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BMC Health Serv Res ; 20(1): 624, 2020 Jul 08.
Article in English | MEDLINE | ID: mdl-32641031

ABSTRACT

BACKGROUND: Emergency Department (ED) crowding reduces staff satisfaction and healthcare quality and safety, which in turn increase costs. Despite a number of proposed solutions, ED length of stay (LOS) - a main cause of overcrowding - remains a major issue worldwide. This retrospective cohort study was aimed at evaluating the effectiveness on ED LOS of a procedure called "Diagnostic Anticipation" (DA), which consisted in anticipating the ordering of blood tests by nurses, at triage, following a diagnostic algorithm approved by physicians. METHODS: In the second half of 2019, the ED of the University Hospital of Ferrara, Italy, adopted the DA protocol on alternate weeks for all patients with chest pain, abdominal pain, and non-traumatic bleeding. A retrospective cohort study on DA impact was conducted. Using ED electronic data, LOS independent predictors (age, sex, NEDOCS and Priority Color Code, imaging tests, specialistic consultations, hospital admission) were evaluated through multiple regression. RESULTS: During the weeks when DA was adopted, as compared to control weeks, the mean LOS was shorter by 18.2 min for chest pain, but longer by 15.7 min for abdominal pain, and 33.3 for non-traumatic bleeding. At multivariate analysis, adjusting for age, gender, triage priority, specialist consultations, imaging test, hospitalization and ED crowding, the difference in visit time was significant for chest pain only (p < 0.001). CONCLUSIONS: The impact of DA varied by patients' condition, being significant for chest pain only. Further research is needed before the implementation, estimating the potential proportion of inappropriate blood tests and ED crowding status.


Subject(s)
Emergency Service, Hospital/organization & administration , Hematologic Tests/nursing , Length of Stay/statistics & numerical data , Nursing Staff, Hospital/psychology , Triage , Adult , Aged , Crowding , Emergency Service, Hospital/statistics & numerical data , Female , Health Services Research , Hospitals, University , Humans , Italy , Male , Middle Aged , Retrospective Studies , Time Factors
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