Big Ten Academic Alliance Nursing Informatics Collaborative Webinar Series

Big Ten Academic Alliance Nursing Informatics Collaborative Webinar Series

Making EHR Data Actionable for Nursing Research: Practical Guides

Thursday, April 25, 2019, noon-1 p.m. EDT

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In this webinar, University of Minnesota faculty will describe practical approaches for making electronic health record (EHR) data actionable for nursing research. The speakers will introduce resources that are available for accessing big data and share methodological expertise and related research using EHR data. Faculty will provide time for questions and dialogue to promote networking.

Objectives

At the end of this webinar, participants will be able to:

  1. describe two ways to make EHR data actionable for nursing research
  2. discuss ways to overcome educational challenges in EHR data use.

Speakers

Connie White Delaney, PhD, RN, FAAN, FACMI, FNAP, is professor and dean at University of Minnesota School of Nursing. She earned a BSN with majors in nursing and mathematics from Viterbo University and an MA in Nursing and a PhD in Educational Administration and Computer Applications from The University of Iowa. She completed postdoctoral study in nursing and medical informatics at the University of Utah and graduate study in integrative health and healing at the University of Minnesota.    

Karen Monsen, PhD, RN, FAAN, FAMIA, PhD, RN, FAAN, FAMIA, is an associate professor at the University of Minnesota School of Nursing. She earned her PhD and MS degrees from the University of Minnesota School of Nursing, her BSN degree from Creighton University, and her BA in Biology from Luther College.

Lisiane Pruinelli, PhD, RN, is an assistant professor at the University of Minnesota School of Nursing. She earned a PhD degree from the University of Minnesota School of Nursing and an MS and a BSN from the Federal University of Rio Grande do Sul, Brazil.

Continuing Education (CE) for Nurses

Nurses who attend the entire webinar and complete the online evaluation may request and receive a certificate awarding 1 CE. Partial CE is not provided. The request for CE and a completed evaluation must be submitted within 30 days following the event. The University of Maryland School of Nursing is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center’s Commission on Accreditation.

Fees and Registration

The Big Ten Academic Alliance’s Nursing Informatics Collaborative is supporting the full cost of these webinars and awarding CE certificates.

Disclosure

Planning committee members and faculty involved this continuing education activity did not disclose any conflict of interest or financial relationship with a commercial interest that would bias the content of this presentation. This educational activity has not received any form of commercial support.


Free Online Course in Nursing Informatics

The Big Ten Academic Alliance Nursing Informatics Collaborative also offers a free course for faculty who are new to nursing informatics and who are interested in a broad overview of the discipline.

The course integrates various nursing informatics standards into the curriculum and provides examples of methods, tools, and learning resources to teach them. Subjects include:

  • knowledge complexity
  • informatics literacy
  • nursing knowledge work
  • data standards and standardized languages
  • clinical decision support
  • future trends.

The course is a collaborative effort between the University of Minnesota, the Gordon and Betty Moore Foundation, and the American Association of Colleges of Nursing.

Take the Course


Explore the 2017-18 Webinar Series:‌

No. 1: Big Data: What is it and why is it important for nursing?

Date:
March 9, 2017

Speaker:
Thomas R. Clancy, PhD, MBA, RN, FAAN
University of Minnesota School of Nursing

Description:
This webinar provides an overview of data science and its potential benefits to research — specifically nursing research. The presentation begins with differentiating between data analytics, data science, and big data. Next, Dr. Clancy discusses the seven V’s of big data (volume, velocity, variety, veracity, variability, visualization, value) then continues with explicating research approaches and methods used with large, complex data sets.  

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No. 2: Machine Learning in the Age of Health Care Analytics

Date:
April 20, 2017

Speaker:
Warren D’Souza, PhD, MBA, FAAPM
Vice President, Enterprise Data & Analytics
University of Maryland Medical System

Description:
This webinar provides an introduction to machine learning and how it applies to the skill sets and training of data scientists.

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No. 3: Big Data in Small Places

Date:
Oct. 26, 2017

Speaker:
Todd Papke, PhD
Technology Innovations Scientist
School of Nursing
University of Iowa

Description:
This webinar discusses mechanisms for acquiring and organizing large datasets; it covers opportunities and challenges in using big data, including:

  • broadening the research group using mobile applications
  • applying Electronic Health Record (EHR) system data to research
  • identifying available data types
  • understanding requirements for data acquisition.

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*requires download of WebEx player

No. 4: Mining Health Data for Prediction and Pattern Identification

Date:
March 12, 2018

Speaker:
Matthew A. Davis, MPH, PhD
University of Michigan School of Nursing

Description:
There is considerable interest among researchers in the application of new methodologies to mine data for prediction and pattern identification. However, there is often a communication disconnect between health content experts and those who possess the technical knowledge of data mining methods.  The purpose of this seminar is to provide a conceptual overview of popular data mining techniques. In doing so, example applications of the techniques covered to health research will be presented.

Watch Webinar