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Our Courses
The Social and Technical Context of Health Informatics
Improving health and healthcare institutions requires understanding of data and creation of interventions at the many levels at which health IT interact and affect the institution. These levels range from the external “world” in which the institution operates down to the specific technologies. Data scientists find that, when they aim at implementing their models in practice, it is the “socio” components that are both novel to them and mission critical to success.
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Course by
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Self Paced
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9 hours
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English
Health Informatics Technology in Population Healthcare Analytics
Explore health informatics solutions that answer population health challenges.
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Course by
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Self Paced
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100
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English
Healthcare Analytics and Decision Making
Healthcare leaders deal with important challenges that can affect public health. Learn about health informatics solutions and financial systems needed to manage planning, quality assurance, risk management, and evidence-based decision-making.
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Course by
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Self Paced
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45
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English
Introduction to Information Systems for Business
This Specialization is for learners seeking to develop skills in information systems. Through each course, learners will apply knowledge and skills to solve problems in their field (e.g., health informatics, legal, project management, customer experience/marketing, finance).
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Course by
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Self Paced
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English
Healthcare Data Management and Information Systems
This course is the continuation of the Health Informatics for Healthcare Professionals course. If you have not yet taken the introductory course, it is recommend that you complete that course prior to this course. The foundational knowledge from the introduction is carried through in this deeper dive into informatics in healthcare. In this course, you will have an opportunity to explore concepts and topics related to the design and management of health information systems.
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Course by
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Self Paced
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16 hours
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English
Health Informatics
This Specialization is intended for health professionals, administrators, health IT staff, vendors, startups, and patients who need or want to participate in the health IT/informatics process. Throughout the five courses of this Specialization, you will learn about the social and technical context of health informatics problems, how to successfully implement health informatics interventions, how to design a health informatics solution for decision support, and how to answer a health informatics problem through data retrieval and analysis.
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Course by
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Self Paced
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English
The Outcomes and Interventions of Health Informatics
For clinical data science to be effective in healthcare—to achieve the outcomes desired—it must translate into decision support of some sort, either at the patient, clinician, or manager level. By the end of this course, students will be able to articulate the need for an intervention, to right size it, to choose the appropriate technology, to describe how knowledge should be obtained, and to design a monitoring plan.
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Course by
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Self Paced
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7 hours
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English
Culminating Project in Health Informatics
This capstone course in the Health Informatics Specialization will allow learners to create a comprehensive plan for an informatics intervention of their choosing, and that will demonstrate to current or future employers the new skills obtained through the completion of this series of five courses in Health Informatics.
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Course by
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Self Paced
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15 hours
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English
Leading Change in Health Informatics
Do you dream of being a CMIO or a Senior Director of Clinical Informatics? If you are aiming to rise up in the ranks in your health system or looking to pivot your career in the direction of big data and health IT, this course is made for you. You'll hear from experts at Johns Hopkins about their experiences harnessing the power of big data in healthcare, improving EHR adoption, and separating out the hope vs hype when it comes to digital medicine.
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Course by
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Self Paced
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15 hours
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English
The Data Science of Health Informatics
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).
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Course by
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Self Paced
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10 hours
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English