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PubMedDate not supplied

Assessment of workflow redesign in community pharmacy.

OBJECTIVE: To assess the effect that workflow enhancements have on dispensing responsibilities and pharmacist-patient interaction in the community pharmacy setting. DESIGN: Pre-post comparison. Pre-assessment data were obtained from a multisite observational study. SETTING: Pharmacy within a regional pharmacy chain. STUDY PARTICIPANTS: 3 pharmacists and 110 patients. INTERVENTION: The pharmacy was physically remodeled to enable workflow changes, including defining dispensing responsibilities with an emphasis on patient counseling, providing an additional 6 feet of counter space, upgrading technology, installing a third computer, implementing tools to augment the filling process, and requesting that cashiers rephrase the offer to counsel to encourage patient acceptance. Patients and pharmacists were surveyed about the experiences and beliefs, and pharmacy activities were observed directly. MAIN OUTCOME MEASURES: Patient counseling and prescription dispensing. activities. RESULTS: The number of pharmacists who perceived that they had adequate time to counsel patients increased as a result of the intervention (0 of 3 responding pharmacists before the intervention, compared with 2 of 2 afterward). Patient satisfaction scores both before and after the intervention were predominantly favorable and did not differ significantly. The most relevant change in dispensing activities was pharmacist involvement with data entry into the computer, which decreased from 61% to 10%. Oral counseling offers to patients increased significantly, from 5% to 85%, but counseling rates remained low throughout the study and were not measurably affected by workload. CONCLUSION: Workflow redesign has positively affected the dispensing activities at the study site. Technicians took more responsibility for dispensing tasks. Given the drastic increase in counseling offers but lack of effect on counseling rates, patient behavior and expectations with regard to counseling likely need to change to further improve dynamics in the community pharmacy.

Architectural Accessibility↗

PubMed1998

Dynamic workflow model for complex activity in intensive care unit.

Cooperation is very important in Medical care, especially in the Intensive Care Unit (ICU) where the difficulties increase which is due to the urgency of the work. Workflow systems are considered as well adapted to modelize productive work in business process. We aim at introducing this approach in the Health Care domain. We have proposed a conversation-based Workflow in order to modelize the therapeutics plan in the ICU [1]. But in such a complex field, the flexibility of the workflow system is essential for the system to be usable. In this paper, we focus on the main points used to increase the dynamicity. We report on affecting roles, highlighting information, and controlling the system We propose some solutions and describe our prototype in the ICU.

Humans↗

PubMed2004

Editing and publishing of a medical journal. Success of an unconventional workflow.

Regional journals often face constraints that threaten their growth, calling for novel coping strategies. This paper outlines the problems and challenges in editing and publishing the SQU Journal for Scientific Research: Medical Sciences, the only peer-reviewed medical journal in the Sultanate of Oman. These included the absence of secretarial support and the consequent need to reduce paperwork, the fact that most papers required substantial editing even after peer review, and the lack of a single workflow for creating documents for the press and the Internet. These challenges were successfully met by creating an unconventional all-electronic workflow that catered to both the print and the online versions. The paper describes this workflow and offers suggestions for journals wishing to streamline theirs.

Editorial Policies↗

PubMed2004

Modeling guidelines for integration into clinical workflow.

The success of clinical decision-support systems requires that they are seamlessly integrated into clinical workflow. In the SAGE project, which aims to create the technological infra-structure for implementing computable clinical practice guide-lines in enterprise settings, we created a deployment-driven methodology for developing guideline knowledge bases. It involves (1) identification of usage scenarios of guideline-based care in clinical workflow, (2) distillation and disambiguation of guideline knowledge relevant to these usage scenarios, (3) formalization of data elements and vocabulary used in the guideline, and (4) encoding of usage scenarios and guideline knowledge using an executable guideline model. This methodology makes explicit the points in the care process where guideline-based decision aids are appropriate and the roles of clinicians for whom the guideline-based assistance is intended. We have evaluated the methodology by simulating the deployment of an immunization guideline in a real clinical information system and by reconstructing the workflow context of a deployed decision-support system for guideline-based care. We discuss the implication of deployment-driven guideline encoding for sharability of executable guidelines.

Decision Making, Computer-Assisted↗

PubMed2002

A web-based workflow system for emergency healthcare.

Emergency healthcare delivery involves a variety of activities performed from the time of a call to the ambulance service till the time of patient's disposal from the emergency department of a hospital. Workflow systems have recently received considerable attention in the healthcare field since they overcome organizational structures and support collaboration and coordination requirements by automatically routing relevant information where and when needed. In particular, healthcare workflow systems implemented over the Web can form the basis for a collaborative environment by bringing together healthcare professionals who are geographically dispersed and, hence, creating virtual healthcare workgroups organized around patient care. In this paper, a web-based workflow system is presented that was developed to support emergency healthcare processes and to provide an infrastructure for the integration of pre-hospital and in-hospital emergency healthcare.

Emergency Service, Hospital↗

PubMed2005

Workflow modeling in critical care: piecing your own puzzle.

The intensive care unit (ICU) is an instance of a very dynamic health care setting where critically ill patients are being managed. It comprises of an extensive amount of communication amongst the role players, use of numerous information systems and operation of devices for monitoring and treatment purposes. The purpose of this research is to study error evolution and management within this environment. Ethnographic observation and semi-structured interview data were used to build individual pieces of the workflow dependent on the individual and the activity concerned. These pieces of the ICU workflow were used to develop a generalizable cognitive model to represent the intricate workflow in health care settings. The proposed model can be used to identify and characterize medical errors and also used for error prediction in practice.

Cognition↗

PubMed1994

From chart tracking to workflow management.

The current interest in system-wide integration appears to be based on the assumption that an organization, by digitizing information and accepting a common standard for the exchange of such information, will improve the accessibility of this information and automatically experience benefits resulting from its more productive use. We do not dispute this reasoning, but assert that an organization's capacity for effective change is proportional to the understanding of the current structure among its personnel. Our workflow manager is based on the use of a Parameterized Petri Net (PPN) model which can be configured to represent an arbitrarily detailed picture of an organization. The PPN model can be animated to observe the model organization in action, and the results of the animation analyzed. This simulation is a dynamic ongoing process which changes with the system and allows members of the organization to pose "what if" questions as a means of exploring opportunities for change. We present, the "workflow management system" as the natural successor to the tracking program, incorporating modeling, scheduling, reactive planning, performance evaluation, and simulation. This workflow management system is more than adequate for meeting the needs of a paper chart tracking system, and, as the patient record is computerized, will serve as a planning and evaluation tool in converting the paper-based health information system into a computer-based system.

Computer Simulation↗

PubMed1998

[Effective use of a laboratory database: quality assurance and laboratory workflow applications].

Recent laboratory information systems have usually adopted a client server system. Computing tools which can provide easy access to a database using simple language are now strongly needed. These functions are provided in an End User Computing (EUC) system. An EUC is defined as follows: 1) General end users can easily access the database of the laboraotry system and extract objective data stored in database. 2) The extracted data will be easily converted to files that can be processed by commercially available software. In this paper, we demonstrate the examples how to use the EUC for a quality assurance system and analyses of laboratory workflow. In the case of quality assurance, we demonstrate the setting of reference intervals from stored laboratory data concerning health care examination programs at our university. Secondly, we developed a system of monitoring quality control data, and set parameters for delta checking and actual zone QC method. We can estimate and design an outline of laboratory workflow from extraction of the time currently required for each task. We can measure the turn-around time for laboratory testing and rate of requests for laboratory tests received from physicians via order entry system. Moreover, we can estimate and simulate the waiting time and time required for analyses by outpatient clinics. These time monitoring systems reflect the design of laboratory workflow such as the labor and equipment time required in laboratory work. These uses of laboratory data are currently expanding further and further in the fields of education and laboratory research. We believe that information technology will facilitate future advances of laboratory medicine.

Clinical Laboratory Information Systems↗

PubMed2024

Evaluating culture-free targeted next-generation sequencing for diagnosing drug-resistant tuberculosis: a multicentre clinical study of two end-to-end commercial workflows.

BACKGROUND: Drug-resistant tuberculosis remains a major obstacle in ending the global tuberculosis epidemic. Deployment of molecular tools for comprehensive drug resistance profiling is imperative for successful detection and characterisation of tuberculosis drug resistance. We aimed to assess the diagnostic accuracy of a new class of molecular diagnostics for drug-resistant tuberculosis. METHODS: We conducted a prospective, cross-sectional, multicentre clinical evaluation of the performance of two targeted next-generation sequencing (tNGS) assays for drug-resistant tuberculosis at reference laboratories in three countries (Georgia, India, and South Africa) to assess diagnostic accuracy and index test failure rates. Eligible participants were aged 18 years or older, with molecularly confirmed pulmonary tuberculosis, and at risk for rifampicin-resistant tuberculosis. Sensitivity and specificity for both tNGS index tests (GenoScreen Deeplex Myc-TB and Oxford Nanopore Technologies [ONT] Tuberculosis Drug Resistance Test) were calculated for rifampicin, isoniazid, fluoroquinolones (moxifloxacin, levofloxacin), second line-injectables (amikacin, kanamycin, capreomycin), pyrazinamide, bedaquiline, linezolid, clofazimine, ethambutol, and streptomycin against a composite reference standard of phenotypic drug susceptibility testing and whole-genome sequencing. FINDINGS: Between April 1, 2021, and June 30, 2022, 832 individuals were invited to participate in the study, of whom 720 were included in the final analysis (212, 376, and 132 participants in Georgia, India, and South Africa, respectively). Of 720 clinical sediment samples evaluated, 658 (91%) and 684 (95%) produced complete or partial results on the GenoScreen and ONT tNGS workflows, respectively, with 593 (96%) and 603 (98%) of 616 smear-positive samples producing tNGS sequence data. Both workflows had sensitivities and specificities of more than 95% for rifampicin and isoniazid, and high accuracy for fluoroquinolones (sensitivity approximately ≥94%) and second line-injectables (sensitivity 80%) compared with the composite reference standard. Importantly, these assays also detected mutations associated with resistance to critical new and repurposed drugs (bedaquiline, linezolid) not currently detectable by any other WHO-recommended rapid diagnostics on the market. We note that the current format of assays have low sensitivity (≤50%) for linezolid and more work on mutations associated with drug resistance is needed. INTERPRETATION: This multicentre evaluation demonstrates that culture-free tNGS can provide accurate sequencing results for detection and characterisation of drug resistance from Mycobacterium tuberculosis clinical sediment samples for timely, comprehensive profiling of drug-resistant tuberculosis. FUNDING: Unitaid.

Humans↗

PubMed2025

PathoSeq-QC: a decision support bioinformatics workflow for robust genomic surveillance.

MOTIVATION: Recommendations on the use of genomics for pathogens surveillance are evidence that high-throughput genomic sequencing plays a key role to fight global health threats. Coupled with bioinformatics and other data types (e.g., epidemiological information), genomics is used to obtain knowledge on health pathogenic threats and insights on their evolution, to monitor pathogens spread, and to evaluate the effectiveness of countermeasures. From a decision-making policy perspective, it is essential to ensure the entire process's quality before relying on analysis results as evidence. Available workflows usually offer quality assessment tools that are primarily focused on the quality of raw NGS reads but often struggle to keep pace with new technologies and threats, and fail to provide a robust consensus on results, necessitating manual evaluation of multiple tool outputs. RESULTS: We present PathoSeq-QC, a bioinformatics decision support workflow developed to improve the trustworthiness of genomic surveillance analyses and conclusions. Designed for SARS-CoV-2, it is suitable for any viral threat. In the specific case of SARS-CoV-2, PathoSeq-QC: (i) evaluates the quality of the raw data; (ii) assesses whether the analysed sample is composed by single or multiple lineages; (iii) produces robust variant calling results via multi-tool comparison; (iv) reports whether the produced data are in support of a recombinant virus, a novel or an already known lineage. The tool is modular, which will allow easy functionalities extension. AVAILABILITY AND IMPLEMENTATION: PathoSeq-QC is a command-line tool written in Python and R. The code is available at https://code.europa.eu/dighealth/pathoseq-qc.

Genomics↗

PubMed2026

sedimix: a workflow for the analysis of hominin nuclear DNA sequences from sediments.

SUMMARY: Sediment DNA-the recovery of genetic material from archaeological sediments-is an exciting new frontier in ancient DNA research, offering the potential to study individuals at a given archaeological site without destructive sampling. In recent years, several studies have demonstrated the promise of this approach by extracting hominin DNA from prehistoric sediments, including those dating back to the Middle or Late Pleistocene. However, a lack of open-source workflows for analysis of hominin sediment DNA samples poses a challenge for data processing and reproducibility of findings across studies. Here, we introduce a snakemake workflow, sedimix, for processing genomic sequences from archaeological sediment DNA samples to identify hominin sequences and generate relevant summary statistics to assess the reliability of the pipeline. By performing simulations and comparing our results to two published studies with human DNA from ∼25,000 years ago (including shotgun data from a sediment sample and capture data from touch DNA recovered from a deer tooth pendant) we demonstrate that sedimix yields accurate and reliable inferences. sedimix offers a reliable and adaptable framework to aid in the analysis of sediment DNA datasets and improve reproducibility across studies. AVAILABILITY AND IMPLEMENTATION: sedimix is available as an open-source software with the associated code, example data, and user manual with installation instructions available at https://github.com/jierui-cell/sedimix. A permanent archived version of this release is available via Zenodo: https://doi.org/10.5281/zenodo.17244854.

Animals↗

PubMed2026

TriosCompass: a snakemake workflow for integrated detection of SNVs, indels, STRs, and structural de novo variants in parent-child trios.

MOTIVATION: The accurate and sensitive identification of de novo variants, which are unique to an individual and not found in the parents' germlines, is critical for understanding the genetic basis of rare diseases, developmental disorders, and evolutionary processes. Existing de novo variant detection pipelines often lack the flexibility to handle multiple variant types, struggle with speed and reproducibility across computational environments, demand extensive manual configuration, or require bioinformatics expertise for downstream curation and analysis, limiting their scalability and usability for large genomic studies. Accordingly, there is a pressing need to better address these challenges. RESULTS: We introduce TriosCompass, an open-source Snakemake workflow that addresses these challenges by providing a modular, accelerated, and environmentally-configurable end-to-end solution for comprehensive de novo variant discovery. It integrates state-of-the-art tools into a reproducible framework, empowering researchers to discover novel genetic insights with greater efficiency and reliability. AVAILABILITY: TriosCompass is implemented as a Snakemake workflow and is freely available at https://github.com/NCI-CGR/TriosCompass_v2 or on Zenodo (10.5281/zenodo.17981062). SUPPLEMENTARY INFORMATION: Supplementary data is available on GitHub at https://github.com/NCI-CGR/TriosCompass_v2/tree/manuscript/report_dashboards. Supplementary methods on DeepTrio benchmark runs can be viewed at: https://github.com/NCI-CGR/TriosCompass_v2/blob/manuscript/TriosCompass_Supp_Methods_deeptrio_benchmark.md.

Software↗

PubMed2025

MetaflowX: a scalable and resource-efficient workflow for multi-strategy metagenomic analysis.

Microbiomes play crucial roles in diverse ecosystems, spanning environmental, agricultural, and human health domains. However, in-depth metagenomic data analysis presents significant technical and resource challenges, particularly at scale. Existing computational pipelines are typically limited to either reference-based or reference-free approaches and exhibit inefficiencies in process large datasets. Here, we introduce MetaflowX (https://github.com/01life/MetaflowX), an open-resource workflow integrating both analytical paradigms for enhanced metagenomic investigations. This modular framework encompasses short-read quality control, rapid microbial profiling, hybrid contig assembly and binning, high-quality metagenome-assembled genome (MAG) identification, as well as bin refinement and reassembly. Benchmarking tests showed that MetaflowX completed full metagenomic analyses up to 14-fold faster and with 38% less disk usage than existing workflows. It also recovered the highest number of high-quality and taxonomically diverse MAGs. A dedicated reassembly module further improved MAG quality, increasing completeness by 5.6% and reducing contamination by 53% on average. Functional annotation modules enable detection of key features, including virulence and antibiotic resistance genes. Designed for extensibility, MetaflowX provides an efficient solution addressing current and emerging demands in large-scale metagenomic research.

Metagenomics↗

PubMed2025

LncRAnalyzer: a robust workflow for long non-coding RNA discovery using RNA-Seq.

Long non-coding RNA (lncRNA) is a major transcript category that lacks protein-coding capabilities, with relatively low abundance and complex expression patterns. Distinguishing lncRNAs from protein-coding genes is a complex process involving multiple filtering steps. We developed an automated pipeline named LncRAnalyzer featuring retrained models for 60 species. This workflow aims to reduce the likelihood of obtaining protein-coding or partial protein-coding transcripts during lncRNA identification by utilizing eight distinct approaches. We conducted a 10-fold cross-validation of the sorghum models and training sets with their standard ones and other approaches using real-life RNA-Seq datasets and known lncRNA and CDS sequences of sorghum. The results showed that the sorghum models and training sets were outperformed. The pipeline output comprises upset plots illustrating the number of lncRNA/NPCTs identified by the approaches, commonly identified lncRNA and their classes, NPCTs, and expression count tables. A feature-level comparison and benchmarking analysis of LncRAnalyzer with four existing pipelines, namely, LncPipe, LncEvo, lncRNA-Annotation, and Plant-LncPipe, demonstrated that LncRAnalyzer is more comprehensive, easier to implement, and accurate in lncRNA predictions. This workflow also ascertains lncRNA origins from various Transposable Elements (TEs) in plants using TE annotations from APTEdb [http://apte.cp.utfpr.edu.br/]. LncRAnalyzer is publicly available on GitLab [https://gitlab.com/nikhilshinde0909/LncRAnalyzer.git] for academic users.

RNA, Long Noncoding↗

PubMed2024

Development of a clinical metagenomics workflow for the diagnosis of wound infections.

BACKGROUND: Wound infections are a common complication of injuries negatively impacting the patient's recovery, causing tissue damage, delaying wound healing, and possibly leading to the spread of the infection beyond the wound site. The current gold-standard diagnostic methods based on microbiological testing are not optimal for use in austere medical treatment facilities due to the need for large equipment and the turnaround time. Clinical metagenomics (CMg) has the potential to provide an alternative to current diagnostic tests enabling rapid, untargeted identification of the causative pathogen and the provision of additional clinically relevant information using equipment with a reduced logistical and operative burden. METHODS: This study presents the development and demonstration of a CMg workflow for wound swab samples. This workflow was applied to samples prospectively collected from patients with a suspected wound infection and the results were compared to routine microbiology and real-time quantitative polymerase chain reaction (qPCR). RESULTS: Wound swab samples were prepared for nanopore-based DNA sequencing in approximately 4 h and achieved sensitivity and specificity values of 83.82% and 66.64% respectively, when compared to routine microbiology testing and species-specific qPCR. CMg also enabled the provision of additional information including the identification of fungal species, anaerobic bacteria, antimicrobial resistance (AMR) genes and microbial species diversity. CONCLUSIONS: This study demonstrates that CMg has the potential to provide an alternative diagnostic method for wound infections suitable for use in austere medical treatment facilities. Future optimisation should focus on increased method automation and an improved understanding of the interpretation of CMg outputs, including robust reporting thresholds to confirm the presence of pathogen species and AMR gene identifications.

Humans↗

PubMed2026

REAPER: a project-centric workflow layer for comparative repeatome analysis.

INTRODUCTION: Repeatome characterization from short-read sequencing data is widely performed using RepeatExplorer2/TAREAN. However, long-lived multisample projects and explicit comparative designs are often executed as ad hoc command sequences that are hard to version, rerun, and monitor on shared compute environments - a gap that motivates a project-centric workflow layer for repeatome analysis. METHODS: We present REAPER (Repeatome Extended Analysis Pipeline-Execution and Reporting), a project-centric workflow layer that couples a modular Snakemake pipeline with a Python project manager to enforce a stable on-disk layout and configuration-driven execution for single-sample and comparative repeatome analyses. REAPER does not implement a new repeat-discovery algorithm; it is an orchestration layer, and biological accuracy for clustering and satellite calling depends on the underlying RepeatExplorer2/TAREAN and satMiner methods it coordinates. REAPER standardizes: Read QC Deterministic subsampling and preparation RepeatExplorer2/TAREAN execution via seqclust, with satMiner-inspired iterative assembly Post-TAREAN BLAST-based annotation against curated repeat collections (optionally including taxon-scoped NCBI-derived resources with freshness checks) Optional graph-based comparative reports The pipeline makes comparative read allocation, prefix policy, and analysis-ready tables explicit; caching supports incremental reruns and structured logs support monitoring. Performance was assessed using a Triticeae short-read dataset (five samples), with rule-level logging of runtime and memory across pipeline stages. RESULTS: Rule-level performance logs show that graph-based clustering dominates runtime and memory, while QC and preparation steps are lightweight by comparison. Graph-report annotations for the Triticeae project additionally link high-ranking clusters to established repeat markers - including pTa794- and pSc119-class entries in curated databases. DISCUSSION: These findings illustrate biologically interpretable outputs (recovery of known Triticeae repeat markers) alongside quantitative performance metrics (identification of graph-based clustering as the dominant computational cost). By making comparative read allocation, prefix policy, and analysis-ready tables explicit - and by supporting caching and structured logging - REAPER supports reproducible comparative repeatome analysis in evolving multisample projects. As an orchestration layer rather than a discovery algorithm, REAPER's contribution lies in reproducibility, monitorability, and comparative-analysis infrastructure, with biological accuracy remaining contingent on the underlying RepeatExplorer2/TAREAN and satMiner methods.

TAREAN↗

PubMed2026

A Practical Workflow for Spatial Transcriptomics Data Analysis: From Data Acquisition to Advanced Analyses.

Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving the two-dimensional spatial context of mRNA molecules within tissue sections, enabling studies of tissue architecture and microenvironment-associated biology. However, ST analysis remains challenging because data import, quality control, integration, deconvolution, spatial statistics, and visualization often require multiple software environments and reproducible parameter choices. This protocol presents a practical computational workflow for public ST datasets in R, beginning with data acquisition and software setup and proceeding through Seurat-based data loading, quality control, normalization, multi-sample integration, clustering, and spatially variable gene analysis. The workflow then applies complementary deconvolution strategies, including reference-guided SPOTlight analysis and unsupervised STdeconvolve topic modeling, followed by Giotto-based spatial cell-cell communication analysis and interactive region-of-interest (ROI) selection using a custom Python Dash application. By emphasizing script-based execution, explicit parameter rationales, expected outputs, and troubleshooting checkpoints, the protocol provides an adaptable framework for standard array-based ST datasets and related platforms after dataset- and platform-specific parameter evaluation.

Spatial Transcriptomics↗

PubMed2026

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome↗