What explains very poor Yelp reviews of oral and maxillofacial surgeons in private practice?

OBJECTIVE: Websites that maintain online physician ratings, such as Yelp.com, have been growing in popularity throughout the United States. The purpose of this study was to determine which factors increase the risk for very poor reviews (1 out of 5 stars) on Yelp.com for oral and maxillofacial surgeons (OMSs) in private practice. STUDY DESIGN: A retrospective cohort study was conducted using data on OMSs from Yelp.com. Predictor variables included clinician characteristics, practice characteristics, and review characteristics. The primary outcome variable was a very poor review. Logistic regression was used to determine risk factors for a very poor review. RESULTS: The final sample consisted of 3802 reviews. Relative to male clinicians, female clinicians were 2.7 times (P < .01) more likely to receive a very poor review. Clinicians who completed residency during the 1970s were over 4.5 times (P < .01) more likely to receive a very poor review relative to clinicians who completed residency during the 2010s. Relative to clinical reviews, nonclinical reviews were more likely (odds ratio = 2.6, P < .01) to be very poor and clinical and nonclinical reviews were less likely (odds ration = 0.5, P < .01) to be very poor. CONCLUSIONS: Nonclinical reviews were more likely to be very poor relative to clinical reviews. Several clinician factors, including female sex and completing OMS residency during the 1970s, were risk factors for receiving a very poor review.

Rapid Response to Drive COVID-19 Research in a Learning Health Care System: Rationale and Design of the Houston Methodist COVID-19 Surveillance and Outcomes Registry (CURATOR).

BACKGROUND: The COVID-19 pandemic has exacerbated the challenges of meaningful health care digitization. The need for rapid yet validated decision-making requires robust data infrastructure. Organizations with a focus on learning health care (LHC) systems tend to adapt better to rapidly evolving data needs. Few studies have demonstrated a successful implementation of data digitization principles in an LHC context across health care systems during the COVID-19 pandemic. OBJECTIVE: We share our experience and provide a framework for assembling and organizing multidisciplinary resources, structuring and regulating research needs, and developing a single source of truth (SSoT) for COVID-19 research by applying fundamental principles of health care digitization, in the context of LHC systems across a complex health care organization. METHODS: Houston Methodist (HM) comprises eight tertiary care hospitals and an expansive primary care network across Greater Houston, Texas. During the early phase of the pandemic, institutional leadership envisioned the need to streamline COVID-19 research and established the retrospective research task force (RRTF). We describe an account of the structure, functioning, and productivity of the RRTF. We further elucidate the technical and structural details of a comprehensive data repository-the HM COVID-19 Surveillance and Outcomes Registry (CURATOR). We particularly highlight how CURATOR conforms to standard health care digitization principles in the LHC context. RESULTS: The HM COVID-19 RRTF comprises expertise in epidemiology, health systems, clinical domains, data sciences, information technology, and research regulation. The RRTF initially convened in March 2020 to prioritize and streamline COVID-19 observational research; to date, it has reviewed over 60 protocols and made recommendations to the institutional review board (IRB). The RRTF also established the charter for CURATOR, which in itself was IRB-approved in April 2020. CURATOR is a relational structured query language database that is directly populated with data from electronic health records, via largely automated extract, transform, and load procedures. The CURATOR design enables longitudinal tracking of COVID-19 cases and controls before and after COVID-19 testing. CURATOR has been set up following the SSoT principle and is harmonized across other COVID-19 data sources. CURATOR eliminates data silos by leveraging unique and disparate big data sources for COVID-19 research and provides a platform to capitalize on institutional investment in cloud computing. It currently hosts deeply phenotyped sociodemographic, clinical, and outcomes data of approximately 200,000 individuals tested for COVID-19. It supports more than 30 IRB-approved protocols across several clinical domains and has generated numerous publications from its core and associated data sources. CONCLUSIONS: A data-driven decision-making strategy is paramount to the success of health care organizations. Investment in cross-disciplinary expertise, health care technology, and leadership commitment are key ingredients to foster an LHC system. Such systems can mitigate the effects of ongoing and future health care catastrophes by providing timely and validated decision support.

Non-Hodgkin's Lymphoma of the Anterior Maxilla Mimicking a Chronic Apical Abscess.

Non-Hodgkin lymphomas (NHLs) are malignant neoplasms of the lymphatic system, typically occurring in the fifth through seventh decades of life. Tumors develop from abnormal lymphocyte proliferation and accumulation. Although a majority of NHLs occur in nodal regions, 40% of cases appear in extranodal sites involving the stomach, spleen, Waldeyer's ring, central nervous system, lung, skin, and bone. Extranodal NHL presents a diagnostic challenge because it may mimic endodontic disease when occurring in intraosseous and soft tissue sites. This case report presents misdiagnosis of a diffuse large B-cell lymphoma (DLBCL) of the anterior maxilla in a 72-year-old man with a history of Waldenstrom's macroglobulinemia, where the lesion was thought to be associated with a necrotic pulp and a chronic apical abscess on tooth #7. Clinical findings of a facial sinus tract, a nonresponsive pulp, large periapical radiolucency, and history of trauma were in support of this diagnosis for tooth #7. On encountering vital pulpal tissues during cavity access of tooth #7, a cone-beam computed tomography scan and lesion biopsy were obtained. Through immunohistochemistry and histologic analysis, a diagnosis of DLBCL was made. During evaluation of lesions with suspected endodontic etiology, the clinician should consider all factors of the patient's health history, hereditary risk, and comprehensive clinical testing to attain a differential diagnosis. A nonodontogenic etiology of disease should always be considered unless ruled out otherwise. Atypical presentation or testing may prompt the need for biopsy and interspecialty assessment.