This application seeks to conduct a large, pragmatic clinical trial demonstration project within the NIH Health Care Systems (HCS) Research Collaboratory. The Dialysis Research Network, comprised of academic investigators and dialysis provider organizations, is proposing the """"""""Time to Reduce Mortality in End-Stage Renal Disease (TiME)"""""""" trial. The TiME trial is a large, cluster-randomized, pragmatic trial that will evaluate the effects on survival, hospitalizations, and health-related quality of life of a systemaic implementation of a hemodialysis session duration of at least four hours for individuals with irreversible kidney failure who are initiating treatment with maintenance hemodialysis. The trial will be conducted in approximately 320 dialysis facilities owned by the two largest dialysis provider organizations in the United States. The electronic data systems of the dialysis provider organizations will be used for identification of participating dialysis facilities, for collection f trial data and outcomes, and for transmission of data to the University of Pennsylvania Clinical Research Computing Unit which will serve as the data coordinating center for the trial. The project will be implemented in two phases: the UH2 planning phase and the UH3 implementation phase, each of which has specific milestones for progress and metrics for evaluating the innovative approaches used for the trial. The Dialysis Research Network application fulfills the objectives of the NIH HCS Research Collaboratory Pragmatic Clinical Trials Demonstration Projects program. The TiME trial is pragmatic: 1) it evaluates an intervention implemented in the usual care setting, 2) it utilizes data that are obtained for routie clinical care, 3) it has minimal restrictions on eligibility, and 4) it requires no specific expertse of practitioners. The outcomes are important both clinically and from the perspective of the patient. The trial will be conducted through a partnership between academic investigators and two health care provider organizations with different business models, cultures, and electronic data systems. Innovative approaches that are relevant and applicable across a broad range of health care systems and diseases will be used for highly centralized execution of the trial, and tools wil be developed and shared with the broader research community. Thus, in addition to efficiently testing a simple but potentially high-impact intervention for patients with kidney failure, the TiM trial demonstration project will generate important advances for conducting cost-effective, large-scale clinical trials that assess the effectiveness of interventions in """"""""real-world"""""""" settings.
The proposed pragmatic clinical trial will test a simple intervention to improve survival and quality of life for patients with kidney failure who require chronic treatment with dialysis. The trial will be conducted through a partnership between academic investigators and two large dialysis provider organizations. The pragmatic design of the trial, the utilization of multiple electronic health record systems for trial implementation, ad the partnership between academia and industry will establish a framework for conducting research within health care delivery systems that will be relevant and applicable to a broad range of diseases and research questions.
| Weinfurt, Kevin P; Hernandez, Adrian F; Coronado, Gloria D et al. (2017) Pragmatic clinical trials embedded in healthcare systems: generalizable lessons from the NIH Collaboratory. BMC Med Res Methodol 17:144 |
| Simon, Gregory E; Coronado, Gloria; DeBar, Lynn L et al. (2017) Data Sharing and Embedded Research. Ann Intern Med 167:668-670 |
| Dember, Laura M; Archdeacon, Patrick; Krishnan, Mahesh et al. (2016) Pragmatic Trials in Maintenance Dialysis: Perspectives from the Kidney Health Initiative. J Am Soc Nephrol 27:2955-2963 |
| Cook, Andrea J; Delong, Elizabeth; Murray, David M et al. (2016) Statistical lessons learned for designing cluster randomized pragmatic clinical trials from the NIH Health Care Systems Collaboratory Biostatistics and Design Core. Clin Trials 13:504-12 |
| Ellenberg, Susan S; Culbertson, Richard; Gillen, Daniel L et al. (2015) Data monitoring committees for pragmatic clinical trials. Clin Trials 12:530-6 |
| Berns, Jeffrey S; Dember, Laura M (2013) Can frequent hemodialysis be too frequent? J Am Soc Nephrol 24:334-6 |
| Richesson, Rachel L; Hammond, W Ed; Nahm, Meredith et al. (2013) Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory. J Am Med Inform Assoc 20:e226-31 |
