User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Autonomic care platform for optimizing query performance

Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

Challenges in evaluating surgical innovation

Research on surgical interventions is associated with several methodological and practical challenges of which few, if any, apply only to surgery. However, surgical evaluation is especially demanding because many of these challenges coincide. In this report, the second of three on surgical innovation and evaluation, we discuss obstacles related to the study design of randomised controlled trials and non-randomised studies assessing surgical interventions. We also describe the issues related to the nature of surgical procedures—for example, their complexity, surgeon-related factors, and the range of outcomes. Although difficult, surgical evaluation is achievable and necessary. Solutions tailored to surgical research and a framework for generating evidence on which to base surgical practice are essential.The Balliol Colloquium has been supported by Ethicon UK with unrestricted educational grants and by the National Institute of Health Research Health Technology Assessment Programme. The Balliol Colloquium was administratively and financially supported by the Nuffield Department of Surgery at the University of Oxford and the Department of Surgery at McGill University. JAC holds a Medical Research Council UK special training fellowship. The University of Aberdeen’s Health Services Research Unit is core funded by the Chief Scientist Offi ce of the Scottish Government Health Directorates. IB is supported by a grant from the Société Française de Rhumatologie and Lavoisier Program (Ministère des Aff aires Etrangères et Européennes). PLE is a DPhil Candidate in Evidence-Based Health Care at Oxford University

The production and deployment of an on-line video learning bank in a skills training environment

This paper describes the introduction of videos as aids in clinical skills teaching. Although the process explored focuses on a nursing clinical skills environment it is relevant to many other disciplines. With the introduction of the pre-registration degree in nursing in Ireland in 2002, the formerly hospital-based schools of nursing amalgamated into larger programmes with their affiliated higher education institutes (HEIs). The result was a considerable increase in class sizes. The current average annual cohort in the School of Nursing, Dublin City University (DCU) is 240 students. This has resulted in a need to review the way we teach clinical skills on campus. These skills form a large part of the programme and are taught to students in the school-based simulated nursing environment to prepare them for their practical experience in the clinical environment. Until 2006 the skills had been taught to groups of 25-30 students using a demonstration and practice technique. This teaching method has posed a number of problems: •Learning experiences vary depending on the mix of demonstration and practice in each session. •It can be difficult for students to absorb all of the information presented in a single demonstration. •It is highly resource intensive. It was decided that video technology incorporating a large scale deployment of skills videos over a video web server, in conjunction with a shift in emphasis in the teaching contact sessions could offer a useful tool to aid the teaching process. This paper will discuss the production process, the implementation of the project in the teaching environment and the evaluation findings

Applying the trigger review method after a brief educational intervention: potential for teaching and improving safety in GP specialty training?

<p>Background: The Trigger Review Method (TRM) is a structured approach to screening clinical records for undetected patient safety incidents (PSIs) and identifying learning and improvement opportunities. In Scotland, TRM participation can inform GP appraisal and has been included as a core component of the national primary care patient safety programme that was launched in March 2013. However, the clinical workforce needs up-skilled and the potential of TRM in GP training has yet to be tested. Current TRM training utilizes a workplace face-to-face session by a GP expert, which is not feasible. A less costly, more sustainable educational intervention is necessary to build capability at scale. We aimed to determine the feasibility and impact of TRM and a related training intervention in GP training.</p> Methods We recruited 25 west of Scotland GP trainees to attend a 2-hour TRM workshop. Trainees then applied TRM to 25 clinical records and returned findings within 4-weeks. A follow-up feedback workshop was held. <p>Results: 21/25 trainees (84%) completed the task. 520 records yielded 80 undetected PSIs (15.4%). 36/80 were judged potentially preventable (45%) with 35/80 classified as causing moderate to severe harm (44%). Trainees described a range of potential learning and improvement plans. Training was positively received and appeared to be successful given these findings. TRM was valued as a safety improvement tool by most participants.</p> <p>Conclusion: This small study provides further evidence of TRM utility and how to teach it pragmatically. TRM is of potential value in GP patient safety curriculum delivery and preparing trainees for future safety improvement expectations.</p&gt

Reducing weight and increasing physical activity in people at high risk of cardiovascular disease: a randomised controlled trial comparing the effectiveness of enhanced motivational interviewing intervention with usual care.

OBJECTIVE: The epidemic of obesity is contributing to the increasing prevalence of people at high risk of cardiovascular disease (CVD), negating the medical advances in reducing CVD mortality. We compared the clinical and cost-effectiveness of an intensive lifestyle intervention consisting of enhanced motivational interviewing in reducing weight and increasing physical activity for patients at high risk of CVD. METHODS: A three-arm, single-blind, parallel-group randomised controlled trial was conducted in consenting primary care centres in south London. We recruited patients aged 40-74 years with a QRisk2 score ≥20.0%, which indicates the probability of having a CVD event in the next 10 years. The intervention was enhanced motivational interviewing which included additional behaviour change techniques and was delivered by health trainers in 10 sessions over 1 year, in either group (n=697) or individual (n=523) format. The third arm received usual care (UC; n=522). The primary outcomes were physical activity (mean steps/day) and weight (kg). Secondary outcomes were changes in low-density lipoprotein cholesterol and CVD risk score. We estimated the relative cost-effectiveness of each intervention. RESULTS: At 24 months, the group and individual interventions were not more effective than UC in increasing physical activity (mean difference=70.05 steps, 95% CI -288.00 to 147.90 and mean difference=7.24 steps, 95% CI -224.01 to 238.50, respectively), reducing weight (mean difference=-0.03 kg, 95% CI -0.49 to 0.44 and mean difference=-0.42 kg, 95% CI -0.93 to 0.09, respectively) or improving any secondary outcomes. The group and individual interventions were not cost-effective at conventional thresholds. CONCLUSIONS: Enhancing motivational interviewing with additional behaviour change techniques was not effective in reducing weight or increasing physical activity in those at high CVD risk