Journal of the American Medical Informatics Association : JAMIA
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J Am Med Inform Assoc · Dec 2013
Using electronic health records data to identify patients with chronic pain in a primary care setting.
To develop and validate an accurate method to identify patients with chronic pain using electronic health records (EHR) data at a multisite community health center. ⋯ We derived a useful method that combines readily available elements from an EHR to identify chronic pain with high accuracy. This method should prove useful to those interested in identifying chronic pain patients in large datasets for research, evaluation or quality improvement purposes.
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J Am Med Inform Assoc · Dec 2013
Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department.
To evaluate a proposed natural language processing (NLP) and machine-learning based automated method to risk stratify abdominal pain patients by analyzing the content of the electronic health record (EHR). ⋯ Automated appendicitis risk categorization based on EHR content, including information from clinical notes, shows comparable performance to physician chart reviewers as measured by their inter-annotator agreement and represents a promising new approach for computerized decision support to promote application of evidence-based medicine at the point of care.
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J Am Med Inform Assoc · Dec 2013
Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory.
Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded within routine care delivery. While pragmatic clinical trials (PCTs) have been performed for decades, they now can draw on rich sources of clinical and operational data that are continuously fed back to inform research and practice. ⋯ Here, we introduce the Collaboratory, focusing on its Phenotype, Data Standards, and Data Quality Core, and present early observations from researchers implementing PCTs within large healthcare systems. We also identify gaps in knowledge and present an informatics research agenda that includes identifying methods for the definition and appropriate application of phenotypes in diverse healthcare settings, and methods for validating both the definition and execution of electronic health records based phenotypes.
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J Am Med Inform Assoc · Nov 2013
Comparative StudyThree-dimensional morphological and signal intensity features for detection of intervertebral disc degeneration from magnetic resonance images.
Advances in MRI hardware and sequences are continually increasing the amount and complexity of data such as those generated in high-resolution three-dimensional (3D) scanning of the spine. Efficient informatics tools offer considerable opportunities for research and clinically based analyses of magnetic resonance studies. In this work, we present and validate a suite of informatics tools for automated detection of degenerative changes in lumbar intervertebral discs (IVD) from both 3D isotropic and routine two-dimensional (2D) clinical T2-weighted MRI. ⋯ Combination of the novel 3D-based shape and signal intensity features on 3D (area under receiver operating curve (AUC) 0.984) and 2D (AUC 0.988) magnetic resonance data deliver a significant improvement in automated classification of IVD degeneration, compared to the combination of previously used 2D radiological measurement and signal intensity features (AUC 0.976 and 0.983, respectively). Further work is required regarding the usefulness of 2D and 3D shape data in relation to clinical scores of lower back pain. The results reveal the potential of the proposed informatics system for computer-aided IVD diagnosis from MRI in large-scale research studies and as a possible adjunct for clinical diagnosis.
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J Am Med Inform Assoc · Nov 2013
Impact of an electronic medication management system on hospital doctors' and nurses' work: a controlled pre-post, time and motion study.
To quantify and compare the time doctors and nurses spent on direct patient care, medication-related tasks, and interactions before and after electronic medication management system (eMMS) introduction. ⋯ eMMS introduction did not result in redistribution of time away from direct care or towards medication tasks. Work patterns observed on these intervention wards were associated with previously reported significant reductions in prescribing error rates relative to the control wards.