数据管理在临床研究中的地位和作用

临床研究中的数据管理是指研究者按照临床试验方案规定的流程采集大量的研究数据,并利用数据管理系统建立标准化的数据库,采用计算机技术辅助人工进行数据的逻辑核查、数据疑问产生和处理、数据盲态下审核与锁定等过程.数据管理的目的是用及时、有效、准确的方式为获得科学可靠的临床研究结论提供精确、正确的临床研究数据.     

基于逻辑回归模型的缺血性脑卒中发病率预测研究

介绍基于逻辑回归模型的缺血性脑卒中发病率预测方法及流程，包括收集和清洗数据、构建大数据平台、提取预测特征、构建基于逻辑回归的模型等。通过仿真实验验证该方法的有效性，为脑卒中数据分析、疾病预防提供技术支持。     

《科技资讯》期刊投稿要求及说明

稿件要求1、稿件应具有科学性、先进性和实用性,论点明确、论据可靠、数据准确、逻辑严谨、文字通顺。     

《科技资讯》期刊投稿要求及说明

稿件要求 1、稿件应具有科学性、先进性和实用性,论点明确、论据可靠、数据准确、逻辑严谨、文字通顺。     

全面数据在医院系统的应用

数据的概念可以分为结构化数据和非结构化数据。结构化数据——即行数据，存储在数据库里，可以用二维表结构来逻辑表达实现的数据；非结构化数据——包括所有格式的办公文档、文本、图片、XML、HTML、各类报表、图像和音频，视频信息等等。简单理解结构化数据为数据库数据，非结构化数据为其他离散的数据。     

《中外医疗》投稿说明

1、稿件应具有科学性、先进性和实用性，论点明确、数据准确、逻辑严谨、文字通顺。     

《科技资讯》期刊投稿要求及说明

稿件应具有科学性、先进性和实用性，论点明确、论据可靠、数据准确、逻辑严谨、文字通顺。     

《科技创新导报》稿件要求及投稿说明

稿件要求；稿件应具有科学性、先进性和实用性，论点明确、论据可靠、数据准确，逻辑严谨、文字通顺。     

《科技资讯》期刊投稿要求及说明

稿件要求： 1、稿件应具有科学生、先进性和实用性，论点明确、数据准确、逻辑严谨、文字通顺。     

《科技资讯》期刊投稿要求及说明

稿件要求 1、稿件应具有科学性、先进性和实用性，论点明确、论据可靠、数据准确、逻辑严谨、文字通顺。     

肾移植数据库管理系统

使用集成式软件Gurn开发了一个肾移植信息数据库管理系统。该系统在用户输入正确的指令之后，便能对肾移植病人的有关资料进行编辑、查询和统计学分析等多种处理，并提供了丰富的图形生成和转换、联机提示及自然语言接口等功能，与统计分析模型库及专家系统能有机地组合成集成式肾移植信息管理系统。     

Assessing the quality of clinical and administrative data extracted from hospitals: the General Medicine Inpatient Initiative (GEMINI) experience

ObjectiveLarge clinical databases are increasingly used for research and quality improvement. We describe an approach to data quality assessment from the General Medicine Inpatient Initiative (GEMINI), which collects and standardizes administrative and clinical data from hospitals.MethodsThe GEMINI database contained 245 559 patient admissions at 7 hospitals in Ontario, Canada from 2010 to 2017. We performed 7 computational data quality checks and iteratively re-extracted data from hospitals to correct problems. Thereafter, GEMINI data were compared to data that were manually abstracted from the hospital’s electronic medical record for 23 419 selected data points on a sample of 7488 patients.ResultsComputational checks flagged 103 potential data quality issues, which were either corrected or documented to inform future analysis. For example, we identified the inclusion of canceled radiology tests, a time shift of transfusion data, and mistakenly processing the chemical symbol for sodium (“Na”) as a missing value. Manual validation identified 1 important data quality issue that was not detected by computational checks: transfusion dates and times at 1 site were unreliable. Apart from that single issue, across all data tables, GEMINI data had high overall accuracy (ranging from 98%–100%), sensitivity (95%–100%), specificity (99%–100%), positive predictive value (93%–100%), and negative predictive value (99%–100%) compared to the gold standard.Discussion and ConclusionComputational data quality checks with iterative re-extraction facilitated reliable data collection from hospitals but missed 1 critical quality issue. Combining computational and manual approaches may be optimal for assessing the quality of large multisite clinical databases.     

把好“三关”提高统计数据质量

目的通过把好病历书写、病案首页信息录入与质量核查三关,提高统计数据质量。方法分析病案首页出现的项目填写不全、错误等缺陷,影响和产生的原因。结果提出医护人员、录入员进行培训和加强自校等改进措施。结论切实执行改进措施把好三关,从而提高统计数据质量。     

Study on Management of Examinees After Multiphasic Health Check-Ups

Although the importance of follow-up and detailed examinations following the detection of abnormalities in thorough routine health checks is recognized extensively, marked interfacility variances are seen in the percentage of individuals advised to receive detailed examination, the percentage of individuals who actually receive the recommended detailed examination and the results of detailed examination. On the basis of the survey data collected by the Clinical Preventive Medicine Committee of the Japanese Association of Hospitals and the data collected during thorough routine health checks at our facility, we analyzed the percentage of individuals who were rated as requiring detailed examination and the percentage who actually received the recommended detailed examination, and found that these percentages varied greatly between different facilities. To minimize interfacility differences in these percentages; it seems necessary to review the criteria currently used for evaluation of health check data at individual facilities. To this end, we must discuss quantitative test data and data yielded by diagnostic imaging separately.     

Factors associated with tobacco sales to minors: lessons learned from the FDA compliance checks

CONTEXT: Tobacco products continue to be widely accessible to minors. Between 1997 and 1999, the US Food and Drug Administration (FDA) conducted more than 150,000 tobacco sales age-restriction compliance checks. Data obtained from these checks provide important guidance for curbing illegal sales. OBJECTIVE: To determine which elements of the compliance checks were most highly associated with illegal sales and thereby inform best practices for conducting efficient compliance check programs. DESIGN AND SETTING: Cross-sectional analysis of FDA compliance checks in 110,062 unique establishments in 36 US states and the District of Columbia. MAIN OUTCOME MEASURE: Illegal sales of tobacco to minors at compliance checks; association of illegal sales with variables such as age and sex of the minor. RESULTS: The rate of illegal sales for all first compliance checks in unique stores was 26.6%. Clerk failure to request proof of age was strongly associated with illegal sales (uncorrected sales rate, 10.5% compared with 89.5% sales when proof was not requested; multivariate-adjusted odds ratio [OR], 0.03; 95% confidence interval [CI], 0.03-0.04). Other factors associated with increased illegal sales were employment of older minors to make the purchase attempt (adjusted ORs for 16- and 17-year-old minors compared with 15-year-olds were 1.52 [95% CI, 1.46-1.63] and 2.43 [95% CI, 2.31-2. 59], respectively), attempt to purchase smokeless tobacco (adjusted OR, 2.16 [95% CI, 1.90-2.45] vs cigarette purchase attempts), and performing checks at or after 5 PM (adjusted OR, 1.28 [95% CI, 1. 21-1.35] vs before 5 PM). Female sex of clerk and minor, Saturday checks, type of store (convenience store selling gas, gas station, drugstore, supermarket and general merchandise), and rural store locations also were associated with increased illegal sales. CONCLUSIONS: This analysis found that a request for age verification strongly predicted compliance with the law. The results suggest several ways in which the process of compliance checks might be optimized. JAMA. 2000;284:729-734     

医学院校学报责任编辑工作重点浅析

通过结合作者自身的工作体会，试论在医学院校学报的责任编辑工作中应着重注意积极与审稿专家、本文编辑及作者沟通，形成互补关系，达成一定统一性；提出可通过实行印前内部交叉审读校对，提高编校质量；指出坚持编辑校对工作中的“齐、清、定”原则，重视样刊质检是保证刊物质量的重要环节。并提出医学院校责任编辑应不断对自身能力进行提高，加强素质培养，在工作实践中不断磨练自己，总结出一套适用的经验，将自己训练成一个合格的责任编辑。     

历代方剂成方年代考

目的：依据方源信息确定成方年代，探讨方剂成方年代的分布情况及其产生原因。方法：研究记载方剂的方源信息，建立“方剂来源出处标准表”，采用字符串相似度算法、计算编辑距离进行相似度排序，再加以人工干预的方法，根据首次记载该方剂的书籍成书年代来推算方剂的成方年代。结果：方剂及方书的产生和发展与社会稳定、战乱等规律基本相符，成方年代统计结果较为可靠。结论：这一方法对于确定方剂产生时间，进而推算方药剂量很有意义，对不同历史年代的方剂信息抽取也是一种补充和帮助。     

An interactive clinical data system

A clinical data system is under development at the Upjohn Company that will reduce the time lag from patient visit to data availability, data entry errors, and the amount of training required for system use. The system design allows generality for both the study monitor and the biostatistician, editing of the data before entry, simplified forms design, direct entry of textual responses without coding, and a reduced need for special programs. Interactive subsystems allow a user to describe a study to the system, generate tailor-made entry/edit programs for each study, update the data base, and produce ad hoc reports. The system is being implemented on top of a data base management system and runs on an IBM 370/148 under VM/CMS.     

Increasing trust in real-world evidence through evaluation of observational data quality

ObjectiveAdvances in standardization of observational healthcare data have enabled methodological breakthroughs, rapid global collaboration, and generation of real-world evidence to improve patient outcomes. Standardizations in data structure, such as use of common data models, need to be coupled with standardized approaches for data quality assessment. To ensure confidence in real-world evidence generated from the analysis of real-world data, one must first have confidence in the data itself. Materials and MethodsWe describe the implementation of check types across a data quality framework of conformance, completeness, plausibility, with both verification and validation. We illustrate how data quality checks, paired with decision thresholds, can be configured to customize data quality reporting across a range of observational health data sources. We discuss how data quality reporting can become part of the overall real-world evidence generation and dissemination process to promote transparency and build confidence in the resulting output.ResultsThe Data Quality Dashboard is an open-source R package that reports potential quality issues in an OMOP CDM instance through the systematic execution and summarization of over 3300 configurable data quality checks.DiscussionTransparently communicating how well common data model-standardized databases adhere to a set of quality measures adds a crucial piece that is currently missing from observational research.ConclusionAssessing and improving the quality of our data will inherently improve the quality of the evidence we generate.