Data Sciences in Pharma - Patient Centered Outcomes Research
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Data Sciences in Pharma - Patient Centered Outcomes Research
Instructor: Susanne Clinch
3,051 already enrolled
Included with
What you'll learn
How patient experience data is used in the drug lifecycle
Developing a patient-centric measurement strategy and using qualitative and quantitative patient experience data as evidence in drug development
Common clinical outcome assessment outputs and considerations when interpreting clinical outcome assessment data
Skills you'll gain
- Psychosocial Assessments
- Clinical Research
- Pharmaceuticals
- Patient-centered Care
- Statistical Analysis
- Data Science
- Statistical Methods
- Quantitative Research
- Clinical Assessment
- Psychological Evaluations
- Drug Development
- Clinical Trials
- Data Literacy
- Oncology
- Pharmaceutical Terminology
- Patient Observation
- Patient Evaluation
Details to know
12 assignments
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There are 4 modules in this course
The course is targeted toward people who are interested in how patient experience data and clinical outcome assessment (COA) data can be used as evidence across drug development, in the pharmaceutical industry. By the end of the course you will better understand how this data is collected and analysed to evidence how patients feel, function or survive in the context of a clinical trial. More specifically, the course will cover: i) a background to COAs; ii) a background to patient experience data; iii) how to select, develop/modify and validate COAs using qualitative data (a) and psychometrics (b); iv) interpreting data on a COA; v) measuring treatment related tolerability via patient reported outcomes; vi) Common COA data outputs.
No experience in the pharmaceutical industry is needed for this course, but it is beneficial. This is an introductory course so an interest in qualitative and quantitative data and some basic knowledge in data analytics and statistics will be helpful for some lessons but is not required.
This module will cover a background of clinical outcome assessments (COAs) and patient experience data, what they are and what they consist of, how this data fits into drug development and the importance of this data as evidence to the external environement (such as health authorities) across the drug lifecycle
What's included
6 videos3 assignments1 plugin
6 videos•Total 22 minutes
- New Video•3 minutes
- 1. Lesson introduction•1 minute
- 2. Describe what a COA is•5 minutes
- 3. How COA evidence fits into the drug development process•3 minutes
- 4. External environment for COA science•4 minutes
- A background to Patient Experience Data•6 minutes
3 assignments•Total 40 minutes
- An introduction to Clinical Outcome Assessments (COAs)•5 minutes
- A background to Patient Experience Data and patient focussed drug development•5 minutes
- Module 1 assignment•30 minutes
1 plugin•Total 94 minutes
- An overview from FDA on Patient Focussed Drug Development - First 94 minutes only•94 minutes
This Module will discuss ways in which qualitative research is used to select, develop, modify or validate a COA. The amount of qualitative research study teams need to conduct can depend on how much qualitative research for the concept of interest in the context of use is already publically available. Qualitative research is often an initial step health authorities such as FDA mandate when they evaluate the suitability of existing and newly developed COAs selected for a clinical trial
What's included
5 videos2 readings3 assignments
5 videos•Total 36 minutes
- What qualitative evidence is needed by health authorities?•9 minutes
- Steps 1 and 2: Qualitative literature reviews and Qualitative concept elicitation•6 minutes
- Steps 3 and 4: Developing a disease conceptual model and reviewing existing COAs•8 minutes
- Step 5: Adapt or develop a measure and conceptual frameworks•5 minutes
- Step 6 and 7: Cognitively debriefing a new instrument and psychometric properties•7 minutes
2 readings•Total 60 minutes
- FDA PFDD guidance 2 - Methods to Identify What Is Important to Patients•30 minutes
- Clinical Outcome Assessments: Conceptual Foundation–Report of the ISPOR Clinical Outcomes Assessment – Emerging Good Practices for Outcomes Research Task Force•30 minutes
3 assignments•Total 41 minutes
- An introduction to Clinical Outcome Assessments (COAs)•6 minutes
- Understanding the steps involved in developing, selecting and modifying COAs•5 minutes
- Module 2 assignment•30 minutes
This Module will discuss some of the common quantitative methods used when selecting, developing, modifying and validating a COA. This will include a background to psychometrics and the different properties that are considered for classical test therory and item response theory. It will also touch on the important topic of evaluating change in a COA, what that change means and methods to establish what threshold in the COA of interest would be described as meaningful from the patient's point of view
What's included
11 videos1 reading3 assignments
11 videos•Total 48 minutes
- 1. Introduction to the lesson•1 minute
- 2. What is psychometrics and why is it important?•2 minutes
- 3. Classical test theory (CTT)•5 minutes
- 4. Item response theory (IRT)•7 minutes
- 5. CTT vs IRT•2 minutes
- 6. Example setup and analysis plans•3 minutes
- 7. Examples of analyses•7 minutes
- 1. The value of establishing meaningful change in a COA•3 minutes
- 2. Approaches to establishing meaningful change in a COA•3 minutes
- 3. Primary and supportive methods for establishing meaningful change•4 minutes
- 4. An example of establishing meaningful change in Alzheimer's disease•12 minutes
1 reading•Total 30 minutes
- Development of the SMA independence scale–upper limb module (SMAIS–ULM): A novel scale for individuals with Type 2 and non-ambulant Type 3 SMA•30 minutes
3 assignments•Total 40 minutes
- Understanding psychometrics in COA development•5 minutes
- COAs - establishing and interpreting meaningful change•5 minutes
- Module 3 assignment•30 minutes
This module will provide an understanding of a how patient reported outcomes (PROs) are used to measure treatment related tolerability, with a focus on a commonly used measure called the PRO-CTCAE as well as common COA outputs and considerations when interpreting COA data
What's included
7 videos2 readings3 assignments
7 videos•Total 27 minutes
- 1. Lesson introduction•1 minute
- 2. PRO-CTCAE background and context•3 minutes
- 3. PRO-CTCAE items and scoring•5 minutes
- 4. PRO-CTCAE item selection•3 minutes
- 5. Reconciliation of PRO-CTCAE items•3 minutes
- 6. PRO-CTCAE Research examples•3 minutes
- Interpreting and summarizing COA data in Clinical Study Reports•8 minutes
2 readings•Total 60 minutes
- Symptomatic Toxicities Experienced During Anticancer Treatment: Agreement Between Patient and Physician Reporting in Three Randomized Trials•30 minutes
- FDA PFDD draft guidance 4 on Incorporating Clinical Outcome Assessments Into Endpoints For Regulatory Decision-Making•30 minutes
3 assignments•Total 42 minutes
- Measuring treatment related tolerability via PROs•5 minutes
- Common COA data outputs and considerations when interpreting COA data•7 minutes
- Module 4 assignment•30 minutes
Instructor
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Course
- Status: Free Trial
Specialization
- Status: PreviewU
University of Glasgow
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