Bmc Med Inform Decis
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Bmc Med Inform Decis · Jan 2010
A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay.
Patients with a prolonged intensive care unit (ICU) length of stay account for a disproportionate amount of resource use. Early identification of patients at risk for a prolonged length of stay can lead to quality enhancements that reduce ICU stay. This study developed and validated a model that identifies patients at risk for a prolonged ICU stay. ⋯ A model that uses patient data from ICU days 1 and 5 accurately predicts a prolonged ICU stay. These predictions are more accurate than those based on ICU day 1 data alone. The model can be used to benchmark ICU performance and to alert physicians to explore care alternatives aimed at reducing ICU stay.
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Bmc Med Inform Decis · Jan 2010
Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score.
Murray score is the result of an equation that gives all its variables the same linear contribution and weight and makes use of consented cut-offs. Everyday physicians' vocabulary is full of terms (adjectives) like: little, small, low, high, etc. that they handle in an intuitive and not always linear way to make therapeutic decisions. The purpose of this paper is to develop a fuzzy logic (FL) vision of Murray's score variables to enable the measurement of physicians' knowledge, experience and intuition in diagnosing lung injury and test if they followed Murray's equation predictions. ⋯ The contiguous categories of the variables confirm the existence of fuzzy frontiers. An overestimation was found in the surveyed group's interpretation of severity. This overestimation was mainly due to the different weight assigned to PO2/FiO2 and chest film variables. The FL approach made it possible to measure knowledge, experience and intuition as they appear in physicians' thinking. FL methodology could overcome a series of restrictions that current tests have due to cut-offs.
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Bmc Med Inform Decis · Jan 2010
ReviewA knowledge-based taxonomy of critical factors for adopting electronic health record systems by physicians: a systematic literature review.
The health care sector is an area of social and economic interest in several countries; therefore, there have been lots of efforts in the use of electronic health records. Nevertheless, there is evidence suggesting that these systems have not been adopted as it was expected, and although there are some proposals to support their adoption, the proposed support is not by means of information and communication technology which can provide automatic tools of support. The aim of this study is to identify the critical adoption factors for electronic health records by physicians and to use them as a guide to support their adoption process automatically. ⋯ The critical adoption factors established here provide a sound theoretical basis for research to understand, support, and facilitate the adoption of electronic health records to physicians in benefit of patients.
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Bmc Med Inform Decis · Jan 2010
Comparative StudyA bootstrap approach for assessing the uncertainty of outcome probabilities when using a scoring system.
Scoring systems are a very attractive family of clinical predictive models, because the patient score can be calculated without using any data processing system. Their weakness lies in the difficulty of associating a reliable prognostic probability with each score. In this study a bootstrap approach for estimating confidence intervals of outcome probabilities is described and applied to design and optimize the performance of a scoring system for morbidity in intensive care units after heart surgery. ⋯ Scoring systems are often designed solely on the basis of discrimination and generalization characteristics, to the detriment of prediction of a trustworthy outcome probability. The present example demonstrates that using a bootstrap method for the estimation of outcome-probability confidence intervals provides useful additional information about score-class statistics, guiding physicians towards the most convenient model for predicting morbidity outcomes in their clinical context.
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Bmc Med Inform Decis · Jun 2009
Multicenter StudySecurity and privacy requirements for a multi-institutional cancer research data grid: an interview-based study.
Data protection is important for all information systems that deal with human-subjects data. Grid-based systems--such as the cancer Biomedical Informatics Grid (caBIG)--seek to develop new mechanisms to facilitate real-time federation of cancer-relevant data sources, including sources protected under a variety of regulatory laws, such as HIPAA and 21CFR11. These systems embody new models for data sharing, and hence pose new challenges to the regulatory community, and to those who would develop or adopt them. These challenges must be understood by both systems developers and system adopters. In this paper, we describe our work collecting policy statements, expectations, and requirements from regulatory decision makers at academic cancer centers in the United States. We use these statements to examine fundamental assumptions regarding data sharing using data federations and grid computing. ⋯ The findings suggest that with additional work, large scale federated sharing of data within a regulated environment is possible. A key challenge is developing suitable models for authentication and authorization practices within a federated environment. Authentication--the recognition and validation of a person's identity--is in fact a global property of such systems, while authorization - the permission to access data or resources--mimics data sharing agreements in being best served at a local level. Nine specific recommendations result from the work and are discussed in detail. These include: (1) the necessity to construct separate legal or corporate entities for governance of federated sharing initiatives on this scale; (2) consensus on the treatment of foreign and commercial partnerships; (3) the development of risk models and risk management processes; (4) development of technical infrastructure to support the credentialing process associated with research including human subjects; (5) exploring the feasibility of developing large-scale, federated honest broker approaches; (6) the development of suitable, federated identity provisioning processes to support federated authentication and authorization; (7) community development of requisite HIPAA and research ethics training modules by federation members; (8) the recognition of the need for central auditing requirements and authority, and; (9) use of two-protocol data exchange models where possible in the federation.