Delphi, non-RAND modified Delphi, RAND/UCLA appropriateness method and a novel group awareness and consensus methodology for consensus measurement: A systematic literature review

Evidence provided by randomised controlled trials (RCTs) is considered the “gold standard” for regulators at the approval level for new therapeutic strategies, biologics, and drugs [1]. However, existing evidence suggests that there is a potential to neglect the perspectives of several stakeholders (such as medical affairs personnel and patients), in the design and conduct of RCTs. Using real-world evidence (RWE), Medialis is bridging the gap between these stakeholders and creating a holistic approach to generating evidence to inform effective patient care.
Importantly, there is an increased recognition among different stakeholders regarding the need for evidence on the history of a particular disease, its treatment results in clinical practice, and the resources associated to it in the real-world setting [2]. In other words, RWD and RWE are crucial components towards understanding the outcomes of an intervention in the real-world setting.
Medialis obtains RWE using methodologies focusing on: (1) The medical product lifecycle following marketing approval; (2) Data collection, such as patient registries [3] and (3) expert consensus and opinion [4]. Utilising the third option, Medialis compared three widely used protocols for the generation of expert consensus (Delphi, non-RAND modified Delphi, RAND/UCLA appropriateness method) with our novel group awareness and consensus methodology known as the Jandhyala Method.
We demonstrated that the Jandhyala Method improves on previous consensus generating methods, by preventing attrition or forced consensus amongst experts and producing outcomes faster and more efficiently. This has been fully shown in our comparison review, published in Current Medical Research and Opinion.
By applying this novel methodology, we are able to engage with multiple stakeholders and generate the RWE that suits their needs best. We have already successfully used this innovative approach to create the XLH (rare disease) patient registry [3], and produce expert consensus opinion on the likely impact of candidate influenza virus and egg-based manufacture on vaccine effectiveness [5].

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References
1. the-use-of-real-world-evidence-in-the-european-context.pdf. Accessed August 25, 2020. https://www.lse.ac.uk/business-and-consultancy/consulting/assets/documents/the-use-of-real-world-evidence-in-the-european-context.pdf
2. Makady A, de Boer A, Hillege H, Klungel O, Goettsch W. What Is Real-World Data? A Review of Definitions Based on Literature and Stakeholder Interviews. Value Health. 2017;20(7):858-865. doi:10.1016/j.jval.2017.03.008
3. Padidela R, Nilsson O, Makitie O, et al. The international X-linked hypophosphataemia (XLH) registry (NCT03193476): rationale for and description of an international, observational study. Orphanet J Rare Dis. 2020;15(1):172. doi:10.1186/s13023-020-01434-4
4. The Multiple Stakeholder Approach to Real-world Evidence Generation: the Results of the Jandhyala Method in Observing Expert Consensus on Quality Indicators of Rare Disease Patient Registries (RDRs) by Stakeholder Group. Published online August 6, 2020. doi:10.21203/rs.3.rs-53391/v1
5. Rajaram S, Wojcik R, Moore C, et al. The impact of candidate influenza virus and egg-based manufacture on vaccine effectiveness: Literature review and expert consensus. Vaccine. 2020;38(38):6047-6056. doi:10.1016/j.vaccine.2020.06.021

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