分诊系统在门诊工作中的应用

医院传统的人工叫号分诊存在工作效率低、病人等待时间长等问题。我们利用门诊分诊系统来解决以上问题。本文在分析门诊现状的基础上,进一步阐述分诊系统的设计理念、功能和应用效果。     

电子分诊叫号系统在急诊分诊中的应用

目的为了改善医院急诊科的就医环境,提高急诊护士的分诊工作效率和病人的满意度。方法在急诊科应用电子分诊叫号系统为急诊护士分诊病人提供帮助。结果使急诊病人候诊秩序得到改善,实现了在挂号时设置专科的诊别状态．将病人的分诊等级、隶属专科资料信息对应到相应的诊室,这样可以在诊室由专科医生直接呼叫病人就诊,又可以在分诊台护士呼叫病人就诊,同时还在候诊区域设置大的显示屏幕显示候诊病人数、播放背景音乐,急诊病人在候诊时能一目了然、舒缓情绪。结论改变了原有的急诊分诊工作模式,减轻了护士工作压力,提高了护理工作效率及质量,提高了医院的服务质量,缩短了急诊病人的候诊时间,改善了就诊环境及就诊秩序,提高了病人满意度。受到医、护、患三方的欢迎。     

电子分诊叫号系统在急诊分诊中的应用

目的为了改善医院急诊科的就医环境,提高急诊护士的分诊工作效率和病人的满意度。方法在急诊科应用电子分诊叫号系统为急诊护士分诊病人提供帮助。结果使急诊病人候诊秩序得到改善,实现了在挂号时设置专科的诊别状态,将病人的分诊等级、隶属专科资料信息对应到相应的诊室,这样可以在诊室由专科医生直接呼叫病人就诊,又可以在分诊台护士呼叫病人就诊,同时还在候诊区域设置大的显示屏幕显示候诊病人数、播放背景音乐,急诊病人在候诊时能一目了然、舒缓情绪。结论改变了原有的急诊分诊工作模式,减轻了护士工作压力,提高了护理工作效率及质量,提高了医院的服务质量,缩短了急诊病人的候诊时间,改善了就诊环境及就诊秩序,提高了病人满意度,受到医、护、患三方的欢迎。     

电子叫号系统在门诊分诊中的应用及常见问题的处理

目的改善服务环境，提高服务质量。方法实施门诊电子叫号系统分诊。结果构建和谐安静就诊环境，提高病人遵医行为，保证医疗安全。结论正确处理电子叫号系统应用中常见问题，能更好地发挥电子叫号系统的作用，体现人性化服务。     

电子叫号系统在门诊分诊中的应用及常见问题的处理

目的改善服务环境,提高服务质量。方法实施门诊电子叫号系统分诊。结果构建和谐安静就诊环境,提高病人遵医行为,保证医疗安全。结论正确处理电子叫号系统应用中常见问题,能更好地发挥电子叫号系统的作用,体现人性化服务。     

分诊培训在门诊管理中的应用

目的：探讨对门诊分诊护士实施分诊培训的效果。方法：通过专家授课、专科培训、案例讨论和院外进修对该院门诊分诊护士进行分诊培训,并对培训前后门诊患者退换号率、高危病人转运时间及门诊患者满意率进行前后自身对照研究,经卡方检验和t检验显示,差异有统计学意义（P ＜ 0.001）。结果：分诊培训后门诊患者退换号率、高位患者转运时间及门诊患者满意度均优于培训前。结论：对门诊分诊护士实施分诊培训有效提高了分诊水平,缩短了病人就诊时间,进一步提升医疗质量。     

排队论数学模型在电子分诊系统中的应用体会

目的：探讨医院电子分诊系统的合理应用模式。方法：从排队论数学模型出发,分析并科学安排医护人员及医疗设备,使患者排队等待流程得到优化。结果：采用排队论数学模型的门诊分诊系统得到了成功应用。结论：利用排队论模型实现电子分诊系统是一种优化门诊排队和提高服务效率的可行方法。     

医疗单位信息化与HIS建设中的问题与建议

通过对医疗单位信息化概念及信息系统建设的阐述,强调了信息化建设是一个在一定程度上应用现代信息技术的集成化的渐进的建设过程;应围绕将基于手工的信息系统逐步改成基于计算机技术、网络技术和数据库技术的人—机系统的渐进过程做工作。同时针对当前对信息化建设的错误认识,从不同角度分析了医疗单位信息化建设中存在的问题,并对如何明确医疗单位信息化的特性、如何做好医疗单位信息系统的规划,科学实施医疗单位信息化提出了建议。     

医院自动分诊系统的应用

为适应医院规模的扩大,医院门诊量不断增加的现状。本文介绍在我院原有"军卫一号"医院信息系统的基础上,结合ORACLE数据库和LED大屏显示技术、语音多媒体技术、设计开发了医院自动分诊系统,并在医院综合门诊投入应用,减轻了分诊护士工作压力、提高了患者满意度、优化了就医流程、提升了医院形象。     

急诊护理电子病历系统研发与应用

结合住院护理电子病历系统,根据急诊科工作特色,研发出急诊护理电子病历系统,并应用于临床。实施后,分诊准确率由82.00%上升至96.00%,急诊抢救室护理文书总修订率由37.85%下降至15.99%,医生对护士的满意度由88%上升至96%,护士对整体工作满意度由78.38%上升至97.23%,患者对护士工作及服务满意度由82.00%上升至94.00%,差异均具有统计学意义（P<0.05）。急诊护理电子病历系统提高了分诊准确率及抢救室工作效率,优化了急诊护理流程,提高了护理质量,保证了护理安全。     

Automatic outbreak detection algorithm versus electronic reporting system

To determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA signals and 4,427 reports of outbreaks caused by Campylobacter spp. or norovirus during 2005-2006 in Germany. Local health departments reported local outbreaks with higher sensitivity and positive predictive value than did AODAs.     

美国的医院分类体系及发展特征

我国在由传统的计划经济向市场经济的转轨过程中,提出了医疗机构分类管理的改革方向。但是,在这个领域国内没有既往的经验可借鉴,必须深入了解国际社会医疗机构分类管理的经验和做法。美国在医疗机构分类管理方面积累了丰富的经验,学习和借鉴美国医院的分类体系将对目前我国进行的改革大有裨益。 美国实行联邦制,有联邦、州和地方(市、县、镇)三级政府,是一个典型的自由市场经济国家。同时,也使整个卫生系统广泛渗透着自由竞争意识。经过长期的发展,卫生已经成为除汽车以外的第二大产业,医院是卫生产业的主要组     

传染病医院CA电子签名系统的技术与实施

为推进医院无纸化进程,保证电子病历的法律效力、减少院内感染,本文论述了传染病医院电子签名基本概念与相关技术原理,通过部署数字证书管理、数字签名验证、电子签章和时间戳系统,将电子签名服务与医院各个系统进行安全集成,实现可靠的电子签名。建立医院统一的电子认证服务体系和业务应用安全支撑体系,保证电子病历的真实性、合法性,减少各业务环节医护人员易受感染的环节,对加强医疗管理、提高医疗效率具有重要意义。     

关于把建立医院分类评价体系作为公立医院改革切入点的建议

<正>公立医院不仅代表了当前我国医疗卫生事业的总体实力和发展方向,而且在守护居民健康的过程中,极大促进了我国经济平稳较快发展与社会和谐稳定。在过去30余年的发展历程中,公立医院凭借     

医院医疗护理不良事件电子上报系统的特点与应用

目的：采用不良事件电子上报系统,解决医院医疗护理不良事件上报无纸化的问题,明确事件的上报流程。方法：通过分析医疗护理过程中不良事件的种类,结合医院的具体上报流程,采用基于ASP.NET开发的不良事件上报系统,制作每种事件类型的对应表单,将流程电子化并与相应表单绑定,通过逐级提交完成上报过程。结果：护士只需简单操作即可填写完成不良事件上报表单,且通过流程图能够查看事件的上报过程,并将所有已提交的不良事件保存,方便日后查看分析。结论：该系统明确了护理人员的岗位职责,以纯信息化方式实现了无纸化办公,大幅提高了医疗不良事件的处理效率,赢得了护理人员的高度评价。     

Rapid and reliable self-screening for nutritional risk in hospital outpatients using an electronic system

ObjectiveThis study examined an electronic nutritional self-screening procedure for feasibility and for reliability, rapidity, and ease of use by hospital outpatients.MethodsOne hundred sixty consecutive patients (ages 18–87 y) attending a gastroenterology clinic measured their weight and height using a modified digital weight and height machine, which transmitted results to a computer. Following input of reported weight loss in the previous 3 mo to 6 mo, malnutrition risk by the Malnutrition Universal Screening Tool (MUST) was instantaneously calculated. The duration and ease of undertaking screening were noted. Screening also was undertaken by a health care professional.ResultsOf the patients in the study, 21.3% were at risk for malnutrition (medium + high risk). There was perfect agreement (kappa = 1.00) between self-screening and health care professional screening, between test–retest self-screening, and between two methods of measuring height (facing toward and away from the stadiometer). A low within-patient coefficient of variation was found for measurement of weight (<0.2%), height (<0.35%) and body mass index (<0.4%), except for two measurements in which height was recorded before correct positioning of the sliding headpiece. The overall time to self-screen was 1.29 ± 0.57 min but it was 2.81 ± 0.92 min in those aged ≥ 75 y. Of the participants, 96.2% rated self-screening as very easy (71.9%) or easy (24.3%) and 3.8% (predominantly patients ages ≥ 75 y) difficult.ConclusionThe study provides evidence that electronic nutritional self-screening can be rapid, easy, reliable, and feasible in a clinical setting. Equipment specifically designed for self-screening and use in other types of patients and settings could facilitate appropriate and routine implementation of self-screening.     

Automatic electronic laboratory-based reporting of notifiable infectious diseases at a large health system

Electronic laboratory-based reporting, developed by the UPMC Health System, Pittsburgh, Pennsylvania, was evaluated to determine if it could be integrated into the conventional paper-based reporting system. We reviewed reports of 10 infectious diseases from 8 UPMC hospitals that reported to the Allegheny County Health Department in southwestern Pennsylvania during January 1-November 26, 2000. Electronic reports were received a median of 4 days earlier than conventional reports. The completeness of reporting was 74% (95% confidence interval [CI] 66% to 81%) for the electronic laboratory-based reporting and 65% (95% CI 57% to 73%) for the conventional paper-based reporting system (p>0.05). Most reports (88%) missed by electronic laboratory-based reporting were caused by using free text. Automatic reporting was more rapid and as complete as conventional reporting. Using standardized coding and minimizing free text usage will increase the completeness of electronic laboratory-based reporting.     

综合医院儿科医院感染临床分析

目的 了解和掌握综合医院儿科医院感染的规律,以便更好地控制和预防医院感染的发生.方法 对4230例儿科住院患儿进行信息查询并分析.结果 4230例患儿中医院感染60例,感染率为1.42％,呼吸道感染为主占53.33％；基础疾病为血液系统疾病第1位占61.67％；病原学检查革兰阳性球菌占38.34％、革兰阴性球菌23.83％、革兰阴性杆菌22.28％、真菌12.44％；医院感染中死亡8.33％高于无医院感染的1.03％；医院感染年龄(5.64±2.67)岁小于无感染组的(7.97±3.80)岁,实施侵入性操作41.67％、预防应用抗菌药物33.33％、住院时间(22.33±9.39)d高于无医院感染组织的11.75％、13.02％、(9.64±3.51)d,均是医院感染危险因素.结论 儿科医院感染影响患儿的预后,其发生发展与多种因素有关,应采取相应措施预防和控制医院感染的发生.     

Evaluation of the capacity of the APR-DRG classification system to predict hospital mortality

Inpatient mortality has increasingly been used as an hospital outcome measure. Comparing mortality rates across hospitals requires adjustment for patient risks before making inferences about quality of care based on patient outcomes. Therefore it is essential to dispose of well performing severity measures. The aim of this study is to evaluate the ability of the All Patient Refined DRG system to predict inpatient mortality for congestive heart failure, myocardial infarction, pneumonia and ischemic stroke. Administrative records were used in this analysis. We used two statistics methods to assess the ability of the APR-DRG to predict mortality: the area under the receiver operating characteristics curve (referred to as the c-statistic) and the Hosmer-Lemeshow test. The database for the study included 19,212 discharges for stroke, pneumonia, myocardial infarction and congestive heart failure from fifteen hospital participating in the Italian APR-DRG Project. A multivariate analysis was performed to predict mortality for each condition in study using age, sex and APR-DRG risk mortality subclass as independent variables. Inpatient mortality rate ranges from 9.7% (pneumonia) to 16.7% (stroke). Model discrimination, calculated using the c-statistic, was 0.91 for myocardial infarction, 0.68 for stroke, 0.78 for pneumonia and 0.71 for congestive heart failure. The model calibration assessed using the Hosmer-Leme-show test was quite good. The performance of the APR-DRG scheme when used on Italian hospital activity records is similar to that reported in literature and it seems to improve by adding age and sex to the model. The APR-DRG system does not completely capture the effects of these variables. In some cases, the better performance might be due to the inclusion of specific complications in the risk-of-mortality subclass assignment.