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PubMed2006

Saving time, improving satisfaction: the impact of a digital radiology system on physician workflow and system efficiency.

The objective of the study was to assess UC Davis Health System's transition to digital radiology. The study involved pre- and post-PACS analyses of workflow and costs, physician satisfaction surveys, and self-recorded radiology interactions by on-call residents. The study revealed significant results. Before the PACS implementation, physicians spent one to three hours searching for films daily and were dissatisfied with radiology services. After implementation, images were readily available, physicians were more likely to view and interpret images themselves, and they reported increased satisfaction. From real-time reporting, residents viewed studies with radiologists 90.2 percent less often. Average image search time decreased, from 16 to 2 minutes, saving 21.5 physician years, worth dollar 1,034,150 annually. Reductions in film printing (73.4 percent) and file clerk full-time equivalents (50.3 percent) saved dollar 1,001,452 annually, and freed up 1,218 hospital and 8,108 warehouse square feet, worth dollar 2,018,320. As a result, UCDHS's digital radiology system improved clinician satisfaction and workflow, increased clinician image viewing, and decreased clinician engagement with radiologists. System implementation saved 21 physician years and dollar 2 million annually.

California↗

PubMed2005

Interruptions in workflow for RNs in a Level One Trauma Center.

An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by ED nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephone, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the outcomes caused by interruptions resulting in medical errors, decreased efficiency and increased cost have not been systematically studied in healthcare. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, and to develop interventions to manage interruptions to improve healthcare quality and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from early studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, identify the bottlenecks of information flow, and develop interventions to improve the efficiency of emergency care through the management of interruptions.

Communication↗

PubMed2006

Medical image registration algorithms assesment: Bronze Standard application enactment on grids using the MOTEUR workflow engine.

Medical image registration is pre-processing needed for many medical image analysis procedures. A very large number of registration algorithms are available today, but their performance is often not known and very difficult to assess due to the lack of gold standard. The Bronze Standard algorithm is a very data and compute intensive statistical approach for quantifying registration algorithms accuracy. In this paper, we describe the Bronze Standard application and we discuss the need for grids to tackle such computations on medical image databases. We demonstrate MOTEUR, a service-based workflow engine optimized for dealing with data intensive applications. MOTEUR eases the enactment of the Bronze Standard and similar applications on the EGEE production grid infrastructure. It is a generic workflow engine, based on current standards and freely available, that can be used to instrument legacy application code at low cost.

Algorithms↗

PubMed1988

Workflow analysis in determining instrumentation needs.

The workflow parameters that have been reviewed should be carefully utilized with all the other traditional evaluation techniques in making an instrument decision. Most laboratory managers make the mistake of purchasing a larger analyzer than is required. The cost of this mistake is not just the usually higher purchase price. Larger and higher speed instruments tend to be more complex, requiring better-trained operators and necessitating more maintenance. In addition, they tend to be less flexible for meeting STAT needs and more difficult to bring out of the stand-by mode. For the smaller laboratory, the oversized analyzer not only raises the operating requirements, but potentially lowers the service capabilities. A careful analysis of the laboratory's workflow and production issues may also do more than help clarify the instrumentation issues. Often an audit of how work is processed will uncover new ways to organize and perform the testing. Instead of a new analyzer solving the perceived problem, the solution that has the most impact may not involve any capital acquisition at all. However, even when the decision reached results in new instrumentation, a better understanding of how the new machine should function in the laboratory's environment will only improve its effectiveness in addressing the need.

Equipment and Supplies↗

PubMed1996

OzCare: a workflow automation system for care plans.

An automated environment for implementing and monitoring care plans and practice guidelines is very important to the reduction of hospital costs and optimization of medical care. The goal of our research effort is to design a general system architecture that facilitates the implementation of (potentially) numerous care plans. Our approach is unique in that we apply the principles and technologies of Oz a multi-user collaborative workflow system that has been used as a software engineering environment framework, to hospital care planning. We utilize not only the workflow modeling and execution facilities of Oz, but also its open-system architecture to interface it with the World Wide Web, the Medical Logic Module server, and other components of the clinical information system. Our initial proof-of-concept system, OzCare, is constructed on top of the existing Oz system. Through several experiments in which we used this system to implement some Columbia-Presbyterian Medical Center care plans, we demonstrated that our system is capable and flexible for care plan automation.

Computer Simulation↗

PubMed1997

A patient workflow management system built on guidelines.

To provide high quality, shared, and distributed medical care, clinical and organizational issues need to be integrated. This work describes a methodology for developing a Patient Workflow Management System, based on a detailed model of both the medical work process and the organizational structure. We assume that the medical work process is represented through clinical practice guidelines, and that an ontological description of the organization is available. Thus, we developed tools 1) for acquiring the medical knowledge contained into a guideline, 2) to translate the derived formalized guideline into a computational formalism, precisely a Petri Net, 3) to maintain different representation levels. The high level representation guarantees that the Patient Workflow follows the guideline prescriptions, while the low level takes into account the specific organization characteristics and allow allocating resources for managing a specific patient in daily practice.

Artificial Intelligence↗

PubMed2027

Workflow for Long-Read Amplicon Sequencing of Chikungunya Virus Using Oxford Nanopore Technology.

This protocol provides a comprehensive, step-by-step workflow for whole-genome sequencing of Chikungunya virus (CHIKV) using an amplicon-based strategy optimized for Oxford Nanopore Technologies (ONT) platforms. The procedure includes detailed instructions for sample handling, viral RNA extraction, quality control, cDNA synthesis, multiplex PCR amplification, library preparation, sequencing, and primary bioinformatic processing. The protocol is designed to maximize reproducibility across laboratories and is suitable for genomic surveillance applications, including outbreak investigation and molecular epidemiology, even when working with low-to-moderate viral loads.

Chikungunya virus↗

PubMed2026

ModiCal: A Targeted Calibration Workflow for Site-Specific m5C Validation by Nanopore Direct RNA Sequencing.

Accurate identification of RNA 5-methylcytidine (m5C) at the single-nucleotide resolution remains a central challenge in nanopore direct RNA sequencing (DRS). Current global scanning and modification-aware basecalling methods enable transcriptome-wide profiling but often yield high false-positive rates and lack site-specific accuracy. To address this, we repurposed ModiDeC, originally a de novo multimodification classifier, into a targeted, high-precision validation tool for RNA modification sites with prior biochemical knowledge. This was implemented through a three-step calibration workflow that alternates between biochemical and computational modules using the well-characterized m5C2278 site in 25S rRNA as a starting point. Baseline training uses short synthetic RNAs carrying either a methylated or unmodified C2278 as ground truth, followed by IVT-derived calibration and validation in methyltransferase knockout yeast. The baseline model accurately detected the bona fide m5C2278 site but initially produced off-target predictions. Iterative retraining with unmodified IVT signals progressively reduced and ultimately eliminated false positives while maintaining a strong signal at the bona fide site. The final model retained enzyme-dependent detection in wild-type versus knockout yeast and, when explicitly targeted, was also able to detect the second rRNA site, C2870, which remained invisible in the initial analysis. Application to native human prerRNA processing intermediates further resolved two distinct m5C deposition regimes on 28S rRNA, while generalization to dengue virus genomic RNA confirmed that the same calibration logic transfers across diverse RNA contexts. Together, this study establishes a reproducible and transferable framework that integrates biochemical validation with iterative neural network refinement, providing a route toward reliable site-specific m5C confirmation by nanopore direct RNA sequencing.

RNA Methylation↗

PubMed2026

A scalable, low-cost, sample hashing workflow for multiomic single-cell analysis using the Seq-Well S3 platform.

In-depth analyses of clinical samples have the potential to provide unparalleled insights into the cellular mechanisms that underlie both health and disease, as well as therapeutic and prophylactic responses. However, these specimens are often paucicellular, necessitating the use of workflows that maximize the amount of information that can be learned. Here we provide a detailed protocol for generating and analyzing single-cell multiomic data from low-input samples with the Seq-Well S3 platform. We further describe a matched pipeline for sample hashing that reduces costs and sources of technical variation in the resulting data while also enhancing throughput. In brief, our streamlined and efficient methodology involves: (1) optionally staining single-cell suspensions with antibody-oligonucleotide conjugates for cell surface protein quantification and/or sample multiplexing; (2) generating Seq-Well S3 sequencing libraries; (3) optionally producing bulk-RNA sequencing libraries via SMART-seq2 to support genetic demultiplexing; and (4) computationally analyzing the resulting data. Each step herein has been designed to leverage readily available reagents and standard laboratory equipment, substantially lowering barriers to entry for researchers. The overall Protocol can yield high-quality multiomic insights from samples in under a week.

Single-Cell Analysis↗

PubMed2025

NanoASV: a snakemake workflow for reproducible field-based Nanopore full-length 16S metabarcoding amplicon data analysis.

SUMMARY: NanoASV is a conda environment and snakemake-based workflow using state-of-the-art bioinformatics software to process full-length SSU rRNA (16S/18S) amplicons acquired with Oxford Nanopore Sequencing technology. Its strength lies in reproducibility, portability, and the possibility to run offline, allowing in-field analysis. It can be installed on the Nanopore MK1C sequencing device and process data locally. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are freely available at https://github.com/ImagoXV/NanoASV and Zenodo archive at https://doi.org/10.5281/zenodo.14730742.

Software↗

PubMed2025

HoloFoodR: a statistical programming framework for holo-omics data integration workflows.

SUMMARY: Holo-omics is an emerging research area that integrates multi-omic datasets from the host organism and its microbiome to study their interactions. Recently, curated and openly accessible holo-omic databases have been developed. The HoloFood database, for instance, provides nearly 10 000 holo-omic profiles for salmon and chicken under controlled treatments. However, bridging the gap between holo-omic data resources and algorithmic frameworks remains a challenge. Combining the latest advances in statistical programming with curated holo-omic data sets can facilitate the design of open and reproducible research workflows in the emerging field of holo-omics. AVAILABILITY AND IMPLEMENTATION: HoloFoodR R/Bioconductor package and the source code are available under the open-source Artistic License 2.0 at the package homepage https://doi.org/10.18129/B9.bioc.HoloFoodR.

Software↗

PubMed2026

LCR-modules: a collection of workflows for cancer genome analysis.

MOTIVATION: The surge of genomic data from advanced sequencing technologies is outpacing current analytical pipelines. We introduce LCR-modules, an open-source suite of bioinformatics tools designed for flexible and automated cancer genome data analysis. LCR-modules enables reproducible analysis of diverse cancer genomics data at scale. The suite comprises 49 Snakemake-based workflows organized into three levels, facilitating tasks from low-level quality control to complex cohort-level analyses. LCR-modules supports various sequencing types and integrates pipelines such as mutation calling, expression quantification, and cohort-level aggregation, ensuring flexibility and reproducibility. LCR-modules represents a significant advancement in genomic data analysis, reducing barriers in reproducibility and scalability and has already been applied to a combination of exomes and genomes from over 10 800 samples. AVAILABILITY: No new data were generated in support of this research. The source code for the LCR-modules is openly available at https://github.com/LCR-BCCRC/lcr-modules.

Software↗

PubMed2026

DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics.

MOTIVATION: Data-independent acquisition (DIA) has become the preferred data acquisition method for mass spectrometry-based proteomics, yet, reproducible workflows for differential expression (DE) analysis and results reporting remain limited. We present DiaReport, an R package that performs precursor- and protein-level DE analysis from DIA-NN output using MSqRob and QFeatures, while generating high-quality, interactive HTML reports through Quarto. DiaReport integrates precursor data, filtering of missing values, normalization, protein summarization and statistical modeling within a single function, supporting both simple pairwise as well as complex experimental designs. The package provides structured outputs and configuration files to ensure computational reproducibility across different studies. To accommodate diverse research needs, DiaReport includes multiple reporting templates tailored to different proteomic applications. Applying DiaReport to an extracellular vesicle (EV) proteomics dataset demonstrates its ability to efficiently analyze DIA data and provide rapid insights into sample quality and protein level differences. AVAILABILITY: DiaReport is an open-source R package available at https://github.com/Gevaert-Lab/diareport (DOI: 10.5281/zenodo.20120604). The package is platform-independent and distributed under the MIT license. Reports are generated using Quarto and require only standard R dependencies. Detailed documentation, installation guides and usage vignettes are provided within the repository. The interactive HTML reports discussed in this study, including the UPS2 benchmark and EV case study, are archived on Zenodo (10.5281/zenodo.20122506 and 10.5281/zenodo.20123378).

Proteomics↗

PubMed2026

UnionLoops: a workflow for calling chromatin loops across related Hi-C datasets with improved specificity, precision, and sensitivity.

Chromatin loop calling from chromatin interaction data often exhibits substantial variability across related samples. We present UnionLoops, a computational workflow for chromatin loop calling across multiple related samples. UnionLoops integrates information across datasets to determine positions and dataset-specificity of looping interactions. It constructs a unified candidate loop set, applies consistent filtering and aggregation, and evaluates loop support across samples. We demonstrate that UnionLoops increases sensitivity for detecting shared chromatin loops, reduces spurious sample-specific calls, and improves concordance with independent genomic features, including CTCF and cohesin occupancy. UnionLoops enables improved biological interpretation of chromatin loop organization and dynamics across related conditions.

Chromatin↗

PubMed2000

New aspects of image distribution and workflow in radiology.

The progressive use of digital image-generating devices and digital communication technology in clinical and practice environments implies changes in radiological workflow and asks for adequate quality assurance in the whole process of radiology report preparation. This improvement potential has to be rigorously reinvestigated with regard to up-to-date procedures and the full exploitation of supporting technologies like linguistic analysis, help desk and trouble ticket systems, competitive allocation algorithms, time-and-event monitoring, and intelligent agents. These approaches are to be evaluated in combination with business process analysis and shall help to reduce turnaround times for radiology reports while maintaining or even increasing quality-assurance levels.

Germany↗

PubMed2005

Comparison of retrospectively ECG-gated and nongated MDCT of the chest in an emergency setting regarding workflow, image quality, and diagnostic certainty.

PURPOSE: This study aims to assess the influence of ECG-gated acquisition on workflow and to compare image quality and diagnostic certainty for retrospectively ECG-gated and nongated multidetector computed tomography of the chest in the emergency suite. MATERIALS AND METHODS: Thirty-two consecutive patients were referred for both an ECG-gated and a nongated CT to rule out traumatic thoracic injury (n=15) or acute aortic dissection (n=17). The time from the start of the transportation from the emergency suite to the CT room until the start of the CT scan was recorded. Using a scoring system, the image quality of axial images and multiplanar reformats, the presence of disease, and the subjective diagnostic certainty were assessed with regard to the vascular structures, the bone structures, and the lung parenchyma. RESULTS: The time needed for transportation and patient preparation was 12.1+/-1.7 min (8.1-14.5 min). The motion artifacts of the thoracic aorta and the supra-aortic vessels were significantly reduced in the ECG-gated data acquisition compared with the nongated technique (P<0.001). Subjective diagnostic certainty for assessment of the aorta was significantly better using ECG gating. The image quality of the lung parenchyma (P<0.005), the spine (P<0.005), and the ribs (P<0.002) was inferior in the ECG-gated data sets but did not compromise the detection rate of traumatic lesions and fractures. CONCLUSION: Performing ECG gating in the emergency room did not slow down the diagnostic workup. ECG-gated acquisition performed better in the assessment of the aorta, but image quality for lung and bone structures was slightly reduced. Further studies are required to assess the influence of the imaging technique on the diagnostic outcome.

Aorta, Thoracic↗

PubMed2004

Using electronic medical record data for clinical workflow and analysis: a single center experience.

This paper focuses on the use of data from an electronic medical record (EMR) within a multi-facility health care organization. It describes how health provider workflow is enhanced by extracting data from multiple sources in a near real-time fashion and presenting it to the user in ways that are unavailable in the electronic medical record applications.

Decision Support Systems, Clinical↗

PubMed2026

Application of PathoChip to urine-derived nucleic acids for broad microbial profiling in men with suspected prostate cancer: setup of a methodological workflow and pilot feasibility study.

BACKGROUND: Urine-based liquid biopsy is an attractive non-invasive source of prostate cancer (PCa) biomarkers, but urinary microbiome studies have mainly relied on 16S rRNA sequencing or shotgun metagenomics. This pilot study optimized and evaluated a practical workflow using PathoChip - a broad-spectrum microarray designed to detect bacterial, viral, fungal, and parasitic signatures - for microbial profiling of urine sediments from men with suspected PCa, an application not previously established. METHODS: First-morning urine was collected without prostatic massage from 35 men scheduled for biopsy; 19 were diagnosed with PCa and 16 were biopsy-negative. Different urine volumes and extraction strategies were evaluated to optimize DNA/RNA recovery. A setup phase compared 25 ng versus 50 ng of urine DNA and RNA input. DNA/RNA isolated from human B cells was used as reference control. An analysis pipeline was developed to detect outlier probes and create a presence/absence matrix. Reproducibility was assessed via library yield, Pearson correlation, blank-control subtraction, outlier probe detection. Prevalence comparisons were performed between clinical groups. RESULTS: An 8 mL starting volume was chosen as consistently available from self-collected urine. Sequential DNA/RNA extraction using the AllPrep DNA/RNA Micro Kit from sediment provided the best balance between nucleic-acid recovery, purity, and clinical compatibility. Reducing the input from 50 ng to 25 ng preserved highly concordant hybridization profiles, with matched samples clustering together with strong correlations. Exploratory analysis revealed PCa- and grade-associated patterns involving Actinomycetaceae, Aerococcaceae, and Streptococcaceae, with Streptococcaceae enriched in PCa of higher grades (ISUP GG ≥ 2). Other signatures, including Mobiluncus, Prevotella, Rhodotorula, Hymenolepis, and JC polyomavirus, were broadly detected but not PCa-discriminating. CONCLUSIONS: PathoChip can be adapted to urine sediments, generating reproducible microbial profiles from limited DNA/RNA input without prostatic massage. This platform provides a quick and accessible approach to broad screening, extending beyond 16S rRNA sequencing by enabling simultaneous multi-kingdom detection. The observed PCa- and grade-associated patterns are hypothesis-generating and require validation in larger independent cohorts.

Pathochip↗