Development and Evaluation of a Risk-Adjusted Measure of Intraoperative Hypotension in Patients Having Nonemergent, Noncardiac Surgery

Development and Evaluation of a Risk-Adjusted Measure of Intraoperative Hypotension in Patients Having Nonemergent, Noncardiac Surgery

Published: Aug 01, 2021
Publisher: Anesthesia & Analgesia, vol. 133, issue 2
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Authors

Ethan Jacobs

Kamal Maheshwari

Karen B. Domino

Karen L. Posner

Alvin F. Stewart

Joseph A. Sanford

Daniel I. Sessler

Key Findings
  • The measure of intraoperative hypotension had sound scientific properties including high signal-to-noise reliability, indicating that the difference between clinicians’ scores was to some extent driven by differences in performance rather than statistical noise.
  • Our analysis also suggests that the measure has predictive validity; high risk-adjusted measure scores (indicating more cases of hypotension than predicted) were associated with increased kidney injury and in-hospital mortality which is consistent with observational analyses.
  • There were substantial variations in clinician-level scores, and the measure score distribution suggests that there may be opportunity to reduce intraoperative hypotension, which may improve patient safety and outcomes.
  • While the risk-adjustment model calibration statistics were acceptable, sensitivity analyses suggest that risk-adjustment remains sub-optimal. With improved data capture in electronic anesthesia records, future versions of the measure should risk-adjust for other important patient and procedural factors.

Background

Intraoperative hypotension is common and associated with organ injury and death, although randomized data showing a causal relationship remain sparse. A risk-adjusted measure of intraoperative hypotension may therefore contribute to quality improvement efforts.

Methods

The measure we developed defines hypotension as a mean arterial pressure less than 65 mmHg sustained for at least 15 cumulative minutes. Comparisons are based on whether clinicians have more or fewer cases of hypotension than expected over 12 months, given their patient mix. The measure was developed and evaluated with data from 225,389 surgeries in 5 hospitals. We assessed discrimination and calibration of the risk-adjustment model, then calculated the distribution of clinician-level measure scores, and finally estimated the signal-to-noise reliability and predictive validity of the measure.

Results

The risk-adjustment model showed acceptable calibration and discrimination (area under the curve was 0.72 and 0.73 in different validation samples). Clinician-level risk-adjusted scores varied widely, and 36% of clinicians had significantly more cases of intraoperative hypotension than predicted. Clinician-level score distributions differed across hospitals, indicating substantial hospital-level variation. The mean signal-to-noise reliability estimate was 0.87 among all clinicians and 0.94 among clinicians with more than 30 cases during the 12-month measurement period. Kidney injury and in-hospital mortality were most common in patients whose anesthesia providers had worse scores. However, a sensitivity analysis in one hospital showed that score distributions differed markedly between anesthesiology fellows and attending anesthesiologists or certified registered nurse anesthetists; score distributions also varied as a function of the fraction of cases that were inpatients.

Conclusions

Intraoperative hypotension was common and was associated with acute kidney injury and in-hospital mortality. There were substantial variations in clinician-level scores, and the measure score distribution suggests that there may be opportunity to reduce hypotension which may improve patient safety and outcomes. However, sensitivity analyses suggest that some portion of the variation results from limitations of risk adjustment. Future versions of the measure should risk adjust for important patient and procedural factors including comorbidities and surgical complexity, although this will require more consistent structured data capture in anesthesia information management systems. Including structured data on additional risk factors may improve hypotension risk prediction which is integral to the measure’s validity.

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