Specific Aim 1: Infrastructure. Leverage the knowledge gained from an existing distributed research network (DEcIDE DRN2) to design and implement an innovative, sustainable, distributed data network with enhanced capabilities (the SPAN network) to support comparative effectiveness research.

  • Develop system architecture to support a distributed research network (DRN) that is interoperable across a range of health-care systems.
  • Develop a research user interface that permits menu-driven querying, analysis of patient-level data, and real-time data extraction.
  • Pilot test and implement all of the above enhancements to expand and increase the scale of the network.

Specific Aim 2: Data Resources and Expansion. Expand the scale of the network and increase the generalizability of comparative effectiveness research (CER) study results by including: a) integrated healthcare delivery systems and b) community partners with differing delivery systems, data structures and patient populations.

  • Standardize the structure of sites’ data files while incorporating files for patient-reported outcomes.
  • Collaborate with 2 community health partners to develop data collection, extraction, and storage capabilities compatible with participating in SPAN cohort development and research queries.
  • Evaluate the usability of the network system across sites over time.
Specific Aim 3: Governance. Develop and implement a collaborative governance plan for SPAN that incorporates:

  • Oversight of electronic health data including data linkage, access, privacy, and confidentiality of patient information.
  • Oversight of operational, scientific, and technical concerns related to study design, implementation and analysis including addressing individual barriers that could impede collaboration.
  • Oversight and review of potential conflicts of interest for SPAN personnel.
  • Obtaining input and representation from patients, researchers, clinicians and other stakeholders regarding data collection, infrastructure, and CER activities.
Specific Aim 4: CER Cohorts. Build four pairs of population-based cohorts suitable for conducting CER that increase in complexity as the network develops, and ultimately incorporate clinical and patient-reported outcomes; illustrate the capacity for these cohorts to serve as a basis for CER.

  • Identify a cohort of children with attention deficit hyperactivity disorder (ADHD) who have received differing treatment strategies.
  • Within the ADHD cohort, develop an additional cohort of children with comorbidities such as oppositional defiant disorder, anxiety disorder, learning disabilities, and developmental disorders.
  • Use the ADHD cohort to 1) assess the positive predictive value of electronic ADHD diagnosis for identifying incident ADHD, b) assess incident medication treatment and  treatment patterns, c) describe proportion of children treated according to HEDIS definitions, and d) describe mental disorder comorbidity.
  • Develop a cohort of adults with obesity who have undergone weight loss surgery.
  • Use the obesity cohort to 1) describe cross site variation in bariatric surgery populations and care processes, 2) develop prognostic risk models to predict successful weight loss at 3- 5 years, 3) evaluate the effect of pre-operative depression on these models.
  • Demonstrate the capacity for CER for all cohorts by 1) assessing the variability in exposures and outcome variables, and 2) test comparative effectiveness hypotheses in the ADHD and obesity cohorts.