We have previously studied system failures involved in medication errors using a limited number of root cause analyses as source. The aim of this study was to describe a larger number of medication errors with respect to harm, involved medicines and involved system problems - thus providing information for the development of IT-based decision support. We evaluated 3,520 medication error reports derived from 12 months of consecutive reporting from 13 hospitals in the Capital Region of Denmark. We found 0.65% errors with serious harm and 16% with moderate harm. A small number of medicines were involved in the majority of the errors. The problems in the medication error process were heterogeneous. Some were related to specific medicines and others were related to the computerized order entry system. Accordingly decision support targeted at specific medicines and improved IT systems are part of the continuing work to reduce the frequency of medication errors.
The article substantiate the necessity to improve the automatization of the information process in the system of medical support in extreme situations and thus to liquidate the disproportion between the medico-diagnostical and information accumulation storage facilities. These facts clearly define the importance of work which is being carried out by Medical Service towards an elaboration of the "Disaster Medicine" automated information retrieval system (AIRS). The data obtained as a result of AIRS processing could be directly used for reference or prediction purposes.
The effective system for the emergency health care in the disaster or calamity situations presupposes a wide application of computer facilities. The article shows the possibilities towards the improvement of medical support with the help of the disaster medicine information dissemination system. The authors give the main functional characteristics of this system which could make it possible to optimize the health care to the wounded and to make a correct distribution of assets.
BACKGROUND: The Two-Pool Glucose (TPG) model has an important role to play in diabetes research since it enables analysis of data obtained from the frequently sampled labeled (hot) glucose tolerance test (FSHGT). TPG modeling allows determination of the separate effects of insulin on the disposal of glucose and on the hepatic production of glucose. It therefore provides a basis for the accurate estimation of glucose effectiveness, insulin sensitivity, and the profile of the rate of endogenous glucose production. Until now, there has been no program available dedicated to the TPG model, and a number of technical reasons have deterred researchers from performing TPG analysis. METHODS AND RESULTS: In this paper, we describe AKA-TPG, a new program that combines automatic kinetic analysis of the TPG model data with database technologies. AKA-TPG enables researchers who have no expertise in modeling to quickly fit the TPG model to individual FSHGT data sets consisting of plasma concentrations of unlabeled glucose, labeled glucose, and insulin. Most importantly, because the entire process is automated, parameters are almost always identified, and parameter estimates are accurate and reproducible. AKA-TPG enables the demographic data of hundreds of individual subjects, their individual unlabeled and labeled glucose and insulin data, and each subject's parameters and indices derived from AKA-TPG to be securely stored in, and retrieved from, a database. We describe how the stratification and population analysis tools in AKA-TPG are used and present population estimates of TPG model parameters for young, healthy (without diabetes) Nordic men. CONCLUSION: Researchers now have a practical tool to enable kinetic and epidemiological analysis of TPG data sets.
Public health surveillance applications are central to the collection, analysis and dissemination of disease and health information. As these applications evolve and mature, it is evident that many of these applications must address similar requirements, such as policies, security and flexibility. It is important a software architecture is created to meet these requirements.
We outline the requirements for a public health surveillance application, and define a set of common components to address these requirements. These components are configured to produce services used in the development of public health applications.
A layered software architecture, the ALPHA architecture, has been developed to support the development of public health applications. The architecture has been used to build eleven surveillance applications for the Public Health Agency of Canada in the areas of disease surveillance, survey, distributed data collection and inventory management.
We have found that a software architecture that addresses requirements on policies, security and flexibility facilitates the development of configurable public health applications. By creating this architecture, key success factors, such as reducing cost and time-to-market of applications, adapting to changing surveillance targets and increasing user efficiency are achieved.
This paper aims to present an activity-theoretical method for studying the effects of user participation in IS development.
This method is developed through a case study of the process of designing a diabetes database.
The method consists of a historical analysis of the design process, an ethnographical study of the use of the database, and researcher-driven interventions into the on-going user-producer interaction. In the historical analysis, we study particularly which user groups of the database have influenced the design work and which perspectives need to be incorporated into the design in the near future. An analytical model consisting of perspectives on local design, particular technology, and societal domain is introduced as a conceptual tool for this analysis. We also introduce the possibility of employing the historical analysis in guiding an ethnographical study of the user sites and researcher-driven interventions, which provide the participants with tools for improving their design process.
This paper reports on the usefulness of a responsive evaluation model in evaluating the clinical skills assessment and training (CSAT) programme at the Faculty of Medicine, Memorial University of Newfoundland, Canada. The purpose of this paper is to introduce the responsive evaluation approach, ascertain its utility, feasibility, propriety and accuracy in a medical education context, and discuss its applicability as a model for medical education programme evaluation.
Robert Stake's original 12-step responsive evaluation model was modified and reduced to five steps, including: (1) stakeholder audience identification, consultation and issues exploration; (2) stakeholder concerns and issues analysis; (3) identification of evaluative standards and criteria; (4) design and implementation of evaluation methodology; and (5) data analysis and reporting. This modified responsive evaluation process was applied to the CSAT programme and a meta-evaluation was conducted to evaluate the effectiveness of the approach.
The responsive evaluation approach was useful in identifying the concerns and issues of programme stakeholders, solidifying the standards and criteria for measuring the success of the CSAT programme, and gathering rich and descriptive evaluative information about educational processes. The evaluation was perceived to be human resource dependent in nature, yet was deemed to have been practical, efficient and effective in uncovering meaningful and useful information for stakeholder decision-making.
Responsive evaluation is derived from the naturalistic paradigm and concentrates on examining the educational process rather than predefined outcomes of the process. Responsive evaluation results are perceived as having more relevance to stakeholder concerns and issues, and therefore more likely to be acted upon. Conducting an evaluation that is responsive to the needs of these groups will ensure that evaluative information is meaningful and more likely to be used for programme enhancement and improvement.
Most patients with symptomatic acute myocardial infarction (AMI), the leading cause of death in western industrialized nations, use the emergency department (ED) as their point of entry. Yet, one identified barrier to early recognition of patients with AMI is ED overcrowding. In this paper, the author presents a quality improvement model that applies Lean Six Sigma guidelines to the clinical setting.
Children with cancer experience many symptoms and problems that often remain unreported and untreated. We therefore, developed PedsChoice, a support system for pediatric cancer symptom assessment and management to provide children with a "voice," and assist nurses and physicians to better address children's symptoms and problems in patient care. We used participatory design techniques where healthy children joined our design team. During this process we explored the role s healthy children can appropriately play to inform the design of a system for children with cancer and their contributions and limitations as participants in the design process. We found that healthy children can contribute considerably in the role as testers, informers and to some extent as partners. Children have very creative design ideas that can considerably improve the software. However, system development for seriously ill children also requires psychological and pedagogical insights and design and usability expertise. This limits the role children can play as full design partners.