Approach to decreasing emergency department ambulance diversion hours

Vilke, Gary M.; Brown, Lana; Skogland, Patty; Simmons, Charles R.; Guss, David A.

doi:10.1016/j.jemermed.2003.07.003

Cited by 43 publications

(32 citation statements)

References 8 publications

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“…EMERGENCY DEPARTMENT (ED) OVERCROWDING is a growing problem in Australia and around the world. [1][2][3] Current understanding is that it is a complex interaction of hospital, ED, patient and ambulance factors. The results can be longer waiting times for patients, increased episodes of ambulance bypass, patients spending long periods "boarding" in the ED awaiting ward beds, and increased clinical risk.…”

Section: Resultsmentioning

confidence: 99%

Improving emergency department efficiency by patient streaming to outcomes-based teams

Kelly¹,

Bryant²,

Jolley³

2007

Aust. Health Review

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Objective: To describe the process and results of a process redesign based on task analysis and lean thinking approaches aimed at improving emergency department (ED) efficiency.Methods: Before-and-after study comparing 12-month periods before and after the process redesign for total episodes of ambulance bypass, waiting times (overall and by triage category) and total ED time (overall and by triage category). Time data were analysed using non-parametric methods. Results:The years were broadly comparable, with the exception that there was an 8.4% increase in total hours of care delivered (a marker of ED workload) in the year after the change. Episodes of ambulance bypass reduced by 55% (120 v 54). There were statistically significant waiting times reductions for triage categories 3 and 5 (median reductions 5 and 11 minutes respectively). There was an increase in total ED time for triage category 3 (median increase 7 min) and a decrease for categories 4 and 5 (median reduction 14 and 18 min, respectively). EMERGENCY DEPARTMENT (ED) OVERCROWDING is a growing problem in Australia and around the world. 1-3 Current understanding is that it is a complex interaction of hospital, ED, patient and ambulance factors. The results can be longer waiting times for patients, increased episodes of ambulance bypass, patients spending long periods "boarding" in the ED awaiting ward beds, and increased clinical risk. [4][5][6][7][8] Access block (shortage of available hospital beds to accommodate emergency patients requiring admission) seems to be the major contributor to ED overcrowding, 1,9,10 and a lot of work has been going into hospital systems to better manage beds. That said, there might be processes within EDs that also contribute to overcrowding. ConclusionThe aim of this project was to analyse ED patient flow processes using a task analysis and lean thinking approach, 11 and re-engineer these processes to improve flow through the ED for all groups of patients. MethodsThis project was undertaken in the ED of Western Hospital, a 300-bed, community teaching hospital in Melbourne, Australia. The ED treats adult patients only and has an annual census of about 32 000. It has two adjacent but separate treatment zones and 26 treatment spaces. It is staffed by a mixture of emergency physicians, registrars in training and other junior medical officers. Indicative admission rates by triage category for the study hospital are National Triage Scale (NTS) 1, 46%; NTS 2, 44%; NTS 3, 32%; NTS 4, 16% and NTS 5, 6%. The project had three main steps: patient flow and task a na lysis using lea n thinking approaches, 11 process redesign, and implementation and evaluation.

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Section: Resultsmentioning

confidence: 99%

Improving emergency department efficiency by patient streaming to outcomes-based teams

Kelly¹,

Bryant²,

Jolley³

2007

Aust. Health Review

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“…Much of the current research on ED staffing involves the addition or modification of duties of physician, nurses, and/or clerical staff to increase patient flow. [6][7][8][9][10][11][12] The addition of physician staff in these studies was typically during periods of increased patient arrivals (i.e., evening shifts) in the ED. However, little or no analysis was presented to justify the allocation of the new staff or the current schedule of physicians.…”

Section: Ré Sumémentioning

confidence: 99%

Developing emergency department physician shift schedules optimized to meet patient demand

Savage

Woolford

Weaver

et al. 2015

CJEM

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Objectives: 1) To assess temporal patterns in historical patient arrival rates in an emergency department (ED) to determine the appropriate number of shift schedules in an acute care area and a fast-track clinic and 2) to determine whether physician scheduling can be improved by aligning physician productivity with patient arrivals using an optimization planning model. Methods: Historical data were statistically analyzed to determine whether the number of patients arriving at the ED varied by weekday, weekend, or holiday weekend. Poisson-based generalized additive models were used to develop models of patient arrival rate throughout the day. A mathematical programming model was used to produce an optimal ED shift schedule for the estimated patient arrival rates. We compared the current physician schedule to three other scheduling scenarios: 1) a revised schedule produced by the planning model, 2) the revised schedule with an additional acute care physician, and 3) the revised schedule with an additional fast-track clinic physician. Results: Statistical modelling found that patient arrival rates were different for acute care versus fast-track clinics; the patterns in arrivals followed essentially the same daily pattern in the acute care area; and arrival patterns differed on weekdays versus weekends in the fast-track clinic. The planning model reduced the unmet patient demand (i.e., the average number of patients arriving at the ED beyond the average physician productivity) by 19%, 39%, and 69% for the three scenarios examined. Conclusions: The planning model improved the shift schedules by aligning physician productivity with patient arrivals at the ED.

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“…This can create a domino effect impacting other hospitals nearby or, if there are no other hospitals to receive the patients, forcing the original hospital to accept more patients until it again gets impacted and goes back onto bypass. The cycle continues ad infinitum [8]. During this time of diversion, the hospital is receiving its own patients as well as patients who originally had requested another hospital as a destination.…”

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confidence: 99%

“…And so the oscillating cycle continues, even leading to defensive ambulance diversion, where the second hospital, though not at saturation status, would go on diversion when hearing that the first hospital just went on diversion. After observing the oscillatory phenomenon, two hospitals that collaborated and committed to staying off ambulance diversion for a week were able to demonstrate that this oscillating effect goes away, patients get to the "right" hospital the first time, and still all of the patients get seen without any detriment to patient care [8].…”

mentioning

confidence: 99%