Systematic review of new medics’ clinical task experience by country

OBJECTIVES: There is a need for research which informs on the overall size and significance of clinical skills deficits among new medics, globally. There is also the need for a meta-review of the similarities and differences between countries in the clinical skills deficits of new medics. DESIGN: A systematic review of published literature produced 68 articles from Google/Scholar, of which 9 met the inclusion criteria (quantitative clinical skills data about new medical doctors). PARTICIPANTS: 1329 new medical doctors (e.g., foundation year-1s, interns, PGY1s). SETTING: Ten countries/regions. MAIN OUTCOME MEASURES: 123 data points and representation of a broad range of clinical procedures. RESULTS: The average rate of inexperience with a wide range of clinical procedures was 35.92% (lower CI 30.84%, upper CI 40.99%). The preliminary meta-analysis showed that the overall deficit in experience is significantly different from 0 in all countries. Focusing on a smaller selection of clinical skills such as catheterisation, IV cannulation, nasogastric tubing and venepuncture, the average rate of inexperience was 26.75% (lower CI 18.55%, upper CI 35.54%) and also significant. England presented the lowest average deficit (9.15%), followed by New Zealand (18.33%), then South Africa (19.53%), Egypt, Kuwait, Gulf Cooperation Council countries and Ireland (21.07%), after which was Nigeria (37.99%), then USA (38.5%), and Iran (44.75%). CONCLUSION: A meta-analysis is needed to include data not yet in the public domain from more countries. These results provide some support for the UK General Medical Council’s clear, detailed curriculum, which has been heralded by other countries as good practice

Design and Effectiveness of a Required Pre-Clinical Simulation-based Curriculum for Fundamental Clinical Skills and Procedures

For more than 20 years, medical literature has increasingly documented the need for students to learn, practice and demonstrate competence in basic clinical knowledge and skills. In 2001, the Louisiana State University Health Science Centers (LSUHSC) School of Medicine – New Orleans replaced its traditional Introduction in to Clinical Medicine (ICM) course with the Science and Practice of Medicine (SPM) course. The main component within the SPM course is the Clinical Skills Lab (CSL). The CSL teaches 30 plus skills to all pre-clinical medical students (Years 1 and 2). Since 2002, an annual longitudinal evaluation questionnaire was distributed to all medical students targeting the skills taught in the CSL. Students were asked to rate their self- confidence (Dreyfus and Likert-type) and estimate the number of times each clinical skill was performed (clinically/non-clinically). Of the 30 plus skills taught, 8 were selected for further evaluation. An analysis was performed on the eight skills selected to determine the effectiveness of the CSL. All students that participated in the CSL reported a significant improvement in self-confidence and in number performed in the clinically/non-clinically setting when compared to students that did not experience the CSL. For example, without CSL training, the percentage of students reported at the end of their second year self-perceived expertise as “novice” ranged from 21.4% (CPR) to 84.7% (GU catheterization). Students who completed the two-years CSL, only 7.8% rated their self-perceived expertise at the end of the second year as “novice” and 18.8% for GU catheterization. The CSL design is not to replace real clinical patient experiences. It's to provide early exposure, medial knowledge, professionalism and opportunity to practice skills in a patient free environment

Artificial Intelligence and Internet of Things for autonomous vehicles

Artificial Intelligence (AI) is a machine intelligence tool providing enormous possibilities for smart industrial revolution. It facilitates gathering relevant data/information, identifying the alternatives, choosing among alternatives, taking some actions, making a decision, reviewing the decision, and predicting smartly. On the other hand, Internet of Things (IoT) is the axiom of industry 4.0 revolution, including a worldwide infrastructure for collecting and processing of the data/information from storage, actuation, sensing, advanced services and communication technologies. The combination of high-speed, resilient, low-latency connectivity, and technologies of AI and IoT will enable the transformation towards fully smart Autonomous Vehicle (AV) that illustrate the complementary between real world and digital knowledge for industry 4.0. The purpose of this book chapter is to examine how the latest approaches in AI and IoT can assist in the search for the AV. It has been shown that human errors are the source of 90% of automotive crashes, and the safest drivers drive ten times better than the average [1]. The automated vehicle safety is significant, and users are requiring 1000 times smaller acceptable risk level. Some of the incredible benefits of AVs are: (1) increasing vehicle safety, (2) reduction of accidents, (3) reduction of fuel consumption, (4) releasing of driver time and business opportunities, (5) new potential market opportunities, and (6) reduced emissions and dust particles. However, AVs must use large-scale data/information from their sensors and devices

Taxonomy, Physiology, and Natural Products of Actinobacteria

Microbial Biotechnolog