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APPLICATIONS OF CONTROL CHARTS FOR QUALITY IMPROVEMENT IN HEALTH CARE
Conditional Remix & Share Permitted
CC BY-NC-SA
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This textbook introduces students to the application methods of control charts to improve quality in health care. The textbook is written to be accessible to any student in the areas of health information management, health care informatics, and health care industrial engineering. Having a basic background in statistics would be beneficial, but such training is not a prerequisite to understanding how to apply the techniques discussed here.  Several How-To sections are included to demonstrate the implementation of the given control charts using software such as Minitab and Excel.  Additionally, samples of a Python code are included and can directly be accessed in a Jupyter Notebook at https://github.com/JeromeNN/Applications-Control-Charts-Quality-Improvement-Health-Care 

Subject:
Health, Medicine and Nursing
Material Type:
Textbook
Author:
Jerome Niyirora
Date Added:
02/26/2020
BASIC TOOLS FOR QUALITY IMPROVEMENT IN HEALTH CARE INFORMATICS
Conditional Remix & Share Permitted
CC BY-NC-SA
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This textbook introduces students to the essential tools of quality improvement. The emphasis is placed on health care informatics, as reflected in the several examples contained in the text. The book is written to be accessible to any student in the areas of health information management, health care informatics, and health care industrial engineering. Although having some statistical background would be a plus, such knowledge is not a prerequisite to understanding and applying the tools presented here.  Several How-To sections are included to demonstrate the hands-on implementation of the discussed concepts using software such as Minitab, Visio, and Excel.

Subject:
Health, Medicine and Nursing
Material Type:
Lecture Notes
Textbook
Author:
Jerome Niyirora
Date Added:
02/26/2020
Delivering Healthcare Part 1
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CC BY-NC-SA
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This unit depicts the medical model of healthcare in the US, with an overview of the organization of healthcare and the physical structure of healthcare delivery in the outpatient, inpatient and long-term care settings, including an overview of the organization of the Veterans Affairs (VA) system. This unit is intended primarily for the student who does not have a background in healthcare, though the topics of this unit will be described at a relatively advanced level.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Lecture
Provider:
Open Michigan
Author:
Oregon Health & Science University
Date Added:
09/26/2014
Ethics and Professionalism
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CC BY-NC-SA
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This unit describes the traditions and values that guide physicians, nurses, and allied health professionals. It explores medical ethics, professionalism and legal duties and applies ethics and professionalism to specific topics, including health informatics.

Subject:
Applied Science
General Law
Health, Medicine and Nursing
Law
Material Type:
Lecture
Provider:
Open Michigan
Provider Set:
Health IT Workforce Curriculum
Author:
Oregon Health & Science University
Date Added:
09/26/2014
FHIR Fundamentals
Only Sharing Permitted
CC BY-NC-ND
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This course provides a comprehensive review of interoperability, health data standards, and other advanced topics including Substitutable Medical Applications, Reusable Technologies (SMART) and Fast Healthcare Interoperability Resources® (FHIR), also known as SMART-on-FHIR applications and Accelerator projects. This course will use Interoperability Land™ to provide learners with a hands-on experience using FHIR resources. Upon successful completion of this course, learners will be able to: explain interoperability and use cases; locate information within JSON and XML files; Create queries in IOL; understand SMART application authorization. Interoperability Land can be purchased on AWS Marketplace at the followinglink: https://aws.amazon.com/marketplace/pp/prodview-f34r2uj3naohe For information regarding education pricing please email contactus@interoperabilityinstitute.org.

Subject:
Health, Medicine and Nursing
Information Science
Material Type:
Activity/Lab
Diagram/Illustration
Full Course
Lesson Plan
Reading
Student Guide
Author:
Interoperability Institute
Date Added:
08/24/2021
Introduction and History of Modern Healthcare in the US
Conditional Remix & Share Permitted
CC BY-NC-SA
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This introductory unit covers definitions of terms used in the component, with an emphasis on paradigm shifts in healthcare, including the transition from physician-centric to patient-centric care, the transition from individual care to interdisciplinary team-based care, and the central role of technology in healthcare delivery. This unit also emphasizes the core values in US healthcare.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Lecture
Provider:
Open Michigan
Author:
Oregon Health & Science University
Date Added:
09/26/2014
Measuring Human Rights: High School Mathematics Unit
Unrestricted Use
CC BY
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In this unit, students will read and interpret primary sources to address the question “How do we measure the attainment of human rights?” By exploring the Universal Declaration of Human Rights, the UN’s Guide to Indicators of Human Rights, and data about development indicators from multiple databases, students will unpack the complexities of using indicators to measure human rights.

Subject:
Mathematics
Material Type:
Assessment
Lesson Plan
Date Added:
11/21/2014
Prying open AI’s black box reveals insights into why cancers recur
Unrestricted Use
CC BY
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Artificial intelligence is making rapid advances in medicine. Already, there are machine learning algorithms that can outperform doctors in some medical fields. There’s only one fairly big problem: experts aren’t quite sure how these algorithms work. While designers know full well what goes into the A-I systems they build and what comes out, the learning part in between is often too complex to comprehend. To their users, machine learning algorithms are effectively black boxes. Now, researchers from the RIKEN Center for Advanced Intelligence Project in Japan are lifting the lid. They’ve developed a deep-learning system that can outperform human experts in predicting whether prostate cancer will reoccur within one year. More importantly, the deep learning system they developed can acquire human-understandable features from unannotated pathology images to offer up critical clues that could help humans make better diagnoses themselves..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/23/2020