A patient-centric model that integrates interprofessional care and the optimized use of healthcare practitioners' scope of practice must be implemented. This proposed research will investigate (1) the model's consequences for FMG operational performance and user resource consumption within the public health system, (2) how to optimize the model for professional roles, interprofessional collaboration and patient-centricity, and (3) the user experiences with the model. The protocol employed in this investigation, as described in this article, is crucial for this research project.A type 2 model-based hybrid implementation approach will be employed. Both quantitative and qualitative data will be collected by us. For the quantitative assessment, considering the single-unit nature of this intervention study, we will employ either or both synthetic control methods and one-sample generalized linear models for analysis at the FMG level. In order to gauge the overall consequences ofIn the context of evaluating the public health system, mixed-effects models and propensity score matching will be critical. In our qualitative research, an interpretative and descriptive approach will be employed to narrate user experiences and identify the variables contributing to an improved scope of professional practice, collaborative procedures, and patient-centric care. Semi-structured, in-depth interviews with healthcare providers, administrative staff, and key stakeholders will be carried out individually.Patient outcomes resulting from the model's implementation.In accordance with the ethical review process of the Sectoral Research in Population Health and Primary Care at the Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale (#2019-1503), this study was approved. The investigation's conclusions will be shared with stakeholders on the advisory committees, as well as at various scientific conferences. The peer-review process awaits manuscripts destined for journals.This study's ethical approval originated from the Sectoral Research in Population Health and Primary Care Ethics Committee of the Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale, reference number #2019-1503. Stakeholders participating in the advisory committees and attendees at several scientific conferences will receive the investigation's conclusions. Submissions of manuscripts to peer-reviewed journals are anticipated.A thorough assessment of interprofessional primary care's impact on patient care and health system efficiency is necessary to understand if it achieves its desired effects, and to steer quality improvement endeavors. A primary objective of this scoping review is to map the literature on primary care performance measurement indicators, in order to identify the extent to which current indicators cover, or could be altered to cover, processes, outputs, and outcomes associated with interprofessional primary care.The review's methodology is anchored in the six-stage framework proposed by Arksey and O'Malley (2005). A search for studies published in English or French between 2000 and 2022, encompassing the themes of performance indicators, frameworks, interprofessional teams, and primary care, will be conducted across MEDLINE, Embase, CINAHL, grey literature, and the bibliographies of key studies. Two independent reviewers will methodically screen all abstracts and full-text research papers for inclusion. Two validated frameworks' proposed process, output, and outcome domains will be used to classify eligible indicators. This study, begun in November 2022, is anticipated to be concluded by July 2023.This analysis does not need to be subject to ethical review. To share the findings, the results will be disseminated via stakeholder presentations, peer-reviewed publications, and presentations at conferences.This assessment does not fall under the purview of ethical review requirements. Through the channels of peer-reviewed publications, presentations at conferences, and presentations to stakeholders, the results will be communicated.Deep brain stimulation (DBS) implantation, carried out under general anesthesia (GA), has been a therapeutic approach for Parkinson's disease (PD) patients experiencing significant comorbidities or disabling off-medication symptoms. Nevertheless, the use of general anesthetics can have a variable impact on intraoperative microelectrode recordings (MER). At the present time, there are a limited number of investigations into the effects of sedatives or general anesthetics on the multi-unit activity profiles recorded by MER during deep brain stimulation in patients with Parkinson's Disease. Consequently, the impact of anesthetic selection on MER continues to be indeterminate.This study, a prospective, randomized controlled non-inferiority trial, is scheduled to be conducted at Beijing Tiantan Hospital, Capital Medical University. Following rigorous eligibility assessments, patients scheduled for elective bilateral subthalamic nucleus (STN)-deep brain stimulation (DBS) will be enrolled. 11 patients will be allocated to conscious sedation (CS), while 177 will be assigned to general anesthesia (GA), out of the 188 patients. High normalised root mean square (NRMS) values, as recorded by the MER signal, are the primary outcome.Approval for the study was given by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University, document number KY2022-147-02. Negative results from studies evaluating GA with desflurane for MER during STN-DBS will imply that this anesthetic's effect on MER is not inferior to the effect of CS during the procedure. This clinical trial's results will be presented at both national and international conferences, and submitted for publication in a peer-reviewed journal.NCT05550714.Regarding NCT05550714.A significant global increase in diabetes cases has contributed to a large disease burden and financial impact. Controlling its prevalence hinges on the capacity for early prediction.In a prospective cohort study, the investigation was carried out.A national survey on Irish representation.Eighty-five hundred and four individuals, all 50 years old or above, were incorporated into the data set.In an effort to collect information on diverse social, financial, health, mental, and family factors, surveys were implemented, yielding over 40,000 data points. In the context of feature selection, logistic regression was applied. Among the algorithms trained were distributed random forest, extremely randomized trees, generalized linear model with regularization, gradient boosting machine, and deep neural network. An optimal model was created by integrating these algorithms into a layered ensemble. The model's effectiveness was quantified using metrics like AUC, log loss, the mean per-classification error, mean square error (MSE), and root mean square error (RMSE). The established model was subjected to interpretation using the SHapley Additive exPlanations (SHAP) technique.Diabetes risk was found to be significantly correlated with 105 baseline characteristics, discovered after two years of study, which encompass sex, low-density lipoprotein cholesterol, and cirrhosis. In predicting diabetes risk, the model with the highest accuracy, robustness, and discrimination performed significantly well in the independent test set, recording an AUC of 0.854, a log loss of 0.187, a mean per classification error of 0.0267, an RMSE of 0.0229, and an MSE of 0.0052. The calibration of the model was also noted as being well-adjusted. The decision-making procedures of the model were illuminated by the SHAP algorithm.Early identification of high-risk individuals for diabetes is facilitated by these findings, allowing for targeted interventions to lower incidence rates.These discoveries can aid physicians in identifying patients at high risk for diabetes early on, leading to the implementation of targeted interventions to decrease the occurrence of diabetes.The escalating rate of innovation in cancer therapies makes it challenging to sequence treatments optimally. Treatment evaluation research often focuses narrowly on a single decision point, lacking the scope to assess how prior treatment choices might influence the efficacy and practicality of future interventions. Dynamic treatment regimes (DTRs) are gaining popularity in evaluation, offering a means to tailor treatment plans that reflect changing patient and treatment conditions. This scoping review aims to systematically evaluate how and to what degree DTRs are assessed in oncology clinical studies, with the goal of building evidence for clinical decision support.To identify clinical studies (including ongoing trials' protocols), with either experimental or observational designs, addressing clinical oncology questions about treatment sequencing using the DTR concept, a methodical search will be undertaken across MEDLINE (PubMed), Web of Science, Scopus, and the WHO International Clinical Trials Registry platform. Data extraction will incorporate information about cancer, clinical context, treatment protocols, personalization elements, decision logic, decision points, and results. This will also encompass the data type, research design, and the statistical methodologies utilized in evaluating DTR. enzyme inhibitors In accordance with the Joanna Briggs Institute Reviewer's manual for scoping reviews, the review will be conducted. No patients are to be involved in this process.This scoping review's use of secondary analysis of published materials renders ethics committee approval superfluous. Scientific journal publications and relevant conference presentations will disseminate the results. This scoping review will provide a clearer picture of the methodologies used to generate evidence on treatment sequencing in oncology, assisting in identifying knowledge and methodological deficiencies that necessitate further investigation.No ethics committee approval is needed for this scoping review as it will only conduct a secondary analysis of the published literature. Dissemination of results will occur via peer-reviewed scientific publications and presentations at relevant academic conferences.