Department of Medicine, and.
Community Health Sciences, Rady College of Medicine, and.
Ann Am Thorac Soc. 2020 Feb;17(2):229-235. doi: 10.1513/AnnalsATS.201902-106OC.
Accurately identifying use of life support in hospital administrative data enhances the data's value for quality improvement and research in critical illness. To assess the accuracy of administrative hospital data for identifying invasive mechanical ventilation (IMV), acute renal replacement therapy (RRT), and intravenous vasoactive drugs in unselected adult intensive care unit (ICU) patients. We employed the administrative dataset of the Discharge Abstract Database from the Province of Manitoba during 2007-2012, using nationally standardized diagnosis and procedure codes to identify the three types of life support. The criterion standard was the Winnipeg ICU Database, which contains daily clinical information about all admissions to all 11 adult ICUs within the Winnipeg Regional Health Authority. For all individuals aged 40 years or older at ICU admission, we calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the administrative data for identifying life support. We also assessed the ability of the administrative data to identify overlapping use of the forms of life support. Over the study period, there were 20,764 eligible ICU admissions; 52.6% (10,914) involved IMV, 46.8% (9,724) involved vasoactive agents, and 4.4% (907) involved acute RRT. Identification of IMV from administrative data procedure codes was good, with all four parameters exceeding 90%. The procedure code for use of selected vasoactive drugs had a sensitivity of zero; addition of diagnosis codes for shock raised the sensitivity to only 23% (95% confidence interval [CI], 22-24%). Both the sensitivity and specificity for acute RRT procedure codes exceeded 92%, but owing to low prevalence of RRT, the PPV was only 55% (95% CI, 53-58%). Addition of diagnosis codes for acute renal failure did not appreciably improve performance. Overlapping use of the three types of life support was substantial. Among those receiving any one of the types of life support, 68-76% received at least one of the two other types assessed. Considering use of any one or more of the three forms of life support, the administrative data had a PPV of 97% (95% CI, 96-97%) and a negative predictive value of 69% (95% CI, 68-70%). Administrative data accurately identify IMV but not use of vasoactive drugs or acute RRT.
准确识别医院管理数据中生命支持的使用情况可以提高数据在重症疾病质量改进和研究中的价值。本研究旨在评估在未经选择的成年重症监护病房（ICU）患者中，使用管理医院数据识别有创机械通气（IMV）、急性肾脏替代治疗（RRT）和静脉血管活性药物的准确性。我们使用了 2007 年至 2012 年期间马尼托巴省出院摘要数据库中的管理数据集，使用国家标准化诊断和程序代码来识别这三种类型的生命支持。标准是温尼伯 ICU 数据库，其中包含了所有在温尼伯地区卫生当局内的 11 个成人 ICU 中所有入院患者的每日临床信息。对于 ICU 入院时年龄在 40 岁或以上的所有个体，我们计算了管理数据识别生命支持的敏感性、特异性、阳性预测值（PPV）和阴性预测值。我们还评估了管理数据识别重叠使用生命支持形式的能力。在研究期间，有 20764 例符合条件的 ICU 入院患者；52.6%（10914 例）涉及 IMV，46.8%（9724 例）涉及血管活性药物，4.4%（907 例）涉及急性 RRT。从管理数据程序代码中识别 IMV 的效果良好，所有四个参数均超过 90%。用于选择血管活性药物的程序代码的敏感性为零；添加休克的诊断代码将敏感性仅提高至 23%（95%置信区间[CI]，22-24%）。急性 RRT 程序代码的敏感性和特异性均超过 92%，但由于 RRT 的患病率较低，PPV 仅为 55%（95%CI，53-58%）。添加急性肾衰竭的诊断代码并没有明显改善性能。三种类型的生命支持的重叠使用非常普遍。在接受任何一种生命支持类型的患者中，有 68-76%的患者至少接受了另外两种评估的生命支持类型之一。考虑使用三种形式的生命支持中的任何一种或更多种，管理数据的 PPV 为 97%（95%CI，96-97%），阴性预测值为 69%（95%CI，68-70%）。管理数据可以准确识别 IMV，但不能识别血管活性药物或急性 RRT 的使用情况。
