- Batorsky, Anna;
- Bowden, Anton E;
- Darwin, Jessa;
- Fields, Aaron J;
- Greco, Carol M;
- Harris, Richard E;
- Hue, Trisha F;
- Kakyomya, Joseph;
- Mehling, Wolf;
- O'Neill, Conor;
- Patterson, Charity G;
- Piva, Sara R;
- Sollmann, Nico;
- Toups, Vincent;
- Wasan, Ajay D;
- Wasserman, Ronald;
- Williams, David A;
- Vo, Nam V;
- Psioda, Matthew A;
- McCumber, Micah
Objective
One aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses.Methods
Consortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and nontabular data (eg, imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium.Results
Clinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected by use of questionnaires across projects. Other nonrequired domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed on the basis of the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging, and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC.Conclusions
BACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs.