BMJ Open Quality (Jul 2022)

Creating an inexpensive hospital-wide surgical complication register for performance monitoring: a cohort study

  • Antti Malmivaara,
  • Antti Kaipia,
  • Heini Huhtala,
  • Ira H Saarinen

DOI
https://doi.org/10.1136/bmjoq-2021-001804
Journal volume & issue
Vol. 11, no. 3

Abstract

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Objectives Basic tools that measure a hospital’s performance are required in order to benchmark or compare hospitals, but multispecialty institutional registries are rarely reported, and there is no consensus on their standard definitions and methodology. This study aimed to describe the setting up and first results of a hospital-wide surgical complication register that uses a minimal set of patient-related risk factors based on bedside data and produces outcomes data based on severity of complications.Design Cohort study.Setting Perioperative data related to all adult surgical procedures in a tertiary referral centre in Finland for 3 years (2016–2018) were included in the study. Complications were recorded according to a modified Clavien-Dindo classification, and the preoperative risk factors were compiled based on the literature and coded as numerical measures. The associations of preoperative risk factors with postoperative complications were analysed using the χ2 test or Fisher’s exact test.Results In total, 19 158 operations were performed between 2016 and 2018. Data on complications (Clavien 0–9) were recorded for 4529 surgical patients (23.6%), and 779 complications were reported (Clavien 1–9), leading to an overall complication rate of 17.2%. Of these, 4.6% were graded as major (Clavien 4–7). Patient-related risk factors with the strongest association with complications were growing American Society of Anesthesiologists Physical Status Classification System score (p<0.001), growing Charlson Index (p<0.001), poor nutritional status (Nutritional Risk Screening 2002), p=0.041) and urgency of surgery (p<0.001).Conclusions We describe an inexpensive hospital-wide surgical complication monitoring system that can produce valid numerical data for monitoring risk-adjusted surgical quality. The results showed that only a few patient-related risk factors were sufficient to account for the case mix.