This course will help lay the foundation of your healthcare data journey and provide you with knowledge and skills necessary to work in the healthcare industry as a data scientist. Healthcare is unique because it is associated with continually evolving and complex processes associated with health management and medical care. We'll learn about the many facets to consider in healthcare and determine the value and growing need for data analysts in healthcare. We'll learn about the Triple Aim and other data-enabled healthcare drivers. We'll cover different concepts and categories of healthcare data and describe how ontologies and related terms such as taxonomy and terminology organize concepts and facilitate computation. We'll discuss the common clinical representations of data in healthcare systems, including ICD-10, SNOMED, LOINC, drug vocabularies (e.g., RxNorm), and clinical data standards. We’ll discuss the various types of healthcare data and assess the complexity that occurs as you work with pulling in all the different types of data to aid in decisions. We will analyze various types and sources of healthcare data, including clinical, operational claims, and patient generated data as well as differentiate unstructured, semi-structured and structured data within health data contexts. We'll examine the inner workings of data and conceptual harmony offer some solutions to the data integration problem by defining some important concepts, methods, and applications that are important to this domain.
제공자:
Health Information Literacy for Data Analytics 특화 과정캘리포니아 대학교 데이비스 캠퍼스이 강좌에 대하여
제공자:
캘리포니아 대학교 데이비스 캠퍼스
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
강의 계획 - 이 강좌에서 배울 내용
Healthcare 101
In this module, you will be able to identify how biological and social systems are features of human well-being and health. You'll be able to describe important organizations in the US healthcare system and be able to discuss specific examples that document high cost and possible waste in the US healthcare system. You'll be able to identify and discuss the knowing-doing gap and be able to describe evidence-based efforts to transform fragmented care processes into coordinated patient-centered activities.
Concepts and Categories
In this module, you will be able to compare forms of communication and describe why people us ontologies to describe the world. You'll be able to describe the evolution of standardized railroads in the US and recognize why the evolution of railroad tracks also applies to medical terminologies. You'll be able to analyze a dataset with disease codes and also be able to select which codes refer to specific diseases. You'll be able to match different terminologies with different descriptive domains as well as be able to contrast the different ways of organizing information into hierarchies or other categories.
Healthcare Data
In this module, you will be able to identify different types of medical processes and be able to explain why specific data formats emerged from these varied processes. You'll be able to list numerous data types that are found within EHRs and link specific clinical processes that created these outputs. You'll be able to trace why various types of administrative data are collected and describe the value of this data for analytics. You'll be able to identify the common ways that gene sequences are stored in computer readable files and be able to describe how big data formats are different than common relational database technologies that require a lot of data modeling and planning.
Data and Conceptual Harmony
In this module, you will be able to tell leaders and coworkers why they should invest time in creating data dictionaries and other meta-data. You'll be able to describe why one burn registry had data fragmentation issues, and how a variety of standardization and centralization processes helped to achieve data harmony. You'll be able to answer why it is necessary to integrate data, even though the data is coming from disparate sources. You'll be able to perform data mapping as well as communicate the technical terms used to describe and perform record linkages.
검토
HEALTHCARE DATA LITERACY의 최상위 리뷰
This course is well loaded with information that is useful for data scientists (or intending data scientists) in healthcare. The instructor did a wonderful job.
Overall I liked the course. I am giving 4 star due to issue with lack of forum responses. Did not look any TA was assigned to the program.
It was an informative learning experience filled with practical & useful insights in healthcare data systems.
Excellent introduction to the context of USA medical care state of business from politeconomy point of view.
Health Information Literacy for Data Analytics 특화 과정 정보
This Specialization is intended for data and technology professionals with no previous healthcare experience who are seeking an industry change to work with healthcare data. Through four courses, you will identify the types, sources, and challenges of healthcare data along with methods for selecting and preparing data for analysis. You will examine the range of healthcare data sources and compare terminology, including administrative, clinical, insurance claims, patient-reported and external data. You will complete a series of hands-on assignments to model data and to evaluate questions of efficiency and effectiveness in healthcare. This Specialization will prepare you to be able to transform raw healthcare data into actionable information.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
강의 및 과제 이용 권한은 등록 유형에 따라 다릅니다. 청강 모드로 강좌를 수강하면 대부분의 강좌 자료를 무료로 볼 수 있습니다. 채점된 과제를 이용하고 수료증을 받으려면 청강 도중 또는 이후에 수료증 경험을 구매해야 합니다. 청강 옵션이 표시되지 않는 경우:
- 강좌에서 청강 옵션을 제공하지 않을 수 있습니다. 대신 무료 평가판을 사용하거나 재정 지원을 신청할 수 있습니다.
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.
Is financial aid available?
예, Coursera에서는 수업료를 낼 수 없는 학습자를 위해 재정 지원을 제공합니다. 왼쪽에 있는 등록 버튼 아래 재정 지원 링크를 클릭하면 지원할 수 있습니다. 신청서를 작성하라는 메시지가 표시되며 승인되면 알림을 받습니다. 성취 프로젝트를 포함하여 전문 분야의 각 강좌에서 이 단계를 완료해야 합니다. 자세히 알아보기.
강좌를 수료하면 대학 학점을 받을 수 있나요?
이 강좌는 대학 학점을 제공하지 않지만, 일부 대학에서 선택적으로 강좌 수료증을 학점으로 인정할 수도 있습니다. 자세한 내용은 해당 기관에 문의하세요. Coursera의 온라인 학위 및 Mastertrack™ 수료증은 대학 학점을 취득할 기회를 제공합니다.
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