Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-26T07:22:32.383Z Has data issue: false hasContentIssue false
  • English
  • Français

Prospective time study derivation of emergency physician workload predictors

Published online by Cambridge University Press:  21 May 2015

Grant D. Innes ,
Robert Stenstrom ,
Eric Grafstein  and
James M. Christenson
Grant D. Innes*
Affiliation:
St. Paul's Hospital and the University of British Columbia, Vancouver, BC
Robert Stenstrom
Affiliation:
St. Paul's Hospital and the University of British Columbia, Vancouver, BC
Eric Grafstein
Affiliation:
St. Paul's Hospital and the University of British Columbia, Vancouver, BC
James M. Christenson
Affiliation:
St. Paul's Hospital and the University of British Columbia, Vancouver, BC
*
Department of Emergency Medicine, St. Paul’s Hospital, 1081 Burrard St., Vancouver BC V6Z 1Y6; [email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Background:

A reliable emergency department (ED) workload measurement tool would provide a method of quantifying clinical productivity for performance evaluation and physician incentive programs; it would enable health administrators to measure ED outputs; and it could provide the basis for an equitable formula to estimate ED physician staffing requirements. Our objectives were to identify predictors that correlate with physician time needed to treat patients and to develop a multivariable model to predict physician workload.

Methods:

During 31 day, evening, night and weekend shifts, a research assistant (RA) shadowed 20 emergency physicians, documenting time spent performing clinical and non-clinical functions for 585 patient visits. The RA recorded key predictors including patient gender, age, vital signs and Glasgow Coma Scale (GCS) score, and the mode of arrival, triage level assigned, comorbidity and procedures performed. Multiple linear regression was used to describe the associations between predictor variables and total physician time per patient visit (TPPV), and to derive an equation for physician workload. Model derivation was based on 16 shifts and 314 patient visits; model validation was based on 15 shifts and 271 additional patient visits.

Results:

The strongest predictor variables were: procedure required, triage level, arrival by ambulance, GCS, age, any comorbidity, and number of prior visits. The derived regression equation is: TPPV = 29.7 + 8.6 (procedure required [Yes]) – 3.8 (triage level [1–5]) + 7.1 (ambulance arrival) – 1.1 (GCS [3–15]) + 0.1 (age in years) – 0.05 (n of previous visits) + 3.1 (any comorbidity). This model predicted 31.3% of the variance in physician TPPV (F [12, 29] = 13.2; p < 0.0001).

Conclusions:

This study clarifies important determinants of emergency physician workload. If validated in other settings, the predictive formula derived and internally validated here is a potential alternative to current simplistic models based solely on patient volume and perceived acuity. An evidence-based workload estimation tool like that described here could facilitate ED productivity measurement, benchmarking, physician performance evaluation, and provide the substrate for an equitable formula to estimate ED physician staffing requirements.

Keywords

manpowerworkloademergencyremunerationstaffing
Type
Original Research • Recherche originale
Information
Canadian Journal of Emergency Medicine , Volume 7 , Issue 5 , September 2005 , pp. 299 - 308
Copyright
Copyright © Canadian Association of Emergency Physicians 2005

References

1.British Association for Emergency Medicine. The workforce in emergency medicine. Available: http://www.baem.org.uk/workforce.doc (accessed 2005 July 23).Google Scholar
2.Weinger, MB, Herndon, OW, Zornow, MH, Paulus, MP, Gaba, DM, Dallen, LT. An objective methodology for task analysis and workload assessment in anesthesia providers. Anesthesiology 1994;80:77–92.CrossRefGoogle ScholarPubMed
3.Parshuram, CS, Dhanani, S, Kirsh, JA, Cox, PN. Fellowship training, workload, fatigue and physical stress: a prospective observational study. CMAJ 2004;170:965–70.Google Scholar
4.Orozco, P, Garcia, E. The influence of workload on the mental state of the primary health care physician. Fam Pract 1993;10:277–82.CrossRefGoogle ScholarPubMed
5.NHS Healthcare Commission. Acute hospital portfolio topic guide: accident and emergency — October 2004. Available: http://www.healthcarecommission.org.uk/assetRoot/04/01/48/51/04014851.pdf (accessed 2005 July 22).Google Scholar
6.Beveridge, R, Ducharme, J, Janes, L, Beaulieu, S, Walter, S. Reliability of the Canadian Emergency Department Triage and Acuity Scale: inter-rater agreement. Ann Emerg Med 1999;34:155–9.Google Scholar
7.Fernandes, CM, Wuerz, R, Clark, S, Djurdjev, O. How reliable is emergency department triage? Ann Emerg Med 1999;34:141–7.Google Scholar
8.Graff, LG, Radford, MJ. Formula for emergency physician staffing. Am J Emerg Med 1990;8:194–9.Google Scholar
9.Cohen, J, Cohen, P. Applied multiple regression/correlation analysis for the behavioral sciences. 2nd ed. Hillsdale (NJ): Er-baum and Associates; 1983.Google Scholar
10.Kleinbaum, D, Kupper, L, Muller, K. Applied regression and other multivariable methods. 2nd ed. Boston (MA): PWS-Kent Publishing; 1988.Google Scholar
11.Beveridge, R, Clarke, B, Janes, L, Savage, N, Thompson, J, Dodd, G, et al.Canadian Emergency Department Triage and Acuity Scale: implementation guidelines. Can J Emerg Med 1999;1(3 suppl). Online version available at: http://www.caep.ca/002.policies/002-02.ctas.htm.Google Scholar
12.Chisholm, CD.Collison, EK., Nelson, DR. Cordell, WH. Emergency department workplace interruptions: Are emergency physicians “interruptdriven” and “multitasking”? Acad Emerg Med 2000;7:1239–43.Google Scholar
13.Graff, LG, Wolf, S, Dinwoodie, R, Buono, D, Mucci, D. Emergency physician workload: a time study. Ann Emerg Med 1993; 22:1156–63.CrossRefGoogle ScholarPubMed
14.Bertram, DA, Hershey, CO, Opila, DA, Quirin, O. A measure of physician mental work load in internal medicine ambulatory care clinics. Med Care 1990;28:458–67.Google Scholar
15.Endsley, S, Kirkegaard, M, Baker, G, Murcko, AC. Getting rewards for your results: pay-for-performance programs. Fam Pract Manag 2004;11(3):45–50.Google ScholarPubMed
16.Khan, NS, Simon, HK. Physician productivity — Can it be enhanced without impacting patient satisfaction and turnaround times? [abstract]. Acad Emerg Med 1999;6(5):401.Google Scholar
17.American Academy of Emergency Medicine. Position statement on emergency physician-to-patient ED staffing ratios. 2001 Feb 22. Available: http://www.AAEM.org.Google Scholar