J Med Syst
-
Healthcare organisations and governments have invested heavily in electronic health records in anticipation that they will deliver improved health outcomes for consumers and efficiencies across emergency departments. Despite such investment, electronic health records designed to support emergency care have been poorly evaluated. Given the accelerated development and adoption of information technology across healthcare, it is timely that a systematic review of this evidence base is updated in order to drive improvements to design, interoperability and overall clinical utility of electronic health record systems implemented in emergency departments. ⋯ The most frequently reported findings were efficiencies, including reductions in diagnostic tests, imaging and costs. This review is the first to report moderate to significant increases in admission rates are associated with electronic health record use in the emergency department, contrasting the findings of previous reviews. Diversity in the methodology employed across the included studies emphasises the need for further research to examine the impact of electronic health record implementation and system design on the findings reported, in order to ensure return on investment for stakeholders and optimised consumer care.
-
Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including camels, cattle, cats and bats. Animal CoVs, such as Middle East respiratory syndrome-CoV, severe acute respiratory syndrome (SARS)-CoV, and the new virus named SARS-CoV-2, rarely infect and spread among humans. On January 30, 2020, the International Health Regulations Emergency Committee of the World Health Organisation declared the outbreak of the resulting disease from this new CoV called 'COVID-19', as a 'public health emergency of international concern'. ⋯ The reliability and acceptability of extracted information and datasets from implemented technologies in the literature were considered. Findings showed that researchers must proceed with insights they gain, focus on identifying solutions for CoV problems, and introduce new improvements. The growing emphasis on data mining and ML techniques in medical fields can provide the right environment for change and improvement.
-
Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data as graphs. ⋯ Graphs representing individual patients are hardly used in research context, only eleven papers considered such kind of graphs in their investigations. The potential of graph theoretical algorithms, which are already well established, could help increasing this research field, but currently there are too few papers to estimate how this area of research will develop. Altogether, the use of such patient graphs could be a promising technique to develop decision support systems for diagnosis, medication or therapy of patients using similarity measurements or different kinds of analysis.
-
Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data as graphs. ⋯ Graphs representing individual patients are hardly used in research context, only eleven papers considered such kind of graphs in their investigations. The potential of graph theoretical algorithms, which are already well established, could help increasing this research field, but currently there are too few papers to estimate how this area of research will develop. Altogether, the use of such patient graphs could be a promising technique to develop decision support systems for diagnosis, medication or therapy of patients using similarity measurements or different kinds of analysis.
-
A shift in healthcare payment models from volume toward value-based incentives will require deliberate input into systems development from both perioperative clinicians and administrators to ensure appropriate recognition of the value of all services provided-particularly ones that are not reimbursable in current fee-for-service payment models. Time-driven activity-based costing (TDABC) methodology identifies cost drivers and reduces inaccurate costing based on siloed budgets. ⋯ As payment models inevitably evolve towards value-based metrics, it will be critical to knowledgably participate in the coordination of these changes. This document provides 8 practical Recommendations from the Society for Perioperative Assessment and Quality Improvement (SPAQI) aimed at outlining the principles of TDABC, creating process maps for patient workflows, understanding payment structures, establishing physician alignment across service lines to create integrated practice units to facilitate development of evidence-based pathways for specific patient risk groups, establishing consistent care delivery, minimizing variability between physicians and departments, utilizing data analytics and information technology tools to track progress and obtain actionable data, and using TDABC to create costing transparency.