A clinical decision support system did not significantly improve correct diagnostic decisions (67% vs. 66%, OR 1.06) or guideline adherence compared to standard practice in non-cardiac surgery.
Does a clinical decision support system improve guideline adherence and diagnostic decision quality in adult patients (ASA III-IV) undergoing non-cardiac surgery?
Implementation of a clinical decision support system for preoperative cardiovascular risk assessment did not improve guideline adherence or diagnostic accuracy compared to standard practice.
Absolute Event Rate: 0% vs 0%
Abstract Background/Introduction Despite clear perioperative guidelines, adherence in clinical practice remains suboptimal, particularly in the preoperative cardiovascular risk assessment of non-cardiac surgical patients. Clinical decision support (CDS) systems may enhance structured, guideline-based care. The KIPeriOP project evaluated the impact of a CDS tool on perioperative guideline adherence and diagnostic decision quality. Purpose To assess whether the implementation of a perioperative CDS tool improves guideline adherence in preoperative risk assessment and diagnostics for patients undergoing non-cardiac surgery. Methods This multicenter randomized controlled interventional study was conducted at two German hospitals. Adult patients (ASA III–IV) scheduled for non-cardiac surgery were randomized to either standard preoperative evaluation (control) or CDS-supported evaluation (intervention). The CDS system (ZAZA-Pro) provided structured risk assessment and evidence-based diagnostic recommendations. Primary endpoints were adherence to guideline-based diagnostic recommendations and diagnostic decision quality. Secondary endpoints included ASA classification concordance and estimated additional time required for guideline implementation. Results A total of 229 patients were randomized (CDS: 123, control: 106). Baseline characteristics were comparable. Concordance between CDS-suggested and user-assigned ASA classification was highest for ASA IV (OR 5.58 95% CI 2.35–13.22, p 0.001), but low for ASA III (OR 0.35 0.18–0.67, p = 0.002). Adherence to guideline-recommended diagnostics was low in both groups and did not differ significantly (e.g., ECG OR 0.78 0.40–1.56, p = 0.518; echocardiography OR 1.33 0.37–5.10, p = 0.774). The proportion of correct diagnostic decisions was similar (CDS 67 % vs. control 66 %, OR 1.06 0.83–1.36, p = 0.679). Underdiagnosis was the main deviation (82.9 % of recommendations not followed in CDS group), whereas overdiagnosis was rare (3.4 %). Full implementation of CDS recommendations would have added a mean additional workload of 20 minutes per patient. Conclusion While CDS provided structured, evidence-based recommendations, it did not significantly improve guideline adherence or diagnostic accuracy compared with standard practice. High rates of underdiagnosis suggest that barriers are behavioral and organizational rather than informational. Targeted implementation strategies and workflow integration are needed to leverage the full potential of perioperative CDS.
Milz et al. (Sun,) reported a other. A clinical decision support system did not significantly improve correct diagnostic decisions (67% vs. 66%, OR 1.06) or guideline adherence compared to standard practice in non-cardiac surgery.