Literature DB >> 24856798

Are anesthesia start and end times randomly distributed? The influence of electronic records.

Litisha G Deal1, Michael E Nyland2, Nikolaus Gravenstein1, Patrick Tighe3.   

Abstract

STUDY
OBJECTIVE: To perform a frequency analysis of start minute digits (SMD) and end minute digits (EMD) taken from the electronic, computer-assisted, and manual anesthesia billing-record systems.
DESIGN: Retrospective cross-sectional review.
SETTING: University medical center. MEASUREMENTS: This cross-sectional review was conducted on billing records from a single healthcare institution over a 15-month period. A total of 30,738 cases were analyzed. For each record, the start time and end time were recorded. Distributions of SMD and EMD were tested against the null hypothesis of a frequency distribution equivalently spread between zero and nine. MAIN
RESULTS: SMD and EMD aggregate distributions each differed from equivalency (P < 0.0001). When stratified by type of anesthetic record, no differences were found between the recorded and expected equivalent distribution patterns for electronic anesthesia records for start minute (P < 0.98) or end minute (P < 0.55). Manual and computer-assisted records maintained nonequivalent distribution patterns for SMD and EMD (P < 0.0001 for each comparison). Comparison of cumulative distributions between SMD and EMD distributions suggested a significant difference between the two patterns (P < 0.0001).
CONCLUSION: An electronic anesthesia record system, with automated time capture of events verified by the user, produces a more unified distribution of billing times than do more traditional methods of entering billing times.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Anesthesia billing; Anesthesia procedure start times; Electronic anesthesia record; End minute digit; Procedure timekeeping; Start minute digit

Mesh:

Year:  2014        PMID: 24856798      PMCID: PMC4099295          DOI: 10.1016/j.jclinane.2013.10.016

Source DB:  PubMed          Journal:  J Clin Anesth        ISSN: 0952-8180            Impact factor:   9.452


  22 in total

1.  Quality of age data in patients from developing countries.

Authors:  Srdjan Denic; Falah Khatib; Hussein Saadi
Journal:  J Public Health (Oxf)       Date:  2004-06       Impact factor: 2.341

Review 2.  Anesthesia information management systems: past, present, and future of anesthesia records.

Authors:  Bassam Kadry; William W Feaster; Alex Macario; Jesse M Ehrenfeld
Journal:  Mt Sinai J Med       Date:  2012 Jan-Feb

3.  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

Review 4.  Anatomy of an anesthesia information management system.

Authors:  Nirav J Shah; Kevin K Tremper; Sachin Kheterpal
Journal:  Anesthesiol Clin       Date:  2011-09

5.  Defining measurable OR-PR scheduling, efficiency, and utilization data elements: the Association of Anesthesia Clinical Directors procedural times glossary.

Authors:  R T Donham
Journal:  Int Anesthesiol Clin       Date:  1998

6.  Observer error and birthweight: digit preference in recording.

Authors:  L Edouard; A Senthilselvan
Journal:  Public Health       Date:  1997-03       Impact factor: 2.427

7.  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

8.  Are automated anesthesia records better?

Authors:  D N Thrush
Journal:  J Clin Anesth       Date:  1992 Sep-Oct       Impact factor: 9.452

9.  Decreases in anesthesia-controlled time cannot permit one additional surgical operation to be reliably scheduled during the workday.

Authors:  F Dexter; S Coffin; J H Tinker
Journal:  Anesth Analg       Date:  1995-12       Impact factor: 5.108

10.  The Visual Analog rating Scale of health-related quality of life: an examination of end-digit preferences.

Authors:  Amir Shmueli
Journal:  Health Qual Life Outcomes       Date:  2005-11-14       Impact factor: 3.186

View more
  3 in total

1.  A retrospective evaluation of the risk of bias in perioperative temperature metrics.

Authors:  Robert E Freundlich; Sara E Nelson; Yuxuan Qiu; Jesse M Ehrenfeld; Warren S Sandberg; Jonathan P Wanderer
Journal:  J Clin Monit Comput       Date:  2018-12-08       Impact factor: 2.502

2.  Comparison of minute distribution frequency for anesthesia start and end times from an anesthesia information management system and paper records.

Authors:  Michael Phelps; Asad Latif; Robert Thomsen; Martin Slodzinski; Rahul Raghavan; Sharon Leigh Paul; Jerry Stonemetz
Journal:  J Clin Monit Comput       Date:  2016-06-07       Impact factor: 2.502

Review 3.  Timing errors and temporal uncertainty in clinical databases-A narrative review.

Authors:  Andrew J Goodwin; Danny Eytan; William Dixon; Sebastian D Goodfellow; Zakary Doherty; Robert W Greer; Alistair McEwan; Mark Tracy; Peter C Laussen; Azadeh Assadi; Mjaye Mazwi
Journal:  Front Digit Health       Date:  2022-08-18
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.