How:

Since project goals and stakeholders are intertwined, you need to identify stakeholders carefully to limit bias. The ideal is to bring people with different perspectives, training and experience to the table.

The range of stakeholders is likely to be wide for a decision support innovation which impacts both on frontline practice and on service models. Examples include:

• Front line professionals who are representative of those who will be using the decision support tools and new content to be developed.
• Guideline authors.
• Knowledge managers and associated roles – e.g., data and information managers, researchers who will often build, structure and populate decision support tools using the knowledge translation toolset offered by the Right Decision Service. Knowledge managers can also play a key role in sourcing the evidence from the literature and experience which underpin decision support tools.
• Clinicians and social care practitioners responsible for safety, quality, service improvement and audit.
• Patients and service users, especially those with experience of the problem that is being addressed.
• Data analysts responsible for identifying trends in practice, emerging challenges and new knowledge arising from a learning health system.
• Managers of services, as the volume and type of demand for their services may be changed as a result of decisions supported by new RDS material.

Team process is important. When meeting with stakeholders, spend some time getting agreement on the team process. Encourage team members to be open to the ideas of others. The team and its leadership should agree on this early and enforce it. Being open to different ideas encourages members to share unique information and perspectives so that all diverse, and conflicting, information is presented before a decision has been made. [Soll, et al. 2015].

Why:

Successful development and implementation of any innovation depends on engaging the right people and keeping them engaged throughout the development and implementation process.

It is also important to avoid a team that lives in an “echo chamber”, when the team reflects on a closed set of views which then get reinforced through repetition. Unfortunately, teams can often composed in ways that accentuate bias, because they often consist of members who think alike. [Kahneman, 2011]. We can overcome biasing tendencies by recruiting a project group with diverse independent perspectives. This includes, for example, people who have access to different information and data, different experiences, different training, and different models of interpreting data and evidence. Diverse teams tend to focus on facts, process those facts carefully, tend to be more innovative, and work faster. [Rock & Grant, 2016; Reynolds & Lewis, 2017].