Clinical Data Management - Using SAS Programming
Learn the essentials of Clinical Data Management using SAS to enhance data accuracy and efficiency in healthcare.
Course Highlights
Data management plays a vital role in ensuring the accuracy and reliability of clinical trial data. Clinical trial companies globally use SAS for clinical analysis and submission. So, master the powerful SAS programming principles with this clinical data management course. This Clinical Data Manager course will enhance your understanding of SAS programming. It will help you prepare for clinical data management jobs using SAS.
The course will educate you about the reliable components of the pharmaceutical industry. It will then take you through the clinical trial life cycle and the types of data collected in clinical trials. Again, it will introduce you to the study documents needed for clinical trials. For instance, you’ll learn about clinical study protocols and ethical consent. The course will also cover the inclusion-exclusion criteria and statistical analysis plans.
The clinical data management training also covers the essentials of an excellent clinical study report. First, it will introduce you to the general SAS programming steps. Next, you’ll learn how to program demographics tables and import raw demographic data into the SAS. You’ll understand how to derive age, sex and race variables and get summary statistics for each variable. Again, you’ll learn how to stack all the statistics together. The course will also explain how to fix precision points. You’ll learn how to transpose data and correct the order of statistical parameters. Then, you’ll understand how to create the final report and add the finishing touches.
So, enrol now to perform excellent clinical data management services.
Learning outcome
- Understand the fundamentals and frameworks of Clinical Data.
- Develop proficiency in SAS programming for data analysis.
- Master the techniques for data validation and quality control.
- Learn data setup, maintenance, and compliance protocols.
- Acquire skills in managing clinical trials data effectively.
Course media
Why should I take this course?
- Essential for mastering Clinical Data Management using industry-standard SAS tools.
- Improves your data handling skills specific to clinical trials.
- Bridges the gap between theoretical knowledge and practical application.
- Enhances career prospects in the booming healthcare data sector.
- Provides certification that is recognized in the healthcare industry.
Career Path
- Clinical Data Manager
- SAS Programmer
- Clinical Data Coordinator
- Clinical Data Analyst
- Data Quality Manager
Requirements
- Basic understanding of data analysis.
- Familiarity with clinical trial processes.
- Eagerness to develop technical skills in SAS programming.
Course Curriculum
Course Curriculum
| Course Promo | |||
| Course Promo | 00:01:00 | ||
| Unit 01: Introduction | |||
| 1.1 Components of the Pharma Industry | 00:05:00 | ||
| 1.2 Phases of Clinical Trials | 00:06:00 | ||
| 1.3 Data and Reports in Clinical Trials | 00:04:00 | ||
| 1.4 Types of Data | 00:05:00 | ||
| Unit 02: Knowledge on Clinical Study Documents | |||
| 2.1 Clinical Study Protocol | 00:02:00 | ||
| 2.2 Ethical Consent | 00:01:00 | ||
| 2.3 Inclusion-Exclusion Criteria | 00:01:00 | ||
| 2.4 Statistical Analysis Plan: SAP, Mockshell and CRF | 00:04:00 | ||
| Unit 03: Developing the Clinical Study Reports | |||
| 3.1 General SAS Programming Steps | 00:02:00 | ||
| 3.2 One Search Report: Demographics Table | 00:04:00 | ||
| 3.3 Understanding the Demographics Table | 00:03:00 | ||
| 3.4 Programming the Demographics Table | 00:05:00 | ||
| 3.5 Importing Raw Demographic Data into the SAS | 00:04:00 | ||
| 3.6 Deciding what Procedure to Use | 00:02:00 | ||
| 3.7 Deriving the AGE variable | 00:10:00 | ||
| 3.8 Obtaining Summary Statistics for AGE | 00:04:00 | ||
| 3.9 Adding the 3rd Treatment Group using Explicit Output | 00:05:00 | ||
| 3.10 Deriving the SEX variable | 00:02:00 | ||
| 3.11 Obtaining Summary Statistics for SEX | 00:03:00 | ||
| 3.12 Concatenating the COUNT and PERCENT Variables | 00:03:00 | ||
| 3.13 Deriving the RACE Variable | 00:03:00 | ||
| 3.14 Obtaining Summary Statistics for RACE | 00:03:00 | ||
| 3.15 Stacking All the 3 Summary Statistics Together | 00:06:00 | ||
| 3.16 Fixing the Precision Points | 00:04:00 | ||
| 3.17 Transposing Data | 00:03:00 | ||
| 3.18 Fixing the Order of Statistical Parameters | 00:05:00 | ||
| 3.19 Building the Final Report | 00:02:00 | ||
| 3.20 Putting the Final Touches to the Report | 00:11:00 | ||
| Resources | |||
| Resources – Clinical Data Analysis with SAS | 00:00:00 | ||
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1 Year Access 
8 Students 
1 hour, 53 minutes