D. McIsaac, G. Hamilton, K. Abdulla, L. Lavallée, H. Moloo, C. Pysyk, J. Tufts, W. Ghali, A. Forster
{"title":"验证新的基于icd -10的患者安全指标,用于识别外科患者的院内并发症:诊断准确性的研究","authors":"D. McIsaac, G. Hamilton, K. Abdulla, L. Lavallée, H. Moloo, C. Pysyk, J. Tufts, W. Ghali, A. Forster","doi":"10.1136/bmjqs-2018-008852","DOIUrl":null,"url":null,"abstract":"Objective Administrative data systems are used to identify hospital-based patient safety events; few studies evaluate their accuracy. We assessed the accuracy of a new set of patient safety indicators (PSIs; designed to identify in hospital complications). Study design Prospectively defined analysis of registry data (1 April 2010–29 February 2016) in a Canadian hospital network. Assignment of complications was by two methods independently. The National Surgical Quality Improvement Programme (NSQIP) database was the clinical reference standard (primary outcome=any in-hospital NSQIP complication); PSI clusters were assigned using International Classification of Disease (ICD-10) codes in the discharge abstract. Our primary analysis assessed the accuracy of any PSI condition compared with any complication in the NSQIP; secondary analysis evaluated accuracy of complication-specific PSIs. Patients All inpatient surgical cases captured in NSQIP data. Analysis We assessed the accuracy of PSIs (with NSQIP as reference standard) using positive and negative predictive values (PPV/NPV), as well as positive and negative likelihood ratios (±LR). Results We identified 12 898 linked episodes of care. Complications were identified by PSIs and NSQIP in 2415 (18.7%) and 2885 (22.4%) episodes, respectively. The presence of any PSI code had a PPV of 0.55 (95% CI 0.53 to 0.57) and NPV of 0.93 (95% CI 0.92 to 0.93); +LR 6.41 (95% CI 6.01 to 6.84) and −LR 0.40 (95% CI 0.37 to 0.42). Subgroup analyses (by surgery type and urgency) showed similar performance. Complication-specific PSIs had high NPVs (95% CI 0.92 to 0.99), but low to moderate PPVs (0.13–0.61). Conclusion Validation of the ICD-10 PSI system suggests applicability as a first screening step, integrated with data from other sources, to produce an adverse event detection pathway that informs learning healthcare systems. However, accuracy was insufficient to directly identify or rule out individual-level complications.","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"209 - 216"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2018-008852","citationCount":"34","resultStr":"{\"title\":\"Validation of new ICD-10-based patient safety indicators for identification of in-hospital complications in surgical patients: a study of diagnostic accuracy\",\"authors\":\"D. McIsaac, G. Hamilton, K. Abdulla, L. Lavallée, H. Moloo, C. Pysyk, J. Tufts, W. Ghali, A. Forster\",\"doi\":\"10.1136/bmjqs-2018-008852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective Administrative data systems are used to identify hospital-based patient safety events; few studies evaluate their accuracy. We assessed the accuracy of a new set of patient safety indicators (PSIs; designed to identify in hospital complications). Study design Prospectively defined analysis of registry data (1 April 2010–29 February 2016) in a Canadian hospital network. Assignment of complications was by two methods independently. The National Surgical Quality Improvement Programme (NSQIP) database was the clinical reference standard (primary outcome=any in-hospital NSQIP complication); PSI clusters were assigned using International Classification of Disease (ICD-10) codes in the discharge abstract. Our primary analysis assessed the accuracy of any PSI condition compared with any complication in the NSQIP; secondary analysis evaluated accuracy of complication-specific PSIs. Patients All inpatient surgical cases captured in NSQIP data. Analysis We assessed the accuracy of PSIs (with NSQIP as reference standard) using positive and negative predictive values (PPV/NPV), as well as positive and negative likelihood ratios (±LR). Results We identified 12 898 linked episodes of care. Complications were identified by PSIs and NSQIP in 2415 (18.7%) and 2885 (22.4%) episodes, respectively. The presence of any PSI code had a PPV of 0.55 (95% CI 0.53 to 0.57) and NPV of 0.93 (95% CI 0.92 to 0.93); +LR 6.41 (95% CI 6.01 to 6.84) and −LR 0.40 (95% CI 0.37 to 0.42). Subgroup analyses (by surgery type and urgency) showed similar performance. Complication-specific PSIs had high NPVs (95% CI 0.92 to 0.99), but low to moderate PPVs (0.13–0.61). Conclusion Validation of the ICD-10 PSI system suggests applicability as a first screening step, integrated with data from other sources, to produce an adverse event detection pathway that informs learning healthcare systems. 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引用次数: 34
摘要
目的:利用管理数据系统识别基于医院的患者安全事件;很少有研究评估它们的准确性。我们评估了一套新的患者安全指标(psi)的准确性;设计用于识别院内并发症)。研究设计对加拿大医院网络中的注册数据(2010年4月1日至2016年2月29日)进行前瞻性定义分析。并发症分别由两种方法指定。国家手术质量改进计划(NSQIP)数据库为临床参考标准(主要结局=任何院内NSQIP并发症);在出院摘要中使用国际疾病分类(ICD-10)代码分配PSI集群。我们的初步分析评估了任何PSI情况与NSQIP中任何并发症的准确性;二次分析评估了并发症特异性psi的准确性。NSQIP数据中捕获的所有住院手术病例。我们采用阳性和阴性预测值(PPV/NPV)以及阳性和阴性似然比(±LR)来评估psi(以NSQIP为参考标准)的准确性。结果:我们确定了12898例相关的护理事件。PSIs和NSQIP分别在2415次(18.7%)和2885次(22.4%)发作中发现并发症。任何PSI编码的存在PPV为0.55 (95% CI 0.53 ~ 0.57), NPV为0.93 (95% CI 0.92 ~ 0.93);+LR 6.41 (95% CI 6.01至6.84)和- LR 0.40 (95% CI 0.37至0.42)。亚组分析(按手术类型和紧急程度)显示相似的结果。并发症特异性psi具有高npv (95% CI 0.92 ~ 0.99),但低至中等ppv(0.13 ~ 0.61)。ICD-10 PSI系统的验证表明,与其他来源的数据相结合,可作为第一步筛选步骤,以产生不良事件检测途径,为学习医疗保健系统提供信息。然而,准确性不足以直接识别或排除个人层面的并发症。
Validation of new ICD-10-based patient safety indicators for identification of in-hospital complications in surgical patients: a study of diagnostic accuracy
Objective Administrative data systems are used to identify hospital-based patient safety events; few studies evaluate their accuracy. We assessed the accuracy of a new set of patient safety indicators (PSIs; designed to identify in hospital complications). Study design Prospectively defined analysis of registry data (1 April 2010–29 February 2016) in a Canadian hospital network. Assignment of complications was by two methods independently. The National Surgical Quality Improvement Programme (NSQIP) database was the clinical reference standard (primary outcome=any in-hospital NSQIP complication); PSI clusters were assigned using International Classification of Disease (ICD-10) codes in the discharge abstract. Our primary analysis assessed the accuracy of any PSI condition compared with any complication in the NSQIP; secondary analysis evaluated accuracy of complication-specific PSIs. Patients All inpatient surgical cases captured in NSQIP data. Analysis We assessed the accuracy of PSIs (with NSQIP as reference standard) using positive and negative predictive values (PPV/NPV), as well as positive and negative likelihood ratios (±LR). Results We identified 12 898 linked episodes of care. Complications were identified by PSIs and NSQIP in 2415 (18.7%) and 2885 (22.4%) episodes, respectively. The presence of any PSI code had a PPV of 0.55 (95% CI 0.53 to 0.57) and NPV of 0.93 (95% CI 0.92 to 0.93); +LR 6.41 (95% CI 6.01 to 6.84) and −LR 0.40 (95% CI 0.37 to 0.42). Subgroup analyses (by surgery type and urgency) showed similar performance. Complication-specific PSIs had high NPVs (95% CI 0.92 to 0.99), but low to moderate PPVs (0.13–0.61). Conclusion Validation of the ICD-10 PSI system suggests applicability as a first screening step, integrated with data from other sources, to produce an adverse event detection pathway that informs learning healthcare systems. However, accuracy was insufficient to directly identify or rule out individual-level complications.