PORTER: a Prototype System for Patient-Oriented Radiology Reporting

Generating colloquial radiology reports with large language models

OBJECTIVES

Patients are increasingly being given direct access to their medical records. However, radiology reports are written for clinicians and typically contain medical jargon, which can be confusing. One solution is for radiologists to provide a "colloquial" version that is accessible to the layperson. Because manually generating these colloquial translations would represent a significant burden for radiologists, a way to automatically produce accurate, accessible patient-facing reports is desired. We propose a novel method to produce colloquial translations of radiology reports by providing specialized prompts to a large language model (LLM).

MATERIALS AND METHODS

Our method automatically extracts and defines medical terms and includes their definitions in the LLM prompt. Using our method and a naive strategy, translations were generated at 4 different reading levels for 100 de-identified neuroradiology reports from an academic medical center. Translations were evaluated by a panel of radiologists for accuracy, likability, harm potential, and readability.

RESULTS

Our approach translated the Findings and Impression sections at the 8th-grade level with accuracies of 88% and 93%, respectively. Across all grade levels, our approach was 20% more accurate than the baseline method. Overall, translations were more readable than the original reports, as evaluated using standard readability indices.

CONCLUSION

We find that our translations at the eighth-grade level strike an optimal balance between accuracy and readability. Notably, this corresponds to nationally recognized recommendations for patient-facing health communication. We believe that using this approach to draft patient-accessible reports will benefit patients without significantly increasing the burden on radiologists.

Transcending Language Barriers: Can ChatGPT Be the Key to Enhancing Multilingual Accessibility in Health Care?

OBJECTIVE

To explore the capabilities of Chat Generative Pre-trained Transformer (ChatGPT) for the purpose of simplifying and translating radiology reports into Spanish, Hindi, and Russian languages, with comparisons to its performance in simplifying to the English language.

METHODS

Fifty deidentified abdomen-pelvis CT reports were fed to ChatGPT (4.0), instructing it to simplify and translate the report. The processed reports were rated on factual correctness (category 1), potential harmful errors (category 2), completeness (category 3), and explanation of medical terms (category 4). The translated versions were also rated on the quality of translation (category 5). The scores in each category were compared between the translated versions and each translated version was compared with the English version in the first four categories. The original reports and the simplified English reports were rated on the Flesch Reading Ease Score and the Flesch Kincaid Grade Level.

RESULTS

The Spanish translation outperformed the Hindi and Russian version significantly in categories 1 and 3 (P < .05). All translated versions performed significantly worse compared with the English version in category 4 (P < .001). Notably, the Hindi translated version performed significantly worse in all four categories (P < .05). The Russian translated version was also significantly worse in category 3 (P < .05). In the first three categories, the Spanish translation, and in the first two categories, the Russian translation demonstrated no statistically significant difference from the English version. No statistically significant difference was observed in the Flesch Reading Ease Score and Flesch Kincaid Grade Level of the simplified English reports. Typographical errors in the original reports negatively affected the translation.

CONCLUSION

ChatGPT demonstrates potential ability in translating reports and communicating pertinent clinical information with limited errors. More training and tailoring are required for languages that are not as commonly used in medical literature. Large language models can be used for translating and simplifying radiology reports, potentially improving access to health care and helping reduce health care costs.

ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports

OBJECTIVES

To assess the quality of simplified radiology reports generated with the large language model (LLM) ChatGPT and to discuss challenges and chances of ChatGPT-like LLMs for medical text simplification.

METHODS

In this exploratory case study, a radiologist created three fictitious radiology reports which we simplified by prompting ChatGPT with "Explain this medical report to a child using simple language." In a questionnaire, we tasked 15 radiologists to rate the quality of the simplified radiology reports with respect to their factual correctness, completeness, and potential harm for patients. We used Likert scale analysis and inductive free-text categorization to assess the quality of the simplified reports.

RESULTS

Most radiologists agreed that the simplified reports were factually correct, complete, and not potentially harmful to the patient. Nevertheless, instances of incorrect statements, missed relevant medical information, and potentially harmful passages were reported.

CONCLUSION

While we see a need for further adaption to the medical field, the initial insights of this study indicate a tremendous potential in using LLMs like ChatGPT to improve patient-centered care in radiology and other medical domains.

CLINICAL RELEVANCE STATEMENT

Patients have started to use ChatGPT to simplify and explain their medical reports, which is expected to affect patient-doctor interaction. This phenomenon raises several opportunities and challenges for clinical routine.

KEY POINTS

• Patients have started to use ChatGPT to simplify their medical reports, but their quality was unknown. • In a questionnaire, most participating radiologists overall asserted good quality to radiology reports simplified with ChatGPT. However, they also highlighted a notable presence of errors, potentially leading patients to draw harmful conclusions. • Large language models such as ChatGPT have vast potential to enhance patient-centered care in radiology and other medical domains. To realize this potential while minimizing harm, they need supervision by medical experts and adaption to the medical field.

Patient-centred pathology reporting improves patient experience and understanding of disease in prostate cancer care

Introduction and Objectives

Patient-centred (PC) and holistic care improves patient satisfaction and health outcomes. We sought to investigate the benefit of utilising a PC pathology report in patients undergoing radical prostatectomy (RP) for prostate cancer (PCa). Our study aimed to evaluate and compare patient understanding of their PCa diagnosis after RP, upon receiving either a standard histopathology report or a personalised and PC report (PCR). Moreover, we evaluated knowledge retention at 4 weeks after the initial consultation.

Methods

We invited patients undergoing RP at three metropolitan Urology clinics to participate in our randomised controlled study. Patients were randomised to receive either a PCR or standard pathology report. Patient satisfaction questionnaires (Perceived Efficacy in Patient-Physician Interactions [PEPPI], Consultation and Relational Empathy [CARE] and Communication Assessment Tool [CAT]) and a knowledge test were conducted within 72 h of the initial appointment and again at 4 weeks. Accurate recollection of Gleason grade group (GGG) and extracapsular extension (ECE) were classified as 'correct'. Baseline demographic data included age, education, marital and employment status, pre-op prostate specific antigen (PSA) and clinical stage. Baseline data were tested for differences between groups using the Student's t test, chi-squared test or Fisher's exact test depending on whether data were continuous, categorical or sparse. Comparison of correctly answered 'knowledge' questions was analysed using chi-squared test. A significance level of p ≤ 0.05 was used.

Results

Data from 62 patients were analysed (30 standard vs. 32 PCR). No significant differences in baseline demographics were found between groups. Both groups reported high levels of satisfaction with their healthcare experiences in all domains of patient-physician rapport, empathy and communication. There were no significant differences between groups in PEPPI (p = 0.68), CAT (p = 0.39) and CARE (p = 0.66) scores, at baseline and 4 weeks. Ninety-three per cent of patients who received the PCR understood the report while 90% felt the report added to their understanding of their PCa. Regarding patient knowledge, the PCR group had significantly more correct answers on GGG and ECE as compared with the standard report group at baseline and 4 weeks (p < 0.001 and 0.001, respectively).

Conclusions

Our findings demonstrate that PC pathology reports improve patient knowledge and understanding of their PCa that is retained for at least 4 weeks after initial receipt of results.

Understanding Health-Related Social Risks

Because of the established contribution of social factors to health outcomes, approaches that address upstream determinants of health have increasingly been recognized as cost-effective means to improve population health. Understanding and usage of precise terminology is important to facilitate collaboration across disciplines. Social determinants of health affect everyone, not just the socially and economically disadvantaged, whereas health-related social risks (HRSR) are specific adverse conditions at the individual or family level that are associated with poor health and related to the immediate challenges individuals face. Health-related social needs account for patient preference in addressing identified social risks. The use of validated screening tools is important to capture risk factors in a standardized fashion to support research and quality improvement. There is a paucity of studies that address HRSR in the context of radiology. This review provides an understanding of HRSR and outlines various ways in which radiologists can work to mitigate them.

Patient-Centered Radiology Communications: Engaging Patients as Partners

Patient-centered care is a model in which, by bringing the patient's perspective to the design and delivery of health care, we can better meet patients' needs, enhancing the quality of care. Patient-centered care requires finding ways to communicate effectively with a diverse patient population that has various levels of health literacy, cultural backgrounds, and unique needs and preferences. Moreover, multimedia resources have the potential to inform and educate patients promoting greater independence. In this review, we discuss the fundamentals of communication with the different modes used in radiology and the key elements of effective communication. Then, we highlight five opportunities along the continuum of care in the radiology practice in which we can improve communications to empower our patients and families and strengthen this partnership. Lastly, we discuss the importance on communication training of the workforce, optimizing and seamlessly integrating technology solutions into our workflows, and the need for patient feedback in the design and delivery of care.

Differences Between Highly Rated vs Poorly Rated Patient Ratings of Radiology Reports

OBJECTIVE

To evaluate differences in quantitative features between poorly versus highly rated patient ratings of radiology reports.

METHODS

A HIPAA-compliant, IRB-waived study was performed from October 2019 to June 2021. Patients completed an optional 2-question survey ("How helpful was the report?" with a 5-star scale and an open text box) embedded into the patient portal, and reports were assessed for readability and brevity. Quantitative analyses were performed between poorly (≤3 stars) and highly rated (>3 stars) CT and MRI reports, including the use of structured reporting, number of words, words per sentence, Flesch Reading Ease, and Flesh-Kincaid Grade level within the findings and impression sections of the radiology reports. A two-tailed nonparametric Mann U Whitney test was performed for continuous variables and Chi2 for categorical variables.

RESULTS

Of the 490 responses, all 135 evaluating CT or MR were included (27%). 106/135 (78%) of the patients gave high ratings (score of 4 or 5). 46/135 (34%), the radiology reports were in a structured format. The proportion of highly rated reports were significantly higher for structured than freeform reports (93.5 vs. 70.8%, p = 0.002). In the findings section, highly rated reports had a lower Flesch Reading Ease score than poorly rated reports (19.6 vs. 28.9, p <0.01). No significant differences were observed between number of words (p=0.27), words per sentence (p=0.94), and Flesh-Kincaid Grade level (p=0.09) in the findings section. In the impression section, no differences were observed between highly vs. poorly rated reports among the measured parameters.

CONCLUSION

Patients preferred highly rated reports that were structured and had lower Flesch Reading Ease scores in the findings section.

ESR paper on structured reporting in radiology-update 2023

Structured reporting in radiology continues to hold substantial potential to improve the quality of service provided to patients and referring physicians. Despite many physicians' preference for structured reports and various efforts by radiological societies and some vendors, structured reporting has still not been widely adopted in clinical routine.While in many countries national radiological societies have launched initiatives to further promote structured reporting, cross-institutional applications of report templates and incentives for usage of structured reporting are lacking. Various legislative measures have been taken in the USA and the European Union to promote interoperable data formats such as Fast Healthcare Interoperability Resources (FHIR) in the context of the EU Health Data Space (EHDS) which will certainly be relevant for the future of structured reporting. Lastly, recent advances in artificial intelligence and large language models may provide innovative and efficient approaches to integrate structured reporting more seamlessly into the radiologists' workflow.The ESR will remain committed to advancing structured reporting as a key component towards more value-based radiology. Practical solutions for structured reporting need to be provided by vendors. Policy makers should incentivize the usage of structured radiological reporting, especially in cross-institutional setting.Critical relevance statement Over the past years, the benefits of structured reporting in radiology have been widely discussed and agreed upon; however, implementation in clinical routine is lacking due-policy makers should incentivize the usage of structured radiological reporting, especially in cross-institutional setting.Key points1. Various national societies have established initiatives for structured reporting in radiology.2. Almost no monetary or structural incentives exist that favor structured reporting.3. A consensus on technical standards for structured reporting is still missing.4. The application of large language models may help structuring radiological reports.5. Policy makers should incentivize the usage of structured radiological reporting.

Striving to be of Value: Building a Virtual Radiology Consult Service for Patients

PURPOSE

Direct interactions between patients and diagnostic radiologists are uncommon, but recent medicolegal developments in the United States may increase patient interest in communicating directly with radiologists. Patient participation rates in prior attempts at direct radiology consultation vary widely in the literature. Our objective was to design and build a virtual radiology consult service for a subset of patients undergoing lung cancer screening CTs to enable communication between patients and radiologists regarding imaging results and radiology recommendations.

METHODS

Patients scheduled for lung cancer screening CTs were identified using a custom scheduling system and offered via text message a free 15-minute consultation with a radiologist to discuss the results.

RESULTS

Of 38 patients texted, 10 (26.3%) responded. Nine (90%) scheduled a consultation, but 5 (55.5%) subsequently cancelled. Of the remaining four, 3 (75%) attended their appointments, with an overall 3/38 (7.9%) text-to-consult conversation rate. The 3 consults averaged 18 (±8.2) minutes.

CONCLUSION

The recruitment rate for our virtual service was between the low rate of a prior phone consult line study and the high rate in consults integrated into another physician visit. Further research is needed to identify patients most interested in a radiology consultation and optimize consultation modality by patient population.

Patient Understanding of Oncologic Radiology Reports: Is Access to Electronic Medical Records Helpful?

Access to electronic medical record (EMR) patient portals made it easier for patients to quickly acquire the results of their radiology studies. However, there is little research on how well oncology patients understand the findings of radiology reports presented in the online portal without patient-physician discussion. This study assessed oncology patients' confidence and accuracy in interpreting radiology reports either with or without layman translations. A survey based on a radiology report was administered to oncology patients and caregivers. Two versions of the radiological report were randomly distributed, either a standard report or one with layman translations to evaluate participant understanding and accuracy of interpreting radiological results. Among 85 participants, a majority (67.8%) reported wanting patient portal access to radiological reports, yet less than a quarter (21.2%) felt confident in reading and interpreting radiological reports. Univariate binary logistic regression models showed that participants who read the lay report were 8 times more likely to find the radiology report easy to read. This research demonstrated that the inclusion of layman translation of standard radiology reports improves oncology patients' and caregivers' understanding of such reports with statistically significant and clinically meaningful increases in readability.

Patient communication in radiology: Moving up the agenda

Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients can be challenging in the setting of busy radiology departments where there is a focus on efficient and accurate diagnosis. Traditionally, most results are provided directly to the referring clinician. However, the importance of direct communication between the radiologist and patient is increasingly relevant, particularly in the context of face-to-face settings such as rapid assessment and ultrasound clinics, and interventional radiology, as well as in written form through electronic patient portals. Artificial intelligence tools may improve efficiency, allowing more time for radiologists to communicate directly with patients. There is a need for dedicated training in communication skills for imaging professionals. This review considers the topic of patient communication in the setting of imaging departments and discusses the ways that communication skills may be improved through training and through harnessing emerging digital technologies that may enhance the quality of communication.

Talking Points: Enhancing Communication Between Radiologists and Patients

Radiologists communicate along multiple pathways, using written, verbal, and non-verbal means. Radiology trainees must gain skills in all forms of communication, with attention to developing effective professional communication in all forms. This manuscript reviews evidence-based strategies for enhancing effective communication between radiologists and patients through direct communication, written means and enhanced reporting. We highlight patient-centered communication efforts, available evidence, and opportunities to engage learners and enhance training and simulation efforts that improve communication with patients at all levels of clinical care.

What radiologists need to know about patients' expectations: P.A.T.I.E.N.T.S C.A.R.E.R.S A.I.M.S

The Patient Advisory Group (PAG) of the European Society of Radiology aims to highlight, in this short paper, patients’ expectations from the radiological community and support workers, throughout the patient’s medical imaging journey for completion of diagnostic or interventional examinations. In order to maintain constant awareness of patients’ expectations, key expectations have been summarised in an easy-to-remember mnemonic: PATIENTS CARERS AIMS.

Due to disparate healthcare systems and medical imaging services in Europe, not all patient expectations can be systematically met, but healthcare providers should be mindful, when setting up new operational procedures, of the need to focus on patient-centred needs and care. At times when new or improved technology is being introduced, such as artificial intelligence applications, telemedicine, robotisation of interventional procedures and digitised records, the impact on radiologist–patient communication and interactions should be considered.

Artificial Intelligence Enabling Radiology Reporting

The radiology reporting process is beginning to incorporate structured, semantically labeled data. Tools based on artificial intelligence technologies using a structured reporting context can assist with internal report consistency and longitudinal tracking. To-do lists of relevant issues could be assembled by artificial intelligence tools, incorporating components of the patient's history. Radiologists will review and select artificial intelligence-generated and other data to be transmitted to the electronic health record and generate feedback for ongoing improvement of artificial intelligence tools. These technologies should make reports more valuable by making reports more accessible and better able to integrate into care pathways.

Consumer understanding of terms used in imaging reports requested for low back pain: a cross-sectional survey

OBJECTIVES

To investigate (1) self-reported societal comprehension of common and usually non-serious terms found in lumbar spine imaging reports and (2) its relationship to perceived seriousness, likely persistence of low back pain (LBP), fear of movement, back beliefs and history and intensity of LBP.

DESIGN

Cross-sectional online survey of the general public.

SETTING

Five English-speaking countries: UK, USA, Canada, New Zealand and Australia.

PARTICIPANTS

Adults (age >18 years) with or without a history of LBP recruited in April 2019 with quotas for country, age and gender.

PRIMARY AND SECONDARY OUTCOME MEASURES

Self-reported understanding of 14 terms (annular fissure, disc bulge, disc degeneration, disc extrusion, disc height loss, disc protrusion, disc signal loss, facet joint degeneration, high intensity zone, mild canal stenosis, Modic changes, nerve root contact, spondylolisthesis and spondylosis) commonly found in lumbar spine imaging reports. For each term, we also elicited worry about its seriousness, and whether its presence would indicate pain persistence and prompt fear of movement.

RESULTS

From 774 responses, we included 677 (87.5%) with complete and valid responses. 577 (85%) participants had a current or past history of LBP of whom 251 (44%) had received lumbar spine imaging. Self-reported understanding of all terms was poor. At best, 235 (35%) reported understanding the term 'disc degeneration', while only 71 (10.5%) reported understanding the term 'Modic changes'. For all terms, a moderate to large proportion of participants (range 59%-71%), considered they indicated a serious back problem, that pain might persist (range 52%-71%) and they would be fearful of movement (range 42%-57%).

CONCLUSION

Common and usually non-serious terms in lumbar spine imaging reports are poorly understood by the general population and may contribute to the burden of LBP.

TRIAL REGISTRATION NUMBER

ACTRN12619000545167.

Patients' perceptions of using artificial intelligence (AI)-based technology to comprehend radiology imaging data

Results of radiology imaging studies are not typically comprehensible to patients. With the advances in artificial intelligence (AI) technology in recent years, it is expected that AI technology can aid patients' understanding of radiology imaging data. The aim of this study is to understand patients' perceptions and acceptance of using AI technology to interpret their radiology reports. We conducted semi-structured interviews with 13 participants to elicit reflections pertaining to the use of AI technology in radiology report interpretation. A thematic analysis approach was employed to analyze the interview data. Participants have a generally positive attitude toward using AI-based systems to comprehend their radiology reports. AI is perceived to be particularly useful in seeking actionable information, confirming the doctor's opinions, and preparing for the consultation. However, we also found various concerns related to the use of AI in this context, such as cyber-security, accuracy, and lack of empathy. Our results highlight the necessity of providing AI explanations to promote people's trust and acceptance of AI. Designers of patient-centered AI systems should employ user-centered design approaches to address patients' concerns. Such systems should also be designed to promote trust and deliver concerning health results in an empathetic manner to optimize the user experience.

Effect of AI Explanations on Human Perceptions of Patient-Facing AI-Powered Healthcare Systems

Ongoing research efforts have been examining how to utilize artificial intelligence technology to help healthcare consumers make sense of their clinical data, such as diagnostic radiology reports. How to promote the acceptance of such novel technology is a heated research topic. Recent studies highlight the importance of providing local explanations about AI prediction and model performance to help users determine whether to trust AI's predictions. Despite some efforts, limited empirical research has been conducted to quantitatively measure how AI explanations impact healthcare consumers' perceptions of using patient-facing, AI-powered healthcare systems. The aim of this study is to evaluate the effects of different AI explanations on people's perceptions of AI-powered healthcare system. In this work, we designed and deployed a large-scale experiment (N = 3,423) on Amazon Mechanical Turk (MTurk) to evaluate the effects of AI explanations on people's perceptions in the context of comprehending radiology reports. We created four groups based on two factors-the extent of explanations for the prediction (High vs. Low Transparency) and the model performance (Good vs. Weak AI Model)-and randomly assigned participants to one of the four conditions. Participants were instructed to classify a radiology report as describing a normal or abnormal finding, followed by completing a post-study survey to indicate their perceptions of the AI tool. We found that revealing model performance information can promote people's trust and perceived usefulness of system outputs, while providing local explanations for the rationale of a prediction can promote understandability but not necessarily trust. We also found that when model performance is low, the more information the AI system discloses, the less people would trust the system. Lastly, whether human agrees with AI predictions or not and whether the AI prediction is correct or not could also influence the effect of AI explanations. We conclude this paper by discussing implications for designing AI systems for healthcare consumers to interpret diagnostic report.

The 21st Century CURES Act in Pediatric Gastroenterology: Problems, Solutions, and Preliminary Guidance

The information blocking (IB) prohibition component of the 21st Century CURES Act (21CCA) comes into effect April 5, 2021, which gives patients and their families near-instant access to almost all clinical notes, lab results, and health data. Exceptions to IB prohibition include risk of harm and patient privacy, but violations can be punished by a fine of up to $1,000,000.00. A committee of pediatric gastroenterologists reviewed the 21CCA regulation and compared local practice policies. Pediatric practitioners need to understand how age will affect local information release policies and to know which note types are released, paying special consideration to trainee notes and confidential information. Extraneous detail should be removed from notes, emotional labeling be avoided, and objective statements be made when referring to the care of other providers. Awareness of the 21CCA provides pediatric gastroenterologists with the opportunity to adapt their medical documentation practices to accommodate the new law.

Computed Tomography for Abdominal Pain: Do Radiology Reports Answer the Clinical Question?

RATIONALE AND OBJECTIVES

To assess whether abdominopelvic computed tomography (CT) radiology reports directly address a cause for pain when pain is included in the scan indication.

MATERIALS AND METHODS

Four hundred and ninety-five random abdominopelvic CT reports containing "pain" in the indication were retrospectively reviewed. The position of pain descriptors within the indication, the presence of an oncology-related indication in addition to pain and whether a cause for pain was addressed in the impression were recorded. Linguistic analysis of indication and impression sections was performed. Comparisons between reports that addressed pain and those that did not were conducted using Chi-square, Fisher exact, and two-tailed t-tests.

RESULTS

A cause for pain was addressed in 454 of 495 (91.7%) report impressions. Indications with both oncology-related and pain-related descriptors were less likely to have pain directly addressed (χ² (1, N = 495) = 16.4, p < .001). There was no significant association between where pain appeared within the indication and whether pain was addressed (χ² (1, N = 495) = 3.2, p = .07). Whether an impression conveyed a normal result did not influence if pain was addressed (p = .49). Impression word count and complexity were higher in the addressed group compared to the not addressed group (word count 66.6 vs. 51.9, p= .02, Composite grade level 30.1 vs. 25.3, p= .02).

CONCLUSION

Radiologists at our institution consistently addressed a cause for pain on abdominopelvic CTs when pain was in the indication. However, oncology patients who also had an indication of pain were less likely to have a cause for pain addressed. Impression complexity was high for all reports, though higher in those where pain was addressed.

Radiology Reporting in the Era of Patient-Centered Care: How Can We Improve Readability?

Radiology reports are consumed not only by referring physicians and healthcare providers, but also by patients. We assessed report readability in our enterprise and implemented a two-part quality improvement intervention with the goal of improving report accessibility. A total of 491,813 radiology reports from ten hospitals within the enterprise from May to October, 2018 were collected. We excluded echocardiograms, rehabilitation reports, administrator reports, and reports with negative scores leaving 461,219 reports and report impressions for analysis. A grade level (GL) was calculated for each report and impression by averaging four readability metrics. Next, we conducted a readability workshop and distributed weekly emails with readability GLs over a period of 6 months to each attending radiologist at our primary institution. Following this intervention, we utilized the same exclusion criteria and analyzed 473,612 reports from May to October, 2019. The mean GL for all reports and report impressions was above 13 at every hospital in the enterprise. Following our intervention, a statistically significant drop in GL for reports and impressions was demonstrated at all locations, but a larger and significant improvement was observed in impressions at our primary site. Radiology reports across the enterprise are written at an advanced reading level making them difficult for patients and their families to understand. We observed a significantly larger drop in GL for impressions at our primary site than at all other sites following our intervention. Radiologists at our home institution improved their report readability after becoming more aware of their writing practices.

Patient Understanding of Abnormal Imaging Findings Under Pennsylvania Act 112: A Call to Revise Mandated Notification Message Language

PURPOSE

The aim of this study was to evaluate the effect of Pennsylvania Act 112 notification reading level and presentation on patient understanding and anxiety.

METHODS

Four notifications were developed by alternating 12th grade and 6th grade reading level Act 112 language with letters or infographics. Using Amazon Mechanical Turk, 909 US adult volunteers were randomly assigned to one notification followed by a survey. Participants who answered all 12 survey questions on understanding, anxiety, and sociodemographics were paid $0.10. Chi-square analysis and multivariate regression were used to determine the impact of notification type and sociodemographic data on understanding of communicated information and anxiety.

RESULTS

Sixty percent of participants (489 of 821) correctly understood all three questions directly answered within notifications regarding Act 112 subject, next steps, and process for obtaining reports. Approximately half of respondents understood that notifications indirectly conveyed "definitely" or "possibly" abnormal test results (344 of 821 [42%] and 99 of 821 [12%], respectively). Compared with the 12th grade letter, correct understanding of all directly communicated information was lower with the 12th grade infographic after adjustment (odds ratio, 0.61; 95% confidence interval, 0.39-0.95; P = .028) and equivalent with the 6th grade infographic and letter (P = .744 and P = .316). Correct indirect understanding of abnormal test results was not associated with notification type after adjustment but was associated with higher anxiety (odds ratio, 2.86; 95% confidence interval, 0.57-1.35; P < .001).

CONCLUSIONS

Layperson understanding of information directly and indirectly communicated in Pennsylvania Act 112 is suboptimal, regardless of reading level or presentation. New Act 112 language is needed to improve patient understanding, which would ideally be coproduced with Pennsylvania patients, policymakers, and other relevant stakeholders.

Engaging patients and families in pediatric radiology

While patient and family-centered care (PFCC) is currently a hot topic in medicine, it has long been a specific focus of pediatrics. The concept of PFCC includes a change in culture where physicians and patients move away from paternalism and instead view patients and families as partners in care. Although there are many ways in which adult-focused radiologists can learn from pediatric radiologists as leaders in PFCC, there remain many opportunities for improvement for all radiologists.

Using informatics to engage patients

As a specialty, radiology has spent much of the last two decades implementing information systems that improve departmental efficiency and the ordering provider's access to information. While our patients have realized benefits such as improved access to care and reduced turnaround times, there has been little focus on using these information systems to improve patient engagement. In the last decade, society has shifted. Now, consumers in every industry expect to be able to use technology to help them accomplish different tasks from scheduling to communicating. Medicine, in general, has been slow to respond to the concept of the patient as a consumer. In this manuscript we describe some of the informatics efforts we have employed in our department to improve patient engagement. We present these initiatives, corresponding to each aspect of the radiology value stream, from the patient's point of view.

Adding Value in Radiology Reporting

The major goal of the radiology report is to deliver timely, accurate, and actionable information to the patient care team and the patient. Structured reporting offers multiple advantages over traditional free-text reporting, including reduction in diagnostic error, comprehensiveness, adherence to national consensus guidelines, revenue capture, data collection, and research. Various technological innovations enhance integration of structured reporting into everyday clinical practice. This review discusses the benefits of innovations in radiology reporting to the clinical decision process, the patient experience, the cost of imaging, and the overall contributions to the health of the population. Future directions, including the use of artificial intelligence, are reviewed.

Creating patient-centered radiology reports to empower patients undergoing prostate magnetic resonance imaging

INTRODUCTION

As we progress to an era when patient autonomy and shared decision-making are highly valued, there is a need to also have effective patient-centered communication tools. Radiology reports are designed for clinicians and can be very technical and difficult for patients to understand. It is important for patients to understand their magnetic resonance imaging (MRI) report in order to make an informed treatment decision with their physician. Therefore, we aimed to create a patient-centered prostate MRI report to give our patients a better understanding of their clinical condition.

METHODS

A prototype patient-centered radiology report (PACERR) was created by identifying items to include based on opinions sought from a group of patients undergoing prostate MRI and medical experts. Data was collected in semi-structured interviews using a salient belief question. A prototype PACERR was created in collaboration with human factors engineering and design, medical imaging, biomedical informatics, and cancer patient education groups.

RESULTS

Fifteen patients and eight experts from urology, radiation oncology, radiology, and nursing participated in this study. Patients were particularly interested to have a report with laymen terms, concise language, contextualization of values, definitions of medical terms, and next course of action. Everyone believed the report should include the risk of MRI findings actually being cancer in the subsequent biopsy.

CONCLUSIONS

A prostate MRI PACERR has been developed to communicate the most important findings relevant to decision-making in prostate cancer using patient-oriented design principles. The ability of this tool to improve patient knowledge and communication will be explored.

Full Radiology Report through Patient Web Portal: A Literature Review

The aim of this study discusses the gap between the patient web portal and providing a full radiology report. A literature review was conducted to examine radiologists, physicians, and patients’ opinions and preferences of providing patients with online access radiology reports. The databases searched were Pubmed and Google Scholar and the initial search included 927 studies. After review, 47 studies were included in the study. We identified several themes, including patients’ understanding of radiology reports and radiological images, as well as the need for decreasing the turnaround time for reports availability. The existing radiology reports written for physicians are not suited for patients. Further studies are needed to guide and inform the design of patient friendly radiology reports. One of the ways that can be used to fill the gap between patients and radiology reports is using social media sites.

Essential Elements of Natural Language Processing: What the Radiologist Should Know

Natural language is ubiquitous in the workflow of medical imaging. Radiologists create and consume free text in their daily work, some of which can be amenable to enhancements through automatic processing. Recent advancements in deep learning and "artificial intelligence" have had a significant positive impact on natural language processing (NLP). This article discusses the history of how researchers have extracted data and encoded natural language information for analytical processing, starting from NLP's humble origins in hand-curated, linguistic rules. The evolution of medical NLP including vectorization, word embedding, classification, as well as its use in automated speech recognition, are also explored. Finally, the article will discuss the role of machine learning and neural networks in the context of significant, if incremental, improvements in NLP.

Patient-centered Radiology: Overview and Opportunities in Cardiothoracic Imaging

Radiology is unique compared with most other medical specialties in that care can sometimes be delivered without speaking to or touching the patient. Although radiologists have increasingly become involved in patient safety, quality improvement, informatics, and advocacy, they must still work harder than other medical specialties to be considered "patient-facing." While cardiothoracic radiologists have likely experienced fewer opportunities to directly interface with patients, shared decision-making with patients around lung cancer screening and radiation dose optimization are both excellent examples of patient-centered and family-centered care in cardiothoracic imaging. Many cardiothoracic examinations necessitate medication administration or customized breath-holds not required of other examinations and create an opportunity for discussion between cardiothoracic radiologists and patients. Opportunities to increase the patient-centered focus in radiology exist at every interface between the radiology practice and the patient. Implementing the principles of patient-centered and family-centered care in a radiology department or practice requires the participation and engagement of all stakeholders, including patients.

Customer Service in Radiology: Satisfying Your Patients and Referrers

Radiology has long been a service-oriented specialty. Although physicians in other specialties have direct interactions with patients, radiologists' interactions with patients are often indirect, most often occurring as a direct result of another provider's order. As such, radiology practices have had to focus on two distinct groups, patients and ordering providers, to grow their businesses and retain their patients. One could argue that during the past 2 decades, many of the most visible customer service initiatives in radiology practices have been directed toward the ordering provider. These initiatives have included implementing picture archiving and communication systems to improve image distribution and availability, voice dictation systems to decrease report turnaround time, computerized order entry to ease the ordering process, and structured reporting to improve the readability of the radiology report. As the practice of radiology is evolving to become more patient oriented, it is clear that the specialty needs to pivot and implement more initiatives that directly benefit patients. In this article, the concepts of customer service and a radiology department's primary customer are defined and discussed, and the concept of service quality is introduced. In addition, the author highlights the five dimensions of service quality: reliability, assurance, tangibles, empathy, and responsiveness. Each dimension is described in detail, first by using an archetypal business example and then by using an example of a project that has been successfully implemented in the author's radiology department. ^©RSNA, 2018.

Integrating Wikipedia Articles and Images into an Information Resource for Radiology Patients

Wikipedia-an open-access online encyclopedia-contains a large number of medically relevant articles and images that may help supplement glossaries of radiology terms. We sought to determine the extent to which concepts from a large online radiology glossary developed as part of the Patient-Oriented Radiology Reporter (PORTER) initiative could be mapped to relevant Wikipedia web pages and images using automated or semi-automated approaches. The glossary included 4090 concepts with their definitions; the concept's preferred name and lexical variants, such as plurals, adjectival forms, synonyms, and abbreviations, yielded a total of 13,030 terms. Of the 4090 concepts, 3063 (74.9%) had a corresponding English-language Wikipedia page identified by automated search with subsequent manual review. We applied the MediaWiki application programming interface (API) to generate web-service calls to identify the images from each concept's corresponding Wikipedia page; three reviewers selected relevant images to associate with the glossary's concepts. Licensing terms for the images were reviewed. For 800 randomly sampled concepts that had associated Wikipedia pages, 362 distinct images were identified from the MediaWiki library and matched to 404 concepts (51%). Three images (1%) had unspecified licensing terms; the rest were in the public domain or available via a Creative Commons license. Wikipedia and the MediaWiki library offer a large collection of medical articles and images that can be incorporated into an online lay-language glossary of radiology terms though a semi-automated approach.

Evaluating Completeness of a Radiology Glossary Using Iterative Refinement

A lay-language glossary of radiology, built to help patients better understand the content of their radiology reports, has been analyzed for its coverage and readability, but not for its completeness. We present an iterative method to sample radiology reports, identify "missing" terms, and measure the glossary's completeness. We hypothesized that the refinement process would reduce the number of missing terms to fewer than 1 per report. A random sample of 1000 radiology reports from a large US academic health system was divided into 10 cohorts of 100 reports each. Each cohort was reviewed in sequence by two investigators to identify terms (single words and multi-word phrases) absent from the glossary. Terms marked as new were added to the glossary and hence was shown as matched in subsequent cohorts. This HIPAA-compliant study was IRB-approved; informed consent was waived. The refinement process added a mean of 288.0 new terms per 100 reports in the first 5 cohorts vs. a mean of 66.0 new terms per 100 reports in the last 5 cohorts; the difference was statistically significant (p < .01). After reviewing 500 reports, the review process found fewer than 1 new term per report in each of 500 subsequent reports. The findings suggest that 500 to 1000 reports is adequate to test the completeness of a glossary, and that the glossary after iterative refinement achieved a high level of completeness to cover the vocabulary of radiology reports.

Structured radiology reporting on an institutional level-benefit or new administrative burden?

Significant technical advances have been made in radiology since the first discovery of X-rays. Diagnostic techniques have become more and more complex, workflows have been digitized, and data production has increased exponentially. However, the radiology report as the main method for communicating examination results has largely remained unchanged. Growing evidence supports that more structured radiology reports offer various benefits over conventional narrative reports. Various efforts have been made to further develop and promote structured reporting. However, regardless of the potential benefits, structured reporting has still not seen widespread implementation into the clinical routine. With recent technical advances, especially new research topics such as big data and machine learning, structured reporting could prove essential for the future of radiology. New interoperable solutions are needed to facilitate the implementation of template-based structured reporting into the clinical routine.

Patient-Centered Radiology Reporting: Using Online Crowdsourcing to Assess the Effectiveness of a Web-Based Interactive Radiology Report

PURPOSE

The aim of this study was to evaluate the effectiveness of a patient-centered web-based interactive mammography report.

METHODS

A survey was distributed on Amazon Mechanical Turk, an online crowdsourcing platform. One hundred ninety-three US women ≥18 years of age were surveyed and then randomized to one of three simulated BI-RADS^® 0 report formats: standard report, Mammography Quality Standards Act-modeled patient letter, or web-based interactive report. Survey questions assessed participants' report comprehension, satisfaction with and perception of the interpreting radiologist, and experience with the presented report. Two-tailed t tests and χ² tests were used to evaluate differences among groups.

RESULTS

Participants in the interactive web-based group spent more than double the time viewing the report than the standard report group (160.0 versus 64.2 seconds, P < .001). Report comprehension scores were significantly higher for the interactive web-based and patient letter groups than the standard report group (P < .05). Scores of satisfaction with the interpreting radiologist were significantly higher for the web-based interactive report and patient letter groups than the standard report group (P < .01). There were no significant differences between the patient letter and web-based interactive report groups.

CONCLUSIONS

Radiology report format likely influences communication effectiveness. For result communication to a non-medical patient audience, patient-centric report formats, such as a Mammography Quality Standards Act-modeled patient letter or web-based interactive report, may offer advantages over the standard radiology report. Future work is needed to determine if these findings are reproducible in patient care settings and to determine how best to optimize radiology result communication to patients.

Structured Reporting in Radiology

Radiology reports are vital for patient care as referring physicians depend upon them for deciding appropriate patient management. Traditional narrative reports are associated with excessive variability in the language, length, and style, which can minimize report clarity and make it difficult for referring clinicians to identify key information needed for patient care. Structured reporting has been advocated as a potential solution for improving the quality of radiology reports. The Association of University Radiologists-Radiology Research Alliance Structured Reporting Task Force convened to explore the current and future role of structured reporting in radiology and summarized its finding in this article. We review the advantages and disadvantages of structured radiology reports and discuss the current prevailing sentiments among radiologists regarding structured reports. We also discuss the obstacles to the use of structured reports and highlight ways to overcome some of those challenges. We also discuss the future directions in radiology reporting in the era of personalized medicine.

Text Simplification Using Consumer Health Vocabulary to Generate Patient-Centered Radiology Reporting: Translation and Evaluation

BACKGROUND

Radiology reporting is a clinically oriented form of documentation that reflects critical information for patients about their health care processes. Realizing its importance, many medical institutions have started providing radiology reports in patient portals. The gain, however, can be limited because of medical language barriers, which require a way for customizing these reports for patients. The open-access, collaborative consumer health vocabulary (CHV) is a terminology system created for such purposes and can be the basis of lexical simplification processes for clinical notes.

OBJECTIVE

The aim of this study was to examine the comprehensibility and suitability of CHV in simplifying radiology reports for consumers. This was done by characterizing the content coverage and the lexical similarity between the terms in the reports and the CHV-preferred terms.

METHODS

The overall procedure was divided into the following two main stages: (1) translation and (2) evaluation. The translation process involved using MetaMap to link terms in the reports to CHV concepts. This is followed by replacing the terms with CHV-preferred terms using the concept names and sources table (MRCONSO) in the Unified Medical Language System (UMLS) Metathesaurus. In the second stage, medical terms in the reports and general terms that are used to describe medical phenomena were selected and evaluated by comparing the words in the original reports with the translated ones. The evaluation includes measuring the content coverage, investigating lexical similarity, and finding trends in missing concepts.

RESULTS

Of the 792 terms selected from the radiology reports, 695 of them could be mapped directly to CHV concepts, indicating a content coverage of 88.5%. A total of 51 of the concepts (53%, 51/97) that could not be mapped are names of human anatomical structures and regions, followed by 28 anatomical descriptions and pathological variations (29%, 28/97). In addition, 12 radiology techniques and projections represented 12% of the unmapped concepts, whereas the remaining six concepts (6%, 12/97) were physiological descriptions. The rate of lexical similarity between the CHV-preferred terms and the terms in the radiology reports was approximately 72.6%.

CONCLUSIONS

The CHV covered a high percentage of concepts found in the radiology reports, but unmapped concepts are associated with areas that are commonly found in radiology reporting. CHV terms also showed a high percentage of lexical similarity with terms in the reports, which contain a myriad of medical jargon. This suggests that many CHV terms might not be suitable for lay consumers who would not be facile with radiology-specific vocabulary. Therefore, further patient-centered content changes are needed of the CHV to increase its usefulness and facilitate its integration into consumer-oriented applications.

Patients' Use and Evaluation of an Online System to Annotate Radiology Reports with Lay Language Definitions

RATIONALE AND OBJECTIVES

The increasing availability of personal health portals has made it easier for patients to obtain their imaging results online. However, the radiology report typically is designed to communicate findings and recommendations to the referring clinician, and may contain many terms unfamiliar to lay readers. We sought to evaluate a web-based interface that presented reports of knee MRI (magnetic resonance imaging) examinations with annotations that included patient-oriented definitions, anatomic illustrations, and hyperlinks to additional information.

MATERIALS AND METHODS

During a 7-month observational trial, a statement added to all knee MRI reports invited patients to view their annotated report online. We tracked the number of patients who opened their reports, the terms they hovered over to view definitions, and the time hovering over each term. Patients who accessed their annotated reports were invited to complete a survey.

RESULTS

Of 1138 knee MRI examinations during the trial period, 185 patients (16.3%) opened their report in the viewing portal. Of those, 141 (76%) hovered over at least one term to view its definition, and 121 patients (65%) viewed a mean of 27.5 terms per examination and spent an average of 3.5 minutes viewing those terms. Of the 22 patients who completed the survey, 77% agreed that the definitions helped them understand the report and 91% stated that the illustrations were helpful.

CONCLUSIONS

A system that provided definitions and illustrations of the medical and technical terms in radiology reports has potential to improve patients' understanding of their reports and their diagnoses.