A retrospective analysis of quality indicators in a mixed-type tertiary center intensive care unit Üçüncü basamak karma bir yoğun bakım ünitesinde kalite göstergelerinin retrospektif değerlendirilmesi

EFE S., Sak İ., İNAL V.

Journal of Medical and Surgical Intensive Care Medicine, vol.9, no.1, pp.1-6, 2018 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 9 Issue: 1
  • Publication Date: 2018
  • Doi Number: 10.5152/dcbybd.2018.1685
  • Journal Name: Journal of Medical and Surgical Intensive Care Medicine
  • Journal Indexes: Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.1-6
  • Keywords: Intensive care, Pabon lasso’s model, Performance evaluation, Quality indicators, Total quality management
  • Bursa Uludag University Affiliated: Yes


© 2018 by Turkish Society of Medical and Surgical Intensive Care Medicine.Objective: We aimed to take a snapshot to assess critical care specific quality indicators and performance of our critical care patients’ management course and to have some clues to improve our total quality as the first step of the “Total Quality Management” course. Material and Methods: The demographic and clinical data of 347 patients admitted to our tertiary center 10-bed mixed-type critical care unit between Jan 1, 2016 and Dec 31, 2016 were retrospectively analyzed at respect of designated quality indicators, herein by Pabon Lasso’s Method. Results: The patients’ mean age was 65±16 years, average LOS was 8.9±16 days, bed turnover rate was 34.7, occupancy rate was 98.3%, mean APACHE II score was 23±9, and standardized mortality rate was <1 (0.97). The readmission rate after 48 h of discharge was 2.6%. The post-discharge 90-day mortality rate was 5.1%, post-operative 48th h mortality rate was 2.2%, central venous catheter rate (CVC) was 82%, CVC related blood stream infections were 12.7%, invasive mechanic ventilator (IMV) rate was 71%, IMV-days was 6.5±3 days, and VAP rate was 12.7%. Conclusion: The common quality indicators are not assumed and are objected to compare the inter-ICUs’ differences, on the other hand, could provide useful information about deficient or inefficient points of data to improvable clinics’ own performance.