A Support System for Content-Based Medical Image Retrieval in Object Oriented Databases

This work describes both the concepts used in an Object Manager for storage of medical images as one more data type associated to objects, and a support system developed to offer this kind of tool to medical application developers. The purpose of this work is to support the retrieval of images through queries based on the graphical contents of the stored images. The usual approach uses icons and textual attributes stored with the images to specify the queries. This work uses a novel modeling technique to define the “image data type,” by means of which it is possible to decide, before the query itself, the key data of each image that must be extracted from the image when it is stored in the database, so the search can be accelerated when queries are issued. This approach enables building of expansible systems, where new image processing algorithms can be added easily, using its syntactic representation stored through an Image Meta-schema into the application database schema. This work shows how such a system has been implemented, and also provides a query language used to refer and execute these algorithms from inside the database management system.     

急诊科护士预防和应对压力的体会

目的 :急诊科护士应用相应的压力研究的知识 ,可以缓解自己的工作压力 ,维持满意的护理服务质量。方法 :个人应对策略和组织部门的支持 ,两方面相辅相成 ,相互配合。结果 :通过压力应对策略可以有效地应对急诊科护士的工作压力。结论 :急诊科护士特殊的工作环境决定了特殊的工作压力 ,通过应用压力应对策略 ,缓解护士的工作疲惫感 ,减轻护士的工作压力 ,提高护理服务质量。     

一种基于XML的病人信息快速查询系统

建立基于网络的病人信息查询系统有助于病人或其亲属自主的通过网络设备了解病人的病情以及治疗情况,减少医生回答问题的时间,提高医疗效率。建立这样的信息系统通常有两种方案：建立一个WEB服务器连接数据库服务器或建立一个WEB月艮务器和一个延缓同步的数据库服务器。提出一种新的设计方案,即基于XML的病人信息查询系统。与前两种设计方案相比,基于XML的实现方案有以下优点：查询不用访问主数据库,对数据库性能没有影响;不用建立数据库系统,仅需XML自身便可用于查询处理;利用JDOM创建,支持各种数据库字符集;配合XSLT实现快速的查询响应。     

SQL查询技术在全样本处方点评中的应用

目的研究建立可操作性、灵活性和实用性的处方评价方法。方法利用SQL查询技术在医院信息系统中提取特定时间段内的处方信息,对全样本处方数据进行多项指标的统计分析。结果共查询2010年全年处方74 366张,执行Select查询语句7次,统计处方评价核心指标6项。统计结果的真实性和工作效率均大大优于传统统计方法。结论 SQL查询技术可用于全样本处方点评,具有快速准确高效的优点。     

Assisting Consumer Health Information Retrieval with Query Recommendations

ObjectiveHealth information retrieval (HIR) on the Internet has become an important practice for millions of people, many of whom have problems forming effective queries. We have developed and evaluated a tool to assist people in health-related query formation.DesignWe developed the Health Information Query Assistant (HIQuA) system. The system suggests alternative/additional query terms related to the user's initial query that can be used as building blocks to construct a better, more specific query. The recommended terms are selected according to their semantic distance from the original query, which is calculated on the basis of concept co-occurrences in medical literature and log data as well as semantic relations in medical vocabularies.MeasurementsAn evaluation of the HIQuA system was conducted and a total of 213 subjects participated in the study. The subjects were randomized into 2 groups. One group was given query recommendations and the other was not. Each subject performed HIR for both a predefined and a self-defined task.ResultsThe study showed that providing HIQuA recommendations resulted in statistically significantly higher rates of successful queries (odds ratio = 1.66, 95% confidence interval = 1.16–2.38), although no statistically significant impact on user satisfaction or the users' ability to accomplish the predefined retrieval task was found.ConclusionProviding semantic-distance-based query recommendations can help consumers with query formation during HIR.     

Semantic-Enhanced Query Expansion System for Retrieving Medical Image Notes

Most current image retrieval methods require constructing semantic metadata for representing image content. To manually create semantic metadata for medical images is time-consuming, yet it is a crucial component for query expansion. We proposed a new method for searching medical image notes that uses semantic metadata to improve query expansion and leverages a knowledge model developed specifically for the medical image domain to create relevant metadata. We used a syntactic parser and the Unified Medical Language System to analyze the corpus and store text information as semantic metadata in a knowledge model. Our new method has an interactive interface that allows users to provide relevance feedback and construct new queries more efficiently. Sixteen medical professionals evaluated the query expansion module, and each evaluator had prior experience searching for medical images. When using the initial query as the baseline standard, expanded queries achieved a performance boost of 22.6% in terms of the relevance score on first ten results (P-value<0.05). When using Google as another baseline, our system performed 24.6% better in terms of relevance score on the first ten results (P-value<0.05). Overall, 75% of the evaluators said the semantic-enhanced query expansion workflow is logical, easy to follow, and comfortable to use. In addition, 62% of the evaluators preferred using our system instead of Google. Evaluators who were positive about our system found the knowledge map-based visualization of candidate medical search terms helpful in refining cases from the initial search results.     

An audit of job application forms in response to adverts in the British Medical Journal

Objective: The aim of this study was to examine the speed of response of human resources departments to requests for job application forms for posts advertised in the British Medical Journal (BMJ). Of particular interest was the closing date for applications, postage cost, and the period to reply. Design: Twenty posts were randomly selected and application forms requested by telephone and then 20 by letter on two separate dates from the BMJ Classified (issues of 21 July 2001 and 28 July 2001). During the first week the forms were requested by telephone on receipt of the BMJ (Friday afternoon). During the second week the forms were requested by first class post. All letters were sent out on Saturday morning. Outcome measures: The date of receipt of the application form/information pack, the cost of postage, and the closing date for application were recorded for each position. Results: Fifteen forms were received after the telephone application and 18 forms after the letter applications. One trust sent two replies spaced one week apart for the same job and two replies contained job application forms for the wrong job. The response rates to telephone requests varied from four to 10 days and by letter from three to 12 days. The minimum time between the reply being received and the closing date was one day, and the maximum 21 days. The time between the closing date for applications and the start date of the job varied from minus one week (closing date before advertisement) to three months. Thirteen replies gave no indication of the start date of the job. The cost of postage varied from 27p to £1.90. Thirty one trusts used first class postage. Conclusion: There is very limited scope to return job application forms on time, and significant delays in sending out application forms and information packs compound this problem. It is recommended that trust human resources departments place advertisements early and respond promptly to requests for application forms.     

基于互联网的生殖健康指导系统的建立

目的：通过“基于ASP模式的优生优育信息服务平台”的开发,实现对生殖健康部分环节的自动化管理和指导。方法：以调查问卷的方式扶取夫妇双方的相关信息,通过一定的分类、查询等逻辑运算分拣出异常信息,并针对这些片常信息根据医学专业知识对使用者给出必要的建议,并运用客服电话、手机短信、电子邮件等方式实现其服务拓展功能,通过对客户的管理和销售统计两大功能实现对市场营销的管理。结果：开发出的系统通过针对性的指导数据库从时间牛物学、遗传医学、妇产科学、心理学、营养学、运动医学、予员防医学等专业角度对夫妇生殖健康问题给出一份具有针对性的个性化指导报告。结论：经过1年的市场运行,证明该系统的运营模式现实可行,内容合理丰富,达到了对生殖健康进行管理和指导的目的。     

医疗安全不良事件内部报告系统设计与实现

目的：设计并开发一套医疗安全不良事件内部报告系统,监控和管理医院内部医疗安全不良事件。方法：基于Java语言开发B／S架构的web应用程序,实现不良事件的上报、查询等功能。结果：医务人员通过系统及时上报医疗不良事件,管理人员根据汇总的数据进行统计分析并将信息反馈与分享。结论：该系统的运行提高了不良事件的上报效率,对提高医院医疗服务质量,保障患者安全方面有着积极意义。     

Federated Querying Architecture with Clinical &; Translational Health IT Application

We present a software architecture that federates data from multiple heterogeneous health informatics data sources owned by multiple organizations. The architecture builds upon state-of-the-art open-source Java and XML frameworks in innovative ways. It consists of (a) federated query engine, which manages federated queries and result set aggregation via a patient identification service; and (b) data source facades, which translate the physical data models into a common model on-the-fly and handle large result set streaming. System modules are connected via reusable Apache Camel integration routes and deployed to an OSGi enterprise service bus. We present an application of our architecture that allows users to construct queries via the i2b2 web front-end, and federates patient data from the University of Utah Enterprise Data Warehouse and the Utah Population database. Our system can be easily adopted, extended and integrated with existing SOA Healthcare and HL7 frameworks such as i2b2 and caGrid.     

危重症临床监护信息系统的应用特点和支撑条件

危重症临床监护信息系统能自动采集监护仪上的生命体征，确认和转换医嘱，准确记录患者的出入量，预先做好模板方便病情描述，查询病历资料，实现病历电子化存储。系统监护仪要有数据输出接口，系统和医院信息无缝连接．系统的整体结构布局。     

semCDI: A Query Formulation for Semantic Data Integration in caBIG

Objectives

To develop mechanisms to formulate queries over the semantic representation of cancer-related data services available through the cancer Biomedical Informatics Grid (caBIG).

Design

The semCDI query formulation uses a view of caBIG semantic concepts, metadata, and data as an ontology, and defines a methodology to specify queries using the SPARQL query language, extended with Horn rules. semCDI enables the joining of data that represent different concepts through associations modeled as object properties, and the merging of data representing the same concept in different sources through Common Data Elements (CDE) modeled as datatype properties, using Horn rules to specify additional semantics indicating conditions for merging data.

Validation

In order to validate this formulation, a prototype has been constructed, and two queries have been executed against currently available caBIG data services.

Discussion

The semCDI query formulation uses the rich semantic metadata available in caBIG to build queries and integrate data from multiple sources. Its promise will be further enhanced as more data services are registered in caBIG, and as more linkages can be achieved between the knowledge contained within caBIG''s NCI Thesaurus and the data contained in the Data Services.

Conclusion

semCDI provides a formulation for the creation of queries on the semantic representation of caBIG. This constitutes the foundation to build a semantic data integration system for more efficient and effective querying and exploratory searching of cancer-related data.     

The use of relational database commands in retrieval of pedigree information

Genetic research frequently requires retrieval of information about families afflicted with some genetic disease. These queries may involve simple retrieval of information on individuals with particular attributes or finding data from sibships or families who meet some set of criteria. Although the former case may be handled by almost any file management system, the latter case cannot be easily managed since family relationships are necessary to the query. These family relationships are normally stored by means of a pointer system that links the record of each individual with those of his parents. Given such a pointer system, the standard commands of a relational database system can be used to perform such retrievals, thus diminishing the need for special programs to perform such queries.     

Refining Boolean queries to identify relevant studies for systematic review updates

ObjectiveSystematic reviews are important in health care but are expensive to produce and maintain. The authors explore the use of automated transformations of Boolean queries to improve the identification of relevant studies for updates to systematic reviews.Materials and MethodsA set of query transformations, including operator substitution, query expansion, and query reduction, were used to iteratively modify the Boolean query used for the original systematic review. The most effective transformation at each stage is identified using information about the studies included and excluded from the original review. A dataset consisting of 22 systematic reviews was used for evaluation. Updated queries were evaluated using the included and excluded studies from the updated version of the review. Recall and precision were used as evaluation measures.ResultsThe updated queries were more effective than the ones used for the original review, in terms of both precision and recall. The overall number of documents retrieved was reduced by more than half, while the number of relevant documents found increased by 10.3%.ConclusionsIdentification of relevant studies for updates to systematic reviews can be carried out more effectively by using information about the included and excluded studies from the original review to produce improved Boolean queries. These updated queries reduce the overall number of documents retrieved while also increasing the number of relevant documents identified, thereby representing a considerable reduction in effort required by systematic reviewers.     

A System for Multiattribute Drug Product Comparison

We describe a system for multiattribute drug product searching. We then demonstrate the system's performance on sample queries, and evaluate the name-based similarity searching component. Ten drug names were used to query a database of existing drug names using five different retrieval methods. Retrieved names were merged into master lists and presented to 15 pharmacists. Pharmacists rated the similarity between the query name and each retrieved names on a scale of 1–5. We report the precision of our five different retrieval methods at 11 levels of recall. The best single measure was editex, with a precision of 17.4% averaged across 11 levels of recall. A regression model using four objective measures of similarity as predictors accounted for 40.6% of the variance in observed mean similarity ratings. Automated, multiattribute drug product searching may improve the effectiveness and efficiency of preapproval screening processes and thereby prevent medication errors.     

用信息技术推动中药材GAP的实施

中药材生产质量管理规范(GAP)在中药实现现代化、国际化的进程中起着非常重要的作用。GAP的实施是一个十分困难的系统工程,它不仅依赖于企业自身,也依赖于社会大环境。就企业而言,良好的基地生态环境、优良的道地药材种质、科学的标准操作程序(SOP)是三项基础,队伍建设是核心,制度管理是保障,而信息技术则可以成为整个体系的重要支柱。江西樟树GAP种植示范基地的GAP实施支撑系统就是用信息化推动GAP实施的一个尝试。该系统由5个子系统构成,即基于手机短信息和Web的信息互动平台,基于SOP工作流的GAP实施监控与管理子系统,GAP生态环境监测子系统,GAP实施全过程风貌展示子系统和数据分析、数据挖掘子系统。系统的目标就是用信息技术来支撑GAP的实施,使GAP实施能“真实、有效、稳定、可控”。     

Query Health: standards-based,cross-platform population health surveillance

Objective

Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects.

Materials and methods

Query Health defined a standards-based approach for distributed population health queries, using an ontology based on the Quality Data Model and Consolidated Clinical Document Architecture, Health Quality Measures Format (HQMF) as the query language, the Query Envelope as the secure transport layer, and the Quality Reporting Document Architecture as the result language.

Results

We implemented this approach using Informatics for Integrating Biology and the Bedside (i2b2) and hQuery for data analytics and PopMedNet for access control, secure query distribution, and response. We deployed the reference implementation at three pilot sites: two public health departments (New York City and Massachusetts) and one pilot designed to support Food and Drug Administration post-market safety surveillance activities. The pilots were successful, although improved cross-platform data normalization is needed.

Discussions

This initiative resulted in a standards-based methodology for population health queries, a reference implementation, and revision of the HQMF standard. It also informed future directions regarding interoperability and data access for ONC''s Data Access Framework initiative.

Conclusions

Query Health was a test of the learning health system that supplied a functional methodology and reference implementation for distributed population health queries that has been validated at three sites.     

Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval

With the increasing amount of medical data available on the Web, looking for health information has become one of the most widely searched topics on the Internet. Patients and people of several backgrounds are now using Web search engines to acquire medical information, including information about a specific disease, medical treatment or professional advice. Nonetheless, due to a lack of medical knowledge, many laypeople have difficulties in forming appropriate queries to articulate their inquiries, which deem their search queries to be imprecise due the use of unclear keywords. The use of these ambiguous and vague queries to describe the patients’ needs has resulted in a failure of Web search engines to retrieve accurate and relevant information. One of the most natural and promising method to overcome this drawback is Query Expansion. In this paper, an original approach based on Bat Algorithm is proposed to improve the retrieval effectiveness of query expansion in medical field. In contrast to the existing literature, the proposed approach uses Bat Algorithm to find the best expanded query among a set of expanded query candidates, while maintaining low computational complexity. Moreover, this new approach allows the determination of the length of the expanded query empirically. Numerical results on MEDLINE, the on-line medical information database, show that the proposed approach is more effective and efficient compared to the baseline.     

Brief communication: External phenome analysis enables a rational federated query strategy to detect changing rates of treatment-related complications associated with multiple myeloma

Electronic health records (EHRs) are increasingly useful for health services research. For relatively uncommon conditions, such as multiple myeloma (MM) and its treatment-related complications, a combination of multiple EHR sources is essential for such research. The Shared Health Research Information Network (SHRINE) enables queries for aggregate results across participating institutions. Development of a rational search strategy in SHRINE may be augmented through analysis of pre-existing databases. We developed a SHRINE query for likely non-infectious treatment-related complications of MM, based upon an analysis of the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database. Using this query strategy, we found that the rate of likely treatment-related complications significantly increased from 2001 to 2007, by an average of 6% a year (p=0.01), across the participating SHRINE institutions. This finding is in keeping with increasingly aggressive strategies in the treatment of MM. This proof of concept demonstrates that a staged approach to federated queries, using external EHR data, can yield potentially clinically meaningful results.