Staup, Tyler
(2024)
Use of Electronic Health Record Data to Produce Estimates of Influenza Vaccine Effectiveness.
Master Essay, University of Pittsburgh.
Abstract
Background/Objective: Influenza causes substantial morbidity and mortality yearly. Annual evaluations are necessary to understand variability in influenza vaccine effectiveness (VE). The COVID-19 pandemic highlighted the potential of using electronic health records (EHRs) to estimate VE for SARS-CoV-2 vaccines, offering advantages over prospective studies such as cost-effectiveness, time-efficiency, and large sample sizes. This study aimed to explore the feasibility of utilizing EHR data to estimate influenza VE.
Methods: Analyzed EHR data from patients hospitalized in the Marshfield Clinic Health System (MCHS) during the 2022-2023 influenza season. The completeness of vaccination records and important covariates were evaluated. The proportion of patients tested for influenza and characteristics associated with testing were assessed using multivariable logistic regression. VE was estimated among tested patients using a test-negative design with multivariable logistic regression, adjusted for age, sex, race, calendar-time, presence of high-risk medical condition, and COVID-19 vaccination.
Results: The study population included 8,884 inpatient admissions. All vaccination records contained vaccine name, record source, and administration date. Vaccine manufacturer, lot number, and route of administration were available in 93%, 94%, and 97% of records respectively. A patient’s race and presence of a high-risk medical condition was significantly associated with likelihood of receiving testing. Among 1,548 patients tested for influenza, VE was 40% (95% CI: 2%, 64%) overall, 69% (95% CI: 2%, 91%) for 18-64 years and 9% (95% CI: -65%, 50%) for ≥65 years. Among children, all influenza cases occurred in unvaccinated patients.
Conclusions: The likelihood of testing varied by patient characteristics which raises concerns about selection bias in testing practices. However, the likelihood of testing was not influenced by influenza vaccination. Confidence intervals were wide, but the high VE estimated in younger adult and pediatric groups was consistent with prior studies reporting relatively high VE during the same influenza season. Our results suggest that the use of EHR data is a potentially promising approach to estimating annual VE, but larger studies are needed to understand potential sources of bias. Our findings emphasize the public health significance of harnessing EHRs to evaluate influenza VE, offering a resource-efficient means to continually assess and comprehend influenza protection in populations.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
Other Thesis, Dissertation, or Long Paper
(Master Essay)
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| Contributors: |
| Contribution | Contributors Name | Email | Pitt Username | ORCID  |
|---|
| Committee Chair | Glynn, Nancy | epidnwg@pitt.edu | epidnwg | UNSPECIFIED | | Committee Member | Hughes Kramer, Kailey | hugheskl4@pitt.edu | hugheskl4 | UNSPECIFIED | | Committee Member | Petrie, Josh | petrie.joshua@marshfieldresearch.org | UNSPECIFIED | UNSPECIFIED |
|
| Date: |
3 January 2024 |
| Date Type: |
Completion |
| Submission Date: |
14 December 2023 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
43 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Epidemiology |
| Degree: |
MPH - Master of Public Health |
| Thesis Type: |
Master Essay |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
n/a |
| Date Deposited: |
03 Jan 2024 17:58 |
| Last Modified: |
03 Jan 2024 17:58 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/45694 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[img]](http://d-scholarship.pitt.edu/style/images/fileicons/application_pdf.png)
![[feed]](/images/feed-icon-32x32.png){kind=icon}