Assessing the impact of streaming in a regional emergency department.
OBJECTIVE
To evaluate the impact of a streaming model, previously validated in metropolitan EDs, on selected performance indicators in a regional ED.


METHODS
Multiple linear regression models were applied to monthly time series data from 43 months prior to the intervention and 15 months following the intervention to measure the impact of the streaming model on the following performance indicators: (i) percentage of emergency patients admitted to an inpatient bed within 8 h; (ii) percentage of non-admitted emergency patients with a length of stay of less than 4 h; and (iii) percentage of emergency patients who left without being seen by a doctor or nurse practitioner.


METHODS
Bendigo Health ED in regional Victoria.


RESULTS
Prior to the introduction of streaming, there was a downward trend in both the percentage of emergency patients admitted to an inpatient bed within 8 h, and the percentage of non-admitted emergency patients with a length of stay of less than 4 h. After the introduction of streaming, these trends were reversed (P = 0.008 and P = 0.004, respectively). There was no statistically significant change in the trend associated with the percentage of emergency patients who left without being seen (P = 0.904).


CONCLUSIONS
The implementation of the streaming model had an impact on the two performance indicators associated with length of stay in this regional ED, but did not have a significant impact (positive or negative) on the percentage of patients who did not wait to be seen. These results might interest other EDs in regional hospitals.
Kinsman
Leigh
L
Monash University School of Rural Health, Bendigo, Victoria, Australia. leigh.kinsman@med.monash.edu.au
Champion
Robert
R
Lee
Geraldine
G
Martin
Mary
M
Masman
Kevin
K
May
Elizabeth
E
Mills
Terry
T
Taylor
Michael D
MD
Thomas
Paulett
P
Williams
Ruth J
RJ
Zalstein
Salomon
S
D004636:Emergency Service, Hospital / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay; D016014:Linear Models; D015233:Models, Statistical; D008962:Models, Theoretical; D010343:Patient Admission / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000706:statistics & numerical data; D013997:Time Factors; D013996:Time and Motion Studies; D014739:Victoria