Automation

Latest Issue of OR Manager
August 2019

AI, machine learning help unlock health data at Michigan Medicine

Editor's Note The University of Michigan’s health system has 34 artificial intelligence (AI) and machine learning research projects underway, 28 of which have principal investigators, the August 12 Health Data Management reports. Projects include analyzing electronic health records (EHRs), ECG monitor data, and analytics to predict acute hemodynamic instability and…

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By: Judy Mathias
August 14, 2019
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Joint Commission names five hospitals as 2019 Pioneers in Quality Expert Contributors

Editor's Note The Joint Commission on July 24 named five hospitals/healthcare systems as 2019 Pioneers in Quality Expert Contributors for their leadership efforts in using electronic clinical quality measure (eCQM) practices to drive their quality improvement. The five are: Baptist Health (Jacksonville, Florida) Johns Hopkins Health System (Baltimore, Maryland) Memorial…

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By: Judy Mathias
July 25, 2019
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Legal and ethical questions temper excitement about AI--Part 2

As part of a special series on artificial intelligence (AI), OR Manager is taking a deep dive into the many facets of this new technology and its impact on patient care. In this issue we continue our examination of the challenges related to AI, which began in last month’s issue…

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By: Cynthia Saver, MS, RN
July 24, 2019
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Editorial

Our series on artificial intelligence (AI) concludes in this issue with part 2 of an in-depth look at legal and ethical questions (cover story) as well as advice for evaluating new AI products (“Consider all angles when choosing AI technology,” p 13). But insights about future trends like AI do…

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By: Elizabeth Wood
July 24, 2019
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Are you prepared for the OR of the Future?

Innovative technology and surgical procedures, including artificial intelligence, will be explored in depth during the OR Manager Conference, September 18-20 in New Orleans. The new OR of the Future gives attendees a unique opportunity to learn through interactive experiences, educational sessions, and discussions with leading experts: product manufacturers as well…

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By: Cynthia Saver, MS, RN
July 24, 2019
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Consider all angles when choosing AI technology

This article concludes OR Manager’s special series on artificial intelligence (AI). Parts 1 and 2 (May 2019 and June 2019) introduced AI, defining the different types of technology and describing its many current and potential applications for surgery. The series also presented examples of AI (June and July 2019). We…

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By: Cynthia Saver, MS, RN
July 24, 2019
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Applications, limitations of AI for fracture detection, classification

Editor's Note Preliminary experience in the automated detection and classification of fractures using artificial intelligence (AI) shows promise, and AI may enhance processing and communicating probabilistic tasks in orthopedic surgery, this study finds. For fracture detection, researchers compared the human findings in 10 studies with AI findings. In two studies,…

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By: Judy Mathias
July 9, 2019
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Study: EHR data limited in capture of patient outcomes, risk factors needed for risk adjustment

Editor's Note Retooling paper-based measures to electronic format for reporting performance measures can help reduce hospitals’ reporting burden. However, in this study by Joint Commission and State University of New York researchers, a simplified risk model using electronic health record (EHR) elements could not capture most risk factors in the…

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By: Judy Mathias
June 26, 2019
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What if healthcare AI is the next asbestos?

Editor's Note At a precision medicine conference in Boston on June 18, Harvard Law School professor Jonathan Zittrain likened the use of artificial intelligence (AI) in healthcare to asbestos, saying: “it’s all over the place, even though at no point did you explicitly install it, and it has possibly some…

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By: Judy Mathias
June 20, 2019
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New technology tracks blood loss, reduces transfusions

Blood loss during labor and delivery (L&D) and surgical procedures can lead to serious complications that might be prevented with early detection; however, detection can be challenging. For example, clinicians have traditionally estimated blood loss visually—a subjective and often inaccurate process. Humans’ eyes simply aren’t good at making precise measurements,…

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By: Cynthia Saver, MS, RN
June 18, 2019
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