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Common Data Models

References:

  1. FDA. Framework for FDA RWE program. Available at: https://www.fda.gov/downloads/ScienceResearch/SpecialTopics/RealWorldEvidence/UCM627769.pdf.
  2. Eworuke, E., Welch, E. C., Tobenkin, A. & Maro, J. C. Use of FDA’s Sentinel System to Quantify Seizure Risk Immediately Following New Ranolazine Exposure. Drug Saf. (2019). doi:10.1007/s40264-019-00798-2
  3. Li, J. et al. Association of Risk for Venous Thromboembolism With Use of Low-Dose Extended- and Continuous-Cycle Combined Oral Contraceptives: A Safety Study Using the Sentinel Distributed Database. JAMA Intern. Med. 178, 1482–1488 (2018).
  4. Maro, J. C. et al. SAT0140 Risk of venous thromboembolism in rheumatoid arthritis patients treated with biologic and non-biologic dmards. Ann. Rheum. Dis. 77, 932–932 (2018).
  5. Sobel, R. E. et al. Do FDA label changes work? Assessment of the 2010 class label change for proton pump inhibitors using the Sentinel System’s analytic tools. Pharmacoepidemiol. Drug Saf. 27, 332–339 (2018).
  6. Cocoros, N. M. et al. FDA-Catalyst—Using FDA’s Sentinel Initiative for large-scale pragmatic randomized trials: Approach and lessons learned during the planning phase of the first trial. Clin. Trials 16, 90–97 (2019).
  7. Schuemie, M. J., Ryan, P. B., Hripcsak, G., Madigan, D. & Suchard, M. A. Improving reproducibility by using high-throughput observational studies with empirical calibration. Philos. Transact. A Math. Phys. Eng. Sci. 376, (2018).
  8. Schuemie, M. J., Hripcsak, G., Ryan, P. B., Madigan, D. & Suchard, M. A. Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data. Proc. Natl. Acad. Sci. U. S. A. 115, 2571–2577 (2018).
  9. Reps, J. M., Schuemie, M. J., Suchard, M. A., Ryan, P. B. & Rijnbeek, P. R. Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J. Am. Med. Inform. Assoc. JAMIA 25, 969–975 (2018).
  10. Clinicaltrials.gov study: Diuretic Comparison Project (DCP). Available at: https://clinicaltrials.gov/ct2/show/NCT02185417.
  11. Califf, R. M. The Patient-Centered Outcomes Research Network: a national infrastructure for comparative effectiveness research. N. C. Med. J. 75, 204–210 (2014).
  12. Collins, F. S., Hudson, K. L., Briggs, J. P. & Lauer, M. S. PCORnet: turning a dream into reality. J. Am. Med. Inform. Assoc. JAMIA 21, 576–577 (2014).
  13. Fleurence, R. L. et al. Launching PCORnet, a national patient-centered clinical research network. J. Am. Med. Inform. Assoc. JAMIA 21, 578–582 (2014).
  14. Kaushal, R. et al. Changing the research landscape: the New York City Clinical Data Research Network. J. Am. Med. Inform. Assoc. JAMIA 21, 587–590 (2014).
  15. Ohno-Machado, L. et al. pSCANNER: patient-centered Scalable National Network for Effectiveness Research. J. Am. Med. Inform. Assoc. JAMIA 21, 621–626 (2014).
  16. Qualls, L. G. et al. Evaluating Foundational Data Quality in the National Patient-Centered Clinical Research Network (PCORnet®). EGEMS Wash. DC 6, 3 (2018).
  17. Toh, S. et al. The National Patient-Centered Clinical Research Network (PCORnet) Bariatric Study Cohort: Rationale, Methods, and Baseline Characteristics. JMIR Res. Protoc. 6, e222 (2017).
  18. Heerman, W. J. et al. Maternal antibiotic use during pregnancy and childhood obesity at age 5 years. Int. J. Obes. 2005 (2019). doi:10.1038/s41366-018-0316-6
  19. Block, J. P. et al. Early Antibiotic Exposure and Weight Outcomes in Young Children. Pediatrics 142, (2018).
  20. Block, J. P. et al. PCORnet Antibiotics and Childhood Growth Study: Process for Cohort Creation and Cohort Description. Acad. Pediatr. 18, 569–576 (2018).
  21. Fishman, E. et al. Validation of a claims-based algorithm identifying eligible study subjects in the ADAPTABLE pragmatic clinical trial. Contemp. Clin. Trials Commun. 12, 154–160 (2018).
  22. Johnston, A., Jones, W. S. & Hernandez, A. F. The ADAPTABLE Trial and Aspirin Dosing in Secondary Prevention for Patients with Coronary Artery Disease. Curr. Cardiol. Rep. 18, 81 (2016).
  23. Pletcher, M. J., Forrest, C. B. & Carton, T. W. PCORnet’s Collaborative Research Groups. Patient Relat. Outcome Meas. 9, 91–95 (2018).
  24. Khare, R. et al. A longitudinal analysis of data quality in a large pediatric data research network. J. Am. Med. Inform. Assoc. JAMIA 24, 1072–1079 (2017).
  25. Lang, J. E. et al. Being Overweight or Obese and the Development of Asthma. Pediatrics 142, (2018).
  26. Jean, J. et al. Retrospective Analysis of Candida-related Conditions in Infancy and Early Childhood Caries. Pediatr. Dent. 40, 131–135 (2018).
  27. Hubbard, R. A. et al. A Bayesian latent class approach for EHR-based phenotyping. Stat. Med. 38, 74–87 (2019).
  28. Waitzfelder, B. et al. Treatment Initiation for New Episodes of Depression in Primary Care Settings. J. Gen. Intern. Med. 33, 1283–1291 (2018).