Search PubMed⌕ Search

PubMed · 9495695

Malpractice risks for urologists.

Abstract

OBJECTIVES: To obtain data regarding the frequency of malpractice suits against urologists. METHODS: Those urologists listed in the Best Doctors in America were sent an anonymous survey that requested their personal malpractice history (group A). Additionally, the professional responsibility history of the candidates for recertification by the American Board of Urology in 1996 (group B) was reviewed. RESULTS: One hundred ten urologists in the United States in group A were surveyed. Ninety-one (83%) responded. Seventy (77%) had been sued (average 2.36 claims per physician who had been sued). Forty-four percent of the claims resulted in payment to the plaintiff. Claims frequency of group A was 0.09 claims per physician per year. Urologists in the Northeast, North Central, and Mid-Atlantic Sections of the American Urological Association were less likely to be sued than urologists in the other five sections. There were 246 urologists in group B. One hundred twenty-two (49%) reported a claim against them (average 1.9 claims per physician who had been sued). Twenty-nine percent of the closed claims resulted in payment to the plaintiff. Claims frequency of group B was 0.09 claims per physician per year. CONCLUSIONS: Most urologists can expect to be sued at least twice in their professional careers. The longer one is in practice, the greater the chance of a suit being filed. Where one practices may be a factor in the likelihood of being sued. There does not seem to be a direct or inverse correlation between professional reputation and the incidence of being sued.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

G W Kaplan. 1998. Malpractice risks for urologists.. https://doi.org/10.1016/s0090-4295(97)00633-x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗