University of California, Davis
Healthcare Data Quality and Governance
University of California, Davis

Healthcare Data Quality and Governance

This course is part of Health Information Literacy for Data Analytics Specialization

Taught in English

Some content may not be translated

Doug Berman

Instructor: Doug Berman

8,183 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.5

(87 reviews)

Intermediate level
Some related experience required
11 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

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Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.5

(87 reviews)

Intermediate level
Some related experience required
11 hours (approximately)
Flexible schedule
Learn at your own pace

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This course is part of the Health Information Literacy for Data Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

In this module, you will be able to define data quality and what drives it. You'll be able to recall and describe four key aspects of data quality. You'll be able to explain why data quality is important for operations, for patient care, and for the finances of healthcare providers. You'll be able to discuss how data may change over time, and how finding those changes allows us to recognize and work with the issues the changes cause. You will be able to explain why requirements for data quality depend on how we intend to use that data and understand four levels of quality that may be applied for different kinds of analysis. You will also be able to discuss how all of this supports our ability to do our best work in the best ways possible.

What's included

6 videos2 readings1 quiz2 discussion prompts

This module focuses on measuring data quality. After this module, you will be able to describe metadata, list what metadata may include, give some examples of metadata and recall some of its uses as it relates to measuring data quality. We will describe data provenance to explains how knowing the origin of a data set can help data analysts determine if a data set is suitable for a particular use. We’ll also describe 5 components of data quality you can recall and use when evaluating data. You will also learn to be able to distinguish between data verification and validation, recalling 4 applicable data validation methods and 3 concepts useful to validate data. In addition to your video lessons, you will read and discuss a scholarly article on Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. We wrap up the module with a framework abbreviated as S-B-A-R that is often used in healthcare team situations to communicate about issues that must be solved.

What's included

7 videos1 reading1 quiz3 discussion prompts

In this module, we focus on monitoring, managing, and improving data quality. You will be able to explain how to monitor data on a day-to-day basis to see that it remains consistent. You will explain how measures can help us monitor the patient health and the quality of care they receive over time. Also, you will be able to discuss establishing the culture of quality throughout the data lifecycle and improving data quality from the baseline by posing questions to determine a baseline of data quality. You will be able to manage data quality through expected and unexpected changes, along with tracking monitoring strategies along the data pipeline. After this module, you will be able to identify and fix common deficiencies in the data and implement change control systems as a monitoring tool. You’ll also recall several best practices you can apply on the job to monitor data quality in the healthcare field.

What's included

5 videos1 quiz1 discussion prompt

IIn this module, we focus on sustaining quality through data governance. We will define data governance and consider why it matters in healthcare. You will discuss who makes up data governance committees, how these committees function relative to data analysts and describe how stakeholders work together to ensure data quality. You’ll be able to describe how high-quality data is a valuable asset for any business. You will also define data governance systems. You will recall several ways data can be repurposed and explain how data governance maintains data quality as it is repurposed for a use other than that for which it was originally gathered. In addition to your video lessons, you will read and discuss the article, Big Data, Bigger Outcomes and practice applying some of these important concepts.

What's included

6 videos3 readings1 quiz1 peer review1 discussion prompt

Instructor

Instructor ratings
4.8 (24 ratings)
Doug Berman
University of California, Davis
2 Courses12,590 learners

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