Background: The waiting time (WT) for a phlebotomy is directly related to patient satisfaction with a health service. However, the processing time varies widely depending on the type of patients. Monitoring of the WT alone may not enable an effective evaluation of the lean performance of the medical staff for patients with different characteristics. The objective of this study was to use process cycle efficiency (PCE) to assess the performance of an intelligent tube preparation system (ITPS) which automatically labeled test tubes and conducted patient rerouting for phlebotomy services, and to interpret the WT during peak hours. Methods: Three time periods were used. The baseline period was from 1 July to 31 July 2014. Phase 1 was after the establishment of the ITPS, with patients ≥80 years old being rerouted. In phase 2, patients ≥78 years old were rerouted. Those data were recorded with a calling system and ITPS, respectively. Results: PCE was significantly improved from 12.9% at baseline to 51.1% (p < 0.001) in phase 1 and 53.0% (p < 0.001) in phase 2. The WT of 16.9 min at baseline was reduced to 3.8 min in phase 1 (p < 0.001), and 3.6 min in phase 2 (p < 0.001). Moreover, the results showed that a WT < 10 min was consistent with a PCE ≥ 25%. Conclusions: Establishing an ITPS for phlebotomy can significantly increase PCE and shorten the WT. Furthermore, the PCE ≥ 25% could be a good assessment reference for the management of appropriate human resources for phlebotomy services, although it is a complex parameter.
We investigated factors associated with postoperative lipiduria and hypoxemia in patients undergoing surgery for orthopedic fractures. We enrolled patients who presented to our emergency department due to traumatic fractures between 2016 and 2017. We collected urine samples within 24 h after the patients had undergone surgery to determine the presence of lipiduria. Hypoxemia was defined as an SpO2 <95% determined with a pulse oximeter during the hospitalization. Patients’ anthropometric data, medical history, and laboratory test results were collected from the electronic medical record. Logistic regression analyses were used to determine the associations of clinical factors with postoperative lipiduria and hypoxemia with multivariate adjustments. A total of 144 patients were analyzed (mean age 51.3 ± 22.9 years, male 50.7%). Diabetes (odd ratio 3.684, 95% CI, 1.256–10.810, p = 0.018) and operation time (odd ratio 1.005, 95% CI, 1.000–1.009, p = 0.029) were independently associated with postoperative lipiduria, while age (odd ratio 1.034, 95% CI, 1.003–1.066, p = 0.029), body mass index (odd ratio 1.100, 95% CI, 1.007–1.203, p = 0.035), and operation time (odd ratio 1.005, 95% CI, 1.000–1.010, p = 0.033) were independently associated with postoperative hypoxemia. We identified several factors independently associated with postoperative lipiduria and hypoxemia in patients with fracture undergoing surgical intervention. Operation time was associated with both postoperative lipiduria and hypoxemia, and we recommend that patients with prolonged operation for fractures should be carefully monitored for clinical signs related to fat embolism syndrome.
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