6,259 research outputs found
Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain
Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of other DSSs that translate written guidelines into actionable, real-time clinical recommendations.http://deepblue.lib.umich.edu/bitstream/2027.42/78267/1/1748-5908-5-26.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/2/1748-5908-5-26.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/3/1748-5908-5-26-S3.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/4/1748-5908-5-26-S2.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/5/1748-5908-5-26-S1.TIFFPeer Reviewe
A systematic review of speech recognition technology in health care
BACKGROUND To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns.Funding for this study was provided by the University of Western Sydney.
NICTA is funded by the Australian Government through the Department of
Communications and the Australian Research Council through the ICT
Centre of Excellence Program. NICTA is also funded and supported by the
Australian Capital Territory, the New South Wales, Queensland and Victorian
Governments, the Australian National University, the University of New South
Wales, the University of Melbourne, the University of Queensland, the
University of Sydney, Griffith University, Queensland University of
Technology, Monash University and other university partners
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Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network.
PurposeTo assess feasibility of training a convolutional neural network (CNN) to automate liver segmentation across different imaging modalities and techniques used in clinical practice and apply this to enable automation of liver biometry.MethodsWe trained a 2D U-Net CNN for liver segmentation in two stages using 330 abdominal MRI and CT exams acquired at our institution. First, we trained the neural network with non-contrast multi-echo spoiled-gradient-echo (SGPR)images with 300 MRI exams to provide multiple signal-weightings. Then, we used transfer learning to generalize the CNN with additional images from 30 contrast-enhanced MRI and CT exams.We assessed the performance of the CNN using a distinct multi-institutional data set curated from multiple sources (n = 498 subjects). Segmentation accuracy was evaluated by computing Dice scores. Utilizing these segmentations, we computed liver volume from CT and T1-weighted (T1w) MRI exams, and estimated hepatic proton- density-fat-fraction (PDFF) from multi-echo T2*w MRI exams. We compared quantitative volumetry and PDFF estimates between automated and manual segmentation using Pearson correlation and Bland-Altman statistics.ResultsDice scores were 0.94 ± 0.06 for CT (n = 230), 0.95 ± 0.03 (n = 100) for T1w MR, and 0.92 ± 0.05 for T2*w MR (n = 169). Liver volume measured by manual and automated segmentation agreed closely for CT (95% limit-of-agreement (LoA) = [-298 mL, 180 mL]) and T1w MR (LoA = [-358 mL, 180 mL]). Hepatic PDFF measured by the two segmentations also agreed closely (LoA = [-0.62%, 0.80%]).ConclusionsUtilizing a transfer-learning strategy, we have demonstrated the feasibility of a CNN to be generalized to perform liver segmentations across different imaging techniques and modalities. With further refinement and validation, CNNs may have broad applicability for multimodal liver volumetry and hepatic tissue characterization
Service Platform for Converged Interactive Broadband Broadcast and Cellular Wireless
A converged broadcast and telecommunication
service platform is presented that is able to create, deliver, and
manage interactive, multimedia content and services for consumption
on three different terminal types. The motivations of
service providers for designing converged interactive multimedia
services, which are crafted for their individual requirements, are
investigated. The overall design of the system is presented with
particular emphasis placed on the operational features of each
of the sub-systems, the flows of media and metadata through the
sub-systems and the formats and protocols required for inter-communication
between them. The key features of tools required for
creating converged interactive multimedia content for a range of
different end-user terminal types are examined. Finally possible
enhancements to this system are discussed. This study is of particular
interest to those organizations currently conducting trials
and commercial launches of DVB-H services because it provides
them with an insight of the various additional functions required
in the service provisioning platforms to provide fully interactive
services to a range of different mobile terminal types
A new topology of the HK97-like fold revealed in Bordetella bacteriophage by cryoEM at 3.5 A resolution.
Bacteriophage BPP-1 infects and kills Bordetella species that cause whooping cough. Its diversity-generating retroelement (DGR) provides a naturally occurring phage-display system, but engineering efforts are hampered without atomic structures. Here, we report a cryo electron microscopy structure of the BPP-1 head at 3.5 Å resolution. Our atomic model shows two of the three protein folds representing major viral lineages: jellyroll for its cement protein (CP) and HK97-like ('Johnson') for its major capsid protein (MCP). Strikingly, the fold topology of MCP is permuted non-circularly from the Johnson fold topology previously seen in viral and cellular proteins. We illustrate that the new topology is likely the only feasible alternative of the old topology. β-sheet augmentation and electrostatic interactions contribute to the formation of non-covalent chainmail in BPP-1, unlike covalent inter-protein linkages of the HK97 chainmail. Despite these complex interactions, the termini of both CP and MCP are ideally positioned for DGR-based phage-display engineering. DOI: http://dx.doi.org/10.7554/eLife.01299.001
Understanding smart contracts as a new option in transaction cost economics
Among different concepts associated with the term blockchain, smart contracts have been a prominent one, especially popularized by the Ethereum platform. In this study, we unpack this concept within the framework of Transaction Cost Economics (TCE). This institutional economics theory emphasizes the role of distinctive (private and public) contract law regimes in shaping firm boundaries. We propose that widespread adoption of the smart contract concept creates a new option in public contracting, which may give rise to a smart-contract-augmented contract law regime. We discuss tradeoffs involved in the attractiveness of the smart contract concept for firms and the resulting potential for change in firm boundaries. Based on our new conceptualization, we discuss potential roles the three branches of government – judicial, executive, and legislative – in enabling and using this new contract law regime. We conclude the paper by pointing out limitations of the TCE perspective and suggesting future research directions
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