Literature DB >> 24838488

The use of a clinical database in an anesthesia unit: focus on its limits.

Grégoire Weil1, Cyrus Motamed, Alexandre Eghiaian, Marie Laurence Guye, Jean Louis Bourgain.   

Abstract

Anesthesia information management system (AIMS) can be used a part of quality assurance program to improve patient care, however erroneous or missing data entries may lead to misinterpretation. This study assesses the accuracy of information extracted for six consecutive years from a database linked to an automatic anesthesia record-keeping system. An observational study was conducted on a database linked AIMS system. The database was filled in real time during surgical/anesthesia procedure and in the post-anesthesia care unit. The following items: name of the anesthetist, duration of anesthesia, duration of monitoring, ventilatory status upon arrival in postoperative care unit, pain scores, nausea and vomiting scores, pain medication (morphine) and anti nausea and vomiting drug consumption (ondansetron) were extracted and analysed in order to determine exhaustivity (percentage of missing data) and accuracy of the database. The analysis covered 55,946 anaesthetic procedures. The rate of missing data was initially high upon installation but decreased over time. It was limited to 5% after 3 years for items such as start of anesthesia or name of the anesthetist. However exhaustivity/completeness of some other variable, such as nausea and vomiting started as low as 50% to reach 20% at 2008. After cross analysing pain and post-operative nausea and vomiting scores with related medication consumption, (morphine and ondansetron) we conclude that missing data was due to omission of a zero score rather than human error. The follow-up of quality assurance program may use data from AIMS provided that missing or erroneous values be mentioned and their impact on calculations accurately analysed.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 24838488     DOI: 10.1007/s10877-014-9581-7

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


  12 in total

1.  Building a large-scale perioperative anaesthesia outcome-tracking database: methodology, implementation, and experiences from one provider within the German quality project.

Authors:  U Bothner; M Georgieff; B Schwilk
Journal:  Br J Anaesth       Date:  2000-08       Impact factor: 9.166

2.  User acceptance of an anaesthesia information management system.

Authors:  L Quinzio; A Junger; B Gottwald; M Benson; B Hartmann; A Jost; A Banzhaf; G Hempelmann
Journal:  Eur J Anaesthesiol       Date:  2003-12       Impact factor: 4.330

3.  Changing medical group behaviors: increasing the rate of documentation of quality assurance events using an anesthesia information system.

Authors:  Michael M Vigoda; Frank Gencorelli; David A Lubarsky
Journal:  Anesth Analg       Date:  2006-08       Impact factor: 5.108

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.  [Impact of a quality assurance program on the use of neuromuscular monitoring and reversal of muscle relaxants].

Authors:  C Motamed; J-L Bourgain
Journal:  Ann Fr Anesth Reanim       Date:  2009-03-21

6.  The Diatek Arkive "Organizer" patient information management system: experience at a university hospital.

Authors:  F E Block; K M Reynolds; J S McDonald
Journal:  J Clin Monit Comput       Date:  1998-02       Impact factor: 2.502

7.  Detection of intraoperative incidents by electronic scanning of computerized anesthesia records. Comparison with voluntary reporting.

Authors:  K V Sanborn; J Castro; M Kuroda; D M Thys
Journal:  Anesthesiology       Date:  1996-11       Impact factor: 7.892

8.  Time of day effects on the incidence of anesthetic adverse events.

Authors:  M C Wright; B Phillips-Bute; J B Mark; M Stafford-Smith; K P Grichnik; B C Andregg; J M Taekman
Journal:  Qual Saf Health Care       Date:  2006-08

9.  The anesthetic record: accuracy and completeness.

Authors:  J H Devitt; T Rapanos; M Kurrek; M M Cohen; M Shaw
Journal:  Can J Anaesth       Date:  1999-02       Impact factor: 5.063

10.  Data recording of problems during anaesthesia: presentation of a well-functioning and simple system.

Authors:  S Fasting; S E Gisvold
Journal:  Acta Anaesthesiol Scand       Date:  1996-11       Impact factor: 2.105

View more
  3 in total

1.  A substitution method to improve completeness of events documentation in anesthesia records.

Authors:  Antoine Lamer; Julien De Jonckheere; Romaric Marcilly; Benoît Tavernier; Benoît Vallet; Mathieu Jeanne; Régis Logier
Journal:  J Clin Monit Comput       Date:  2015-01-30       Impact factor: 2.502

2.  Assessment of the time-dependent need for stay in a high dependency unit (HDU) after major surgery by using data from an anesthesia information management system.

Authors:  Jan Betten; Aleksander Kirkerud Roness; Birger Henning Endreseth; Håkon Trønnes; Stig Sverre Tyvold; Pål Klepstad; Trond Nordseth
Journal:  J Clin Monit Comput       Date:  2015-05-27       Impact factor: 2.502

3.  Pain after Interventional Radiology in Oncology: A Case-Control Study from a 5-Year Cohort.

Authors:  Narimane Ayaden; Philippe Sitbon; Arnaud Pages; Lambros Tselikas; Jean-Louis Bourgain
Journal:  Cancers (Basel)       Date:  2022-05-24       Impact factor: 6.575

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.