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. The table below provides a description of the different types of cohort identification strategies and tools that can be used to perform a level 2 analysis. 

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
Type

Cohort
Identification
Strategy

Description

Type 2 + Propensity Score Analysis Tool

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.

Type 2 +
Multiple Factor Matching Tool
Identify
Exposures and Follow-up Time and
Calculate
Effect Estimates 

The Multple Factor Matching (MFM) tool performs effect estimation by comparing exposure exact matched parallel new user cohorts or comparing a new user cohort to a never-exposed cohort. Multiple factor matching 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 MFM 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 Multiple Factor Matching Tool on Sentinel's Git Repository.

Type 3

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.