Literature DB >> 23283561

Near real-time notification of gaps in cuff blood pressure recordings for improved patient monitoring.

Bala G Nair1, Mayumi Horibe, Shu-Fang Newman, Wei-Ying Wu, Howard A Schwid.   

Abstract

Blood pressure monitoring during anesthesia is an American Society of Anesthesiology standard. However, the anesthesia provider sometimes fails to engage the patient monitor to make periodic (generally every 3-5 min) measurements of Non-Invasive Blood Pressure (NIBP), which can lead to extended periods (>5 min) when blood pressure is not monitored. We describe a system to automatically detect such gaps in NIBP measurement and notify clinicians in real-time to initiate measurement. We applied a decision support system called the Smart Anesthesia Messenger (SAM) to notify the anesthesia provider if NIBP measurements have not been made in the last 7 min. Notification messages were generated only if direct arterial blood pressure was not being monitored. NIBP gaps were analyzed for 9 months before and after SAM notification was initiated (12,000 cases for each period). SAM notification was able to reduce the occurrence of extended NIBP gaps >15 min from 15.7 ± 4.5 to 6.7 ± 2.0 instances per 1,000 cases (p < 0.001). In addition, for extended gaps (>15 min) the mean gap duration declined from 23.1 ± 2.0 to 18.6 ± 1.1 min after SAM notification was initiated (p < 0.001). However, for 7-15 min gaps, SAM notification was not effective in reducing the occurrence. The maximum gap encountered before SAM was 64 min, while it was 27 min with SAM notification. Real-time notification using SAM is an effective way to reduce both the number of instances and the duration of inadvertent, extended (>15 min) gaps in blood pressure measurements in the operating room. However, the frequency of gaps <15 min could not be reduced using the current configuration of SAM.

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Year:  2013        PMID: 23283561     DOI: 10.1007/s10877-012-9425-2

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


  12 in total

1.  Improving documentation of a beta-blocker quality measure through an anesthesia information management system and real-time notification of documentation errors.

Authors:  Bala G Nair; Gene N Peterson; Shu-Fang Newman; Wei-Ying Wu; Vickie Kolios-Morris; Howard A Schwid
Journal:  Jt Comm J Qual Patient Saf       Date:  2012-06

2.  Feedback mechanisms including real-time electronic alerts to achieve near 100% timely prophylactic antibiotic administration in surgical cases.

Authors:  Bala G Nair; Shu-Fang Newman; Gene N Peterson; Wei-Ying Wu; Howard A Schwid
Journal:  Anesth Analg       Date:  2010-09-14       Impact factor: 5.108

3.  Automated electronic reminders to improve redosing of antibiotics during surgical cases: comparison of two approaches.

Authors:  Bala G Nair; Shu-Fang Newman; Gene N Peterson; Howard A Schwid
Journal:  Surg Infect (Larchmt)       Date:  2010-12-20       Impact factor: 2.150

4.  Automated documentation error detection and notification improves anesthesia billing performance.

Authors:  Stephen F Spring; Warren S Sandberg; Shaji Anupama; John L Walsh; William D Driscoll; Douglas E Raines
Journal:  Anesthesiology       Date:  2007-01       Impact factor: 7.892

5.  Electronic reminders improve procedure documentation compliance and professional fee reimbursement.

Authors:  Sachin Kheterpal; Ruchika Gupta; James M Blum; Kevin K Tremper; Michael O'Reilly; Paul E Kazanjian
Journal:  Anesth Analg       Date:  2007-03       Impact factor: 5.108

Review 6.  The impact of intraoperative monitoring on patient safety.

Authors:  James B Mayfield
Journal:  Anesthesiol Clin       Date:  2006-06

Review 7.  Using real-time clinical decision support to improve performance on perioperative quality and process measures.

Authors:  Anthony Chau; Jesse M Ehrenfeld
Journal:  Anesthesiol Clin       Date:  2011-03

8.  Improving timely surgical antibiotic prophylaxis redosing administration using computerized record prompts.

Authors:  Paul St Jacques; Neal Sanders; Nimesh Patel; Thomas R Talbot; Jayant K Deshpande; Michael Higgins
Journal:  Surg Infect (Larchmt)       Date:  2005       Impact factor: 2.150

9.  Real-time checking of electronic anesthesia records for documentation errors and automatically text messaging clinicians improves quality of documentation.

Authors:  Warren S Sandberg; Elisabeth H Sandberg; Andreas R Seim; Shaji Anupama; Jesse M Ehrenfeld; Stephen F Spring; John L Walsh
Journal:  Anesth Analg       Date:  2008-01       Impact factor: 5.108

Review 10.  Principles and techniques of blood pressure measurement.

Authors:  Thomas G Pickering
Journal:  Cardiol Clin       Date:  2002-05       Impact factor: 2.213

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  4 in total

1.  Intraoperative blood glucose management: impact of a real-time decision support system on adherence to institutional protocol.

Authors:  Bala G Nair; Katherine Grunzweig; Gene N Peterson; Mayumi Horibe; Moni B Neradilek; Shu-Fang Newman; Gail Van Norman; Howard A Schwid; Wei Hao; Irl B Hirsch; E Patchen Dellinger
Journal:  J Clin Monit Comput       Date:  2015-06-12       Impact factor: 2.502

Review 2.  A systematic review of near real-time and point-of-care clinical decision support in anesthesia information management systems.

Authors:  Allan F Simpao; Jonathan M Tan; Arul M Lingappan; Jorge A Gálvez; Sherry E Morgan; Michael A Krall
Journal:  J Clin Monit Comput       Date:  2016-08-16       Impact factor: 2.502

3.  Development and Feasibility of a Real-Time Clinical Decision Support System for Traumatic Brain Injury Anesthesia Care.

Authors:  Taniga Kiatchai; Ashley A Colletti; Vivian H Lyons; Rosemary M Grant; Monica S Vavilala; Bala G Nair
Journal:  Appl Clin Inform       Date:  2017-01-25       Impact factor: 2.342

4.  Influence of non-invasive blood pressure measurement intervals on the occurrence of intra-operative hypotension.

Authors:  Grant H Kruger; Amy Shanks; Sachin Kheterpal; Tyler Tremper; Chi-Jung Chiang; Robert E Freundlich; James M Blum; Albert J Shih; Kevin K Tremper
Journal:  J Clin Monit Comput       Date:  2017-09-30       Impact factor: 2.502

  4 in total

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