Southern Danielle A, Burnand Bernard, Droesler Saskia E, Flemons Ward, Forster Alan J, Gurevich Yana, Harrison James, Quan Hude, Pincus Harold A, Romano Patrick S, Sundararajan Vijaya, Kostanjsek Nenad, Ghali William A
*Department of Community Health Sciences and the O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada †Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland ‡Faculty of Health Care, Niederrhein University of Applied Sciences, Krefeld, Germany §Cumming School of Medicine, University of Calgary, Calgary, AB ∥Department of Medicine, University of Ottawa, Ottawa ¶Canadian Institute of Health Information, ON, Canada #Flinders University, Adelaide, SA, Australia **Department of Psychiatry, Columbia University and the New York State Psychiatric Institute ††Irving Institute for Clinical and Translational Research at Columbia University and New York-Presbyterian Hospital, New York, NY ‡‡RAND Corporation, Pittsburgh, PA §§Division of General Medicine, University of California-Davis School of Medicine, Sacramento, CA ∥∥Department of Medicine, St. Vincent's Hospital, University of Melbourne ¶¶Department of Medicine, Southern Clinical School, Monash University, Melbourne, Vic., Australia ##World Health Organization, Classifications, Terminology and Standards, Geneva, Switzerland.
Med Care. 2017 Mar;55(3):252-260. doi: 10.1097/MLR.0000000000000649.
Existing administrative data patient safety indicators (PSIs) have been limited by uncertainty around the timing of onset of included diagnoses.
We undertook de novo PSI development through a data-driven approach that drew upon "diagnosis timing" information available in some countries' administrative hospital data.
Administrative database analysis and modified Delphi rating process.
All hospitalized adults in Canada in 2009.
We queried all hospitalizations for ICD-10-CA diagnosis codes arising during hospital stay. We then undertook a modified Delphi panel process to rate the extent to which each of the identified diagnoses has a potential link to suboptimal quality of care. We grouped the identified quality/safety-related diagnoses into relevant clinical categories. Lastly, we queried Alberta hospital discharge data to assess the frequency of the newly defined PSI events.
Among 2,416,413 national hospitalizations, we found 2590 unique ICD-10-CA codes flagged as having arisen after admission. Seven panelists evaluated these in a 2-round review process, and identified a listing of 640 ICD-10-CA diagnosis codes judged to be linked to suboptimal quality of care and thus appropriate for inclusion in PSIs. These were then grouped by patient safety experts into 18 clinically relevant PSI categories. We then analyzed data on 2,381,652 Alberta hospital discharges from 2005 through 2012, and found that 134,299 (5.2%) hospitalizations had at least 1 PSI diagnosis.
The resulting work creates a foundation for a new set of PSIs for routine large-scale surveillance of hospital and health system performance.
现有的行政数据患者安全指标（PSI）受到所纳入诊断发病时间不确定性的限制。
我们通过数据驱动的方法重新开展PSI的开发，该方法利用了一些国家行政医院数据中可用的“诊断时间”信息。
行政数据库分析和改进的德尔菲评级过程。
2009年加拿大所有住院成人。
我们查询了住院期间出现的所有ICD - 10 - CA诊断代码的住院情况。然后我们进行了改进的德尔菲小组过程，以评估每个已识别诊断与次优医疗质量潜在关联的程度。我们将已识别的与质量/安全相关的诊断归类到相关临床类别中。最后，我们查询了艾伯塔省医院出院数据，以评估新定义的PSI事件的发生频率。
在2416413例全国住院病例中，我们发现2590个独特的ICD - 10 - CA代码被标记为入院后出现。七名小组成员在两轮审查过程中对这些代码进行了评估，并确定了一份640个ICD - 10 - CA诊断代码的清单，这些代码被判定与次优医疗质量相关，因此适合纳入PSI。然后，患者安全专家将这些代码归类为18个临床相关的PSI类别。然后我们分析了2005年至2012年艾伯塔省2381652例医院出院数据，发现134299例（5.2%）住院病例至少有1个PSI诊断。
这项工作为一套新的PSI奠定了基础，用于对医院和卫生系统绩效进行常规大规模监测。
