The application of social network analysis to the organization of healthcare delivery is a relatively new area of research that may not be familiar to health services statisticians and other methodologists. We present a methodological introduction to social network analysis with a case study of physicians' adherence to clinical guidelines regarding use of implantable cardioverter defibrillators (ICDs) for the prevention of sudden cardiac death. We focus on two hospital referral regions (HRRs) in Indiana, Gary and South Bend, characterized by different rates of evidence-based ICD use (86% and 66%, respectively). Using Medicare Part B claims, we construct a network of physicians who care for cardiovascular disease patients based on patient-sharing relationships. Approaches for weighting physician dyads and aggregating physician dyads by hospital are discussed. Then, we obtain a set of weighted network statistics for the positions of hospitals in their referral region, global statistics for the physician network within each hospital, and of the network positions of individual physicians within hospitals, providing the mathematical specification and sociological intuition underlying each measure. We find that adjusting for network measures can reduce the observed differences between referral regions for evidence-based ICD therapy. This study supports previous reports on how variation in physician network structure relates to utilization of care, and motivates future work using physician network measures to examine variation in evidence-based medicine.
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http://dx.doi.org/10.1007/s10742-016-0152-x | DOI Listing |
Med Phys
December 2024
Department of Echocardiography, Ultrasound Diagnostic Center, The First Hospital of Jilin University, Changchun, China.
Background: Dialysis Access (DA) stenosis impacts hemodialysis efficiency and patient health, necessitating exams for early lesion detection. Ultrasound is widely used due to its non-invasive, cost-effective nature. Assessing all patients in large hemodialysis facilities strains resources and relies on operator expertise.
View Article and Find Full Text PDFJ Pers Med
December 2024
Division of Neurotology and Skull Base Surgery, Department of Otolaryngology-Head and Neck Surgery, University of California, Irvine, CA 92697, USA.
This study aimed to develop a machine learning (ML) algorithm that can predict unplanned reoperations and surgical/medical complications after vestibular schwannoma (VS) surgery. All pre- and peri-operative variables available in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (n = 110), except those directly related to our outcome variables, were used as input variables. A deep neural network model consisting of seven layers was developed using the Keras open-source library, with a 70:30 breakdown for training and testing.
View Article and Find Full Text PDFJ Pers Med
December 2024
Department of Clinical Research, University of Southern Denmark, 5230 Odense, Denmark.
Artificial intelligence (AI) is becoming increasingly influential in ophthalmology, particularly through advancements in machine learning, deep learning, robotics, neural networks, and natural language processing (NLP). Among these, NLP-based chatbots are the most readily accessible and are driven by AI-based large language models (LLMs). These chatbots have facilitated new research avenues and have gained traction in both clinical and surgical applications in ophthalmology.
View Article and Find Full Text PDFCirc Cardiovasc Qual Outcomes
December 2024
RAND Corporation, Santa Monica, CA (C.B.G., C.L.D., S.Z., M.S., L.J.M., I.P.).
Background: Differences in the quality of hospitals where Black and White patients receive coronary artery bypass grafting (CABG) surgery have been documented. We examined the contributions of physician networks to the gap.
Methods: This was a cross-sectional study of all Medicare fee-for-service Black and White patients undergoing elective CABG during 2017 to 2019; the primary care physicians and cardiologists treating them for 12 months before surgery (the patients' physician network); and CABG-performing hospitals within 100 miles of each patient.
Cureus
December 2024
College of Medicine, Dar Al Uloom University, Riyadh, SAU.
Background Inflight medical emergencies (IMEs) present a challenging situation due to the availability of limited medical resources and a complex cabin environment. The physicians have an ethical responsibility to aid in such situations. This study aims to assess the attitudes of Saudi physicians regarding IMEs.
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