Related Experiment Video
Updated: May 19, 2026
06:55
Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Multicohort models in cost-effectiveness analysis: why aggregating estimates over multiple cohorts can hide useful
James F O'Mahony1,2, Joost van Rosmalen1, Ann G Zauber3
1Department of Public Health, Erasmus MC, Erasmus University, Rotterdam, the Netherlands (JFO’M, JvR, MvB)
Summary
Aggregating cost-effectiveness analysis (CEA) estimates across multiple patient cohorts can obscure important differences. Analyzing per-cohort data is crucial for accurate health policy decisions in screening programs.
Area of Science:
- Health economics
- Public health policy
- Screening program evaluation
Background:
- Cost-effectiveness analysis (CEA) models for screening programs can utilize single or multiple birth cohorts.
- Real-world screening implementation often involves multiple concurrent patient cohorts due to long-term, multi-stage screening processes.
- While modeling all cohorts is advocated for accuracy, aggregating estimates masks cohort-specific cost-effectiveness variations.
Purpose of the Study:
- To demonstrate the drawbacks of combining cost-effectiveness estimates from multiple cohorts without examining individual cohort data.
- To highlight how aggregated estimates can lead to different policy recommendations compared to per-cohort analyses.
- To illustrate potential disadvantages of aggregating CEA estimates across cohorts in screening programs.
Main Methods:
- Developed a multicohort model to estimate the cost-effectiveness of two alternative cervical screening tests.
- Compared aggregated cost-effectiveness estimates with per-cohort estimates.
- Analyzed scenarios where policy choices differed based on aggregated versus disaggregated results.
Main Results:
- Identified instances where aggregated and per-cohort cost-effectiveness estimates suggested different optimal policy choices.
- Demonstrated that aggregating estimates can obscure significant heterogeneity in cost-effectiveness across cohorts.
- Highlighted the policy relevance of variations in cost-effectiveness, particularly in cancer screening with concurrent birth cohorts.
Conclusions:
- The recommendation to consider multiple cohorts in CEA is valid.
- Aggregating cost-effectiveness estimates across multiple cohorts into a single figure is not advisable.
- Per-cohort analysis is essential for nuanced and accurate policy recommendations in screening programs.
Related Concept Videos
01:27Confounding in Epidemiological Studies
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
01:29Bias in Epidemiological Studies
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
01:11Bioavailability Study Design: Single Versus Multiple Dose Studies
Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
01:12Analysis of Population Pharmacokinetic Data
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
01:20Study Designs in Epidemiology
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...