CERTaIN: Observational Studies and Registries from edX

While randomized controlled trials are considered to be the "gold standard" in health research, they cannot always be performed, for ethical or practical reasons. Observational studies gather information from data that has already been collected, or by observing and measuring patients' changes in health status and their response to interventions outside of a clinical trial. In this course, you will learn to identify the characteristics of observational studies, to interpret the results of observational studies, and to describe the use of health registries in comparative effectiveness research (CER).

This course includes the following 11 lectures:

Overview of Using Observational Data in Comparative Effectiveness Research (CER)
Cancer Registries and Data Linkage
SEER-Medicare and Other Data Sources
Overview of Analytic Methods I
Overview of Analytic Methods II
Longitudinal Data Analysis
Advanced Methods in CER I
Advanced Methods in CER II
Survival Analysis
Analysis of Medical Cost Data in Observational Studies
Healthcare Policy Research

This course is intended for anyone interested in comparative effectiveness research (CER) and patient-centered outcomes research (PCOR) methods.

This course is supported by grant number R25HS023214 from the Agency for Healthcare Research and Quality.

What's inside

Learning objectives

Define several types of observational studies and describe their characteristics
Interpret observational study results

Describe how health registries can be used for cer

Define several types of observational studies and describe their characteristics
Interpret observational study results
Describe how health registries can be used for cer

Syllabus

Overview of Using Observational Data in Comparative Effectiveness Research (CER)

When to use observational studies in CER

Observational study biases

Observational study data sources

Cancer Registries and Data Linkage

Data linkage definition

Why cancer registries link their data

Basics of data linkage methods

SEER-Medicare and Other Data Sources

Uses of cancer registry data

Overview of Analytic Methods I

Correlation definition

Statistical methods for continuous outcome variables

Simple linear regression and multiple linear regression

Overview of Analytic Methods II

Statistical methods for categorical data

Mantel Haenszel Method

Logistic regression

Longitudinal Data Analysis

Longitudinal data situations and the problems of repeated measures

Common approaches to measure change over time

Understanding basic results obtained from longitudinal analysis of linear and logistic regression

Advanced Methods in CER I

Limitations of randomized clinical trials and advantages of observational studies

Propensity score definition and estimation

Checking the proper use of propensity scores

Advanced Methods in CER II

Endogeneity bias definition

Conditions and properties of instrumental variable estimation and models

Survival Analysis

Censoring and person-time

Application of life tables

Kaplan Meier estimator

Using the log-rank test to compare survival curves

Hazard function definition and hazard ratio computation

Applying the Cox proportional hazards model

Analysis of Medical Cost Data in Observational Studies

Importance of medical cost analysis

Basic elements of medical cost data

Types of medical cost studies and their analytical methods

Healthcare Policy Research

Objectives and stages of the policy-making process

Comparison and contrast of CER and policy research

Policy changes and evaluation results of a case study

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops knowledge and skills in identifying the characteristics of observational studies, interpreting the results of observational studies, and describing the use of health registries in comparative effectiveness research (CER)

Explores observational studies, which gather information from data that has already been collected, or by observing and measuring patients' changes in health status and their response to interventions outside of a clinical trial

Covers advanced methods in CER, including propensity score estimation and endogeneity bias

Emphasizes the importance of medical cost analysis in observational studies, and the role of registries like SEER-Medicare

Provides an overview of analytic methods for continuous and categorical outcome variables

Taught by experienced instructors, Maria E. Suarez-Almazor, MD, PhD, and Sharon H. Giordano, MD, MPH, FASCO

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in CERTaIN: Observational Studies and Registries with these activities:

Review the basic principles of epidemiology and biostatistics

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Reviewing the basic principles of epidemiology and biostatistics will provide you with a solid foundation for understanding the concepts and methods used in observational studies.

Browse courses on Epidemiology

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Review the key concepts of epidemiology, including measures of disease frequency and association
Review the key concepts of biostatistics, including statistical tests and measures of effect size
Apply these concepts to real-world examples

Develop a plan for conducting a comparative effectiveness research study using observational data

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Developing a plan for conducting a CER study will provide you with hands-on experience in applying the skills and knowledge gained in this course, allowing you to independently design and plan a research project.

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Identify a research question that can be addressed using observational data
Select the appropriate type of observational study design
Develop a data collection plan
Write a research proposal

Show all two activities

Career center

Learners who complete CERTaIN: Observational Studies and Registries will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians collect, analyze, interpret, and present data. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Statisticians to understand in order to effectively analyze data from a variety of sources. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Statisticians to have.

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Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Data Analysts to understand in order to effectively analyze data from a variety of sources. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Data Analysts to have.

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Health Educator

Health Educators develop and implement educational programs to promote health and prevent disease. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Health Educators to understand in order to effectively evaluate the impact of health education programs. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Health Educators to have.

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Epidemiologist

Epidemiologists study the distribution and determinants of health-related states and events in populations. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Epidemiologists to understand in order to effectively design and conduct studies to investigate the causes of disease. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Epidemiologists to have.

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Biostatistician

Biostatisticians apply statistical methods to solve problems in the life sciences. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Biostatisticians to understand in order to effectively design and conduct studies in the life sciences. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Biostatisticians to have.

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Research Scientist

Research Scientists conduct research to advance scientific knowledge and develop new products and technologies. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Research Scientists to understand in order to effectively design and conduct research studies. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Research Scientists to have.

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Pharmacist

Pharmacists dispense medications and provide advice on their use. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Pharmacists to understand in order to effectively monitor and manage medication therapy for their patients. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Pharmacists to have.

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Health Policy Analyst

Health Policy Analysts develop and evaluate policies and programs to improve the health of the population. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Health Policy Analysts to understand in order to effectively evaluate the impact of health policies and programs. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Health Policy Analysts to have.

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Medical Writer

Medical Writers create written materials about medical products, services, and procedures. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Medical Writers to understand in order to effectively communicate complex medical information to a variety of audiences. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Medical Writers to have.

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Clinical Research Associate

Clinical Research Associates (CRAs) play a vital role in the development of new drugs and treatments by ensuring that clinical trials are conducted ethically and in accordance with good clinical practice guidelines. This course provides a strong foundation in the principles of observational studies and registries, which are essential for CRAs to understand in order to effectively monitor and manage clinical trials. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for CRAs to have.

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Public Health Nurse

Public Health Nurses work to promote health and prevent disease in the community. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Public Health Nurses to understand in order to effectively assess the health needs of the community and develop and implement health promotion programs. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Public Health Nurses to have.

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Health Information Manager

Health Information Managers oversee the collection, storage, and analysis of health information. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Health Information Managers to understand in order to effectively manage health information. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Health Information Managers to have.

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Research Assistant

Research Assistants assist researchers with their research projects. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Research Assistants to understand in order to effectively assist researchers with their research projects. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Research Assistants to have.

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Medical Statistician

Medical Statisticians apply statistical methods to solve problems in medicine. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Medical Statisticians to understand in order to effectively design and conduct studies in medicine. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Medical Statisticians to have.

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Cancer Registrar

Cancer Registrars collect, manage, and analyze data on cancer patients. This course provides a strong foundation in the principles of observational studies and registries, which are essential for Cancer Registrars to understand in order to effectively collect and analyze data on cancer patients. The course also covers topics such as data linkage, analytic methods, and survival analysis, which are all important skills for Cancer Registrars to have.

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