol. Process evaluations and audits—such as reviews of therapy sessions or surgical outcomes—can help assess fidelity.

10. Statistical Analysis

Data should be analyzed using an intention-to-treat (ITT) approach to preserve the benefits of randomization. Statistical models must account for potential clustering by clinician or site, often using mixed-effects models. Results should report both group-level effects and any variation between clinicians.

11. Ethical Considerations

Participants must be clearly informed about the expertise-based design, including the fact that they will receive treatment from a specialist in their assigned intervention. Both treatment options must reflect current standard practices to ensure ethical soundness.

12. Interpretation and Reporting

When reporting results, researchers should follow CONSORT guidelines and clearly explain the expertise-based design in both methods and discussion sections. They should also reflect on how clinician expertise may have influenced the results and discuss the relevance of findings for real-world practice.

Example reporting:

Participants were randomized to receive treatment from experienced surgeons (n=100) or physiotherapists (n=100). Objective recovery outcomes were assessed at 6 and 12 months.

Advantages

• Minimizes performance bias by ensuring that only experienced clinicians deliver the intervention.
• More accurately reflects real-world clinical settings.
• Enhances the quality and consistency of treatment delivery within each arm.

Challenges

• Requires access to a sufficient number of expert clinicians.
• Participant blinding may not be feasible.
• Residual variability in clinician performance may still influence outcomes, even among experts.

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Bibliography

1. Cook JA, Ramsay CR, Fayers P. Statistical evaluation of learning curve effects in surgical trials. Clinical Trials. 2004;1(5):421–427.
2. Biau DJ, Porcher R, Trinquart L. Meta-analyses incorporating randomized trials and observational studies on the same topic: a review of methods and examples. Journal of Clinical Epidemiology. 2008;61(1):3–10.
3. Beard DJ, Campbell MK, Blazeby JM, et al. Considerations and methods for expertise-based randomised controlled trials in surgery. Trials. 2009;10:5.
4. Cook JA. The challenges faced in the design, conduct and analysis of surgical randomised controlled trials. Trials. 2009;10:9.
5. McLeod RS, Wright JG, Solomon MJ, et al. Randomized controlled trials in surgery: issues and problems. Surgery. 2005;137(2):140–146.

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Adapted for educational use. Please cite relevant trial methodology sources when using this material in research or teaching.