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Project Information

THE DEVELOPMENT OF STATISTICAL TOOLS FOR COMPARATIVE EFFECTIVENESS RESEARCH

Agency:
AHRQ

HHS/Agency for Healthcare Research and Quality

Project Number:
1K99HS022192-01
Contact PI / Project Leader:
BAIOCCHI, MIKE
Awardee Organization:
STANFORD UNIVERSITY

Description

Abstract Text:
DESCRIPTION (provided by applicant): I am a PhD statistician who specializes in observational studies and comparative effectiveness research (CER). I have just completed the first year of a three-year fellowship in the statistics department of Stanford University. My long-term goal is to become a tenure track professor in a health services, biostatistics or statistics department. Project 1: Make an instrumental variable technique, known as "near-far matching," more accessible to CER researchers. Near-far matching is similar to propensity score matching, but is capable of estimating unbiased treatment effects even when there is confounding caused by unobserved covariates. Project 2: Combine causal inference techniques (i.e., ways to obtain unbiased treatment effects) with cutting edge predictive modeling techniques (e.g., nonparametric, fast algorithms for discovering interesting parts of the covariate space). The proposed techniques can use observational data to identify subpopulations which have large (or very small) responses to a given treatment (a.k.a. "treatment effect heterogeneity"). Interestingly, we propose a prediction technique which is still valid when there is unobserved confounding. Project 3: Propose an empirical Bayes technique which uses patient-level information (e.g., demographic covariates) plus patient-level longitudinal experience (e.g., repeated measurements of HA1c or pain scores) to enhance prognostic ability for chronic care patients. I have assembled an interdisciplinary team of scientist from Stanford University who are highly committed to my career development. My primary mentor is Phil Lavori PhD, the chair of the Department of Health Research and Policy. My co-mentor is Mark Cullen MD, chief of the Division of General Medical Disciplines in Stanford Medical School. In addition to my mentors, I have four advising consultants: two statistician - Trevor Hastie and Tze Lai; two health economists - Victor Fuchs and Jay Bhattacharya. I have specific projects I will work on with each of these researchers. These projects require regular meetings between me and each of my supporters. Much of my mentoring will come through an apprenticeship model of collaboration. The career development program outlined in this application contains formal mentorship, didactic coursework, and seminars structured around three areas: (1) predictive modeling, (2) longitudinal analysis and (3) health disparities and health systems. During the first year of the K99 phase I will audit three classes that specifically address these three topics. Stanford has very active statistics and CER groups; I will attend several regularly reoccurring workshops and seminars in order to build my experience with these research communities. Additionally, I will have biweekly meetings with Professor Cullen's Alcoa Study research group - led by Professor Cullen and consisting of postdocs, research fellows, and junior faculty discussing research issues.
Project Terms:
Address; Algorithms; Area; Biometry; career development; Chronic Care; Collaborations; Commit; Communities; comparative effectiveness; Data; Development; Discipline; Doctor of Philosophy; Educational workshop; effectiveness research; experience; Faculty; Fellowship; Goals; Health; health disparity; Health Services; Health system; Heterogeneity; interest; longitudinal analysis; Measurement; Medical; medical schools; meetings; Mentors; Mentorship; Modeling; Observational Study; Pain; Patients; Phase; Policy Research; Postdoctoral Fellow; predictive modeling; professor; prognostic; programs; Research; Research Personnel; research study; response; Scientist; statistics; Structure; Techniques; tool; treatment effect; Universities; Work

Details

Contact PI / Project Leader Information:
Name:  BAIOCCHI, MIKE
Other PI Information:
Not Applicable
Awardee Organization:
Name:  STANFORD UNIVERSITY
City:  STANFORD    
Country:  UNITED STATES
Congressional District:
State Code:  CA
District:  18
Other Information:
Fiscal Year: 2013
Award Notice Date: 22-Feb-2013
DUNS Number: 009214214
Project Start Date: 01-Mar-2013
Budget Start Date: 01-Mar-2013
CFDA Code: 226
Project End Date: 28-Feb-2014
Budget End Date: 28-Feb-2014
Agency: ?

Agency: The entity responsible for the administering of a research grant, project, or contract. This may represent a federal department, agency, or sub-agency (institute or center). Details on agencies in Federal RePORTER can be found in the FAQ page.

HHS/Agency for Healthcare Research and Quality
Project Funding Information for 2013:
Year Agency

Agency: The entity responsible for the administering of a research grant, project, or contract. This may represent a federal department, agency, or sub-agency (institute or center). Details on agencies in Federal RePORTER can be found in the FAQ page.

FY Total Cost
2013 AHRQ

HHS/Agency for Healthcare Research and Quality

$105,602

Results

i

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