Accuracy of administrative coding in identifying hip and knee primary replacements and revisions

Rationale, aims and objectives Hospital discharge notes can be used to identify rates of revisions in hip and knee arthroplasty surgeries if such administrative codes are accurate. In order to trust the data taken from the hospital discharge abstracts it is important to assess their reliability. The purpose of this study is to evaluate the accuracy of the administrative coding used in measuring revision rates for total hip and knee arthroplasty. Methods Validation coding was determined by two orthopaedic surgery residents who reviewed the operative, radiological and discharge summaries in order to identify the revision rates for total hip and knee arthroplasty. A random sample of 637 patients from two tertiary care hospitals was studied. These patients had total hip or knee arthroplasty between 1996 and 2006. All of these patients had an International Classification of Disease (ICD)‐9CM or ICD‐10CM code indicating what procedure they had done. The validation reviewers were blinded to the administrative codes used. The sensitivity, specificity and positive and negative predictive values of the administrative codes for revision rates were measured. Results Based on 1201 procedures performed on 637 patients, when comparing validation review versus hospital administrative chart coding for primary and revision surgeries of total hip and knee arthroplasty, the following data were obtained: for total hip arthroplasty sensitivity is 99%, specificity is 91%, positive predictive value is 91% and negative predictive value is 99%; for total knee arthroplasty sensitivity is 89%, specificity is 98%, positive predictive value is 97% and negative predictive value is 93%. The accuracy of ICD‐9CM and ICD‐10CM were 96% and 95%, respectively. Conclusion This study demonstrates that ICD‐9CM and ICD‐10CM codes can be used accurately when analysing hip and knee arthroplasty. This study was conducted in a large tertiary academic centre where a significant number of records analysts are employed; therefore, there should be little inter‐hospital error. These results should help researchers understand the potential accuracy of classification for these procedures as part of an audit or quality assurance project.     

国内外护理分级的比较分析

护理分级也称患者分类系统,其在护理实践中对量化患者护理需求、衡量护理工作量、确定护理人力资源配置以及核定护理费用起着重要作用。本文通过文献检索,对国内外护理分级的评判标准、分类内容等进行对比,以期在借鉴和参考国外护理分级的基础上,补充、完善我国护理分级的内容,使其更好地适应我国临床护理的发展。     

脂质前列腺素E1对急性肺损伤T细胞特异性转录因子T-bet与Gata-3的作用

目的 探讨脂质体前列腺素E1(Lipo-PGE1)对脂多糖(lipopolysaccharide,LPS)诱导的小鼠急性肺损伤中表达失衡的转录因子T-bet/Gata-3的影响及其对Th1/Th2平衡的调节机制.方法 60只雌性BALB/C小鼠随机(随机数字法)分成3组(每组20只):尾静脉注射生理盐水10 ml/kg为对照组,尾静脉注射LPS 5 mg/kg(稀释至0.5 mg/ml)为LPS模型组,给予LPS 1 h后给予脂质前列腺素E1 15 μg/kg尾静脉注射为治疗组(LPS+ PGE1组).各组于6h后观察肺组织变化,并测定肺湿/干质量比(W/D).采用流式细胞仪分别检测Th1、Th2细胞的阳性率,SYBRGreen Ⅰ实时荧光定量PCR技术检测T-bet和Gata-3 mRNA的表达.应用SPSS 13.0统计软件行单因素方差分析.结果 模型组肺组织出现病理学改变,W/D为(5.74±0.31)较对照组(4.79±0.27)升高(P＜0.01),而PGE1治疗组W/D(4.92±0.27)较模型组明显降低(P＜0.01),肺组织病理学改变也明显减轻.模型组Th1、Th2细胞的阳性率及两者比值[(16.65±1.70)％,(9.40±1.25)％,(1.77 ±0.03)]较对照组[(23.67±2.10)％,(12.17±1.80)％,(1.95±0.04)]均显著降低,差异具有统计学意义(P＜0.01);与模型组比较,PGE1治疗组上述3个指 标[(20.31±2.20)％,(10.50±0.80)％,(1.93 ±0.05)]均升高,差异具有统计学意义(P＜0.01).模型组转录因子T-bet与Gata-3基因表达量及两者比值[(1.183 ±0.495),(0.693±0.285),(1.713 ±0.131)]较对照组[(3.439 ±0.557),(1.203±0.238),(2.857±0.290)]均降低,差异具有统计学意义(P＜0.01);与模型组比较,PGE1治疗组T-bet基因的表达量(1.827 ±0.705),T-bet与Gata-3表达量比值(2.502±0.352)均明显增高,差异有统计学意义(P＜0.01),而Gata-3的表达量(0.719 ±0.186)增高不明显,差异无统计学意义(P＞0.05).结论 脂质前列腺素E1可能通过增加T-bet基因的表达,纠正Th1/Th2平衡失调,从而改善相应的炎性症状.     

心脏病患者室性心律失常Lown分级及室早指数分析

目的:探讨室性心律失常Lown分级、室早指数及昼夜分布情况对器质性心脏病患者的临床应用价值.方法:回顾性分析2004年1月～2011年12月常规心电图、动态心电图检出的540例室性心律失常患者的临床资料,比较器质性心脏病组(Ⅰ组,n=334)、非器质性心脏病组(Ⅱ组,n=206)室性心律失常Lown分级特点,两组间Lown分级Ⅲ级以上室性心律失常的室早指数及其昼夜分布特点.结果:Ⅰ组检出的Lown分级Ⅲ级以上室性心律失常159例(47.6%)显著高于Ⅱ组检出的30例(14.6%)(P＜0.01);Ⅰ组Lown分级Ⅲ级以上室性心律失常的室早指数为0.99±0.11,显著低于Ⅱ组的1.17±0.15(P＜0.01);Ⅰ组室性心律失常高峰出现在日间220例(66%),显著高于Ⅱ组的89例(43%)(P＜0.01).结论:对室性心律失常患者进行Lown分级、室早指数、室性心律失常高峰时间分布的综合分析,有助于区分室性心律失常的性质及提高对其预后的预测价值.     

基层医院实施护士分层级管理的方法与效果

目的结合基层医院实际情况,探讨护士分层级管理的实施方法和效果。方法制订护士各个层级标准,确定各层级护士职责及在临床中的使用。结果患者满意度由90.91%上升到97.84%,护士工作满意度由82.83%上升到100.00%,护理质量合格率由95.57%上升到99.35%,差异均具有统计学意义(P<0.01或P<0.05)。结论实施护士分层级管理能提高患者及护士的满意度,有效调动各层级护士的工作积极性。     

住院病人分类指标体系框架的构建

目的初步构建住院病人分类指标体系的框架。方法运用德尔菲法,选择50名护理管理专家对拟定的备选指标进行两轮函询。结果两轮函询,问卷的有效回收率分别为83．33％和100．00％,专家意见协调系数分别为0．24和0．32（P〈0．01）,专家权威程度系数为0．83,最终确定病人分类指标体系框架由生活护理需求、治疗护理需求、心理社会需求3个一级指标、14个二级指标、89个三级指标构成。结论住院病人分类指标体系框架为护理人员能准确衡量病人的护理需求及进一步构建系统、可操作化的病人分类指标体系奠定研究基础。     

声触诊组织量化技术对进展期胃癌Lauren分型的初步研究

目的 探讨声触诊组织量化(VTQ)技术对进展期胃癌Lauren分型的评估价值.方法 对术前胃镜活检术后经病理证实的41例胃癌患者术前行VTQ检查,测量各病灶组织的剪切波速度(SWV),术后对胃癌标本行HE染色及AB-PAS黏液染色,并据此进行Lauren分型.比较胃癌不同Lauren亚型间SWV的差异.结果 41例胃癌标本组织学诊断为弥漫型者26例,肠型者15例.弥漫型胃癌SWV明显高于肠型胃癌,差异有统计学意义[(1.72±0.83) m/s对(1.05±0.66)m/s,t=2.819,P=0.008].由ROC曲线可知,当SWV截值=1.045m/s(曲线下最大面积=0.795)时,其预测弥漫型胃癌的敏感性和特异性分别为80.8％和73.3％.结论 利用VTQ检查可以在术前初步判断进展期胃癌的Lauren分型.     

双相式护理分级模式的研究

对双相式护理分级的概念、现行分级护理模式的局限性、实施双相式护理分级的必要性与可行性进行综述,为今后开展双相式护理分级的进一步研究提供借鉴和思考。     

2017版WHO垂体神经内分泌肿瘤分类临床指导及国际疾病分类法编码分析

2017年世界卫生组织发布第四版内分泌肿瘤分类(以下简称2017版分类),对垂体肿瘤分类的理论基础进行更新.垂体转录因子的发现使垂体腺瘤的分类更细化,使既往无法明确诊断、易混淆、无法判断预后的垂体腺瘤的分类得以明确.本文按照2017版分类对每种垂体腺瘤分类、诊断和预后进行分析,并结合国际疾病分类法-10(ICD-10)...     

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.