Dataset Information

The impact of the incorporation of a feasible postoperative mortality model at the Post-Anaesthestic Care Unit (PACU) on postoperative clinical deterioration: A pragmatic trial with 5,353 patients

ABSTRACT:

Background

Practical use of risk predictive tools and the assessment of their impact on outcome reduction is still a challenge. This pragmatic study of quality improvement (QI) describes the preoperative adoption of a customised postoperative death probability model (SAMPE model) and the evaluation of the impact of a Postoperative Anaesthetic Care Unit (PACU) pathway on the clinical deterioration of high-risk surgical patients.

Methods

A prospective cohort of 2,533 surgical patients compared with 2,820 historical controls after the adoption of a quality improvement (QI) intervention. We carried out quick postoperative high-risk pathways at PACU when the probability of postoperative death exceeded 5%. As outcome measures, we used the number of rapid response team (RRT) calls within 7 and 30 postoperative days, in-hospital mortality, and non-planned Intensive Care Unit (ICU) admission.

Results

Not only did the QI succeed in the implementation of a customised risk stratification model, but it also diminished the postoperative deterioration evaluated by RRT calls on very high-risk patients within 30 postoperative days (from 23% before to 14% after the intervention, p = 0.05). We achieved no survival benefits or reduction of non-planned ICU. The small group of high-risk patients (13% of the total) accounted for the highest proportion of RRT calls and postoperative death.

Conclusion

Employing a risk predictive tool to guide immediate postoperative care may influence postoperative deterioration. It encouraged the design of pragmatic trials focused on feasible, low-technology, and long-term interventions that can be adapted to diverse health systems, especially those that demand more accurate decision making and ask for full engagement in the control of postoperative morbi-mortality.

SUBMITTER: de Souza Gutierrez C

PROVIDER: S-EPMC8592468 | biostudies-literature |

REPOSITORIES: biostudies-literature

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