435例非计划再次手术的科室分布及原因分析

目的 通过对非计划再次手术的发生率、科室来源、发生原因进行统计分析,探讨非计划再次手术的防范措施,提高全院的手术质量。方法 对某三级甲等综合医院2014年度所有手术患者的临床资料进行回顾性分析。结果 共回顾性分析62 179份手术患者的资料,其中发生重返手术室的有2411人次,发生非计划再次手术的有435人次,非计划再次手术发生率为6.94‰,非计划再次手术主要发生在男性、40～59岁年龄组患者中,非计划再次手术主要科室来源为神经外科（143例）、心胸外科（39例）及口腔颌面外科（27例）,术后出血/血肿、未达到效果手术再调整、术后漏、切口问题及手术部位感染为非计划再次手术发生的主要原因,占总原因的78.85%。结论 加强围手术期质量管理,严格执行非计划再次手术的上报制度,对非计划再次手术发生率高的重点科室、重点手术进行监管,是降低非计划再次手术发生率的有效措施。     

肿瘤患者非计划再次手术原因分析及对策

目的 为提高手术质量、保障医疗质量提供管理依据。方法 回顾性分析某三甲肿瘤专科医院2008—2013年442例非计划再次手术病例,对非计划再次手术的发生情况进行分析。结果 肿瘤手术患者非计划再次手术发生率为1.0%,发生的主要原因为术后出血、吻合口瘘、手术切口问题。非计划再次手术的发生与手术难度、手术者专业水平及患者病情因素等因素有关。结论 作为手术质量评价的重要指标,医院应将非计划再次手术监管作为提高质量管理的抓手。     

基于PDCA循环的非计划再次手术管理方法设计与实现

目的 针对非计划再次手术管理需求设计了一种管理方法。为医院非计划再次手术的管理以及医疗质量改进提供参考。方法 参考国家对非计划再次手术管理的相关规范及标准文件,遵循 PDCA 循环的思想,结合信息技术,最终建立一个“非计划再次手术”专用的管理方法。结果 方法实施前后非计划再次手术的发生率有了显著的下降,发生率从方法实施前（2014年下半年）的1.02%降低到方法实施后（2015年7—12月）的0.71%。结论 方法有效降低了非计划再次手术发生率,符合医疗管理的需求,有利于提升手术质量,以实现医疗质量的持续性改进。

     

品管圈降低肝胆外科非计划再手术发生率的应用研究

??????? 目的 降低肝胆二科非计划再次手术发生率。方法 综合运用品管圈的管理方法,分析影响非计划再次手术的主要原因,制定针对性措施实施过程改进。结果 实施改进措施后,非计划再次手术发生率由1.12%降低至0.21%,达到目标值＜0.5%（P=0.045）,月平均住院日由14.32天缩短至10.52天（P<0.001）。结论 品管圈管理方法的应用显著降低非计划再次手术发生率,缩短患者平均住院日,有利于提升手术质量,减少不良事件发生,保障患者生命安全。     

非计划再次手术关键环节管理与效果分析

目的 探索有效降低非计划再次手术发生率的管理方法。方法 对2012年1月—2016年12月住院并进行手术的患者进行主动监测,加强管理,发现非计划再次手术病例,统计发生率及引发原因。结果 225 944例手术共发生非计划再次手术914例,平均发生率为0.40%且五年呈显著下降趋势。引发原因以手术部位感染、切口裂开、切口疝或愈合不良,术后出血,出现漏或瘘为主,共占73.9%。结论 完善主动监测与报告系统、加强院科两级管理、注重原因分析与改进可有效降低非计划再次手术的发生率。     

关于加强非计划再次手术监管的探讨

目的 探索非计划再次手术的原因,为提高医院手术病人的医疗质量、降低非计划再手术的发生率提供依据。方法 对42例非计划再次手术进行回顾性分析。结果 非计划再次手术的平均住院日、医疗费用与前一年度院平均值比较差异显著,且有统计学意义。结论 医务人员应加强手术责任心,预防再手术的发生,同时医院应加强非计划再次手术的监管工作。     

PDCA循环降低非计划再次手术发生率的效果评价

目的 探讨降低非计划再次手术发生率的有效方式,为医疗质量改进提供参考。方法 运用PDCA循环原理,对非计划再次手术的发生情况进行分析,找出影响非计划再次手术的主要原因,制定针对性措施实施过程改进。结果 实施改进措施后,非计划再次手术发生率由1.2%降低至0.9%。结论 PDCA循环的应用降低了非计划再次手术发生率,有利于提高手术质量,以实现医疗质量的持续性改进。     

非计划再次手术的精细化管理体系建立

通过对非计划再次手术这一指标的特性的分析，提出非计划再次手术精细化管理体系的构建，管理必须分层与分类相结合，纵向和横向相结合，个案与总体相结合，重点与效率相结合，从实际出发，建立重点明确，管理有效，注重效率的精细化管理体系。     

非计划再手术与医疗纠纷关系研究

以某综合性三甲医院2007—2008年全部住院手术患者为研究对象,研究该医院非计划再手术纠纷发生率,通过分析非计划再手术纠纷病例,探讨非计划再手术率纠纷发生原因。 2007—2008年非计划再手术病例共432例,纠纷13例,非计划再手术纠纷发生率为3%。非计划再手术是医疗纠纷发生的危险因素,医院应该对高出平均水平的非计划再手术发生率事件提高警觉,寻找其发生的原因,改进手术质量。     

北京市某医院非计划再手术原因分析

以某综合性三甲医院2007—2008年全部住院手术患者为研究对象,通过分析非计划再手术病例,探讨非计划再手术发生原因。共分析2007—2008年非计划再手术病例共432例,未达预期效果手术再调整、切口问题、手术后出血、手术部位感染、手术损伤是导致二次或多次手术发生的主要原因。医院应该监测非计划再手术事件,寻找其发生的原因,发现围手术期存在的质量问题,以提高医疗质量。     

基于故障树方法的非计划再次手术风险评估

目的 探索一种适合于在过程复杂、环境多变、风险多样的手术治疗系统中,对术前准备、术中操作、术后医疗护理及管理等贯穿围手术期全过程进行风险评估的方法。方法 通过危险事件的风险影响因子识别、定性分析与定量分析、基本事件综合风险等级评价,绘制具有实践操作意义的风险矩阵图,全面识别手术治疗系统风险、科学分析危险事件与风险影响因子,有效评价风险等级与可容忍度。结果 构建包括7个中间事件、29个基本事件、9个逻辑或门和1个逻辑与门的非计划再次手术故障树模型,故障树由8个一阶割集和104个二阶割集组成。当所有最小割集均存在时,被调查医院非计划再次手术的发生概率为0.950 10,同时确定25个基本事件在该医院的综合风险重要性等级,并根据绘制的风险图谱进一步确定风险应对的优先顺序。结论 基于故障树的手术治疗系统风险评估方法,可以全面识别手术治疗系统风险,科学分析风险影响因子,有效评价风险等级。     

北京大学所属6家医院洁净手术部质量管理监测分析

????? 目的 通过对医院洁净手术部综合性能和管理现状监测结果的分析,发现质量管理中存在的问题,促进医院加强管理,保障洁净手术部有效运行。方法 回顾性分析洁净手术部检查资料,了解质量管理中存在的问题及薄弱环节,提出有效的改进措施。结果 洁净手术部的管理还存在着一定的缺陷,应进一步加强管理力度,定期监测。结论 洁净手术部的管理涉及多专业,多学科,多部门,是对医院感染管理工作的挑战。需要制定与此相适应的科学合理的运行和管理的措施,以保障洁净手术部的安全运行。     

北京大学所属医院洁净手术部质量管理监测结果分析

目的 通过对医院洁净手术部综合性能和管理现状监测结果的分析,发现质量管理中存在的问题,促进医院加强管理,保障洁净手术部有效运行。方法 回顾性分析洁净手术部检查资料,了解质量管理中存在的问题及薄弱环节,提出有效的改进措施。结果 洁净手术部的管理还存在着一定的缺陷,应进一步加强管理力度,定期监测。结论 洁净手术部的管理涉及多专业,多学科,多部门,是对医院感染管理工作的挑战。需要制定与此相适应的科学合理的运行和管理的措施,以保障洁净手术部的安全运行。     

An analysis of the genetics of schizophrenia

Abstract

Two samples of unplanned and planned children, matched for education, were compared for emotional disturbance on three different instruments. Unplanned children scored consistently higher, in some cases significantly so, particularly among the lower classes. In the second sample, mothers were also compared for neuroticism and for parental attitudes. Mothers of unplanned children scored higher, but not significantly so. No differences in maternal attitudes of rejection and protection were found. In the second study, unplanned children came from significantly larger families than did planned children. It is postulated that the greater the adversity of circumstance of the family, the more negative the effects of unplanned status will be on emotional adjustment.     

Derivation and validation of a clinical model to predict death or cardiac hospitalizations while on the cardiac surgery waitlist

Background:Waitlist management is a global challenge. For patients with severe cardiovascular diseases awaiting cardiac surgery, prolonged wait times are associated with unplanned hospitalizations. To facilitate evidence-based resource allocation, we derived and validated a clinical risk model to predict the composite outcome of death and cardiac hospitalization of patients on the waitlist for cardiac surgery.Methods:We used the CorHealth Ontario Registry and linked ICES health care administrative databases, which have information on all Ontario residents. We included patients 18 years or older who waited at home for coronary artery bypass grafting, valvular or thoracic aorta surgeries between 2008 and 2019. The primary outcome was death or an unplanned cardiac hospitalizaton, defined as nonelective admission for heart failure, myocardial infarction, unstable angina or endocarditis. We randomly divided two-thirds of these patients into derivation and one-third into validation data sets. We derived the model using a multivariable Cox proportional hazard model with backward stepwise variable selection.Results:Among 62 375 patients, 41 729 patients were part of the derivation data set and 20 583 were part of the validation data set. Of the total, 3033 (4.9%) died or had an unplanned cardiac hospitalization while waiting for surgery. The area under the curve of our model at 15, 30, 60 and 89 days was 0.85, 0.82, 0.81 and 0.80, respectively, in the derivation cohort and 0.83, 0.80, 0.78 and 0.78, respctively, in the validation cohort. The model calibrated well at all time points.Interpretation:We derived and validated a clinical risk model that provides accurate prediction of the risk of death and unplanned cardiac hospitalization for patients on the cardiac surgery waitlist. Our model could be used for quality benchmarking and data-driven decision support for managing access to cardiac surgery.

Waitlist management is an ongoing challenge for publicly funded health care systems because available resources are finite. This challenge has become more pervasive since the onset of the COVID-19 pandemic, as many nonemergent procedures have been postponed to preserve system capacity for patients with COVID-19.¹The decision to triage patients booked for cardiac surgery balances the likelihood of disease decompensation and the availability of operating room and intensive care unit resources. Our group has previously developed and validated the CardiOttawa Length of Stay Score to estimate the likelihood of high or low needs for postoperative intensive care unit resources,² and the CardiOttawa Waitlist Mortality Score to support evidence-based prioritization for cardiac surgeries. These risk models have been combined into a single triage decision support tool that is used on a daily basis at our institution (available with sign up at https://cardiottawa.ottawaheart.ca). No models are available to predict unplanned hospitalizations for patients on the waitlist for definitive surgical interventions. We therefore conducted a population-based study in Ontario, Canada to derive and validate a clinical model to predict the composite outcome of death or unplanned cardiac hospitalizations in patients on the waitlist for cardiac surgery.     

超声引导下髂腹下－髂腹股沟神经阻滞应用于男性全身麻醉后导尿管相关膀胱刺激征临床效果的回顾性研究

摘要 目的：探讨超声引导髂腹下－髂腹股沟神经阻滞应用于男性全身麻醉后导尿管相关膀胱刺激征（CRBD）的临床效果。方法：回顾性分析本院收治的60例择期全身麻醉下行下肢清创、皮瓣转移或植皮的男性患者,且术中需留置导尿管者的临床资料。按是否行超声引导下髂腹下－髂腹股沟神经阻滞分为观察组和对照组,观察组在全身麻醉后,超声引导下进行双侧髂腹下-髂腹股沟神经阻滞,神经阻滞完成后行导尿管留置术。对照组麻醉诱导完成后,即行导尿管留置术。记录拔除气管导管后10 min（T1）、1h（T2）、3h（T3）CRBD严重程度评分和Riker镇静-躁动评分。记录术前（T0）和T1、T2、T3对应时点的收缩压（SBP）、舒张压（DBP）、心率（HR）,对比两组的苏醒质量和麻醉相关不良反应。结果：术后各时段观察组CRBD严重程度评分和Riker镇静-躁动评分均明显低于对照组（P＜0.05）;术后各时段观察组的SBP、DBP、HR与对照组相比均明显降低 （P＜0.05）;观察组PACU内非计划性使用镇痛药、非计划性拔除尿管的比例低于对照组,PACU的停留时间短于对照组（P <0.05）;两组麻醉相关不良反应发生率对比未见统计学意义（P >0.05）。结论：超声引导下髂腹下－髂腹股沟神经阻滞操作简便,减轻全身麻醉后CRBD的效果确切,患者对导尿管有良好的耐受,术后血流动力学和循环更稳定,苏醒质量更高。     

Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures

ObjectiveTo examine the effect of the method of data display on physician investigators’ decisions to stop hypothetical clinical trials for an unplanned statistical analysis.DesignProspective, mixed model design with variables between subjects and within subjects (repeated measures).SettingComprehensive cancer centre.Participants34 physicians, stratified by academic rank, who were conducting clinical trials.InterventionsParticipants were shown tables, pie charts, bar graphs, and icon displays containing hypothetical data from a clinical trial and were asked to decide whether to continue the trial or stop for an unplanned statistical analysis.ResultsAccuracy of decisions was affected by the type of data display and positive or negative framing of the data. More correct decisions were made with icon displays than with tables, pie charts, and bar graphs (82% v 68%, 56%, and 43%, respectively; P=0.03) and when data were negatively framed rather than positively framed in tables (93% v 47%; P=0.004).ConclusionsClinical investigators’ decisions can be affected by factors unrelated to the actual data. In the design of clinical trials information systems, careful consideration should be given to the method by which data are framed and displayed in order to reduce the impact of these extraneous factors.

Key messages

• In clinical trials formal interim monitoring points, at which statistical tests are conducted, are designated a priori, but investigators also conduct informal interim monitoring, when statistical tests are not used
• This study investigated the effect of the method of displaying results on clinical investigators’ decisions to conduct unplanned analyses of a hypothetical clinical trial
• The method of displaying results significantly influenced the accuracy of decisions, as did the framing of these results (positive or negative)
• The display formats preferred by the clinical investigators did not lead to the most accurate decisions
• Careful consideration should be given to the method of data display in information systems supporting clinical research

     

Comparison of Unplanned Intensive Care Unit Readmission Scores: A Prospective Cohort Study

PurposeEarly discharge from the intensive care unit (ICU) may constitute a strategy of resource consumption optimization; however, unplanned readmission of hospitalized patients to an ICU is associated with a worse outcome. We aimed to compare the effectiveness of the Stability and Workload Index for Transfer score (SWIFT), Sequential Organ Failure Assessment score (SOFA) and simplified Therapeutic Intervention Scoring System (TISS-28) in predicting unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU.MethodsWe conducted a prospective cohort study in a single tertiary hospital in southern Brazil. All adult patients admitted to the ICU for more than 24 hours from January 2008 to December 2009 were evaluated. SWIFT, SOFA and TISS-28 scores were calculated on the day of discharge from the ICU. A stepwise logistic regression was conducted to evaluate the effectiveness of these scores in predicting unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU. Moreover, we conducted a direct accuracy comparison among SWIFT, SOFA and TISS-28 scores.ResultsA total of 1,277 patients were discharged from the ICU during the study period. The rate of unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU was 15% (192 patients). In the multivariate analysis, age (P = 0.001), length of ICU stay (P = 0.01), cirrhosis (P = 0.03), SWIFT (P = 0.001), SOFA (P = 0.01) and TISS-28 (P<0.001) constituted predictors of unplanned ICU readmission or unexpected death. The SWIFT, SOFA and TISS-28 scores showed similar predictive accuracy (AUC values were 0.66, 0.65 and 0.74, respectively; P = 0.58).ConclusionsSWIFT, SOFA and TISS-28 on the day of discharge from the ICU have only moderate accuracy in predicting ICU readmission or death. The present study did not find any differences in accuracy among the three scores.