Development and field testing of a decision support tool to facilitate shared decision making in contraceptive counseling

ObjectiveWe developed and formatively evaluated a tablet-based decision support tool for use by women prior to a contraceptive counseling visit to help them engage in shared decision making regarding method selection.MethodsDrawing upon formative work around women’s preferences for contraceptive counseling and conceptual understanding of health care decision making, we iteratively developed a storyboard and then digital prototypes, based on best practices for decision support tool development. Pilot testing using both quantitative and qualitative data and cognitive testing was conducted. We obtained feedback from patient and provider advisory groups throughout the development process.ResultsNinety-six percent of women who used the tool in pilot testing reported that it helped them choose a method, and qualitative interviews indicated acceptability of the tool’s content and presentation. Compared to the control group, women who used the tool demonstrated trends toward increased likelihood of complete satisfaction with their method. Participant responses to cognitive testing were used in tool refinement.ConclusionOur decision support tool appears acceptable to women in the family planning setting.Practice implicationsFormative evaluation of the tool supports its utility among patients making contraceptive decisions, which can be further evaluated in a randomized controlled trial.     

Feasibility,acceptability, and effectiveness of a decision aid versus an informational website to promote clinical trial decision-making among cancer patients: A pilot randomized controlled trial

ObjectiveTo assess intervention feasibility and acceptability, and compare the effectiveness of the CHOICES Decision Aid (DA) versus the National Cancer Institute (NCI) Cancer Clinical Trials (CCT) website to improve knowledge about CCTs and preparedness to make an informed decision.MethodsOncology patients (n = 101) with a scheduled clinic visit were enrolled and randomized. Decision-making variables were collected at two timepoints. Post-intervention scores were examined via paired t-tests and multivariate regression analyses. Predictors of the magnitudes of the change in scores were examined in multivariable regression analyses.ResultsThe interventions were feasible to implement and acceptable to participants. Both interventions increased objective and subjective knowledge, improved clarity of opinions, and reduced decisional conflict (p-values < 0.01). Improvements in the belief that one could find out about CCTs were observed in the CHOICES DA arm (p < 0.001). Multivariable analyses controlling for educational attainment showed no significant differences in the magnitude of change in outcome variables between intervention arms, but did find that improvements in some variables in the NCI arm – but not CHOICES DA arm – were associated with previous educational attainment.ConclusionsInterventions were feasible to implement and acceptable. Improvements in knowledge and decision-making outcomes were observed in both arms, supporting the view that interventions to improve CCT decision making are effective and feasible. Our results suggest that the CHOICES DA may be more effective than an informational website in improving decision-making outcomes regardless of participants’ educational attainment.Practice implicationsCCT resources should support informed decision-making among all cancer survivors, regardless of educational attainment.     

The processes leading to deception: ERP spatiotemporal principal component analysis and source analysis

The cognitive and neural mechanisms leading to deception were studied by the event-related brain potential (ERP) technique. In a simulated deception situation with graded monetary incentives, participants made a decision to lie or be truthful in each trial and held their response until a delayed imperative signal was presented. Spatiotemporal principal component analysis (PCA) and source analysis revealed that brain activities dominant in the left lateral frontal area approximately 800–1,000 ms post-stimulus and over the central-frontal-parietal and right frontal areas after 1,300 ms were significantly more negative in the deceptive condition than in the truthful condition. These results suggest that two serial cognitive processes, decision making and response preparation, are related to deliberate deception.     

决策树在天津市某区公务员健康状况影响因素分析中的应用

目的了解天津市某区公务员健康状况的影响因素,为提高该人群的健康水平提供依据。方法于2008年9-12月,采用整群抽样的方法抽取天津市某区部分公务员,发放问卷740份,进行健康状况和相关影响因素的问卷调查。利用705份有效问卷,应用SAS8.2 Enterprise Miner模块建立决策树模型,对该区公务员人群的健康状况影响因素进行分析和预测。结果该区公务员总体患病率为47.0%,患病率较高的前4种疾病为高血压(17.87%),高血脂(17.73%),脂肪肝(15.89%),颈、腰椎疾病(12.77%)。决策树筛检出的健康状况影响危险因素(重要性)包括年龄大(1.0000)、吸烟(0.8359)、不按时吃饭(0.7972)、心理健康分值低(0.5860)、体质指数高(0.4748)、被动吸烟(0.3673)、教育系统公务员(0.2876)、文化程度高(0.2832)、饮酒(0.1365);保护性因素(重要性)包括充足的睡眠时间(0.3873)、充足的体育锻炼时间(0.2845)、女性(0.2636)、亚健康分值低(0.2364)。决策树模型ROC曲线下面积为0.8881(95%CI:0.8643～0.9119),预测的准确度为80%。结论公务员人群健康状况不容乐观,各种慢性病患病率较高,是今后开展健康管理的重点群体。     

Online scheduling of pick-up and delivery tasks in hospitals

ObjectiveThe aim of this study was to develop an algorithm for scheduling pick-up and delivery tasks in hospitals. The number of jobs and the dynamic nature of the problem, in having jobs arriving over time, makes the use of information technology indispensable. An optimized scheduling for all types of transportation tasks occurring in a hospital accelerates medical procedures, and reduces the patient’s waiting time and costs.MethodsIn the design of the algorithm we use techniques from classical scheduling theory. In addition, due to some special properties and constraints, we model the problem using methods from graph theory. The resulting algorithm combines both approaches in a transparent manner.ConclusionsTo optimize the schedules, we define the average weighted flow time as an objective function that corresponds to a measure for the task throughput. An evaluation of the algorithm at the Natters State Hospital in Austria shows that it has a superior performance than the current scheduling mechanism.     

基于前列腺影像报告和数据系统第2版的机器学习模型诊断高级别前列腺癌

目的 建立基于前列腺影像报告和数据系统第2版（PI-RADS v2）的支持向量机（SVM）、决策树（DT）和Logistic回归3种机器学习模型,评价上述模型对高级别前列腺癌的诊断价值。方法 回顾性分析于我院接受前列腺多参数MR扫描并取得病理结果的194例患者的资料,其中高级别癌63例,非高级别癌131例。将评价因素（PI-RADS v2评分、年龄、游离前列腺特异抗原、前列腺特异性抗原比值、前列腺特异抗原密度）录入SVM、DT和Logistic回归3种机器学习模型进行诊断,通过ROC曲线评价PI-RADS v2评分和3种机器学习模型诊断高级别前列腺癌的价值。结果 PI-RADS v2、SVM、DT和Logistic回归模型诊断高级别前列腺癌的敏感度分别为72.73%、69.09%、87.27%和70.91%;特异度分别为87.29%、93.22%、93.22%和95.76%。DT模型诊断高级别前列腺癌ROC的AUC（AUC=0.90,P<0.01）最大,且与PI-RADS v2评分、SVM、Logistic回归比较差异均有统计学意义（P均<0.05）。结论 PI-RADS v2评分、SVM、DT和Logistic回归模型诊断高级别前列腺癌的价值均较好。     

医院信息化:临床决策支持系统构建

临床决策支持系统是医院信息化的一部分,本文提出一种基于电子病历的冠心病临床决策支持系统,对系统的结构及功能进行设计,包括前端显示、数据库模块、服务器功能模块,介绍系统的工作流程。通过该系统可以返回与待诊治病例相似度高的已治愈病例,不仅有助于医生实现个性化诊疗,同时对临床路径的发展具有推动作用。     

基于商业智能的区域卫生综合辅助决策支持系统建设与应用

为提高卫生管理效率和决策水平,以区域卫生信息平台为基础,基于商业智能的思想创建区域卫生综合辅助决策支持系统,介绍该系统的技术方案、建设内容及在卫生管理中的应用示例。     

模型研究方法在药物经济学中的应用概述

摘 要 目的： 概述国内外药物经济学研究中应用到的模型研究方法,为我国药物经济学研究提供参考。方法: 以近年来国内外发表的文献为依据,进行分析、整理和归纳。结果: 概述各研究模型在药物经济学中的应用方法及注意事项,为我国进行药物经济学研究提供一定的理论及案例支持。结论: 各模型研究方法所针对的研究范围及研究方向各不相同,通过对文献进行综述,讲述了各模型的具体应用方法,为我国开展高质量的药物经济学研究提供参考。