Literature DB >> 11901325

Evaluation of staff workload during resuscitation of trauma patients.

Mu-Shun Huang1, Yun-Fu Yang, Chen-Hsen Lee.   

Abstract

OBJECTIVE: Evaluating the medical staff workload during resuscitation of trauma patients is one of the important quality assurance activities to provide adequate medical manpower, especially for patients with life-threatening or severe injuries. Nevertheless, there is no method available to measure and calculate the amount of workload during resuscitation. We sought to develop a new framework of Workload Scoring System (WSS) to evaluate and quantify the medical staff workload during resuscitation.
METHODS: From July 1996 to July 1998, the records of 11,800 trauma patients were prospectively collected from our computer-stored medical record system. The Workload Scoring System points with reference to age, different triage category on the basis of triage version of the Revised Trauma Score (RTS), level category on the basis of Injury Severity Score (ISS), and Abbreviated Injury Scale (AIS) in six body regions were calculated to survey the medical staff workload.
RESULTS: The WSS points were 18.51 +/- 0.80 for triage I, 11.88 +/- 0.17 for triage II, and 6.90 +/- 0.04 for triage III trauma patients. The WSS points were 23.10 +/- 0.67 for Level I, 20.34 +/- 0.25 for Level II, 12.87 +/- 0.08 for Level III, and 6.03 +/- 0.02 for Level IV trauma patients. There were statistically significant differences among triage I, II, and III trauma patients, and among Level I, II, III, and IV trauma patients (p < 0.01). The worse the physiologic status and the greater the anatomic damage, the more medical staff workload was needed. Multiple regression with linear model may predict WSS points as an equation of -8.920 + 1.375 ISS + 1.785 RTS + 0.424 Age (r2 = 0.621), which accounts for 62.1% of the variance in WSS points.
CONCLUSION: WSS provides a valuable tool to measure and quantify the medical staff workload during resuscitation as a function of -8.920 + 1.375 ISS + 1.785 RTS + 0.424 Age. The greatest benefit of this methodology is to forecast the expected medical staff workload to allocate sufficient medical manpower to provide the desired trauma care.

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Year:  2002        PMID: 11901325     DOI: 10.1097/00005373-200203000-00013

Source DB:  PubMed          Journal:  J Trauma        ISSN: 0022-5282


  3 in total

1.  A new approach to the analysis of multiple injuries using data from a national trauma registry.

Authors:  L Aharonson-Daniel; V Boyko; A Ziv; M Avitzour; K Peleg
Journal:  Inj Prev       Date:  2003-06       Impact factor: 2.399

2.  Treatment provider is most predictive of ED dismissal in minimally-injured trauma patients: a retrospective review.

Authors:  Diane L S Hunt; Gina M Berg; Rosalee E Zackula; Francie H Ekengren; Diana Lippoldt; Elizabeth Ablah; Ruth Wetta
Journal:  J Trauma Manag Outcomes       Date:  2013-05-16

3.  Studying the Variability in Patient Inflow and Staffing Trends on Sundays versus Other Days in the Academic Emergency Department.

Authors:  K T Madavan Nambiar; Nisanth Menon Nedungalaparambil; Ottapura Prabhakaran Aslesh
Journal:  J Emerg Trauma Shock       Date:  2017 Jul-Sep
  3 in total

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