Objective. Patient-reported outcomes (PROs) are an integral part of treat-to-target approaches in managing rheumatoid arthritis (RA). In clinical practice, however, routine collection, documentation, and discussion of PROs with patients are highly variable. The RISE LC (Rheumatology Informatics System for Effectiveness Learning Collaborative) was established to develop and share best practices in PRO collection and use across adult rheumatology practices in the United StatesMethods. The goals of the RISE LC were developed through site surveys and in-person meetings. Participants completed a baseline survey on PRO collection and use in their practices. RISE LC learning sessions focused on improving communication around PROs with patients and enhancing shared decision-making in treatment plans. During the coronavirus disease 2019 (COVID-19) pandemic, the RISE LC pivoted to adapt PRO tools for telehealth.Results. At baseline, all responding sites (n = 15) had established workflows for collecting PROs. Most sites used paper forms alone. PRO documentation in electronic health records was variable, with only half of the sites using structured data fields. To standardize and improve the use of PROs, participants iteratively developed a Clinical Disease Activity Index-based RA Disease Activity Communication Tool to solicit treatment goals and improve shared decision-making across sites. The COVID-19 pandemic necessitated developing a tool to gauge PROs via telehealth.Conclusion. The RISE LC is a continuous, structured method for implementing strategies to improve PRO collection and use in rheumatological care, initially adapting from the Learning Collaborative model and extending to include features of a learning network. Future directions include measuring the impact of standardized PRO collection and discussion on shared decision-making and RA outcomes.
Objective Using the American College of Rheumatology Rheumatology Informatics System for Effectiveness (RISE) registry, our objective was to examine performance on rheumatoid arthritis (RA) quality measures and to assess the association between practice characteristics and changes in performance over time among participating practices. Methods We analyzed data from practices enrolled in RISE between January 1, 2015 and December 31, 2017. Eight quality measures in the areas of RA disease management, cardiovascular risk reduction, and patient safety were examined. Variability in performance was evaluated at the practice level. Multivariate linear models were used to predict change in measure performance by year and to determine the effect of practice characteristics on change in performance over time. Results Data from 59,986 patients from 54 practices were examined. The mean ± SD age was 62 ± 14 years, 77% were female, 69% were Caucasian, and most patients were seen in a single‐specialty group practice (46%). The average performance on measures related to RA treatments was consistently high (>90%) across the study period. Measures related to RA functional status and disease activity assessment had the greatest improvements over time (8.4% and 13.0% increase per year, respectively; P < 0.001). Single‐specialty group practices had the fastest rates of improvement over time across all measures. Conclusion Among practices participating in RISE between 2015 and 2017, performance on most RA quality measures improved. Single‐specialty group practices saw the fastest rates of improvement over time. Identification of workflow patterns leading to dramatic improvements in quality of care will help guide process redesign to address gaps in priority areas, such as tuberculosis screening and blood pressure control.
Globally, an approximate of 380,000 patients succumbed to death due to the pandemic COVID-19 which also infected more than six million people since December 2019. Not sparing anyone, COVID-19 infections are widely reported among healthcare professionals, sanitation workers and researchers too while global leaders and various governments are providing their best in defending their citizens against this airborne and contact spread virus. In order to contain the virus and protect millions of lives from this deadly coronavirus, there is a need to have a combination of advanced engineering technology and medical facilities. Application of applied science, engineering and technology diffuse almost every aspect of contemporary living. Grasping the fundamentals to determine humanity's most imperative and forthcoming challenges is essential. Artificial Intelligence, the technology that learns, adapts and reciprocates the actions according to the situations, finds optimum position in the fight against corona virus and acts as a powerful tool against this pandemic. In this research article, the authors discusses how Artificial Intelligence (AI) can be leveraged to fight the deadly virus. The research paper further discusses the efficient utilization of AI across the globe to help in testing, treating and serving the population in these hard times. This manuscript focuses on the potential impact of the process in which AI can be implemented to prevent, test and treat.
Objective The study sought to describe the contributions of clinical informatics (CI) fellows to their institutions’ coronavirus disease 2019 (COVID-19) response. Materials and Methods We designed a survey to capture key domains of health informatics and perceptions regarding fellows’ application of their CI skills. We also conducted detailed interviews with select fellows and described their specific projects in a brief case series. Results Forty-one of the 99 CI fellows responded to our survey. Seventy-five percent agreed that they were “able to apply clinical informatics training and interest to the COVID-19 response.” The most common project types were telemedicine (63%), reporting and analytics (49%), and electronic health record builds and governance (32%). Telehealth projects included training providers on existing telehealth tools, building entirely new virtual clinics for video triage of COVID-19 patients, and pioneering workflows and implementation of brand-new emergency department and inpatient video visit types. Analytics projects included reports and dashboards for institutional leadership, as well as developing digital contact tracing tools. For electronic health record builds, fellows directly contributed to note templates with embedded screening and testing guidance, adding COVID-19 tests to order sets, and validating clinical triage workflows. Discussion Fellows were engaged in projects that span the breadth of the CI specialty and were able to make system-wide contributions in line with their educational milestones. Conclusions CI fellows contributed meaningfully and rapidly to their institutions’ response to the COVID-19 pandemic.
Classical Hodgkin's lymphoma (CHL) presenting with exclusively pulmonary symptoms is very unusual. We report two cases of CHL with atypical clinical presentations mimicking pulmonary infections. The first case represents a stage IV CHL with secondary lung involvement, and the second case demonstrates a very rare case of CHL with isolated lung involvement, also known as primary pulmonary Hodgkin's lymphoma. The second patient was initially misdiagnosed and treated with six months of antibiotics before the correct diagnosis was made by a lung biopsy. Both patients received chemotherapy; one patient achieved complete remission and the other achieved near-complete remission.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.