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This study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners.

The goal of this research is to learn how the editorial staffs of bioinformatics and medical informatics journals provide support for cross-community exposure. Models such as co-citation and co-author analysis measure the relationships between researchers; but they do not capture how environments that support knowledge transfer across communities are organized.

Few instruments are available to measure the performance of intensive care unit (ICU) clinical information systems. Our objectives were: 1) to develop a survey-based metric that assesses the automation and usability of an ICU's clinical information system; 2) to determine whether higher scores on this instrument correlate with improved outcomes in a multi-institution quality improvement collaborative.

Hyperglycemia worsens clinical outcomes in critically ill patients. Precise glycemia control using intravenous insulin improves outcomes. To determine if we could improve glycemia control over a previous paper-based, manual protocol, authors implemented, in a surgical intensive care unit (SICU), an intravenous insulin protocol integrated into a care provider order entry (CPOE) system.

Developments in information technology offer new opportunities to design electronic patient record systems (EPR) which integrate a broad range of functions such as clinical decision support, order entry, or electronic alerts. It has been recently suggested that EPR could support new applications for disease surveillance and patient safety. We describe the integration of a voluntary incident reporting system into an EPR used in operating theatres, to allow the reporting of [...]

There are limited data regarding implementing electronic health records (EHR) in underserved settings. We evaluated the implementation of an EHR within the Indian Health Service (IHS), a federally funded health system for Native Americans.

Broadly, to create a bidirectional communication link between public health surveillance and clinical practice. Specifically, to measure the impact of integrating public health surveillance data into an existing clinical prediction rule. We incorporate data about recent local trends in meningitis epidemiology into a prediction model differentiating aseptic from bacterial meningitis.

This document comprises an AMIA Board of Directors approved White Paper that presents a roadmap for national action on clinical decision support. It is published in JAMIA for archival and dissemination purposes. The full text of this material has been previously published on the AMIA Web site (www.amia.org/inside/initiatives/cds). AMIA is the copyright holder.