Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

From Theory to Intervention: Mapping Theoretically Derived Behavioural Determinants to Behaviour Change Techniques

Theory provides a helpful basis for designing interventions to change behaviour but offers little guidance on how to do this. This paper aims to illustrate methods for developing an extensive list of behaviour change techniques (with definitions) and for linking techniques to theoretical constructs. A list of techniques and definitions was generated from techniques published in two systematic reviews, supplemented by "brainstorming" and a systematic search of nine textbooks used in training applied psychologists. Inter-rater reliability of extracting the techniques and definitions from the textbooks was assessed. Four experts judged which techniques would be effective in changing 11 theoretical constructs associated with behaviour change. Thirty-five techniques identified in the reviews were extended to 53 by brainstorming and to 137 by consulting textbooks. Agreement for the 53 definitions was 74.7 per cent (15.4% cells completed and 59.3% cells empty for both raters). Agreement about the link between the 35 techniques and theoretical constructs was 71.7 per cent of 385 judgments (12.2% agreement that effective and 59.5% agreement that not effective). This preliminary work demonstrates the possibility of developing a comprehensive, reliable taxonomy of techniques linked to theory. Further refinement is needed to eliminate redundancies, resolve uncertainties, and complete technique definitions.Institute of Applied Health Sciences, Chief Scientist Office of the Scottish Government Health Directive, NHS NIHR Academic Unit Fundin

Extracting information from the text of electronic medical records to improve case detection: a systematic review

Background: Electronic medical records (EMRs) are revolutionizing health-related research. One key issue for study quality is the accurate identification of patients with the condition of interest. Information in EMRs can be entered as structured codes or unstructured free text. The majority of research studies have used only coded parts of EMRs for case-detection, which may bias findings, miss cases, and reduce study quality. This review examines whether incorporating information from text into case-detection algorithms can improve research quality. Methods: A systematic search returned 9659 papers, 67 of which reported on the extraction of information from free text of EMRs with the stated purpose of detecting cases of a named clinical condition. Methods for extracting information from text and the technical accuracy of case-detection algorithms were reviewed. Results: Studies mainly used US hospital-based EMRs, and extracted information from text for 41 conditions using keyword searches, rule-based algorithms, and machine learning methods. There was no clear difference in case-detection algorithm accuracy between rule-based and machine learning methods of extraction. Inclusion of information from text resulted in a significant improvement in algorithm sensitivity and area under the receiver operating characteristic in comparison to codes alone (median sensitivity 78% (codes + text) vs 62% (codes), P = .03; median area under the receiver operating characteristic 95% (codes + text) vs 88% (codes), P = .025). Conclusions: Text in EMRs is accessible, especially with open source information extraction algorithms, and significantly improves case detection when combined with codes. More harmonization of reporting within EMR studies is needed, particularly standardized reporting of algorithm accuracy metrics like positive predictive value (precision) and sensitivity (recall)

Study protocol for the Anesthesiology Control Tower—Feedback Alerts to Supplement Treatments (ACTFAST-3) trial: A pilot randomized controlled trial in intraoperative telemedicine [version 1; referees: 2 approved]

Background: Each year, over 300 million people undergo surgical procedures worldwide. Despite efforts to improve outcomes, postoperative morbidity and mortality are common. Many patients experience complications as a result of either medical error or failure to adhere to established clinical practice guidelines. This protocol describes a clinical trial comparing a telemedicine-based decision support system, the Anesthesiology Control Tower (ACT), with enhanced standard intraoperative care. Methods: This study is a pragmatic, comparative effectiveness trial that will randomize approximately 12,000 adult surgical patients on an operating room (OR) level to a control or to an intervention group. All OR clinicians will have access to decision support software within the OR as a part of enhanced standard intraoperative care. The ACT will monitor patients in both groups and will provide additional support to the clinicians assigned to intervention ORs. Primary outcomes include blood glucose management and temperature management. Secondary outcomes will include surrogate, clinical, and economic outcomes, such as incidence of intraoperative hypotension, postoperative respiratory compromise, acute kidney injury, delirium, and volatile anesthetic utilization. Ethics and dissemination: The ACTFAST-3 study has been approved by the Human Resource Protection Office (HRPO) at Washington University in St. Louis and is registered at clinicaltrials.gov (NCT02830126). Recruitment for this protocol began in April 2017 and will end in December 2018. Dissemination of the findings of this study will occur via presentations at academic conferences, journal publications, and educational materials

Determining information for inclusion in a decision-support intervention for clinical trial participation : A modified Delphi approach

Peer reviewedPostprin

Widespread Adoption of Information Technology in Primary Care Physician Offices in Denmark: A Case Study

Describes the use of electronic medical records, standardized clinical communications, and patient identification numbers by Denmark's primary care physicians; a nonprofit organization's role in implementation and certification; and elements of success