Online Error Reporting for Managing Quality Control Within Radiology

Collaborative Development of a PACS-Integrated Quality Control Dashboard: a Single Institutional Experience

Regular communication between technologists and radiologists is necessary for maintaining optimal diagnostic image quality throughout a radiology practice. In a large hospital system with multiple sites, this task becomes increasingly difficult without simultaneously causing significant disruptions in the clinical workflow and decreased throughput. Thus, establishing a system for quality control reporting that enables effective communication in a seamless and convenient manner is imperative. In this report, we describe the development of a new integrated system, in collaboration with our PACS vendor, with tools that allow for instant reporting of quality errors and dashboards providing real-time up-to-date quality data across our hospital system, directly accessible from PACS. To date, 8,167 quality reports have been logged in our new system with roughly 355 submissions per month. Early user engagement and consensus feedback among radiologists and technologists have been positive suggesting an overall improvement from prior systems. We hope this report can help inform other radiology enterprises seeking to improve quality control reporting within their clinical practice.

Quality Assurance of a Cross-Border and Sub-Specialized Teleradiology Service

Background: The current literature discusses aspects of quality assurance (QA) and sub-specialization. However, the challenges of these topics in a teleradiology network have been less explored. In a project report, we aimed to review the development and enforcement of sub-specialized radiology at Telemedicine Clinic (TMC), one of the largest teleradiology providers in Europe, and to describe each step of its QA. Evaluation: The company-specific background was provided by the co-authors—current and former staff members of TMC. Detailed descriptions of the structures of sub-specialization and QA at TMC are provided. Exemplary quantitative evaluation of caseloads and disagreement rates of secondary reviews are illustrated. Description of Sub-specialization and Quality Assurance at TMC: Sub-specialization at TMC is divided into musculoskeletal radiology, neuroradiology, head and neck, a body, and an emergency section operating at local daytime in Europe and Australia. Quality assurance is based on a strict selection process of radiologists, specific reporting guidelines, feedback through the secondary reading of 100% of all radiology reports for new starters, and a minimum of 5% of radiology reports on a continuous basis for all other radiologists, knowledge sharing activities and ongoing training. The level of sub-specialization of each radiologist is monitored continuously on an individual basis in detail. After prospective secondary readings, the mean disagreement rate at TMC indicating at least possibly clinically relevant findings was 4% in 2021. Conclusion: With continuing and current developments in radiology in mind, the essential features of sub-specialization and innovative QA are relevant for further expansion of teleradiology services and for most radiology departments worldwide to respond to the increasing demand for value-based radiology.

Usability evaluation of selected picture archiving and communication systems at the national level: Analysis of users' viewpoints

BACKGROUND AND OBJECTIVES

Picture Archiving and Communication System (PACS) can be considered as one of the most important information systems used in healthcare facilities and its usability problems can lead to delays in the acceptance of information systems, increased medical errors and also user dissatisfaction. The primary purpose of this study was to evaluate the usability of PACS from the perspective of its main users.

METHODS

This study used a combination of qualitative and quantitative methods and was carried out in 2019 where the research community consisted of PACS in five selected companies in Iran. The statistical sample included 200 individuals using the PACS in several hospitals across the country. Moreover, the sample was selected using the multistage random method. The data were then collected using the standard Computer System Usability Questionnaire (CSUQ) consisting of 5 sections and 19 items. Finally, the data were analyzed by SPSS software, version 18 using both descriptive and inferential methods. Content analysis was done for the qualitative data sets.

RESULTS

It was indicated that ease of use, as a category, was not significantly different from the perspective of various PACS users. However, the ANOVA test revealed that there were significant differences in terms of information quality, user interface quality, overall user satisfaction and usability of PACS from the users' perspectives. Furthermore, content analysis of users' comments showed that speeding up the image processing and frequent system failures were amongst the most positive and negative aspects of the PACS, respectively.

CONCLUSIONS

According to the perspective of the users of the investigated PACS in Iran, the usability of these PACS had a favorable status regarding ease of use while provided lower information quality. Generally, based on the users' viewpoints, the PACS from Company B were the most usable while the PACS provided by Company D were the least usable. It is suggested that the information quality and user interface of systems be improved by using appropriate analysis and needs assessment of the end users.

Medical error reporting software program development and its impact on pediatric units' reporting medical errors

Objective:

The purpose of this quasi-experimental study was to developing web-based, anonymous reporting system to increase reporting of medication errors, blood transfusion errors and patient falls in pediatric units and to compare the computerized system with the written system already in use at the institution.

Methods:

This study was conducted in all pediatric units of a research hospital. All physicians and nurses working in these units agreed to participate in the study. All units were visited to introduce the new reporting system. The number and quality of the reports sent on the new system in years 2014 and 2015 were compared to the reports sent the previous year using the written system.

Results:

There was considerable increase in rates of reporting: 234% increase in medication error reporting rate, and 100% increase in the reports of blood transfusion errors. One of the most important results of this study that near-miss errors were not reported at all while the written system of the study institution was being used, whereas it was the most commonly reported type of errors in the electronic error reporting system.

Conclusion:

The web-based reporting system, which makes reporting easy, promoted the development of safety culture among doctors and nurses in common language.

Detecting Technical Image Quality in Radiology Reports

Image interpretation accuracy is critical to ensure optimal care, yet many diagnostic reports contain expressions of uncertainty often due to shortcomings in technical quality among other factors. While radiologists will usually attempt to interpret images and render a diagnosis even if the imaging quality is suboptimal, often the details related to any quality concerns are dictated into the report. Despite imaging exam quality being an import factor for accurate image interpretation, there is a significant knowledge gap in terms of understanding the nature and frequency of technical limitations mentioned in radiology reports. To address some of these limitations, in this research we developed algorithms to automatically detect a broad spectrum of acquisition-related quality concerns using a dataset containing 1,210,858 exams. There was some type of a quality concern mentioned in 2.4% of exams with motion being the most frequent.

Value-Based Assessment of Radiology Reporting Using Radiologist-Referring Physician Two-Way Feedback System-a Design Thinking-Based Approach

In the era of value-based healthcare, many aspects of medical care are being measured and assessed to improve quality and reduce costs. Radiology adds enormously to health care costs and is under pressure to adopt a more efficient system that incorporates essential metrics to assess its value and impact on outcomes. Most current systems tie radiologists' incentives and evaluations to RVU-based productivity metrics and peer-review-based quality metrics. In a new potential model, a radiologist's performance will have to increasingly depend on a number of parameters that define "value," beginning with peer review metrics that include referrer satisfaction and feedback from radiologists to the referring physician that evaluates the potency and validity of clinical information provided for a given study. These new dimensions of value measurement will directly impact the cascade of further medical management. We share our continued experience with this project that had two components: RESP (Referrer Evaluation System Pilot) and FRACI (Feedback from Radiologist Addressing Confounding Issues), which were introduced to the clinical radiology workflow in order to capture referrer-based and radiologist-based feedback on radiology reporting. We also share our insight into the principles of design thinking as applied in its planning and execution.

Implementation of a Point-of-Care Radiologist-Technologist Communication Tool in a Quality Assurance Program

OBJECTIVE

We implemented an Image Quality Reporting and Tracking Solution (IQuaRTS), directly linked from the PACS, to improve communication between radiologists and technologists.

MATERIALS AND METHODS

IQuaRTS launched in May 2015. We compared MRI issues filed in the period before IQuaRTS implementation (May-September 2014) using a manual system with MRI issues filed in the IQuaRTS period (May-September 2015). The unpaired t test was used for analysis. For assessment of overall results in the IQuaRTS period alone, all issues filed across all modalities were included. Summary statistics and charts were generated using Excel and Tableau.

RESULTS

For MRI issues, the number of issues filed during the IQuaRTS period was 498 (2.5% of overall MRI examination volume) compared with 78 issues filed during the period before IQuaRTS implementation (0.4% of total examination volume) (p = 0.0001), representing a 625% relative increase. Tickets that documented excellent work were 8%. Other issues included images not pushed to PACS (20%), film library issues (19%), and documentation or labeling (8%). Of the issues filed, 55% were MRI-related and 25% were CT-related. The issues were stratified across six sites within our institution. Staff requiring additional training could be readily identified, and 80% of the issues were resolved within 72 hours.

CONCLUSION

IQuaRTS is a cost-effective online issue reporting tool that enables robust data collection and analytics to be incorporated into quality improvement programs. One limitation of the system is that it must be implemented in an environment where staff are receptive to quality improvement.