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.
Programa especializado Health Information Literacy for Data Analytics
Launch Your Data Science Career in Healthcare. Transfer your data analysis skills to the complex world of healthcare
ofrecido por
Programa especializado Health Information Literacy for Data AnalyticsUniversidad de California, Davis
Acerca de este Programa Especializado
Qué aprenderás
Analyze the various types and sources of healthcare data, including clinical, operational, claims, and patient generated data.
Compare and contrast common data models used in healthcare data systems.
Assess the quality of healthcare data and make appropriate interpretations of meaning according to data sources and intended uses.
Create a data dictionary to communicate the source and value of data.
Habilidades que obtendrás
Data Modelhealthcare terminologyhealthcare data
Cómo funciona Programa Especializado
Toma cursos
Un programa especializado de Coursera es un conjunto de cursos que te ayudan a dominar una aptitud. Para comenzar, inscríbete en el programa especializado directamente o échale un vistazo a sus cursos y elige uno con el que te gustaría comenzar. Al suscribirte a un curso que forme parte de un programa especializado, quedarás suscrito de manera automática al programa especializado completo. Puedes completar solo un curso: puedes pausar tu aprendizaje o cancelar tu suscripción en cualquier momento. Visita el panel principal del estudiante para realizar un seguimiento de tus inscripciones a cursos y tu progreso.
Proyecto práctico
Cada programa especializado incluye un proyecto práctico. Necesitarás completar correctamente el proyecto para completar el programa especializado y obtener tu certificado. Si el programa especializado incluye un curso separado para el proyecto práctico, necesitarás completar cada uno de los otros cursos antes de poder comenzarlo.
Obtén un certificado
Cuando completes todos los cursos y el proyecto práctico, obtendrás un Certificado que puedes compartir con posibles empleadores y tu red profesional.
Hay 4 cursos en este Programa Especializado
Curso1
Healthcare Data Literacy
4.6
5 calificaciones
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.
Curso2
Healthcare Data Models
Career prospects are bright for those qualified to work in healthcare data analytics. Perhaps you work in data analytics, but are considering a move into healthcare where your work can improve people’s quality of life. If so, this course gives you a glimpse into why this work matters, what you’d be doing in this role, and what takes place on the Path to Value where data is gathered from patients at the point of care, moves into data warehouses to be prepared for analysis, then moves along the data pipeline to be transformed into valuable insights that can save lives, reduce costs, to improve healthcare and make it more accessible and affordable. Perhaps you work in healthcare but are considering a transition into a new role. If so, this course will help you see if this career path is one you want to pursue. You’ll get an overview of common data models and their uses. You’ll learn how various systems integrate data, how to ensure clear communication, measure and improve data quality. Data analytics in healthcare serves doctors, clinicians, patients, care providers, and those who carry out the business of improving health outcomes. This course of study will give you a clear picture of data analysis in today’s fast-changing healthcare field and the opportunities it holds for you.
Curso3
Healthcare Data Quality and Governance
Career prospects are bright for those qualified to work with healthcare data or as Health Information Management (HIM) professionals. Perhaps you work in data analytics but are considering a move into healthcare, or you work in healthcare but are considering a transition into a new role. In either case, Healthcare Data Quality and Governance will provide insight into how valuable data assets are protected to maintain data quality. This serves care providers, patients, doctors, clinicians, and those who carry out the business of improving health outcomes.
"Big Data" makes headlines, but that data must be managed to maintain quality. High-quality data is one of the most valuable assets gathered and used by any business. This holds greater significance in healthcare where the maintenance and governance of data quality directly impact people’s lives. This course will explain how data quality is improved and maintained. You’ll learn why data quality matters, then see how healthcare professionals monitor, manage and improve data quality. You’ll see how human and computerized systems interact to sustain data quality through data governance. You’ll discover how to measure data quality with metadata, tracking data provenance, validating and verifying data, along with a communication framework commonly used in healthcare settings.
This knowledge matters because high-quality data will be transformed into valuable insights that can save lives, reduce costs, to improve healthcare and make it more accessible and affordable. You will make yourself more of an asset in the healthcare field by what you gain from this course.
Curso4
Analytical Solutions to Common Healthcare Problems
In this course, we’re going to go over analytical solutions to common healthcare problems. I will review these business problems and you’ll build out various data structures to organize your data. We’ll then explore ways to group data and categorize medical codes into analytical categories. You will then be able to extract, transform, and load data into data structures required for solving medical problems and be able to also harmonize data from multiple sources. Finally, you will create a data dictionary to communicate the source and value of data. Creating these artifacts of data processes is a key skill when working with healthcare data.
Instructores
Brian Paciotti
Healthcare Data ScientistResearch IT
Doug Berman
Director, Data Acquisition and ArchitectureUC Davis Health System
Acerca de Universidad de California, Davis
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.
Preguntas Frecuentes
¿Cuál es la política de reembolsos?
¿Puedo inscribirme en un solo curso?
¡Sí! Para empezar, haz clic en la tarjeta del curso que te interesa e inscríbete. Puedes inscribirte y completar el curso para obtener un certificado que puedes compartir o puedes acceder al curso como oyente para ver los materiales del curso de manera gratuita. Cuando cancelas la suscripción de un curso que forma parte de un programa especializado, se cancela automáticamente la suscripción de todo el programa especializado. Visita el panel del estudiante para realizar un seguimiento de tu progreso.
¿Hay ayuda económica disponible?
¿Puedo tomar este curso de manera gratuita?
¿Este curso es 100 % en línea? ¿Necesito asistir a alguna clase en persona?
Este curso es completamente en línea, de modo que no necesitas ir a un aula en persona. Puedes acceder a tus lecciones, lecturas y tareas en cualquier momento y cualquier lugar a través de Internet o tu dispositivo móvil.
¿Cuánto tiempo se necesita para completar un programa especializado?
Each course was designed to take an average learner one-month to complete, so four months in total.
What background knowledge is necessary?
This Specialization expects that you come in with some data analysis skills already, as we will not be teaching how to analyze data in any specific language. We are helping to build your healthcare data literacy.
Do I need to take the courses in a specific order?
There is no required order, but we do have a recommended order to complete the Specialization.
¿Recibiré crédito universitario por completar el programa especializado?
This Specialization is not eligible for university credit.
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