Translating clinical informatics interventions into routine clinical care: how can the RE-AIM framework help?
OBJECTIVE
Clinical informatics intervention research suffers from a lack of attention to external validity in study design, implementation, evaluation, and reporting. This hampers the ability of others to assess the fit of a clinical informatics intervention with demonstrated efficacy in one setting for implementation in their setting. The objective of this model formulation paper is to demonstrate the applicability of the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework with proposed extensions to clinical informatics intervention research and describe the framework's role in facilitating the translation of evidence into practice and generation of evidence from practice. Both aspects are essential to reap the clinical and public health benefits of clinical informatics research.


METHODS
We expanded RE-AIM through the addition of assessment questions relevant to clinical informatics intervention research including those related to predisposing, enabling, and reinforcing factors and validated it with two case studies.


RESULTS
The first case study supported the applicability of RE-AIM to inform real world implementation of a clinical informatics intervention with demonstrated efficacy in randomized controlled trials (RCTs)--the Choice (Creating better Health Outcomes by Improving Communication about Patients' Experiences) intervention. The second, an RCT of a personal digital assistant-based decision support system for guideline-based care, illustrated how RE-AIM can be used to inform the design of an efficacy RCT that captures essential contextual details typically lacking in RCT design and reporting.


CONCLUSIONS
The case studies validate, through example, the applicability of RE-AIM to inform the design, implementation, evaluation, and reporting of clinical informatics intervention studies.
Bakken
Suzanne
S
School of Nursing, Department of Biomedical Informatics, Columbia University, 630 W. 168 Street, Mail Box 6, New York, NY 10032, USA. suzanne.bakken@dbmi.columbia.edu
Ruland
Cornelia M
CM
D034201:Computers, Handheld; D020000:Decision Support Systems, Clinical; D006284:Health Plan Implementation; D006801:Humans; D008490:Medical Informatics; D008962:Models, Theoretical; D019982:Organizational Case Studies; D016032:Randomized Controlled Trials as Topic / Q000379:methods; D015203:Reproducibility of Results; D012107:Research Design; D057170:Translational Research, Biomedical / Q000379:methods* / Q000458:organization & administration; D014481:United States