DCS together with the University of Pittsburgh and UPMC (Pitt), Penn State College of Medicine and Hershey Medical Center, and Johns Hopkins University School of Medicine, University of Utah Health Care have formed a PCORnet Clinical Data Research Network (CDRN) called PaTH. Our network structure accommodates the concerns, cultural norms, and skills of the participating health care systems, research teams, and patient populations. Our Steering Committee defines network policies, which are locally implemented consistent with the culture and workflow norms of each site. Pitt serves as the PaTH coordinating center, lead contracting site, lead statistical analysis group, and lead informatics group and convenes the weight cohort; Penn State convenes the rare disease cohort, idiopathic pulmonary fibrosis (IPF); DCS convenes the PCORnet Common Data Model (CDM) work group; Johns Hopkins serves as the PaTH central institutional review board (IRB) and convenes the common disease cohort, atrial fibrillation (AF).
PaTH has developed and implemented governance policies to facilitate our participation in CDRN-specific and PCORnetwide activities, including: standardization of data; data sharing within the CDRN, with PCORnet, and with external researchers; streamlining of IRB oversight, including executed reliance agreements and data use agreements (DUAs); and securely de-identifying and re-identifying data. The PaTH Network Protocol Review Committee (PNPRC) engages IRB professionals and community representatives from each PaTH site to ensure that our ethics reviews emphasize patient perspectives and foster innovation to support patient-centered pragmatic clinical trials (PCTs).
PaTH maintains analysis-ready, quality-checked, and regularly refreshed data sets that meet relevant regulatory and legal requirements. We are developing and implementing procedures for ensuring network data quality and disseminating our experience to promote PCORnet-wide data quality standards. Concurrently, we are pursuing strategies to link with external sources to enhance data completeness.