Rabil Maximilian J, Jalfon Michael, Palencia Peter, Heckscher Dylan, Kong Victoria, Golos Aleksandra, Richmond Rhys, Chess Adam, Kim Isaac Y, Leapman Michael S, Cavallo Jaime A
Yale University School of Medicine, New Haven, CT.
Yale University School of Medicine, New Haven, CT; Veterans Affairs Connecticut Healthcare System, West Haven and Newington, CT.
Urol Oncol. 2025 Aug 29. doi: 10.1016/j.urolonc.2025.07.028.
Variation in outcomes following radical prostatectomy and inclusion of prostate cancer surgery metrics in hospital ratings signal need for procedure-specific quality improvement (QI) efforts. We hypothesized that a novel electronic medical record (EMR)-based, automated algorithm-driven algorithm for surgical outcomes and quality metrics following robot-assisted laparoscopic radical prostatectomy (RALP) would demonstrate >90% sensitivity and specificity and significant inter-rater reliability (IRR) with National Surgical Quality Improvement Program (NSQIP) abstraction.
We developed an algorithm to automatically abstract RALP outcomes and quality metrics retrospectively from the EMR. Pathology results were abstracted through text extraction; surgical outcomes were abstracted using ICD-10 codes, CPT codes, and EMR data variables. Sensitivity, specificity, and IRR between the algorithm and NSQIP-abstraction were assessed using Cohen's kappa with statistical significance set P < 0.05.
Total of 927 cases were mutually tracked. IRR was highest for mortality (k = 1.00) and lowest for dialysis and ureteral obstruction (k = 0.00). IRR was fair for: sepsis (k = 0.28), renal insufficiency (k = 0.32), and prolonged NGT/NPO (k = 0.39); moderate: UTI (k = 0.50) and stage (k = 0.53); substantial: surgical margins (k = 0.94), urine leak (k = 0.60), C-Diff (k = 0.67), pneumonia (k = 0.80). Sensitivity of the algorithm was > 90% for all mutually tracked outcomes except rectal injury (0%) and specificity was >97%.
This novel algorithm for RALP outcomes matches or exceeds sensitivity and specificity of institutional NSQIP abstraction for all but 1 variable. Substantial agreement between the algorithm and NSQIP supports automated extraction of outcome metrics as an acceptable replacement for trained abstractors, and broader application provides opportunities to facilitate and reduce cost of outcomes and quality metric benchmarking.
根治性前列腺切除术后结果存在差异，且医院评级中纳入前列腺癌手术指标，这表明需要针对该手术进行特定的质量改进（QI）工作。我们假设，一种基于新型电子病历（EMR）的、由自动化算法驱动的机器人辅助腹腔镜根治性前列腺切除术（RALP）手术结果及质量指标算法，其敏感性和特异性将超过90%，并且与国家外科质量改进计划（NSQIP）摘要具有显著的评分者间可靠性（IRR）。
我们开发了一种算法，用于从EMR中自动回顾性提取RALP结果及质量指标。病理结果通过文本提取获得；手术结果使用ICD - 10编码、CPT编码和EMR数据变量进行提取。使用Cohen's kappa评估算法与NSQIP摘要之间的敏感性、特异性和IRR，设定统计学显著性P < 0.05。
总共相互追踪了927例病例。死亡率的IRR最高（k = 1.00），透析和输尿管梗阻的IRR最低（k = 0.00）。以下情况的IRR为一般：败血症（k = 0.28）、肾功能不全（k = 0.32）和鼻胃管/禁食时间延长（k = 0.39）；中等：尿路感染（k = 0.50）和分期（k = 0.53）；较高：手术切缘（k = 0.94）、尿漏（k = 0.60）、艰难梭菌感染（k = 0.67）、肺炎（k = 0.80）。除直肠损伤（0%）外，该算法对所有相互追踪结果的敏感性均超过90%，特异性超过97%。
这种用于RALP结果的新型算法，除了1个变量外，其敏感性和特异性与机构NSQIP摘要相当或更高。该算法与NSQIP之间的高度一致性支持将结果指标的自动提取作为训练有素的摘要员的可接受替代方法，更广泛的应用为促进和降低结果及质量指标基准测试的成本提供了机会。
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