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Propensity score-based methods for comparative effectiveness research (CER) using multilevel data: what works best when
Investigator (PI): Kim, Mi Ok
Performing Organization (PO): (Current): University of California, San Francisco, Helen Diller Family Comprehensive Cancer Center / (877) 827-3222
(Past): Cincinnati Children's Hospital Medical Center / (513) 636-4200
Supporting Agency (SA): Patient-Centered Outcomes Research Institute (PCORI)
Initial Year: 2015
Final Year: 2019
Record Source/Award ID: PCORI/ME-1403-13922-IC ; PCORI/ME-1403-13922
Funding: Total Award Amount: $652,777
Award Type: Contract
Award Information: PCORI: More information and project results (when completed)
Abstract: The decision to adopt a treatment is complex, and the doctor, patient, and parents/guardians interact and consider a number of factors. Some of these factors may predict better or worse patient outcomes regardless of whether the treatment is effective. This problem is known as confounding. Confounding, when present, may complicate explaining the relationship between the outcome and the treatment as other factors may be responsible for the relationship. Confounding is often present when treatments are selected rather than randomly assigned. Thus confounding, unless properly addressed, may render the results of a study invalid or even irrelevant. The proper treatment of confounding gets more complex for studies where patients are clustered, for example, by geographical area of residence, health care provider (hospital/clinic or physician), or health plan. This study will focus on how to properly address confounding in this complex situation. The proper treatment consists of two parts, first accounting for its effect in relating the observed outcome to the treatment as best as one can by using available data, and second examining how easily or dramatically the outcome relationship with the treatment changes if confounding is not sufficiently well addressed with the available data. We will develop novel approaches for both parts. To facilitate the development of the methodologies, we will use both computer simulated data and real data examples. The two complement each other for comprehensively evaluating the novel approaches developed in this study. The complex situation with confounding occurs commonly in studies using registries, network databases or electronic health record (EHR) databases. The Patient-Centered Outcomes Research Institute specifically launched a new initiative of forming national patient-centered clinical research network (PCORnet) to facilitate comparative effectiveness research (CER). It currently funds 29 individual data networks (18 PPRNs and 11 CDRNs). CER studies using this PCORnet will face a complex situation. This study will contribute significantly to the PCORI's mission. More on this project: E. Nehus, C. Liu, D.K. Hooper et al. Clinical Practice of Steroid Avoidance in Pediatric Kidney Transplantation. American Journal of Transplantation 15(8) (August 2015): 2203-2210.
MeSH Terms:
  • Algorithms
  • Comparative Effectiveness Research /*methods
  • Computer Simulation
  • Data Interpretation, Statistical
  • Databases, Factual
  • Electronic Health Records
  • Humans
  • Outcome Assessment (Health Care)
  • Patient-Centered Care
  • Program Development
  • * Propensity Score
  • Registries
  • Research Design
  • United States
Country: United States || United States
State: California || Ohio
Zip Code: 45229 / 94143
UI: 20152319
Project Status: Completed
Record History: ('2019: Project extended to 2019 ',) ('2017: Project extended to 2018',) ('2018: PO changed',)