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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About this Course
최근 조회 2,929회
배울 내용
Identify opportunities for healthcare informatics interventions.
Apply a structured framework for articulating the components of decision support.
Design knowledge acquisition for decision support.
Outline a health informatics solution for decision support
귀하가 습득할 기술
Knowledge AcquisitionDecision TreeDecision-MakingDecision Support SystemHealth Informatics
강의 계획 - 이 강좌에서 배울 내용
주
1완료하는 데 1시간 필요
Knowing Where to Intervene
In this module, you will be introduced to the course through a range of decision support interventions used in health care. We will examine the Five Rights of decision support and go on to discuss the basics for deciding whether to build an intervention and, having done so, how to evaluate it.
5개 동영상 (총 61분), 1 quiz
5개의 동영상
Should You?11m
Should You? II: HIMSS Framework13m
Does It Work?: Testing8m
Is It Used? Does It Accomplish Goals?7m
1개 연습문제
Module 1 Quiz
주
2완료하는 데 1시간 필요
Defining Decision Support
In this module, we will focus on issues of design, both for decision support and as they apply more broadly across multiple environments.
8개 동영상 (총 47분), 1 quiz
8개의 동영상
Types of Clinical Decision Support7m
Design Phase9m
Define Phase7m
Ideate Phase2m
Prototype Phase2m
Test Phase3m
Deploy Phase9m
1개 연습문제
Module 2 Quiz30m
주
3완료하는 데 2시간 필요
Using Transactional and Summative Data and Knowledge for Decision Support
In this module, we return to decision support, focusing on rules-- the key structure in most decision support. We'll provide a key framework for making sure you have all the minimum components for ensuring a successful implementation. We'll also address issues of languages used by rules and how to keep rules consistent within and between institutions.
7개 동영상 (총 84분), 1 quiz
7개의 동영상
What's in a Rule? Part II10m
The Language of Rules5m
Data Dictionary and Taxonomy14m
Value Sets11m
Semantic Networks14m
Ontology15m
1개 연습문제
Module 3 Quiz30m
주
4완료하는 데 4시간 필요
Eliciting and Creating Knowledge for Decision Support
In this module, we will go behind the scenes of decision support, examining where and how we get the knowledge that drives decision support --including data science-- for generating knowledge from data.
9개 동영상 (총 70분), 2 quizzes
9개의 동영상
Expert Knowledge13m
Decision Support Committee3m
Eliciting Expert Knowledge11m
The Literature13m
Data -- Knowledge7m
Statistical Methods11m
AI Dangers6m
Summary2m
1개 연습문제
Module 4 Quiz35m
4.5
4개의 리뷰The Outcomes and Interventions of Health Informatics의 최상위 리뷰
Learned that there are different ways to input and access information through a system. Also the types of thought processes on how to achieve the outcome.
I enjoyed the class sooooooo much I want to be a Mentor for the class!!
강사
Harold P. Lehmann, MD, Ph.D.
Professor and DirectorDivision of Health Sciences Informatics
Paul Nagy, PhD, FSIIM
Associate Professor of RadiologyDivision of Health Sciences Informatics
존스홉킨스대학교 정보
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.
의료 정보학 전문 분야 정보
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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