Enhancing laboratory report contents to improve outpatient management of test results

In today''s environment, providers are extremely time-constrained. Assembling relevant contextual data to make decisions on laboratory results can take a significant amount of time from the day. The Regenstrief Institute has created a system which leverages data within Indiana Health Information Exchange''s (IHIE''s) repository, the Indiana Network for Patient Care (INPC), to provide well-organized and contextual information on returning laboratory results to outpatient providers. The system described here uses data extracted from INPC to add historical test results, medication-dispensing events, visit information, and clinical reminders to traditional laboratory result reports. These “Enhanced Laboratory Reports” (ELRs) are seamlessly delivered to outpatient practices connected through IHIE via the DOCS4DOCS clinical messaging service. All practices, including those without electronic medical record systems, can receive ELRs. In this paper, the design and implementation issues in creating this system are discussed, and generally favorable preliminary results of attitudes by providers towards ELRs are reported.     

Fisher information matrix for nonlinear mixed effects multiple response models: Evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model

We focus on the Fisher information matrix used for design evaluation and optimization in nonlinear mixed effects multiple response models. We evaluate the appropriateness of its expression computed by linearization as proposed for a single response model. Using a pharmacokinetic–pharmacodynamic (PKPD) example, we first compare the computation of the Fisher information matrix with approximation to one derived from the observed matrix on a large simulation using the stochastic approximation expectation–maximization algorithm (SAEM). The expression of the Fisher information matrix for multiple responses is also evaluated by comparison with the empirical information obtained through a replicated simulation study using the first‐order linearization estimation methods implemented in the NONMEM software (first‐order (FO), first‐order conditional estimate (FOCE)) and the SAEM algorithm in the MONOLIX software. The predicted errors given by the approximated information matrix are close to those given by the information matrix obtained without linearization using SAEM and to the empirical ones obtained with FOCE and SAEM. The simulation study also illustrates the accuracy of both FOCE and SAEM estimation algorithms when jointly modelling multiple responses and the major limitations of the FO method. This study highlights the appropriateness of the approximated Fisher information matrix for multiple responses, which is implemented in PFIM 3.0, an extension of the R function PFIM dedicated to design evaluation and optimization. It also emphasizes the use of this computing tool for designing population multiple response studies, as for instance in PKPD studies or in PK studies including the modelling of the PK of a drug and its active metabolite. Copyright © 2009 John Wiley & Sons, Ltd.     

Working‐correlation‐structure identification in generalized estimating equations

Selecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well‐known criterion of QIC for selecting a working correlation structure, and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads us to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study. Copyright © 2008 John Wiley & Sons, Ltd.     

探究医院电子信息交换标准HL7

医药信息学在医学应用中的最大领域就是医院信息系统(Hospital Infornation System,HIS),随着HIS的快速发展,需要我们有一个开放的,统一的HIS开发和交换的标准.HL7是1987年开始发展起来的一个专门规范医疗机构用于临床信息,财务信息和管理信息电子信息交换的标准.它特别适合于解决不同厂商开发的医院信息系统、临床实验室系统及药学信息系统之间的互连问题.HL7在国内的发展刚刚起步,但是我国医疗卫生信息化发展很快,尤其是医疗保险、社区医疗和区域卫生信息系统等,都十分需要标准化的支持,HL7将成为建设这些系统的重要基础和关键技术.     

随机系统的最小熵控制

本文放弃传统的MSE准则,从信息论观点出发,发展了随机系统的一种最小熵(ME)控制方法,并从ME控制的等价性、控制限度、存在性、唯一性及必要条件等方面,研究了ME控制的合理性和实用性。ME方法是一种全局分析法,它不仅包含了MSE和MAP准则,且由于全文在整个推导中并未假定高斯性、线性和非时变等,因而原则上适用于诸如非高斯、非线性、时变等传统方法难以处理的复杂系统;不仅适用于工程系统,将其推广到决策、社会、经济等领域会更为自然和切合实际。     

我国学术期刊如何应对加入WTO后的机遇与挑战

针对目前我国学术期刊的发展现状及存在的问题，探讨入世对学术期刊出版的影响，并对我国学术期刊业如何应对入世的挑战提出相应的发展对策和措施。     

Causality Between the Amplitude and Frequency of Cardiac Oscillations

Using an information-theoretic approach, causality between the systolic amplitude in blood pressure and the frequency of the heart beat was analyzed. Blood pressure and ECG were noninvasively recorded in young, healthy subjects. Three successive measurements were performed: during spontaneous breathing and during paced respiration—at frequencies both higher and lower than that of spontaneous respiration. We demonstrate that the amplitude and frequency of the cardiac rhythm are synchronized for most of the time. The synchronization is stronger during paced respiration at a frequency lower than that of spontaneous breathing. Episodes where the cardiac frequency was driven by the systolic pressure were also detected during slow, paced respiration.     

医院洁净手术室智能监控系统的设计与实现

随着信息技术和自动化技术的发展,实现手术室的智能监控有助于提高工作效率和确保手术安全进行.本文简要介绍了"医院洁净手术室智能监控系统"的设计理念及其相关功能,给出了系统的硬件配置和软件实现.     

医疗设备维护管理信息系统的开发与研究

本文基于C Builder和SQLServer开发平台,介绍了设备维护管理信息系统的开发设计,实施及应用拓展,为医院对医疗设备的维护管理及科学决策作出积极探索。     

On information field of clinical diagnosis

“Field” is a universal phenomenon existing in both nature and society, and determines the existence and significance of all materials or information. The man being has always been generating and carrying a large quantity of life information in his whole life. Each piece of life information has an independent information field. The life information field includes such three subfields as bioinformation field, psychoinformation field and psycho-bioinformation field.The clinical diagnosis information field which is a specific information field within the information field of human activities consists of all information concerning man‘s health. Only after we have cognized and ascertained the clinic diagnosis information field, can we accurately utilize its function to serve the human being.