Literature DB >> 21415437

Automatic notifications mediated by anesthesia information management systems reduce the frequency of prolonged gaps in blood pressure documentation.

Jesse M Ehrenfeld1, Richard H Epstein, Stephen Bader, Sachin Kheterpal, Warren S Sandberg.   

Abstract

BACKGROUND: Arterial blood pressure (BP) measurement at least every 5 minutes is part of the American Society of Anesthesiologists' monitoring standard, but prolonged BP gaps in electronic anesthesia records have been noted. We undertook multicenter studies to determine the frequency of cases with at least 1 interval ≥10 minutes between successive BP measurements and then to ascertain whether educational feedback via an electronic, near real-time notification system alerting providers to the presence of such gaps would reduce their incidence.
METHODS: We evaluated 212,706 electronic anesthesia records from 3 large academic centers. We determined the fraction of cases with ≥10-minute BP monitoring gaps at baseline and did a root cause analysis to determine common causes for these lapses. We then designed and implemented automated systems at 2 of the hospitals to notify point-of-care providers immediately after such 10-minute gaps occurred and determined the subsequent impact of this feedback on BP gap incidence, compared with baseline.
RESULTS: At Hospital A, the notification system reduced the incidence of cases with at least 1 BP gap (1.48%± 0.19% SD vs 0.79% ± 0.36% SD, P < 0.0001). At Hospital B, the gap incidence was not significantly altered when notification was provided after a 10-minute gap had already occurred (2.72% ± 0.60% SD vs 2.45% ± 0.48% SD, P = 0.27), but the incidence was reduced when such notification was provided after 6 minutes without a BP reading (2.72% ± 0.60% SD vs 1.54% ± 0.19% SD, P < 0.0001). At Hospital C, where notification was not implemented, the baseline rate of BP gaps was consistent across the preintervention and follow-up periods (7.03% ± 1.27% SD vs 7.13% ± 0.11% SD, P = 0.74). Although monitors disconnected during position change was the most common identifiable cause of BP gaps, reasons for the missing BP measurements were often not documented. During a week when the electronic charting system was temporarily inoperable, no BP gaps were noted on a convenience sample of 500 paper records from Hospital A (99% upper confidence limit = 0.83%).
CONCLUSIONS: BP gaps of ≥10 minutes were common in electronic anesthesia records, and their incidence was reduced but not eliminated by near real-time feedback to providers. The American Society of Anesthesiologists' standard for BP documentation every 5 minutes might not be achievable with current practices and technology. Anesthesia information management systems users need to be cognizant of the potential for gaps in BP measurement, take steps to minimize their occurrence, and document an explanation when such failures occur.

Entities:  

Mesh:

Year:  2011        PMID: 21415437      PMCID: PMC3121913          DOI: 10.1213/ANE.0b013e31820d95e7

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  24 in total

1.  Arterial blood pressure and heart rate discrepancies between handwritten and computerized anesthesia records.

Authors:  D L Reich; R K Wood; R Mattar; M Krol; D C Adams; S Hossain; C A Bodian
Journal:  Anesth Analg       Date:  2000-09       Impact factor: 5.108

2.  Psychological bulletin.

Authors:  J P FRANKMANN; J A ADAMS
Journal:  Psychol Bull       Date:  1962-07       Impact factor: 17.737

3.  Blood pressure cuff compression injury of the radial nerve.

Authors:  C C Lin; B Jawan; M V de Villa; F C Chen; P P Liu
Journal:  J Clin Anesth       Date:  2001-06       Impact factor: 9.452

4.  Implications of event entry latency on anesthesia information management decision support systems.

Authors:  Richard H Epstein; Franklin Dexter; Jesse M Ehrenfeld; Warren S Sandberg
Journal:  Anesth Analg       Date:  2009-03       Impact factor: 5.108

5.  Automatic updating of times remaining in surgical cases using bayesian analysis of historical case duration data and "instant messaging" updates from anesthesia providers.

Authors:  Franklin Dexter; Richard H Epstein; John D Lee; Johannes Ledolter
Journal:  Anesth Analg       Date:  2009-03       Impact factor: 5.108

6.  Role of monitoring devices in prevention of anesthetic mishaps: a closed claims analysis.

Authors:  J H Tinker; D L Dull; R A Caplan; R J Ward; F W Cheney
Journal:  Anesthesiology       Date:  1989-10       Impact factor: 7.892

Review 7.  Human factors in accidents.

Authors:  M F Allnutt
Journal:  Br J Anaesth       Date:  1987-07       Impact factor: 9.166

8.  Prevention of intraoperative anesthesia accidents and related severe injury through safety monitoring.

Authors:  J H Eichhorn
Journal:  Anesthesiology       Date:  1989-04       Impact factor: 7.892

9.  Compartment syndrome in a patient monitored with an automated blood pressure cuff.

Authors:  G Celoria; J A Dawson; D Teres
Journal:  J Clin Monit       Date:  1987-04

10.  Predictors of pulse oximetry data failure.

Authors:  D L Reich; A Timcenko; C A Bodian; J Kraidin; J Hofman; M DePerio; S N Konstadt; T Kurki; J B Eisenkraft
Journal:  Anesthesiology       Date:  1996-04       Impact factor: 7.892

View more
  14 in total

1.  Documentation and Treatment of Intraoperative Hypotension: Electronic Anesthesia Records versus Paper Anesthesia Records.

Authors:  Torin D Shear; Mark Deshur; Brittany Lapin; Steven B Greenberg; Glenn S Murphy; Joseph Szokol; Michael Ujiki; Rebecca Newmark; Jessica Benson; Cody Koress; Connor Dwyer; Jeffery Vender
Journal:  J Med Syst       Date:  2017-04-11       Impact factor: 4.460

2.  Clinical Decision Support Tools Need to Improve More Than Just Process Outcomes.

Authors:  Robert E Freundlich; Jonathan P Wanderer; Jesse M Ehrenfeld
Journal:  Anesthesiology       Date:  2018-09       Impact factor: 7.892

3.  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

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

Authors:  Bala G Nair; Mayumi Horibe; Shu-Fang Newman; Wei-Ying Wu; Howard A Schwid
Journal:  J Clin Monit Comput       Date:  2013-01-03       Impact factor: 2.502

5.  Innovation & market consolidation among electronic health record vendors: an acute need for regulation.

Authors:  J Wanderer; P Mishra; J Ehrenfeld
Journal:  J Med Syst       Date:  2014-01       Impact factor: 4.460

Review 6.  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

7.  Automated near-real-time clinical performance feedback for anesthesiology residents: one piece of the milestones puzzle.

Authors:  Jesse M Ehrenfeld; Matthew D McEvoy; William R Furman; Dylan Snyder; Warren S Sandberg
Journal:  Anesthesiology       Date:  2014-01       Impact factor: 7.892

8.  Development and implementation of an integrated mobile situational awareness iPhone application VigiVU™ at an academic medical center.

Authors:  Jason S Lane; Warren S Sandberg; Brian Rothman
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-04-07       Impact factor: 2.924

9.  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

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.