The impact of a multimodal intervention on emergency department crowding and patient flow

M C Christien van der Linden; H M E Jet van Ufford; Project Group Medical Specialists; N Naomi van der Linden

doi:10.1186/s12245-019-0238-7

The impact of a multimodal intervention on emergency department crowding and patient flow

Int J Emerg Med. 2019 Aug 27;12(1):21. doi: 10.1186/s12245-019-0238-7.

Authors

M C Christien van der Linden¹, H M E Jet van Ufford²; Project Group Medical Specialists; N Naomi van der Linden³

Collaborators

Project Group Medical Specialists:
Roeline A Y de Beaufort, Robert W Grauss, Herman M A Hofstee, Jochem M Hoogendoorn, Sven A G Meylaerts, Roselyne M Rijsman, Theo P W de Rooij, Christiaan Smith, Frans J de Voeght, Olga J G Warffemius, Geesje van Woerden

Affiliations

¹ Haaglanden Medical Center (HMC), P.O. Box 432, 2501 CK, The Hague, the Netherlands.
² HMC, P.O. Box 432, 2501 CK, The Hague, the Netherlands.
³ Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, the Netherlands. naomivanderlinden@gmail.com.

Abstract

Objective: The objective of this study is to assess the impact of a multimodal intervention on emergency department (ED) crowding and patient flow in a Dutch level 1 trauma center.

Methods: In this cross-sectional study, we compare ED crowding and patient flow between a 9-month pre-intervention period and a 9-month intervention period, during peak hours and overall (24/7). The multimodal intervention included (1) adding an emergency nurse practitioner (ENP) and (2) five medical specialists during peak hours to the 24/7 available emergency physicians (EPs), (3) a Lean programme to improve radiology turnaround times, and (4) extending the admission offices' openings hours. Crowding is measured with the modified National ED OverCrowding Score (mNEDOCS). Furthermore, radiology turnaround times, patients' length of stay (LOS), proportion of patients leaving without being seen (LWBS) by a medical provider, and unscheduled representations are assessed.

Results: The number of ED visits were grossly similar in the two periods during peak hours (15,558 ED visits in the pre-intervention period and 15,550 in the intervention period) and overall (31,891 ED visits in the pre-intervention period vs. 32,121 in the intervention period). During peak hours, ED crowding fell from 18.6% (pre-intervention period) to 3.5% (intervention period), radiology turnaround times decreased from an average of 91 min (interquartile range 45-256 min) to 50 min (IQR 30-106 min., p < 0.001) and LOS reduced with 13 min per patient from 167 to 154 min (p < 0.001). For surgery, neurology and cardiology patients, LOS reduced significantly (with 17 min, 25 min, and 8 min. respectively), while not changing for internal medicine patients. Overall, crowding, radiology turnaround times and LOS also decreased. Less patients LWBS in the intervention period (270 patients vs. 348 patients, p < 0.001) and less patients represented unscheduled within 1 week after the initial ED visit: 864 (2.7%) in the pre-intervention period vs. 645 (2.0%) patients in the intervention period, p < 0.001.

Conclusions: In this hospital, a multimodal intervention successfully reduces crowding, radiology turnaround times, patients' LOS, number of patients LWBS and the number of unscheduled return visits, suggesting improved ED processes. Further research is required on total costs of care and long-term effects.

Keywords: Crowding; Emergency department; Nurse practitioner; Patient flow; Quality of healthcare; Staffing.