...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>BMC Medical Informatics and Decision Making >Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis
【24h】

Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

机译：SOVAT的评估：用于社区健康评估数据分析的OLAP-GIS决策支持系统

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p Conclusion Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis.
机译：背景社区健康评估（CHA）中的数据分析涉及大型数值和空间数据集的收集，集成和分析，以便确定健康优先事项。地理信息系统（GIS）允许使用空间数据进行管理和分析，但是由于其传统的数据库体系结构，在执行数字数据分析方面存在局限性。在线分析处理（OLAP）是一个多维数据仓库，旨在方便查询大型数值数据。将GIS的空间功能与OLAP数值分析相结合，可能会增强CHA数据分析。 OLAP-GIS系统是由大学研究人员和公司开发的，但是对于CHA数据分析的潜力还知之甚少。为了评估OLAP-GIS决策支持系统解决CHA问题的潜力，我们将OLAP-GIS与许多公共卫生专业人员当前使用的标准信息技术（IT）进行了比较。方法将匹兹堡大学开发的OLAP-GIS决策支持系统SOVAT与当前IT进行比较，以进行CHA数据分析。对于本研究，当前的IT被认为是SPSS和GIS（“ SPSS-GIS”）的组合使用。招募了匹兹堡大学的研究生，研究人员和健康科学系。每个回合包括：评估系统的教学视频，两个练习任务，五个评估任务和一个研究后问卷。客观和主观的度量包括：任务完成时间，回答任务是否成功以及系统满意度。结果13人参加。使用线性混合模型分析来分析推断统计量。对于SPSS-GIS，SOVAT在满意度和时间上均具有统计学意义（α= .01）（p结论与SPSS和GIS的组合使用相比，使用SOVAT可以更高效地完成任务，成功率更高，满意度更高这项研究的结果表明，OLAP-GIS决策支持系统有可能成为CHA数据分析的宝贵工具。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号