Level 2 Modular Program Queries

Level 2 modular program queries identify cohorts of interest, perform more complex adjustment for confounding, and generate effect estimates and confidence intervals. Below you will find descriptions of the different types of cohort identification strategies and tools that can be used to perform a Level 2 analysis. 

Level 2 Cohort Identification Strategies & Tools

For more details on the functional and technical documentation of each type, please visit Sentinel's Git Repository located externally. The Git Repository serves as Sentinel's version control tracking system for analytic packages and technical documentation.

Cohort Identification Strategy:

Identify Exposures and Follow-up Time and Perform Propensity Score Matching


This program 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), and matches patients in an exposed cohort to patients in a comparator cohort based on propensity score. Propensity score estimation and matching is performed within each Sentinel Data Partner site. Treatment effects are estimated using the matched comparisons. Output includes tables of patient characteristics (unmatched and matched cohorts), measures of covariate balance, distribution of propensity score by exposure group, hazard ratios (with 95% confidence intervals) and incidence rate differences (with 95% confidence intervals).

Continue reading about Propensity Score Analysis Tool on Sentinel's Git Repository.

Cohort Identification Strategy:

Identify Exposures and Follow-up Time and Calculate Effect Estimates


The Covariate Stratification (CS) tool performs effect estimation by comparing exposure exact matched parallel new user cohorts or comparing a new user cohort to a never-exposed cohort. Covariate stratification is conducted within each Sentinel Data Partner site via distributed programming code; data are returned to the Sentinel Operations Center (SOC), aggregated, and used to calculate effect estimates.

The CS tool will find an exact match between patients in exposed and comparator cohorts based on any requester-defined combination of sex, age group, and/or year of index date. Patients in exposed and comparator cohorts are matched in 1:1 or variable 1:n (n≤10) ratios.

Continue reading about Covariate Stratification Tool on Sentinel's Git Repository.

Cohort Identification Strategy:

Self-Controlled Risk Interval Design


This program identifies exposure, defines risk and control windows relative to the exposure date, and examines the occurrence of HOIs during the risk and control windows. Output metrics include number of exposure episodes, exposed individuals, individuals with an HOI in the risk and/or control windows, and censored individuals, overall and stratified by requester-defined age group, sex, year, year-month, and time-to-event (in days). Estimates of relative risk (RR) and 95% confidence intervals are provided.

Continue reading about Self-Controlled Risk Interval Design on Sentinel's Git Repository.


RSS Feed Scroll to Top