The objective of this application is to support the career development of Linnea Polgreen, PhD. Her long-term goal is to become an independent investigator with a research program focused on developing methods for determining the best treatment options based on observational data. She has assembled a team of experienced mentors, including both clinical and quantitative researchers. These mentors not only bring diverse and complementary areas of expertise, but also, all of them have been successful mentors of students and young faculty. With this team of mentors, she will gain insight into what clinical questions she should attempt to answer using quantitative methods, and how to answer them. Although randomized controlled trials (RCTs) are the gold standard for determining treatment effectiveness, RCTs are difficult to perform: they are expensive and slow. In the absence of findings from RCTs, observational data are often used to inform treatment decisions. There are a number of strategies available to analyze treatment outcomes using observational data, but exactly which strategy is likely to be most accurate is currently unclear. Her objective in this application is to develop a general framework using methods from economics, epidemiology and computer science and outcome-based observational data to determine treatment effectiveness for medical interventions in general. Specifically, she will use Medicare Part A, B and D data from a cohort of acute myocardial infarction (AMI) patients treated with angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARB) to prevent subsequent AMIs, followed 1 year prior to, and up to 4 years post, the index AMI.
For Aim 1, she will identify the approach that most accurately reflects ACE inhibitor/ARB outcomes as given by previous RCTs.
For Aim 2, she will identify the approach that most accurately estimates treatment effectiveness for patients not generally eligible for RCTs. Upon successful completion of these aims, she expects to have developed a framework for identifying the advantages and disadvantages of different methods for estimating treatment effectiveness using observational data for a broad range of cardiac and pulmonary diseases.

Public Health Relevance

Although randomized controlled trials (RCTs) are the 'gold standard' for determining treatment effectiveness, they are very expensive and time-consuming to perform, and for rare diseases, RCTs are even more difficult to organize and complete. Using observational data is a cost-effective alternative, but current methods are subject to multiple forms of bias. My research objective is to develop a general framework to use outcome-based observational data for determining the treatment effectiveness of medical interventions, specifically ACE/ARB treatment for patients with acute myocardial infarctions, a major cause of morbidity and mortality.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
1K25HL122305-01A1
Application #
8890985
Study Section
Special Emphasis Panel (MPOR (JA))
Program Officer
Cooper, Lawton S
Project Start
2015-04-01
Project End
2019-03-31
Budget Start
2015-04-01
Budget End
2016-03-31
Support Year
1
Fiscal Year
2015
Total Cost
$144,563
Indirect Cost
$10,708
Name
University of Iowa
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52246
Simmering, J E; Cavanaugh, J E; Polgreen, L A et al. (2018) Warmer weather as a risk factor for hospitalisations due to urinary tract infections. Epidemiol Infect 146:386-393
Anthony, Chris A; Peterson, Ryan A; Sewell, Daniel K et al. (2018) The Seasonal Variability of Surgical Site Infections in Knee and Hip Arthroplasty. J Arthroplasty 33:510-514.e1
Kennelty, Korey A; Polgreen, Linnea A; Carter, Barry L (2018) Team-Based Care with Pharmacists to Improve Blood Pressure: a Review of Recent Literature. Curr Hypertens Rep 20:1
Riedle, Benjamin N; Polgreen, Linnea A; Cavanaugh, Joseph E et al. (2017) Phantom Prescribing: Examining the Frequency of Antimicrobial Prescriptions Without a Patient Visit. Infect Control Hosp Epidemiol 38:273-280
Simmering, Jacob E; Tang, Fan; Cavanaugh, Joseph E et al. (2017) The Increase in Hospitalizations for Urinary Tract Infections and the Associated Costs in the United States, 1998-2011. Open Forum Infect Dis 4:ofw281
Peterson, Ryan A; Polgreen, Linnea A; Cavanaugh, Joseph E et al. (2017) Increasing Incidence, Cost, and Seasonality in Patients Hospitalized for Cellulitis. Open Forum Infect Dis 4:ofx008
Anthony, Chris A; Peterson, Ryan A; Polgreen, Linnea A et al. (2017) The Seasonal Variability in Surgical Site Infections and the Association With Warmer Weather: A Population-Based Investigation. Infect Control Hosp Epidemiol 38:809-816
Simmering, Jacob E; Polgreen, Linnea A; Hornick, Douglas B et al. (2017) Weather-Dependent Risk for Legionnaires' Disease, United States. Emerg Infect Dis 23:1843-1851
Miller, Aaron C; Polgreen, Linnea A; Cavanaugh, Joseph E et al. (2016) Hospital Clostridium difficile infection (CDI) incidence as a risk factor for hospital-associated CDI. Am J Infect Control 44:825-9
Zahr, Roula S; Peterson, Ryan A; Polgreen, Linnea A et al. (2016) Diabetes as an increasingly common comorbidity among patient hospitalizations for tuberculosis in the USA. BMJ Open Diabetes Res Care 4:e000268

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