The effect of social relationships on the rates of referral to specialists

Novel Method to Manage Student Questions in the Anatomy Laboratory Using a Virtual Meeting Platform

Large class sizes and often few instructors in anatomy courses make it challenging for student laboratory groups to have their questions addressed in a timely manner. Instructors are often unaware of the number of requests for assistance, as well as the order in which assistance is requested, and students often spend a long time waiting for an instructor to become available. As a result of brainstorming with some of our students, a call button system of sorts was suggested. Instructors in consultation with the college's IT department came up with the idea of using Zoom Meetings question and answer (Q&A) feature to manage student questions. Zoom allows one to broadcast a Zoom Meeting to up to 50,000 participant attendees, and instructors, logged in as panelists (on a mobile device, e.g., iPad), can interact with the student attendees via the Q&A feature. The students join the webinar using their dissection table number as their ID and request assistance in the Q&A. These requests show up with a time stamp and are automatically queued on the panelist's Q&A window. Instructors employ the type answer feature to acknowledge the question by typing in their respective initials, which can be seen live by the other instructors (panelists). This allows student questions to be queued so that the instructors can address them in a timely, first-in/first-out order. Student feedback regarding the use of this system for the Small Animal Anatomy course was positive.

A Bibliometric Analysis and Visualization of Decision Support Systems for Healthcare Referral Strategies

BACKGROUND

The referral process is an important research focus because of the potential consequences of delays, especially for patients with serious medical conditions that need immediate care, such as those with metastatic cancer. Thus, a systematic literature review of recent and influential manuscripts is critical to understanding the current methods and future directions in order to improve the referral process.

METHODS

A hybrid bibliometric-structured review was conducted using both quantitative and qualitative methodologies. Searches were conducted of three databases, Web of Science, Scopus, and PubMed, in addition to the references from the eligible papers. The papers were considered to be eligible if they were relevant English articles or reviews that were published from January 2010 to June 2021. The searches were conducted using three groups of keywords, and bibliometric analysis was performed, followed by content analysis.

RESULTS

A total of 163 papers that were published in impactful journals between January 2010 and June 2021 were selected. These papers were then reviewed, analyzed, and categorized as follows: descriptive analysis (n = 77), cause and effect (n = 12), interventions (n = 50), and quality management (n = 24). Six future research directions were identified.

CONCLUSIONS

Minimal attention was given to the study of the primary referral of blood cancer cases versus those with solid cancer types, which is a gap that future studies should address. More research is needed in order to optimize the referral process, specifically for suspected hematological cancer patients.

Beyond patient-sharing: Comparing physician- and patient-induced networks

The sharing of patients reflects collaborative relationships between various healthcare providers. Patient-sharing in the outpatient sector is influenced by both physicians' activities and patients' preferences. Consequently, a patient-sharing network arises from two distinct mechanisms: the initiative of the physicians on the one hand, and that of the patients on the other. We draw upon medical claims data to study the structure of one patient-sharing network by differentiating between these two mechanisms. Owing to the institutional requirements of certain healthcare systems rather following the Bismarck model, we explore different triadic patterns between general practitioners and medical specialists by applying exponential random graph models. Our findings imply deviation from institutional expectations and reveal structural realities visible in both networks.