Repeat prescribing of medications: a system-centred risk management model for primary care organisations

Rationale, aims and objectives: Reducing preventable harm from repeat medication prescriptions is a patient safety priority worldwide. In the United Kingdom, repeat prescriptions items issued has doubled in the last 20 years from 5.8 to 13.3 items per patient per annum. This has significant resource implications and consequences for avoidable patient harms. Consequently, we aimed to test a risk management model to identify, measure, and reduce repeat prescribing system risks in primary care. Methods: All 48 general medical practices in National Health Service (NHS) Lambeth Clinical Commissioning Group (an inner city area of south London in England) were recruited. Multiple interventions were implemented, including educational workshops, a web-based risk monitoring system, and external reviews of repeat prescribing system risks by clinicians. Data were collected via documentation reviews and interviews and subject to basic thematic and descriptive statistical analyses. Results: Across the 48 participating general practices, 62 unique repeat prescribing risks were identified on 505 occasions (eg, practices frequently experiencing difficulty interpreting medication changes on hospital discharge summaries), equating to a mean of 8.1 risks per practice (range: 1-33; SD = 7.13). Seven hundred sixty-seven system improvement actions were recommended across 96 categories (eg, alerting hospitals to illegible writing and delays with discharge summaries) with a mean of 15.6 actions per practice (range: 0-34; SD = 8.0). Conclusions: The risk management model tested uncovered important safety concerns and facilitated the development and communication of related improvement recommendations. System-wide information on hazardous repeat prescribing and how this could be mitigated is very limited. The approach reported may have potential to close this gap and improve the reliability of general practice systems and patient safety, which should be of high interest to primary care organisations internationally

Effectiveness Of Educating Health Care Professionals In Managing Chronic Pain Patients Through A Supervised Student Inter-Professional Pain Clinic

Objective: To address the need for increased and more effective medical education regarding chronic pain and pain management, an inter-professional (IP) training program in the form of a supervised student IP pain clinic was implemented in 2016. In the current study, we evaluated its feasibility and effectiveness in improving health care professional students’ skills in 1) managing chronic pain and 2) working in an IP team. Methods: From January 2016 to December 2018, we assembled 12 IP teams that included students from the following six professions at the University of New England: nursing, osteopathic medicine (OM), occupational therapy (OT), pharmacy, physical therapy (PT), and social work (SW). During this 12-week training program, each team conducted the initial evaluation, generated treatment plans, and performed follow-up examinations for its assigned patient under the supervision of a pain specialist at the Mercy Pain Center. Surveys were conducted with all participating students and patients. Results: Overall, students showed significant improvement in knowledge regarding pain physiology and chronic pain management as well as attitude and perception regarding IP practice and perceived team skills. Specifically, prior to the program, nursing students showed the greatest pain-related knowledge and perceived team skills, while OT students scored the highest in attitude and perception regarding IP practice. Following the program, improvement in various measures were observed in all professions with PT students showing the most significant improvement in all areas. Surveys also indicated patients’ satisfaction with their IP pain clinic experience. Conclusions: These results demonstrated the feasibility and the effectiveness of this IP training program for all participating professions

Spatio-temporal momentum: jointly learning time-series and cross-sectional strategies

The authors introduce spatio-temporal momentum strategies, a class of models that unify both time-series and cross-sectional momentum strategies by trading assets based on their cross-sectional momentum features over time. Although both time-series and cross-sectional momentum strategies are designed to systematically capture momentum risk premiums, these strategies are regarded as distinct implementations and do not consider the concurrent relationship and predictability between temporal and cross-sectional momentum features of different assets. They model spatio-temporal momentum with neural networks of varying complexities and demonstrate that a simple neural network with only a single fully connected layer learns to simultaneously generate trading signals for all assets in a portfolio by incorporating both their time-series and cross-sectional momentum features. Back testing on portfolios of 46 actively traded US equities and 12 equity index futures contracts, they demonstrate that the model is able to retain its performance over benchmarks in the presence of high transaction costs of up to 5–10 basis points. In particular, they find that the model when coupled with least absolute shrinkage and turnover regularization results in the best performance over various transaction cost scenarios

Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces

biological space

Gravitational Waves and Proton Decay: Complementary Windows into Grand Unified Theories

Proton decay is a smoking gun signature of grand unified theories (GUTs). Searches by Super-Kamiokande have resulted in stringent limits on the GUT symmetry-breaking scale. The large-scale multipurpose neutrino experiments DUNE, Hyper-Kamiokande, and JUNO will either discover proton decay or further push the symmetry-breaking scale above 1016 GeV. Another possible observational consequence of GUTs is the formation of a cosmic string network produced during the breaking of the GUT to the standard model gauge group. The evolution of such a string network in the expanding Universe produces a stochastic background of gravitational waves which will be tested by a number of gravitational wave detectors over a wide frequency range. We demonstrate the nontrivial complementarity between the observation of proton decay and gravitational waves produced from cosmic strings in determining SO(10) GUT-breaking chains. We show that such observations could exclude SO(10) breaking via flipped SU(5) × U(1) or standard SU(5), while breaking via a Pati-Salam intermediate symmetry, or standard SU(5) × U(1), may be favored if a large separation of energy scales associated with proton decay and cosmic strings is indicated. We note that recent results by the NANOGrav experiment have been interpreted as evidence for cosmic strings at a scale of ∼ 10 14 GeV. This would strongly point toward the existence of GUTs, with SO(10) being the prime candidate. We show that the combination with already available constraints from proton decay allows us to identify preferred symmetry-breaking routes to the standard model