Impact of Follow-Up Imaging Recommendation Specificity on Adherence.

Radiology reports often contain follow-up imaging recommendations, but failure to comply with them in a timely manner can lead to delayed treatment, poor patient outcomes, complications, and legal liability. Using a dataset containing 2,972,164 exams for over 7 years, in this study we explored the association between recommendation specificity on follow-up rates. Our results suggest that explicitly mentioning the follow-up interval as part of a follow-up imaging recommendation has a significant impact on adherence making these recommendations 3 times more likely (95% CI: 2.95 - 3.05) to be followed-up, while explicit mentioning of the follow-up modality did not have a significant impact. Our findings can be incorporated into routine dictation macros so that the follow-up duration is explicitly mentioned whenever clinically applicable, and/or used as the basis for a quality improvement project focussed on improving adherence to follow-up imaging recommendations.

[Development and Validation of Dose Management Software in IVR Utilizing Radiation Information System].

PURPOSE: In each clinical case, the equipment display dose is used for interventional radiology (IVR) dose management and conform to the Japan diagnostic reference levels 2020 (DRLs 2020). However, dose management software corresponding to the DRLs 2020 using radiation dose structured report (RDSR) is not sufficiently widespread. This study aimed to assess the usefulness of in-house developed dose management software in IVR utilizing radiology information system (RIS), which can record both procedures and lesions. METHODS: In this study, IVR from July to September 2020 was analyzed (cardiac regions: 141 cases and other regions: 149 cases). The evaluation items were air kerma-area product, air kerma at the patient entrance reference point, and patient information (height, weight, and BMI). Each subject of DRLs 2020 was analyzed by 12 radiological technologists in charge of IVR. The difference between results of the manual analysis and those of the in-house developed dose management software was calculated using paired t-test in terms of analysis time. RESULTS: The analysis time for the cardiac and other regions was 4180.25±1161.79 s and 4366.92±1393.19 s in the manual analysis, and 36.25±15.32 s and 38.08±17.34 s in the software. The use of software indicated a significant reduction in analysis time (p<0.05). The analysis accuracy of the cardiac and other regions was 96.30% and 98.89% in the software. CONCLUSION: These results show the usefulness of dose management software utilizing RIS.

[Variation of the Implementation of PACS Functions and Image Data Management: Questionnaire Survey in Hokkaido Prefecture].

The image management function of picture archiving and communication system (PACS) plays a very important role while electronically preserving medical records. However, details of these mechanisms vary from manufacturer to manufacturer, which could be a problem if system specifications or image management functions are not confirmed by a user during system installation or operation. The purpose of this research was to record the differences in PACS settings and image data management in hospitals. A questionnaire survey was conducted in 261 hospitals having the PACS system in Hokkaido prefecture, Japan. Questionnaire contents consisted of a face sheet and the following two items: 1) PACS image deletion method, 2) rules regarding the PACS receiving an image of data that was already registered. Results of the questionnaire survey showed that the image deletion method in the PACS server, and the overwriting rule in case of existent images being re-transmitted to the server were different between different hospitals. Furthermore, these variations were not dependent on the vendors or manufacturers, but on the settings of each hospital. Since the image management method of PACS is not standardized, we were considered to be needed more attention and appropriate regulation for safe management of electronic medical records as per the national guideline.

Development and Validation of the Radiology Common Data Model (R-CDM) for the International Standardization of Medical Imaging Data.

PURPOSE: Digital Imaging and Communications in Medicine (DICOM), a standard file format for medical imaging data, contains metadata describing each file. However, metadata are often incomplete, and there is no standardized format for recording metadata, leading to inefficiency during the metadata-based data retrieval process. Here, we propose a novel standardization method for DICOM metadata termed the Radiology Common Data Model (R-CDM). MATERIALS AND METHODS: R-CDM was designed to be compatible with Health Level Seven International (HL7)/Fast Healthcare Interoperability Resources (FHIR) and linked with the Observational Medical Outcomes Partnership (OMOP)-CDM to achieve a seamless link between clinical data and medical imaging data. The terminology system was standardized using the RadLex playbook, a comprehensive lexicon of radiology. As a proof of concept, the R-CDM conversion process was conducted with 41.7 TB of data from the Ajou University Hospital. The R-CDM database visualizer was developed to visualize the main characteristics of the R-CDM database. RESULTS: Information from 2801360 cases and 87203226 DICOM files was organized into two tables constituting the R-CDM. Information on imaging device and image resolution was recorded with more than 99.9% accuracy. Furthermore, OMOP-CDM and R-CDM were linked to efficiently extract specific types of images from specific patient cohorts. CONCLUSION: R-CDM standardizes the structure and terminology for recording medical imaging data to eliminate incomplete and unstandardized information. Successful standardization was achieved by the extract, transform, and load process and image classifier. We hope that the R-CDM will contribute to deep learning research in the medical imaging field by enabling the securement of large-scale medical imaging data from multinational institutions.

A silver bullet? The role of radiology information system data mining in defining gunshot injury trends at a South African tertiary-level hospital.

BACKGROUND: South Africa (SA) has no national injury surveillance system, and hence, non-fatal gunshot injuries are not routinely recorded. Most firearm-related injuries require multi-detector computer tomography (MDCT) assessment at a tertiary-level facility. MDCT scanning for victims with gunshot injuries thus provide an indication of the societal burden of firearm trauma. The potential of the modern radiology information system (RIS) to serve as a robust research tool in such settings is not fully appreciated. OBJECTIVE: The aim of this study was to evaluate the use of institutional RIS data in defining MDCT scanning trends for gunshot victims presenting to a tertiary-level SA hospital. METHOD: A single-institution, retrospective, comparative study was conducted at the Tygerberg Hospital (TBH) Trauma Unit for the years 2013 and 2018. Using data-mining software, customised RIS searches for information on all gunshot-related emergency computed tomography scans in the respective years were performed. Demographic, temporal, anatomical and scan-protocol trends were analysed by cross tabulation, Chi-squared and Fisher's exact tests. RESULTS: Gunshot-related emergency MDCT scans increased by 62% (546 vs. 887) from 2013 to 2018. Lower-limb CT angiography was the commonest investigation in both periods. A higher proportion of victims in 2018 sustained thoracic injuries (12.5% vs. 19.8%; p < 0.01) and required imaging of more than two body parts (13.1% vs. 19.2%; p < 0.01). CONCLUSION: By using RIS data to demonstrate the increasing gunshot-related MDCT workload in the review period, as well as a pattern of more complex and potentially life-threatening injury, this study highlights the burden of firearm trauma in the society and the potential role of the modern RIS as a robust research tool.

Implementing an Integrated Large-Scale Clinical Information System for ISSSTE's Hospital Network in Mexico.

The Institute for Security and Social Services for State Workers (ISSSTE) is a large public provider of health care services that serve around 13.2 million Mexican government workers and their families. To attain process efficiencies, cost reductions, and improvement of the quality of diagnostic and imaging services, ISSSTE was set out in 2019 to create a digital filmless medical image and report management system. A large-scale clinical information system (CIS), including radiology information system (RIS), picture archiving and communication system (PACS), and clinical data warehouse (CDW) components, was implemented at ISSSTE's network of forty secondary- and tertiary-level public hospitals, applying global HL-7 and Digital Imaging and Communications in Medicine (DICOM) standards. In just 5 months, 40 hospitals had their endoscopy, radiology, and pathology services functionally interconnected within a national CIS and RIS/PACS on secure private local area networks (LANs) and a secure national wide area network (WAN). More than 2 million yearly studies and reports are now in digital form in a CDW, securely stored and always available. Benefits include increased productivity, reduced turnaround times, reduced need for duplicate exams, and reduced costs. Functional IT solutions allow ISSSTE hospitals to leave behind the use of radiographic film and printed medical reports with important cost reductions, as well as social and environmental impacts, leading to direct improvement in the quality of health care services rendered. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s42399-020-00713-2) contains supplementary material, which is available to authorized users.

Switching off for future-Cost estimate and a simple approach to improving the ecological footprint of radiological departments.

PURPOSE: Besides diagnostic imaging devices, in particular computed tomography (CT) and magnetic resonance imaging (MRI), numerous reading workstations contribute to the high energy consumption of radiological departments. It was investigated whether switching off workstations after core working hours can relevantly lower energy consumption considering both ecological and economical aspects. METHODS: Besides calculating different theoretical energy consumption scenarios, we measured power consumption of 3 workstations in our department over a 6-month period under routine working conditions and another 6-month period during which users were asked to switch off workstations after work. Staff costs arising from restarting workstations manually were calculated. RESULTS: Our approach to switching off workstations after core working hours reduced energy consumption by about 5.6 %, corresponding to an extrapolated saving of 3.2 tons in carbon dioxide (CO2) emissions and 2100.70 USD/year in electricity costs for 227 workstations. Theoretical calculations indicate that consistent automatic shutdown after core working hours could result in a potential total reduction of energy consumption of 38.6 %, equaling 22.2 tons of CO2 and 14,388.28 USD/year. However, staff costs resulting from waiting times after manually restarting workstations would amount to 36,280.02 USD/year. CONCLUSIONS: Switching off workstations after core working hours can considerably reduce energy consumption and costs, but varies with user adherence. Staff costs caused by waiting time after manually starting up workstations outweigh energy savings by far. Therefore, an energy-saving plan with automated shutdown/restart besides enabling an energy-saving mode would be the most effective way of saving both energy and costs.

Sistema de Información Radiológica XAVIA RIS / Radiology Information System XAVIA RIS

El Sistema para el Almacenamiento, Transmisión y Visualización de Imágenes Médicas XAVIA PACS, desarrollado por la Universidad de las Ciencias Informáticas, se utiliza en múltiples instituciones de salud de Cuba. El propósito de estas herramientas es manejar la imagen médica, por lo que no gestionan la información que se capta en los servicios de diagnóstico por imágenes, entre los que se encuentran los datos del paciente, del estudio imagenológico y el informe diagnóstico. En este trabajo se exponen los resultados del desarrollo de un sistema informático para la gestión de la información imagenológica integrado al sistema XAVIA PACS para garantizar el control automatizado de la información en los servicios de diagnóstico por imágenes. Para el desarrollo previsto fue determinante la necesidad de reutilizar el código fuente ya implementado en el sistema XAVIA PACS; se seleccionó Microsoft.NET Framework, ASP.NET 3.5, C# 3.5 como lenguaje de programación, PostgreSQL como sistema de gestión de Base de Datos. Adicionalmente, fueron tenidos en cuenta la portabilidad, el procesamiento complejo interno, la facilidad de la instalación, y la facilidad del cambio. El sistema desarrollado automatiza la gestión de las listas de trabajo en los servicios de diagnósticos por imágenes, la gestión de la información del paciente, las citaciones, la planificación del trabajo de las modalidades médicas, y especialistas de radiología. La implantación del sistema desarrollado en diferentes instituciones de salud que emplean el sistema XAVIA PACS, validó la pertinencia y aplicabilidad del mismo(AU)

The XAVIA PACS Medical Images Storage, Transmission and Visualization System, developed by the University of Computer Sciences is used in multiple Cuban health institutions. The purpose of these tools is to manage the medical image, so they do not manage the information that is captured in the diagnostic imaging services, among which are the patient's data, the imaging study and the diagnostic report. This article presents a computer system for the management of imaging information integrated into the XAVIA PACS system to ensure automated control of information in diagnostic imaging services. For the planned development, the need to reuse the source code already implemented in the XAVIA PACS system was decisive; Microsoft.NET Framework, ASP.NET 3.5, C # 3.5 were selected as the programming language, PostgreSQL as the Database management system. Additionally, portability, complex internal processing, ease of installation, and ease of change were considered. The developed system automates the management of work lists in diagnostic imaging services, the management of patient information, appointments, work planning of medical modalities, and radiology specialists. The implementation of the system developed in different health institutions that use the XAVIA PACS system, validated its relevance and applicability(AU)

[Usefulness of a Contrast Dose Administration System Using the Radiology Information System].

We report on the construction of a system for managing prior information and injection condition used for contrast enhance CT examination using radiology information system (RIS). Contrast dose administration system using the RIS was possible to retrospectively investigate optimal injection conditions from the database. As the prior information, we designed the patient's profile information of the hospital information system (HIS) to reflect the patient's height, weight, and kidney function (eGFR, Cre), which is necessary information for contrast enhance CT examination, in the RIS. By adding E-Box (DICOM Gateway) to the injector, it became possible to reflect the amount of contrast agent used in patients and injection conditions at contrast enhance CT examination. The contrast agent use information is transmitted to RIS by using modality performed procedure step (MPPS). Database of injection condition at contrast enhance CT examination using the RIS, to determine the optimal injection conditions retrospectively. By utilizing the massive amount of clinical information stored in the RIS, the amount of contrast agent and injection condition at contrast enhance CT examination could be optimized. Reproducibility of the contrast effect can be secured. In the CE, evidence system linked with RIS, when considering the reproducibility at follow-up observation and comparative diagnosis in clinical practice, the contrast effect could be made constant. Contrast dose administration system using the RIS was useful.

"CHOICES": An acronym to aid in delineating potential causes of non-metabolic, non-infectious acute toxic leukoencephalopathy.

PURPOSE: To describe non-metabolic, non-infectious etiologies of acute toxic leukoencephalopathy (ATL) on DWI MRI, and provide a useful acronym to remember them. MATERIAL AND METHODS: Our PACS archive was reviewed, yielding 185 patients with suspected ATL per MRI reports and clinical follow up; infectious or metabolic causes were excluded. RESULT/DISCUSSION: The 87 included non-infectious, non-metabolic ATL patients' etiologies are represented by the acronym 'CHOICES': chemotherapy ('C',n = 34); heroin-induced ('H',n = 6), opioid analogues ('O',n = 14); immunosuppressant ('I',n = 11) or imidazole (n = 2); cocaine ('C',n = 1); environmental or ethanol abuse ('E',n = 5), splenial lesions ('S',n = 9), and 'other' (n = 5). CONCLUSION: The "CHOICES" acronym delineates various toxic etiologies of ATL.

Digital subtract angiography and lipiodol deposits following embolization in cirrhotic nodules of LIRADS category ≥3.

PURPOSE: To assess the correlation between Liver Imaging Reporting and Data System (LIRADS) and digital substract angiography (DSA) and lipiodol deposits in cirrhotic nodules of LIRADS category ≥3 receiving interventional treatment. METHODS: From June 2014 to June 2016, patients with cirrhotic nodules were identified retrospectively and MR images were reviewed by sub-specialty radiologists according to modified LIRADS v2014. Correlation between nodules of LIRADS category ≥3 and DSA findings and lipiodol deposits were analyzed. RESULTS: 71 cirrhotic nodules were evaluated in 33 patients. 39/71 nodules were classified as LR-3, 9/71 nodules were categorized as LR-4, 23/71 nodules were grouped into LR-5. 43 nodules presented positive DSA, 37 nodules showed presence of lipiodol deposits during follow up. With the upgrade of LIRADS category of cirrhotic nodules, DSA and lipiodol deposits became more conspicuous. Spearman analysis demonstrated positive correlations between LIRADS and DSA (r = 0.567, P = 0.000) as well as LIRADS and lipiodol deposits (r = 0.616, P = 0.000). ROC analysis revealed a cut-off value of LR ≥ 4 resulted in a sensitivity of 67.4% and specificity of 89.3% in predicting positive DSA (RUC = 0.799, P ＜ 0.0001), and a sensitivity of 75.7% and specificity of 88.2% in predicting lipiodol deposits (RUC = 0.818, P ＜ 0.0001). Of 39 lesions of LR-3, 64.1% (25/39) showed negative DSA, and 76.9% (30/39) showed absence of lipiodol deposits during follow up. Logistic regression analysis identified arterial enhancement (OR = 26.837, P = 0.002) and lesion size (OR = 1.325, P = 0.022) were independently associated with positive DSA in nodule of LIRADS category ≥3, while no factors were associated with lipiodol deposits. CONCLUSION: The LIRADS can be used to predict DSA findings and lipiodol deposits in nodules with LIRADS score 3 and above. LIRADS 3 nodules tend to be DSA-negative and have less lipiodol deposits. DSA and lipiodol deposits become more conspicuous in nodules from LIRADS 3 to 5.

Structured Reporting versus Free-Text Reporting for Appendiceal Computed Tomography in Adolescents and Young Adults: Preference Survey of 594 Referring Physicians, Surgeons, and Radiologists from 20 Hospitals.

OBJECTIVE: To survey care providers' preference between structured reporting (SR) and free-text reporting (FTR) for appendiceal computed tomography (CT) in adolescents and young adults. MATERIALS AND METHODS: An ethical committee approved this prospective study. The requirement for participant consent was waived. We distributed the Likert scale-based SR form delivering the likelihood of appendicitis across 20 hospitals through a large clinical trial. In the final phase of the trial, we invited 706 potential care providers to participate in an online survey. The survey questions included usefulness in patient management, communicating the likelihood of appendicitis, convenience, style and format, and overall preference. Logistic regression analysis was performed for the overall preference. Three months after the completion of the trial, we checked if the use of the SR was sustained. RESULTS: Responses were analyzed from 594 participants (175 attendings and 419 trainees; 225 radiologists, 207 emergency physicians, and 162 surgeons). For each question, 47.3-64.8% of the participants preferred SR, 13.1-32.7% preferred FTR, and the remaining had no preference. The overall preference varied considerably across the hospitals, but slightly across the departments or job positions. The overall preference for SR over FTR was significantly associated with attendings, SR experience for appendiceal CT, hospitals with small appendectomy volume, and hospitals enrolling more patients in the trial. Five hospitals continued using the SR in usual care after the trial. CONCLUSION: Overall, the care providers preferred SR to FTR. Further investigation into the sustained use of the SR is needed.

The Role of the Integrated Digital Radiology System in Assessing the Impact of Patient Load on Emergency Computed Tomography (CT) Efficiency.

Time-critical management is of particular significance in the trauma and emergency setting, where intervals from patient arrival to diagnostic imaging and from imaging to radiology report are key determinants of outcome. This study, based in the Trauma and Emergency Unit of a large, tertiary-level African hospital with a fully digital radiology department, assessed the impact of increased workload on computerised tomography (CT) efficiency. Sequential, customised searches of the institutional radiology information system (RIS) were conducted to define two weekends in 2016 with the lowest and highest emergency CT workloads, respectively. The electronic RIS timestamps defining the intervals between key steps in the CT workflow were extracted and analysed for each weekend. With the exception of radiologist reporting time, workflow steps were significantly prolonged by increased workload. This study highlights the potential role of the integrated digital radiology system in enabling a detailed analysis of imaging workflow, thereby facilitating the identification and appropriate management of bottlenecks.

¿Cómo y por qué migrar hacia el informe radiológico estructurado contextualizado? / How and Why to Migrate to Radiology Structured and Contextualized Report?

Los informes estructurados contextualizados cumplen tres características fundamentales: tienen una estructura uniforme que responde una pregunta clínica, son el producto de listas de chequeo estandarizadas o de árboles de conocimiento previamente concertados con equipos clínicos multidisciplinarios y se construyen a partir de cuadros de selección de atributos incorporados en los sistemas de informe electrónicos, adicionalmente, el atributo contextualizado hace referencia a la capacidad del informe de responder las preguntas clínicas de la situación actual del paciente, otorgando información relevante de forma concisa y clara a los médicos tratantes. Dentro de las principales ventajas de migrar hacia el informe estructurado se encuentran la uniformidad y la alta calidad del informe, el aumento en la concordancia intra e interobservador, así como la reducción de las tasas de error diagnóstico y una mejora significativa en la comunicación con los médicos tratantes. Se presenta una revisión temática que abarca las características esenciales del informe estructurado contextualizado, los argumentos a favor y en contra de este, los pasos recomendados para su implementación y las oportunidades de mejora hacia el futuro.

Structured reporting in radiology fulfill three fundamental characteristics: they have a uniform structure that answers a clinical question, they are the product of standardized checklists or of knowledge trees previously arranged with multidisciplinary clinical teams, and they are incorporated in option-selection boxes available in electronic reporting systems. Among the main advantages of migrating towards structured reporting are the uniformity and high quality of the report, the increase in intra and interobserver concordance, as well as the reduction of the diagnostic error rates and a significant improvement in communication with the clinical practitioner. This thematic review covers the essential characteristics of the structured report, the arguments for and against it, the recommended steps for its implementation, and the future opportunities for improvement.

Structured Reporting versus Free-Text Reporting for Appendiceal Computed Tomography in Adolescents and Young Adults: Preference Survey of 594 Referring Physicians, Surgeons, and Radiologists from 20 Hospitals

OBJECTIVE: To survey care providers' preference between structured reporting (SR) and free-text reporting (FTR) for appendiceal computed tomography (CT) in adolescents and young adults. MATERIALS AND METHODS: An ethical committee approved this prospective study. The requirement for participant consent was waived. We distributed the Likert scale-based SR form delivering the likelihood of appendicitis across 20 hospitals through a large clinical trial. In the final phase of the trial, we invited 706 potential care providers to participate in an online survey. The survey questions included usefulness in patient management, communicating the likelihood of appendicitis, convenience, style and format, and overall preference. Logistic regression analysis was performed for the overall preference. Three months after the completion of the trial, we checked if the use of the SR was sustained. RESULTS: Responses were analyzed from 594 participants (175 attendings and 419 trainees; 225 radiologists, 207 emergency physicians, and 162 surgeons). For each question, 47.3–64.8% of the participants preferred SR, 13.1–32.7% preferred FTR, and the remaining had no preference. The overall preference varied considerably across the hospitals, but slightly across the departments or job positions. The overall preference for SR over FTR was significantly associated with attendings, SR experience for appendiceal CT, hospitals with small appendectomy volume, and hospitals enrolling more patients in the trial. Five hospitals continued using the SR in usual care after the trial. CONCLUSION: Overall, the care providers preferred SR to FTR. Further investigation into the sustained use of the SR is needed.

A Platform for Innovation and Standards Evaluation: a Case Study from the OpenMRS Open-Source Radiology Information System.

Open-source development can provide a platform for innovation by seeking feedback from community members as well as providing tools and infrastructure to test new standards. Vendors of proprietary systems may delay adoption of new standards until there are sufficient incentives such as legal mandates or financial incentives to encourage/mandate adoption. Moreover, open-source systems in healthcare have been widely adopted in low- and middle-income countries and can be used to bridge gaps that exist in global health radiology. Since 2011, the authors, along with a community of open-source contributors, have worked on developing an open-source radiology information system (RIS) across two communities-OpenMRS and LibreHealth. The main purpose of the RIS is to implement core radiology workflows, on which others can build and test new radiology standards. This work has resulted in three major releases of the system, with current architectural changes driven by changing technology, development of new standards in health and imaging informatics, and changing user needs. At their core, both these communities are focused on building general-purpose EHR systems, but based on user contributions from the fringes, we have been able to create an innovative system that has been used by hospitals and clinics in four different countries. We provide an overview of the history of the LibreHealth RIS, the architecture of the system, overview of standards integration, describe challenges of developing an open-source product, and future directions. Our goal is to attract more participation and involvement to further develop the LibreHealth RIS into an Enterprise Imaging System that can be used in other clinical imaging including pathology and dermatology.

Augmentation of the think aloud method with users' perspectives for the selection of a picture archiving and communication system.

OBJECTIVES: Users attitude toward a picture archiving and communication system (PACS) and their interaction with this system are among the most important factors that influence its acceptance. This study aimed to augment the user's interaction with the user's perspective to select a usable PACS among three systems available on the market. METHODS: We augmented the think aloud (TA) usability evaluation method with the Post-Study System Usability Questionnaire (PSSUQ) to compare user interaction problems of three PACS user interfaces. Four radiologists and four internist physicians participated in this study. Usability characteristics including efficiency, effectiveness, learnability, error, and satisfaction were used to assess the usability of each PACS. RESULTS: There was a significant difference in efficiency (p = 0.01), effectiveness (p = 0.005), learnability (p = 0.001), and satisfaction (p = 0.009). However, no significant difference in the number of errors (p = 0.18), mouse clicks and keystrokes (p = 0.12), and the number of usability problems (p = 0.6) were observed among the three PACS systems studied. CONCLUSIONS: This study showed that applying the proposed approach to augment TA with the user's perspective addresses almost all of the theoretical aspects of usability and can be employed to select the most usable PACS.

Machine Learning for Predicting Patient Wait Times and Appointment Delays.

Being able to accurately predict waiting times and scheduled appointment delays can increase patient satisfaction and enable staff members to more accurately assess and respond to patient flow. In this work, the authors studied the applicability of machine learning models to predict waiting times at a walk-in radiology facility (radiography) and delay times at scheduled radiology facilities (CT, MRI, and ultrasound). In the proposed models, a variety of predictors derived from data available in the radiology information system were used to predict waiting or delay times. Several machine-learning algorithms, such as neural network, random forest, support vector machine, elastic net, multivariate adaptive regression splines, k-th nearest neighbor, gradient boosting machine, bagging, classification and regression tree, and linear regression, were evaluated to find the most accurate method. The elastic net model performed best among the 10 proposed models for predicting waiting times or delay times across all four modalities. The most important predictors were also identified.

Assessing Documentation of Critical Imaging Result Follow-up Recommendations in Emergency Department Discharge Instructions.

To facilitate follow-up of critical test results across transitions in patient care settings, we implemented an electronic discharge module that enabled care providers to include follow-up recommendations in the discharge instructions. We assessed the impact of this module on documentation of follow-up recommendations for critical imaging findings in Emergency Department (ED) discharge instructions. We studied 240 patients with critical imaging findings discharged from the ED before (n = 80) and after (n = 160) implementation of the module. We manually reviewed hand-written forms and electronic discharge instructions to determine if follow-up recommendations were documented. Follow-up recommendations in ED discharge instructions increased from 60.0% (48/80) to 73.8% (118/160) post-module implementation (p = 0.03), a relative increase of 23%. There was no significant change in the rate of documented critical imaging findings in the discharge instructions (77.5% [62/80] before the intervention and 76.9% [123/160] after the intervention; p = 0.91). Implementation of a discharge module was associated with increased documentation of critical imaging finding follow-up recommendations in ED discharge instructions. However, one in four patients still did not receive adequate follow-up recommendations, suggesting further opportunities for performance improvement exist.

Checklist for a Radiology Information System Go-Live.

This article highlights the experience of a single center institution undergoing a change in radiology information system (RIS) software platforms, transitioning to an electronic medical record-RIS driven workflow. Ten planning and execution topics with recommendations are presented in checklist form from the radiology department perspective. The build process of creating a site specific RIS takes many months, beginning with the organization of a steering committee. On Go-Live, several checklist items are offered to help streamline the troubleshooting process and improve communication throughout the radiology department. The groundwork of the group effort in creating the infrastructure of the build process can continue to be useful beyond Go-Live, as RIS features are continually optimized.