A quantitative analysis of the impact of a computerised information system on nurses' clinical practice using a realistic evaluation framework

Objective: To explore nurses' perceptions of the impact on clinical practice of the use of a computerised hospital information system. Design: A realistic evaluation design based on Pawson and Tilley's work has been used across all the phases of the study. This is a theory-driven approach and focuses evaluation on the study of what works, for whom and in what circumstances. These relationships are constructed as context-mechanisms-outcomes (CMO) configurations. Measurements: A questionnaire was distributed to all nurses working in in-patient units of a university hospital in Spain (n = 227). Quantitative data were analysed using SPSS 13.0. Descriptive statistics were used for an overall overview of nurses' perception. Inferential analysis, including both bivariate and multivariate methods (path analysis), was used for cross-tabulation of variables searching for CMO relationships. Results: Nurses (n = 179) participated in the study (78.8% response rate). Overall satisfaction with the IT system was positive. Comparisons with context variables show how nursing units' context had greater influence on perceptions than users' characteristics. Path analysis illustrated that the influence of unit context variables are on outcomes and not on mechanisms. Conclusion: Results from the study looking at subtle variations in users and units provide insight into how important professional culture and working practices could be in IT (information technology) implementation. The socio-technical approach on IT systems evaluation suggested in the recent literature appears to be an adequate theoretical underpinning for IT evaluation research. Realistic evaluation has proven to be an adequate method for IT evaluation. (C) 2009 Elsevier Ireland Ltd. All rights reserved

On the road to personalised and precision geomedicine: medical geology and a renewed call for interdisciplinarity

Our health depends on where we currently live, as well as on where we have lived in the past and for how long in each place. An individual’s place history is particularly relevant in conditions with long latency between exposures and clinical manifestations, as is the case in many types of cancer and chronic conditions. A patient’s geographic history should routinely be considered by physicians when diagnosing and treating individual patients. It can provide useful contextual environmental information (and the corresponding health risks) about the patient, and should thus form an essential part of every electronic patient/health record. Medical geology investigations, in their attempt to document the complex relationships between the environment and human health, typically involve a multitude of disciplines and expertise. Arguably, the spatial component is the one factor that ties in all these disciplines together in medical geology studies. In a general sense, epidemiology, statistical genetics, geoscience, geomedical engineering and public and environmental health informatics tend to study data in terms of populations, whereas medicine (including personalised and precision geomedicine, and lifestyle medicine), genetics, genomics, toxicology and biomedical/health informatics more likely work on individuals or some individual mechanism describing disease. This article introduces with examples the core concepts of medical geology and geomedicine. The ultimate goals of prediction, prevention and personalised treatment in the case of geology-dependent disease can only be realised through an intensive multiple-disciplinary approach, where the various relevant disciplines collaborate together and complement each other in additive (multidisciplinary), interactive (interdisciplinary) and holistic (transdisciplinary and cross-disciplinary) manners

Opening the Black Box: Explaining the Process of Basing a Health Recommender System on the I-Change Behavioral Change Model

Recommender systems are gaining traction in healthcare because they can tailor recommendations based on users' feedback concerning their appreciation of previous health-related messages. However, recommender systems are often not grounded in behavioral change theories, which may further increase the effectiveness of their recommendations. This paper's objective is to describe principles for designing and developing a health recommender system grounded in the I-Change behavioral change model that shall be implemented through a mobile app for a smoking cessation support clinical trial. We built upon an existing smoking cessation health recommender system that delivered motivational messages through a mobile app. A group of experts assessed how the system may be improved to address the behavioral change determinants of the I-Change behavioral change model. The resulting system features a hybrid recommender algorithm for computer tailoring smoking cessation messages. A total of 331 different motivational messages were designed using 10 health communication methods. The algorithm was designed to match 58 message characteristics to each user pro le by following the principles of the I-Change model and maintaining the bene ts of the recommender system algorithms. The mobile app resulted in a streamlined version that aimed to improve the user experience, and this system's design bridges the gap between health recommender systems and the use of behavioral change theories. This article presents a novel approach integrating recommender system technology, health behavior technology, and computer-tailored technology. Future researchers will be able to build upon the principles applied in this case study.European Union's Horizon 2020 Research and Innovation Programme under Grant 68112