Level 2 Analyses

What this program does:

• Identifies exposures, follow-up time, outcomes, and covariates
• Estimates a propensity score (based on predefined covariates and/or via a high-dimensional propensity score approach)
• Uses matching, stratification, inverse probability of treatment weighting (IPTW), or stratum weighting for confounder adjustment and follows the analytic cohort for outcome assessment in a survival analysis framework

Output metrics include:

• Tables of patient characteristics (unadjusted and adjusted cohorts)
• Measures of covariate balance
• Distribution of propensity score by exposure group
• Hazard ratios (with 95% confidence intervals)
• Kaplan-Meier curves
• IPTW/PS stratum weights
• Attrition table

​​​Continue reading about propensity score analysis on Sentinel's Git Repository. 

What this program does: 

• Conducts covariate stratification within each Sentinel Data Partner site via distributed programming code; returns data to the Sentinel Operations Center (SOC), aggregated, and used to calculate effect estimates
• Groups patients in exposed and comparator cohorts into strata defined by unique values for any requester-defined combination of sex, age group, and/or year of index date

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Continue reading about covariate stratification on Sentinel's Git Repository. 

What this program does:

• Identifies exposure of a medical product of interest
• Defines risk and control windows relative to the exposure date
• Examines the occurrence of health outcomes of interest during the risk and control windows

Output metrics include:

• Number of exposure episodes
• Exposed individuals
• Individuals with a health outcome of interest in the risk and/or control windows
• Censored individuals overall
• Attrition table

Stratified by requester-defined:

• Age group
• Sex
• Year
• Year-month
• Time-to-event (in days)
• Race (available upon request)
• Ethnicity (available upon request)
• Geographic region (available upon request)

This program provides estimates of relative risk (RR) and 95% confidence intervals.

Continue reading about self-controlled risk interval design on Sentinel's Git Repository. 

What this program does:

• Identifies exposures, follow-up time, outcomes, and covariates in a population of pregnant women
• Estimates a propensity score (based on predefined covariates and/or via a high-dimensional propensity score approach)
• Uses matching, stratification, inverse probability of treatment weighting (IPTW), or stratum weighting for confounder adjustment and a binary outcome assignment framework for maternal outcome assessment among the pregnant mothers or birth outcome assessment among the infants or a survival analysis framework for maternal outcomes assessment among pregnant mothers

Output metrics include:

• Tables of patient characteristics (unadjusted and adjusted cohorts)
• Hazard ratios (with 95% confidence intervals)
• IPTW/PS stratum weights
• Measures of covariate balance
• Distribution of propensity score by exposure group
• Risk ratios (with 95% confidence intervals)
• Attrition table

Continue reading about propensity score analysis on Sentinel's Git Repository. 

What this program does: 

• Conducts covariate stratification within each Sentinel Data Partner site via distributed programming code; returns data to the Sentinel Operations Center (SOC), aggregated, and used to calculate effect estimates
• Groups patients in exposed and comparator cohorts into strata defined by unique values for any requester-defined combination of sex, age group, and/or year of index date

Continue reading about covariate stratification on Sentinel's Git Repository. ​​​​​​