The Protective Effect of Influenza Vaccine for Vulnerable Population
Conditions: Fracture, Influenza Vaccination
Sponsor: Taipei Medical University Hospital

Study Protocol and Statistical Analysis Plan 
1. Data Source 
This study utilized data from Taiwan’s National Health Insurance (NHI) program, a 
universal health system established in 1996 that covers over 99% of the population. 
The claims database provides comprehensive and validated medical records for 
research use. All personal identifiers were encrypted to protect patient privacy. The 
study protocol was approved by the Institutional Review Board and conducted in 
accordance with the Declaration of Helsinki. 
2. Study Design 
A nested retrospective cohort design was adopted to evaluate the association 
between influenza vaccination (IV) and clinical outcomes following fracture-related 
hospitalizations. 
From the nationwide NHI cohort of more than 23 million insured individuals, we 
identified 561,566 patients aged ≥65 years admitted for fracture treatment between 
2009 and 2020. Among them, 213,381 received IV within 12 months prior to 
admission, while 348,185 had not. 
To reduce confounding, 1:1 propensity score matching (PSM) was performed 
between vaccinated and nonvaccinated patients. Matching variables included: 
 
Demographics: age, sex 
 
Socioeconomic status (low-income vs. non-low-income) 
 
Fracture type and comorbidities (within 24 months) 
 
Emergency visits and hospitalizations during the prior year 
3. Outcomes 
The primary outcomes, assessed within 30 days postadmission, included: 
 
Pneumonia 
 
Septicemia 
 
Urinary tract infection 
 
Intensive care use 
 
Hospital length of stay 
 
Total medical expenditure 
 
30-day mortality 
Postfracture infections were identified by physician-coded diagnoses during 
hospitalization or subsequent claims. Patients with pneumonia or septicemia within 6 
months before the fracture were excluded. 
4. Measures and Definitions 
 
Socioeconomic status: categorized as low-income or non-low-income per 
NHI copayment exemption criteria. 

 
Comorbidities: identified from 24-month pre-fracture claims using 
ICD-9-CM codes. 
 
Postfracture infections: defined by ICD-9-CM diagnostic codes (listed in 
Table S1). 
 
Influenza vaccine types: summarized in Table S2. 
5. Statistical Analysis 
Propensity scores were estimated using multivariable logistic regression, including 
clinically relevant covariates (Table 1). Matching was performed via a greedy 
algorithm with a caliper width of 0.2 SD of the logit of the propensity score. 
 
Categorical variables: summarized as counts and percentages; compared 
using the chi-square test. 
 
Continuous variables: expressed as mean ± SD; compared using independent 
t-tests. 
 
Risk estimation: Adjusted odds ratios (ORs) with 95% confidence intervals 
(CIs) were derived from logistic regression to assess IV effects on infections 
and mortality. 
 
Sensitivity analyses: stratified by age, sex, comorbidity burden, and fracture 
type.