Literature DB >> 31813832

Making Sense of Big Data to Improve Perioperative Care: Learning Health Systems and the Multicenter Perioperative Outcomes Group.

Michael R Mathis1, Timur Z Dubovoy2, Matthew D Caldwell2, Milo C Engoren2.   

Abstract

Mesh：

Year:  2019        PMID： 31813832     DOI： 10.1053/j.jvca.2019.11.012

Source DB:  PubMed          Journal:  J Cardiothorac Vasc Anesth        ISSN： 1053-0770            Impact factor:   2.628


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  5 in total

1.  Prevalence of aberrant blood pressure readings across two automated intraoperative blood pressure monitoring systems among patients undergoing caesarean delivery.

Authors:  Robert B Schonberger; Antonio Gonzalez-Fiol; Kristen L Fardelmann; Amit Bardia; George Michel; Feng Dai; Trevor Banack; Aymen Alian
Journal:  Blood Press Monit       Date:  2021-02-01       Impact factor: 1.444

2.  Variation in propofol induction doses administered to surgical patients over age 65.

Authors:  Robert B Schonberger; Amit Bardia; Feng Dai; George Michel; David Yanez; Jeptha P Curtis; Michelle T Vaughn; Matthew M Burg; Michael Mathis; Sachin Kheterpal; Shamsuddin Akhtar; Nirav Shah
Journal:  J Am Geriatr Soc       Date:  2021-03-31       Impact factor: 7.538

3.  Clarifying the concept of a learning health system for healthcare delivery organizations: Implications from a qualitative analysis of the scientific literature.

Authors:  Douglas Easterling; Anna C Perry; Rachel Woodside; Tanha Patel; Sabina B Gesell
Journal:  Learn Health Syst       Date:  2021-07-22

4.  Observation on the Effect of Intelligent Machine-Assisted Surgery and Perioperative Nursing.

Authors:  Liping Lei
Journal:  J Healthc Eng       Date:  2022-03-21       Impact factor: 2.682

Review 5.  The learning health system for pediatric nephrology: building better systems to improve health.

Authors:  Charles D Varnell; Peter Margolis; Jens Goebel; David K Hooper
Journal:  Pediatr Nephrol       Date:  2022-04-20       Impact factor: 3.651
  5 in total

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