Effectiveness and efficiency of training in digital healthcare packages: Training doctors to use digital medical record keeping software

Objective: Fiona Stanley Hospital (FSH) is the first hospital in Western Australia to implement a digital medical record (BOSSnet, Core Medical Solutions, Australia). Formal training in the use of the digital medical record is provided to all staff as part of the induction program. The aim of the present study was to evaluate whether the current training program facilitates efficient and accurate use of the digital medical record in clinical practice. Methods: Participants were selected from the cohort of junior doctors employed at FSH in 2015. An e-Learning package of clinically relevant tasks from the digital medical record was created and, along with a questionnaire, completed by participants on two separate occasions. The time taken to complete all tasks and the number of incorrect mouse clicks used to complete each task were recorded and used as measures of efficiency and accuracy respectively. Results: Most participants used BOSSnet more than 10 times per day in their clinical roles and self-rated their baseline overall computer proficiency level as high. There was a significant increase in the self-rating of proficiency levels in successive tests. In addition, a significant improvement in both efficiency and accuracy for all participants was measured between the two tests. Interestingly, both groups ended up with similar accuracy on the second trial, despite the second group of participants starting with significantly poorer accuracy. Conclusions: Overall, the greatest improvements in task performance followed daily ward-based experience using BOSSnet rather than formalised training. The greatest benefits of training were noted when training was delivered in close proximity to the onset of employment. What is known about the topic? Formalised training in the use of information and communications technology (ICT) is widespread in the health service. However, there is limited evidence to support the modes of learning typically used. Formalised training is often costly and there is little other than anecdotal evidence that currently supports its efficacy in the workplace. What does the paper add? Assessment of accuracy when using the BOSSnet system over time revealed that daily use rather than formalised training appeared to have the most impact on performance. Formalised training was rated poorly, and this appeared to correlate with time between training and use. The present study suggests that formalised training, if required, should be delivered close in time to actual use of the system to benefit end-users. The study also shows that daily experience is more effective than formalised training to improve accuracy. What are the implications for practitioners? Formalised training for ICT needs to be scheduled in close proximity to end-user use of the ICT. Current scheduling may be beneficial for ease of delivery, but unless it is delivered at a suitable time the benefits are minimal. Formalised training programs may not be critical for all staff and all staff improve with contextualised experience given time. Training may be better suited to optional rather than compulsory delivery programs with ongoing delivery to suit user schedules

A randomised trial of the effectiveness of instructor versus automated manikin feedback for training junior doctors in life support skills

Introduction: Australian Standards require that clinicians undergo regular training in skills required to respond to the acute deterioration of a patient. Training focuses on the ability to appropriately respond to cardiac arrest, including delivering cardiac compressions, ventilation and appropriate defibrillation. Providing such training comes at a significant cost to the organisation and impacts on clinician time in direct patient care. If effective, the use of an automated manikin could significantly reduce costs and provide consistent training experiences. Methods: Fifty-six resident medical officers were randomised to two groups to test two skills components of hospital life support training under two feedback conditions. The skills components were cardiac compressions and bag-valve-mask ventilation. The feedback conditions were automated feedback delivered by a simulation manikin and traditional feedback delivered by an instructor. All participants were exposed to both skills components and both feedback conditions in a counterbalanced block design. Participants completed surveys before and after training. Results: The results demonstrated significantly better performance in cardiac compressions under the automated manikin feedback condition compared with the instructor feedback condition. This difference was not observed in bag-valve-mask ventilation. The majority of participants found the automated manikin feedback more useful than the instructor feedback. Discussion: Automated manikin feedback was not inferior to instructor feedback for skill acquisition in cardiac compressions training. The automated feedback condition did not achieve the same level of significance in bag-valve-mask ventilation training. Results suggest training with automated feedback presents a cost-effective opportunity to lessen the training burden, whilst improving skill acquisition

The jigsaw model: A biogeographic model that partitions habitat heterogeneity from area

Species–area models now frequently include habitat heterogeneity. These models often fit real-world data better than those that exclude this factor. However, such models usually link the effects of habitat heterogeneity and study area. Critically, we show that difficulties in quantifying habitat heterogeneity within these models can lead to distortions of the apparent effect of area on species richness. Here, we derive a model that minimises these distortions by partitioning the influence of habitat heterogeneity from that of area, without compromising ease of application. This ‘jigsaw model’ achieves this by assuming that different habitats within an area can support similar numbers of species. We compare the behaviour of this model to that of existing models of similar complexity using both simulated island ecosystems and 40 published empirical datasets. The effects of habitat heterogeneity and area on species richness vary independently in our simulations, and these independent effects are recovered by the jigsaw model. This flexibility, however, is not present when the same data are analysed using other models of similar complexity. When applied to real-world data, the jigsaw model demonstrates that the relative importance of area and habitat heterogeneity varies depending on the study system. The jigsaw model provides the best fit to real-world data (according to AICc) of all tested models in logarithmic form, and the second best fit, after the choros model, in power-law form. Our results demonstrate the importance of partitioning the effects of habitat heterogeneity and area on species richness in biogeographic models. The jigsaw model is a simple but powerful tool for such partitioning. It has the potential to elucidate the underlying drivers of species richness patterns, and to be used as a tool in biological conservation projects, where data are often incomplete

Metabolomic Profiling in the Characterization of Degenerative Bone and Joint Diseases

Osteoarthritis and inflammatory arthropathies are a cause of significant morbidity globally. New research elucidating the metabolic derangements associated with a variety of bone and joint disorders implicates various local and systemic metabolites, which further elucidate the underlying molecular mechanisms associated with these destructive disease processes. In osteoarthritis, atty acid metabolism has been implicated in disease development, both locally and systemically. Several series of rheumatoid arthritis patients have demonstrated overlapping trends related to histidine and glyceric acid, while other series showed similar results of increased cholesterol and glutamic acid. Studies comparing osteoarthritis and rheumatoid arthritis reported elevated gluconic acid and glycolytic- and tricarboxylic acid-related substrates in patients with osteoarthritis, while lysosphingolipids and cardiolipins were elevated only in patients with rheumatoid arthritis. Other bone and joint disorders, including osteonecrosis, intervertebral disc degeneration, and osteoporosis, also showed significant alterations in metabolic processes. The identification of the molecular mechanisms of osteoarthritis and inflammatory arthropathies via metabolomics-based workflows may allow for the development of new therapeutic targets to improve the quality of life in these patient populations