What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
Article
This course is part of Health Informatics Specialization
Instructors: Hadi H. K. Kharrazi, MD, Ph.D
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Beginner level
While there are no prerequisites, prior experience with, or knowledge of, health, healthcare, technology, and statistics are helpful.
(209 reviews)
Recommended experience
Beginner level
While there are no prerequisites, prior experience with, or knowledge of, health, healthcare, technology, and statistics are helpful.
Articulate different forms of clinical and population level data.
Describe the data required to answer a healthcare information problem.
Distinguish between data questions and data queries when dealing with a healthcare information problem.
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Health data are notable for how many types there are, how complex they are, and how serious it is to get them straight. These data are used for treatment of the patient from whom they derive, but also for other uses. Examples of such secondary use of health data include population health (e.g., who requires more attention), research (e.g., which drug is more effective in practice), quality (e.g., is the institution meeting benchmarks), and translational research (e.g., are new technologies being applied appropriately). By the end of this course, students will recognize the different types of health and healthcare data, will articulate a coherent and complete question, will interpret queries designed for secondary use of EHR data, and will interpret the results of those queries.
In this module, we will begin by introducing and defining databases, and placing the role of databases within the context of clinical informatics. We will continue by introducing the common health data types such as demographics, diagnosis, medications, procedures, and utilization data. We will finish this module by reviewing the emerging health data such as lab orders/results, vital signs, social data, and patient-generated data.
6 videos1 assignment
In this module, we review the data specifications extracted from insurance claims and electronic health records. We will then discuss the common challenges in using health data, specifically issues with data quality, data interoperability, and data system architectures. Finally, we will describe the “Big Data” challenges of health data and explain some of the data problems that may hinder analytical efforts.
5 videos1 assignment
With this understanding of the data available, it’s time to see how to turn questions you and your colleagues will have into queries the database can understand. Besides getting rules of thumb for doing this translation, you will also be introduced to three online tools available to test some of these skills. You will also watch an interview with Sam Meiselman, course instructor and the data manager in charge of the Johns Hopkins Enterprise Data Warehouse, who has to use these skills on a daily basis.
6 videos1 assignment
To send home the recurring message on the challenges and art of translating questions into queries, you will see interviews with two professionals: One who comes from the data management side of the equation, and one who comes from the domain. They will give you perspectives that are both similar (the need to understand the problem for which the data are being retrieved) and different (the multiplicity of data available vs the richness of the domain problem).
8 videos1 assignment1 peer review
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
University of Minnesota
Course
Johns Hopkins University
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Imperial College London
Specialization
University of Michigan
Course
209 reviews
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Reviewed on Sep 7, 2022
this was exhirilating and intence..its worth going for...
Reviewed on Feb 7, 2024
Effectively conveys the interdisciplinary nature of your research, showcasing the utilization of data science techniques within the realm of health informatics. Well done!
Reviewed on Mar 21, 2021
Definitely the best course in this specialization. Lots of tangible and good resources for health practitioners to learn how to pull data and function within the U.S. Health Informatics universe.
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