ABSTRACT
No standard tool to measure pathologist workload currently exists. An accurate measure of workload is needed for determining the number of pathologists to be hired, distributing the workload fairly among pathologists, and assessing the overall cost of pathology consults. Initially, simple tools such as counting cases or slides were used to give an estimate of the workload. More recently, multiple workload models, including relative value units (RVUs), the Royal College of Pathologists (RCP) point system, Level 4 Equivalent (L4E), Work2Quality (W2Q), and the University of Washington, Seattle (UW) slide count method, have been developed. There is no "ideal" model that is universally accepted. The main differences among the models come from the weights assigned to different specimen types, differential calculations for organs, and the capture of additional tasks needed for safe and timely patient care. Academic centers tend to see more complex cases that require extensive sampling and additional testing, while community-based and private laboratories deal more with biopsies. Additionally, some systems do not account for teaching, participation in multidisciplinary rounds, quality assurance activities, and medical oversight. A successful workload model needs to be continually updated to reflect the current state of practice.Awareness about physician burnout has gained attention in recent years and has been added to the World Health Organization's International Classification of Diseases (World Health Organization, WHO) as an occupational phenomenon. However, the extent to which this affects pathologists is not well understood. According to the WHO, burnout syndrome is diagnosed by the presence of three components: emotional exhaustion, depersonalization from one's work (cynicism related to one's job), and a low sense of personal achievement or accomplishment. Three drivers of burnout are the demand for productivity, lack of recognition, and electronic health records. Prominent consequences of physician burnout are economic and personal costs to the public and to the providers.Wellness is physical and mental well-being that allows individuals to manage stress effectively and to thrive in both their professional and personal lives. To achieve wellness, it is necessary to understand the root causes of burnout, including over-work and working under stressful conditions. Wellness is more than the absence of stress or burnout, and the responsibility of wellness should be shared by pathologists themselves, their healthcare organization, and governing bodies. Each pathologist needs to take their own path to achieve wellness.
Subject(s)
Burnout, Professional , Pathologists , Workload , HumansSubject(s)
Breast Neoplasms , Prostate-Specific Antigen , Male , Female , Humans , Breast Neoplasms/diagnosis , Biomarkers, TumorABSTRACT
BACKGROUND/AIM: Renal cell carcinoma is one of the most common types of cancer worldwide. Understanding tumor pathogenesis is important in developing better treatment. Micro RNAs (miRNAs) are key players in controlling cancer behavior. Transcription factors (TFs) are potentially responsible for controlling miRNA expression and dysregulation in kidney cancer. The objective of this study was to better understand the TF-miRNA axis of interaction. MATERIALS AND METHODS: We utilized publicly available databases to investigate miRNA-TF interactions, including ChipBase database for TFs that binds to the promoters of miRNAs which are dysregulated in renal cell carcinoma. Renal cancer-specific TFs were extracted from the list using the GENT Database. We assessed the prognostic significance of these TFs using cBioPortal. RESULTS: We identified TFs which bind to miRNA promoters, including hepatocyte nuclear factor-4 alpha (HNF-4α), E2F transcription factor 4 (E2F4), signal transducer and activator of transcription 1 (STAT1), Sp1 transcription factor (SP1), GATA binding protein 6 (GATA6), and nuclear factor kappa B (NFκB). These TFs were positively correlated with their targeted miRNAs, including miR-200c, miR-15a, miR-146b, miR-155, and miR-223. We recognized unique patterns of interactions, including a divergent effect in which multiple miRNAs are simultaneously affected by the same TF. CONCLUSION: Our results show that miRNA-TF interaction is complex. Expression levels of these TFs were found to correlate with renal carcinoma prognosis and have potential utility as biomarkers for aggressive tumor behavior. Targeting these TFs may result in modulating the expression of their target genes and miRNAs, with subsequent therapeutic implications.
Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , MicroRNAs , Carcinoma, Renal Cell/genetics , Female , Gene Regulatory Networks , Humans , Kidney Neoplasms/genetics , Male , MicroRNAs/metabolismABSTRACT
Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately overtakes the existing market. Typically, when disruptive innovations are introduced, their performance is initially less than existing standard technologies, but because of their ability to bring the cost down, and with gradual improvement, they end up replacing established service standards.Disruptive technologies have their fingerprints in health care. Pathology and laboratory medicine are fertile soils for disruptive innovations because they are heavily reliant on technology. Disruptive innovations have resulted in a revolution of our diagnostic ability and will take laboratory medicine to the next level of patient care. There are several examples of disruptive innovations in the clinical laboratory. Digitizing pathology practice is an example of disruptive technology, with many advantages and an extended scope of applications. Next-generation sequencing can be disruptive in two ways. The first is by replacing an array of laboratory tests, which each requires expensive and specialized instruments and expertise, with a single cost-effective technology. The second is by disrupting the current paradigm of the clinical laboratory as a diagnostic service by taking it into a new era of preventive or primary care pathology. Other disruptive innovations include the use of dry chemistry reagents in chemistry analyzers and also point of care testing. The use of artificial intelligence is another promising disruptive innovation that can transform the future of pathology and laboratory medicine. Another emerging disruptive concept is the integration of two fields of medicine to create an interrelated discipline such as "histogenomics and radiohistomics." Another recent disruptive innovation in laboratory medicine is the use of social media in clinical practice, education, and publication.There are multiple reasons to encourage disruptive innovations in the clinical laboratory, including the escalating cost of health care, the need for better accessibility of diagnostic care, and the increased demand on the laboratory in the era of precision diagnostics. There are, however, a number of challenges that need to be overcome such as the significant resistance to disruptive innovations by current technology providers and governmental regulatory bodies. The hesitance from health care providers and insurance companies must also be addressed.Adoption of disruptive innovations requires a multifaceted approach that involves orchestrated solutions to key aspects of the process, including creating successful business models, multidisciplinary collaborations, and innovative accreditation and regulatory oversight. It also must be coupled with successful commercialization plans and modernization of health care structure. Fostering a culture of disruptive innovation requires establishing unique collaborative models between academia and industry. It also requires uncovering new sources of unconventional funding that are open to high-risk high-reward projects. It should also be matched with innovative thinking, including new approaches for delivery of care and identifying novel cohorts of patients who can benefit from disruptive technology.