Monitoring the performance of a dedicated weaning unit using risk-adjusted control charts for the weaning rate in prolonged mechanical ventilation

Abstract

Background: Weaning rate is an important quality indicator of care for patients with prolonged mechanical ventilation (PMV). However, diverse clinical characteristics often affect the measured rate. A risk-adjusted control chart may be beneficial for assessing the quality of care. Methods: We analyzed patients with PMV who were discharged between 2018 and 2020 from a dedicated weaning unit at a medical center. We generated a formula to estimate monthly weaning rates using multivariate logistic regression for the clinical, laboratory, and physiologic characteristics upon weaning unit admission in the first two years (Phase I). We then applied both multiplicative and additive models for adjusted p-charts, displayed in both non-segmented and segmented formats, to assess whether special cause variation existed. Results: A total of 737 patients were analyzed, including 503 in Phase I and 234 in Phase II, with average weaning rates of 59.4% and 60.3%, respectively. The p-chart of crude weaning rates did not show special cause variation. Ten variables from the regression analysis were selected for the formula to predict individual weaning probability and generate estimated weaning rates in Phases I and II. For risk-adjusted p-charts, both multiplicative and additive models showed similar findings and no special cause variation. Conclusion: Risk-adjusted control charts generated using a combination of multivariate logistic regression and control chart-adjustment models may provide a feasible method to assess the quality of care in the setting of PMV with standard care protocols.

Keywords

• Control chart
• Prolonged mechanical ventilation
• Quality of health care
• Risk adjustment
• Weaning