Home-based diagnostic imaging services: Capturing the Stakeholders' Views

Facilitators and barriers to person-centred diagnostic imaging care in low- and middle-income countries: A qualitative study.

What general practitioners require of diagnostic imaging departments: A case study

Disparities over Time in Volume, Day of the Week, and Patient Complexity between Paracentesis and Thoracentesis Procedures Performed by Radiologists versus Those Performed by Nonradiologists

The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. The goal of this ultrasound hands‐on workshop is to demonstrate quality control (QC) testing in diagnostic ultrasound and to provide updates in ACR ultrasound accreditation requirements. The first half of this workshop will include two presentations reviewing diagnostic ultrasound QA/QC and ACR ultrasound accreditation requirements. The second half of the workshop will include live demonstrations of basic QC tests. An array of ultrasound testing phantoms and ultrasound scanners will be available for attendees to learn diagnostic ultrasound QC in a hands‐on environment with live demonstrations and on‐site instructors. The targeted attendees are medical physicists in diagnostic imaging. Learning Objectives: Gain familiarity with common elements of a QA/QC program for diagnostic ultrasound imaging dentify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools Learn ACR ultrasound accreditation requirementsJennifer Walter is an employee of American College of Radiology on Ultrasound Accreditation.

The goal of this ultrasound hands‐on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound.HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well‐defined regions of necrosis. This completely non‐invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands‐on demonstrations with on‐site instructors at separate stations.The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands‐on environment with live demonstrations of the techniques.Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high‐intensity focused ultrasound and in diagnostic ultrasound QC.Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state‐of‐the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands‐on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant 5R25NS080949 and Philips Healthcare research grant C32

Impact of prospective payment systems on diagnostic imaging servicesRH MuilenburgAudio Available | Share

En este artículo se presenta un estudio de caso de una empresa ficticia perteneciente al sector salud. Dicha empresa se especializa en el servicio de diagnóstico por imágenes, la cual permitirá ilustrar la aplicación del sistema ABC a partir del costeo de tres exámenes de alta demanda del servicio. El objetivo planteado es proponer una metodología que explique cómo aplicar el sistema de costos ABC en estas empresas. Asimismo, se pretende aportar en la formación de los profesionales de salud en capacidades gerenciales para analizar la información de costo y elaborar reportes de costos que coadyuven a mejorar la asignación de recursos y la toma de decisiones.

Veterinary RecordVolume 167, Issue 26 p. 991-991 News … Report Diagnostic imaging service First published: 25 December 2010 https://doi.org/10.1136/vr.c7100Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give...

Audit in a diagnostic breast imaging service.

To examine geographic variation in providers' use of diagnostic imaging to identify potential targets for quality improvement initiatives after adjusting for imaging referral across hospital referral regions (HRRs). Using two Centers for Medicare and Medicaid Services datasets, the authors included all claims for beneficiaries enrolled in the Medicare fee-for-service program. Diagnostic imaging procedures were selected on the basis of common procedure coding system codes, excluding interventional procedures. The authors assessed providers' use of imaging for each HRR after creating an imaging referral index (IRI) to adjust for imaging referral rates across HRRs. Relative risk statistics were used to assess geographic variation. The authors calculated two imaging measures for computed tomography (CT) and magnetic resonance (MR) imaging: IRI-adjusted utilization intensity (number of examinations per 1000 beneficiaries) and total payments (in dollars, after deducting deductibles and coinsurances) in each HRR. High-impact regions were defined as those in the highest deciles for both imaging intensity and payment. For 34 million Medicare beneficiaries, 124 million unique diagnostic imaging services (totaling $5.6 billion) were performed in 2012. The average adjusted CT utilization intensity ranged from 330.4 studies per 1000 beneficiaries in the lowest decile to 684.0 in the highest decile (relative risk, 2.1); adjusted MR imaging utilization intensity varied from 105.7 studies per 1000 beneficiaries to 256.3 (relative risk, 2.4). The most common CT and MR imaging procedures were head CT and lumbar spine MR imaging. With use of public data, the authors identified a wide variation in imaging use across the United States. Potential targets for future imaging quality improvement initiatives include head CT and lumbar spine MR imaging.

Introductionthe provision of basic diagnostic imaging services is pivotal to achieving universal health coverage. An estimated two-thirds of the world's population have no access to basic diagnostic imaging. Accurate data on current imaging equipment resources are required to inform health delivery strategy and policy at national level. This is an audit of Zimbabwean public sector diagnostic ultrasound resources and services.Methodsutilising the Ministry of Health and Child Care (MHCC) database, sequential interviews were conducted with provincial health authorities and local facility managers. Ultrasound equipment, personnel and services in all hospitals and clinics, nationally were recorded, collated, and analysed for the whole country, and by province.Resultsof the 1798 Zimbabwean public sector healthcare facilities, sixty-six (n=66, 3.67%) have ultrasound equipment. Ninety-nine (n=99) ultrasound units are distributed across the sonar facilities, representing a national average of 8 units per million people. More than half the equipment units (n=53, 54%) are in secondary-level healthcare facilities (district and mission hospitals), and approximately one-fifth (n=22, 22%) in the central hospitals (quaternary level). The best-resourced province has twice the resources of the least resourced. One-hundred and forty-two (n=142) healthcare workers, from six different professional groups, provide the public sector ultrasound service. Most facilities with sonar equipment (n=64/66, 97%) provide obstetrics and gynaecology services, while general abdominal scanning is available at one third (n=22, 33%). Two facilities with ultrasound equipment have no capacity to offer a sonography service.Conclusionin order to reach the WHO recommendation of 20 sonar units per million people, an estimated 140 additional sonar units are required nationally. The need is greatest in Masvingo, Midlands and Mashonaland East Provinces. Task-shifting plays a key role in the provision of Zimbabwean sonar services. Consideration should be given to formal training and accreditation of all healthcare workers involved in sonar service delivery.

This study is to introduce a cloud-based, AI-driven architecture that can address the above-mentioned challenges properly and demonstrate its feasibility through real-scale implementations and practical testing in a major traditional hospital in Asia that typically operates a variety of diagnostic imaging services. A typical scenario is that vital organ medical images need immediate attention and response from any physician and hospital. CT brain imaging and PET-CT, Gallium imaging of the whole body, glucose, and myocardial ischemia will be implemented and tested in this project. These diagnostic imaging devices usually generate cross-sectional images of patients and typically produce an average of 500 - 600 high-resolution images each. In the local hospital, the human eye ballot reading and deep learning mean image classifications take a considerable amount of time to present the results. This project will take advantage of the cloud, AI, and web-based technology to rapidly assist physicians in providing better medical services. The research objectives of this project are summarized as follows: (1) Gaining experience and lessons by deploying AI technology on a real hospital scale. AI/HA medical imaging services operated in the cloud can be made available for other hospitals to use.

Many countries have already succeeded in improving diagnostic quality and equity in access to radiology services by developing a centralized teleradiological services using cloud technologies that support standardized workflows, intertwined with Artificial Intelligence (AI) algorithms. In those systems, a unified teleradiology system enables faster reporting, higher diagnostic accuracy, and better resource distribution across regions.Kazakhstan faces similar challenges: fragmented radiology infrastructure, uneven distribution of specialists, inconsistent reporting quality, and a lack of unified standards for teleradiology and AIassisted imaging. This policy brief assesses the current challenges in Kazakhstan’s radiology ecosystem, compares national capabilities with international best practices, and proposes three policy options aimed at building a unified, AIenabled teleradiology system, outlines a strategy for building a modern, nationwide imaging ecosystem that includes centralized data storage, unified workflows, and certified AImodules used for triage, detection, and decision support.The envisioned approach integrates regulatory reform, cloud-based imaging architecture, and workforce development to not only enhance diagnosticservices but also deliver a scalable and sustainable high-performing radiology network across the country.What is the problem? Kazakstan's radiology service is structurally, technically, and regulatory challenged to ensure equity in quality diagnostic services throughout the country.1. Fragmented radiology infrastructure with no centralized archiving of images.Regions use heterogeneous Picture Archiving and Communication System/Vendor Neutral Archive /Radiology Information System solutions without centralized storage or unified workflows. Imaging data cannot be shared effectively, and quality control is inconsistent. There is no centralized DICOM archive, and there is no unified monitoring of device loads, and lack of internet connectivity in rural and remote areas. Kazakhstan still stores data locally and inconsistently. . Radiologist shortage and uneven distribution, geographic inequality in access to diagnostics.In rural and remote settings, there is an overall lack of radiologists, particularly subspecialists such as neuroradiology, thoracic radiology, musculoskeletal studies, and pediatrics. These delays commonly result in misdiagnoses and increased referrals.3. There is no national framework of governance for teleradiology and AIThere are no regulations defining the operations of teleradiology, quality standards, turnaround times, AIvalidation pathways, or post-market monitoring of algorithm performance.4. Lack of Interoperability and Standardization of DataIncomplete implementation of Health Level 7 Fast Healthcare Interoperability Resources, Digital Imaging and Communications in Medicine –Web Services, Systematized Nomenclature of Medicine –Clinical Terms, Logical Observation Identifiers Names andCodes, and unified metadata schemas prevent seamless data exchange between regions and systems.5. Lack of Central Quality Assurance MechanismKazakhstan lacks a national “second-opinion” hub or expert review system to ensure consistent and high-quality reporting for computed tomography, magnetic resonance imaging, X-ray across all regions. There is no unified national standardization of descriptions, or audit of radiology services.6. Lack of a unified governmental AIintegration platform.While volumes continue to increase annually, there is a lack of a uniform national platform that allows systematic deployment, monitoring, and integration of AIbased diagnostic tools. Unified "Artificial Intelligence marketplace," enabling safe, controlled rollout of multiple AImodels.Policy options–Creation of a regulatory framework in the field of teleradiology and uniform standards for diagnostic imaging AI solutions;–Creation of an Integrated Teleradiology Platform;–Build Radiology and AIWorkforce Capacity.Vision for implementing policy optionsThe implementation will follow a phased national strategy that begins with establishing regulatory foundations and piloting a centralized imaging platform in selected regions. As the system matures, cloud-based storage, unified workflows, and AIassisted triage will be expanded to all major hospitals, ensuring consistent access to high-quality diagnostics. A central expert hub will be created to support complex case review, monitor reporting quality, and provide continuous professional development for radiologists. Over time, AI modules will be integrated into routine workflows to enhance accuracy, accelerate reporting, and balance workload between regions. By the end of the implementation period, Kazakhstan will have a fully unified, scalable, and data-driven radiology ecosystem that delivers equitable, efficient, and high-quality diagnostic services nationwide.Keywords: medical imaging, teleradiology, centralized radiology systems, structured reporting, radiology workflow optimization, interoperability, digital health transformation, quality assurance, health data governance, clinical decision support, nationwide imaging platform, Kazakhstan.

Socio-economic factors affecting health care can lead to delays in diagnosis of neurological conditions, consequentially affecting treatment and morbidity rates. This inequality in health care can leave patients from lower socio-economic backgrounds more vulnerable to a poorer quality of care from health care providers in the United Kingdom (U.K.). Aims: In this systematic review, we assess the impact of socio-economic status on the use of diagnostic neuroimaging in the U.K., measured by the timeliness, accessibility and appropriate use of computed tomography (CT), magnetic resonance imaging (MRI), ultrasonography, electroencephalography (EEG) and single-photon emission computed tomography (SPECT). We specifically evaluate the non-surgical use of neuroimaging techniques as this relies on the judgment of primary care-givers (e.g., doctors and radiologists), where health disparities are most common. This study includes the analysis of diagnostic imaging used for dementia, minor head injury, stroke, cancer, epilepsy, chronic inflammatory demyelinating polyneuropathy and Parkinson’s disease. With this study, we aim to assess the health inequalities at disease diagnosis. Methods: Using Medline (via Ovid), PubMed and Web of Science databases as sources of information, we critically appraise existing studies on neuroimaging use in the U.K. health care system, published between January 2010 and February 2021. Findings: A total of 18 studies were included in this research, revealing that there was an increase in patients of Black and Asian communities diagnosed with dementia and at an earlier age. There was little evidence to suggest that a lack of access to diagnostic imaging is associated with socio-economic status. However, there are data to suggest that people of a lower socio-economic background require more specialist services with diagnostic neuroimaging tools. In addition, there is evidence to suggest that diagnostic neuroimaging techniques could be utilised more effectively by health care workers to prevent unnecessary delays in diagnosis for patients in lower socio-economic areas.

A roadmap for expanding access to affordable diagnostic imaging services in West and Central Africa: Lessons from Cameroon.