Related Experiment Video
Updated: Nov 12, 2025
06:05
The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
Published on: February 19, 2021
1.5K
Cost-Effectiveness Analysis in Implementation Science: a Research Agenda and Call for Wider Application
1Faculty of Health Sciences, Simon Fraser University, 8888 University Drive V5A 1S6, Burnaby, British Columbia, Canada.
Current HIV/AIDS Reports
|March 20, 2021
Summary
Cost-effectiveness analysis (CEA) can improve public health strategies by evaluating implementation trade-offs. Integrating implementation science into CEA is crucial for real-world context and tailored recommendations.
Area of Science:
- Public Health
- Health Economics
- Implementation Science
Background:
- Cost-effectiveness analysis (CEA) is vital for decision-making in public health strategy implementation.
- Current application of CEA in implementation science studies is limited.
- Broader implementation of evidence-based public health interventions requires further research.
Purpose of the Study:
- To identify areas for development to enhance the uptake and impact of model-based CEA in implementation science.
- To integrate implementation science concepts into CEA for real-world applicability.
- To provide tailored guidance for evidence-based public health action.
Main Methods:
- Review of current practices and literature on CEA in implementation science.
- Description of examples integrating implementation science concepts into model-based CEA.
- Proposal of methodological advancements for CEA in implementation research.
Main Results:
- Model-based CEA can quantify the added value of implementation strategy components and phases.
- Integration of implementation science into CEA is needed for diverse delivery contexts.
- Six distinct domains for methodological advancement are proposed.
Conclusions:
- Enhancing model-based CEA uptake requires explicit integration of implementation science.
- Tailored recommendations for public health action can be provided by integrating CEA and implementation science.
- Further methodological development is needed to maximize the impact of CEA in implementation science research.
Related Concept Videos
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
249
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,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
249
01:26Methods Of Healthcare Delivery System
3.7K
At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is...
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is...
3.7K
01:20Study Designs in Epidemiology
602
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...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
602
01:20Comparing the Survival Analysis of Two or More Groups
392
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
392
01:19Overview of Biostatistics in Health Sciences
3.8K
Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
3.8K
01:25Strategies for Assessing and Addressing Confounding
213
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
213