Effect of guideline based computerised decision support on decision making of multidisciplinary teams: cluster randomised trial in cardiac rehabilitation

Objective To determine the extent to which computerised decision support can improve concordance of multidisciplinary teams with therapeutic decisions recommended by guidelines

Does technology acceptance determine attitudes towards health information technology? The case of electronic remote blood delivery

For many Healthcare Technology Interventions (HIT) attitudes and experiences can have a significant impact on successful implementations. Within transfusion services it is recognized that differences in perspective between blood bank staff and nursing staff affect the adoption of safety practices or interventions. This multi-center study used a questionnaire survey to investigate differences in technology acceptance and attitudes towards Electronic Remote Blood Delivery (ERBD) between blood bank and operating room staff. The results of the survey revealed a significant correlation between attitudes and usage of technology and ERBD acceptance and usability scores (p<.01) as well as a significant effect of role on ERBD acceptance and usability scores (p<.05)

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Health Figures: An Open Source JavaScript Library for Health Data Visualization

The way we look at data has a great impact on how we can understand it, particularly when the data is related to health and wellness. Due to the increased use of self-tracking devices and the ongoing shift towards preventive medicine, better understanding of our health data is an important part of improving the general welfare of the citizens. Electronic Health Records, self-tracking devices and mobile applications provide a rich variety of data but it often becomes difficult to understand. We implemented the hFigures library inspired on the hGraph visualization with additional improvements. The purpose of the library is to provide a visual representation of the evolution of health measurements in a complete and useful manner. We researched the usefulness and usability of the library by building an application for health data visualization in a health coaching program. We performed a user evaluation with Heuristic Evaluation, Controlled User Testing and Usability Questionnaires. In the Heuristics Evaluation the average response was 6.3 out of 7 points and the Cognitive Walkthrough done by usability experts indicated no design or mismatch errors. In the CSUQ usability test the system obtained an average score of 6.13 out of 7, and in the ASQ usability test the overall satisfaction score was 6.64 out of 7. We developed hFigures, an open source library for visualizing a complete, accurate and normalized graphical representation of health data. The idea is based on the concept of the hGraph but it provides additional key features, including a comparison of multiple health measurements over time. We conducted a usability evaluation of the library as a key component of an application for health and wellness monitoring. The results indicate that the data visualization library was helpful in assisting users in understanding health data and its evolution over time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016

Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review

<p>Abstract</p> <p>Background</p> <p>The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations).</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes.</p> <p>Results</p> <p>Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported.</p> <p>Conclusions</p> <p>A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.</p

A model on factors affecting nurses adoption of health information technology

Healthcare organisations are using Health Information Technology (HIT) to improve efficiency, reduce cost and reduce medical errors. This study focused on the factors that influence the acceptance of HIT among nurses in Saudi hospitals. This research used a 6 stage mixed-methods research approach. Literature was used to search for established models and frameworks of technology acceptance, and the many factors that could play a role. In the field study, the nature of practical HIT issues at the Prince Sultan Military Medical City (PSMMC) and the Heraa Hospital were studied, and combined with literature to create a HIT Implementation Issues Framework. The framework consolidates elements from the Technological, Organisational, Environmental and Human dimensions. The researcher participated in further PSMMC projects in the design and implementation of the new Cardio Pulmonary Resuscitation System and the Nurses and Pharmacists’ Communication System. From the implementation experience, pertinent factors were added to the Technology Acceptance Model and the “Nurses Acceptance Model” was proposed. The proposed model has eleven independent parameters, two dependent parameters, as well as seven moderators of key relationships. A questionnaire with 71 entries was distributed to over 2800 nurses in 52 wards in PSMMC. SPSS was used for data screening and descriptive statistics. The SmartPLS software was used for analysis and testing of the proposed hypotheses. The findings refined the “Nurses Acceptance Model” and highlight the significance of User Involvement and Training. The “Nurses Acceptance Model” enhances the scientific understanding of variables that affect technology acceptance among nurses in Saudi hospitals. The HIT Implementation Issues Framework helps hospital decision makers to plan HIT projects to improve the likelihood of successful adoption

The role of personal mitigating factors in criminal sentencing judgments: an empirical investigation

Criminal sentencers must weight and integrate many different factors to reach a judgment, including aggravating factors that argue for a harsher sentence, and mitigating factors that suggest a more lenient sentence. Personal Mitigating Factors (PMFs) relate to the offender, rather than the offence (e.g., remorse or youth/immaturity). Research shows that discretionary sentencing produces inconsistency and bias and lacks the transparency needed to maintain public trust in justice. Although many jurisdictions have introduced more structured sentencing, the mitigation process remains largely discretionary. Structuring personal mitigation could help produce fairer sentences. Any structured approach must, however, be informed by empirical data, and little is known about how sentencers use PMFs, or how the public judges them. This thesis examined the role of three commonly occurring PMFs: remorse, good character, and addressing addiction. Study 1 examined sentencers’ use of PMFs in cases of assault and burglary through a statistical analysis of annual sentencing data from the Crown Court in England and Wales. Study 2 used a qualitative analysis of interviews with a small sample of Crown Court judges to further explore the findings of Study 1 and identify topics for future research. Studies 3 and 4 used experimental designs to measure how the three PMFs influenced public judgments about sentencing fairness and choice of sentence length. Study 4’s “idiographic” design permitted evaluation of the variation between individuals’ judgments about PMFs. The present thesis identified several issues with current sentencing practice, notably the underweighting of multiple co-occurring PMFs, and proposed some practical options for structuring the personal mitigation process. The thesis also identified conflicts between sentencers’ use of PMFs and public judgments, and suggested how the gap between sentencers and the public could be closed. Lastly, the thesis illustrates how methodology from psychology can be used to advance our understanding of criminal sentencing