Related Experiment Video
Updated: Jul 26, 2026
11:18
Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
Published on: January 22, 2011
Creating a Common Data Model for Comparative Effectiveness with the Observational Medical Outcomes Partnership
F FitzHenry1, F S Resnic2, S L Robbins2
1Tennessee Valley Healthcare System, Veterans Affairs Medical Center , Nashville, TN ; Department of Biomedical Informatics; Vanderbilt University, Nashville , TN.
Applied Clinical Informatics
|October 9, 2015
Summary
Transforming health data to a common data model (CDM) like OMOP CDM is resource-intensive but enables efficient, multi-site comparative effectiveness research by standardizing cohort identification and analysis.
Area of Science:
- Health Informatics
- Comparative Effectiveness Research
- Data Standardization
Background:
- Large-scale distributed comparative effectiveness analyses require common data models (CDM) across health systems.
- Several CDMs exist, including Mini-Sentinel and the Observational Medical Outcomes Partnership (OMOP) CDM.
Purpose of the Study:
- To describe the challenges and opportunities of using the OMOP CDM for a study-specific case.
- To present three comparative effectiveness use cases developed from the OMOP CDM.
Main Methods:
- Two health system databases were transformed into the OMOP CDM using provided crosswalks.
- Cohorts for three comparative effectiveness use cases were developed from the transformed CDMs.
- Data included administrative/billing, demographic, order history, medication, and laboratory information.
Main Results:
- Differences in record counts per person month were observed between civilian and federal datasets.
- Data extraction methods for medications (orders vs. pharmacy fills) impacted counts.
- The federal system exhibited a higher prevalence of conditions across all three use cases.
- Manual coding was necessary for certain data types during the CDM transformation.
Conclusions:
- Data transformation to the OMOP CDM was time-consuming and resource-intensive.
- Manual data coding presented limitations during the conversion process.
- Once converted, the OMOP CDM facilitated consistent cohort identification and analysis across sites, minimizing cross-site effort.
Related Concept Videos
01:11Observational Studies
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies ā Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
There are three types of observational studies ā Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
01:26Methods of Documentation II: POMR
The Problem-Oriented Medical Record (POMR) revolutionized medical record-keeping by introducing a systematic approach focusing on the patient's problems rather than merely listing symptoms. Dr. Lawrence Weed's introduction of this method in the 1960s marked a significant advancement in medical documentation. The POMR framework consists of four key components: the database, problem list, plan of care, and progress notes.
01:15Methods of Documentation VI: Case Management Model
The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...
For example, a patient with a chronic illness...
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...
00:59Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
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.