Assigning responsibility to close the loop on radiology test results

Impact of Early Direct Patient Notification on Follow-Up Completion for Nonurgent Actionable Incidental Radiologic Findings

PURPOSE

The aim of this study was to evaluate whether early direct patient notification in addition to an existing multistage recommendation-tracking system (Backstop) increases follow-up completion rates for actionable incidental findings (AIFs). Patient attitudes toward early notification were also assessed.

METHODS

This prospective, randomized controlled trial recruited patients with AIFs requiring follow-up being enrolled into the Backstop system. Patients were randomized into four groups: those receiving additional early direct notification in a mailed letter (group 1, similar to Pennsylvania Act 112), by phone (group 2), or in an electronic portal message (group 3) and a control group (group 4) without additional notifications added to the existing Backstop system. Differences in follow-up completion rates among these groups were determined using χ2 tests. Patients were surveyed on binary yes/no and Likert-type scale questions, and descriptive statistics are reported.

RESULTS

Data from 2,548 randomized patients were analyzed for the study, including 593 patients notified by letter, 637 notified by phone, 701 notified by portal, and 617 control patients. Group 3 demonstrated the lowest rate of follow-up completion within 1 month of the follow-up due date at 36.4%, compared with 58.7% for group 1, 60.4% for group 2, and 53.2% for group 4 (P < .0001 for all). Group 2 was the only group to have a significantly higher completion rate than group 4 (P = .014). Patients responded positively regarding early notification and preferred electronic portal communication.

CONCLUSIONS

Early direct notification had a mixed impact on follow-up completion rates on the basis of communication modality but was positively received by patients and may have health care benefits when implemented within a recommendation-tracking system.

White Paper: Best Practices in the Communication and Management of Actionable Incidental Findings in Emergency Department Imaging

PURPOSE

Actionable incidental findings (AIFs) are common in radiologic imaging. Imaging is commonly performed in emergency department (ED) visits, and AIFs are frequently encountered, but the ED presents unique challenges for communication and follow-up of these findings. The authors formed a multidisciplinary panel to seek consensus regarding best practices in the reporting, communication, and follow-up of AIFs on ED imaging tests.

METHODS

A 15-member panel was formed, nominated by the ACR and American College of Emergency Physicians, to represent radiologists, emergency physicians, patients, and those involved in health care systems and quality. A modified Delphi process was used to identify areas of best practice and seek consensus. The panel identified four areas: (1) report elements and structure, (2) communication of findings with patients, (3) communication of findings with clinicians, and (4) follow-up and tracking systems. A survey was constructed to seek consensus and was anonymously administered in two rounds, with a priori agreement requiring at least 80% consensus. Discussion occurred after the first round, with readministration of questions where consensus was not initially achieved.

RESULTS

Consensus was reached in the four areas identified. There was particularly strong consensus that AIFs represent a system-level issue, with need for approaches that do not depend on individual clinicians or patients to ensure communication and completion of recommended follow-up.

CONCLUSIONS

This multidisciplinary collaboration represents consensus results on best practices regarding the reporting and communication of AIFs in the ED setting.

Creating a Safety Net Process to Improve Colon Cancer Diagnosis in Patients With Rectal Bleeding

Background Failure to follow up on patients with rectal bleeding is common and may result in a delay in diagnosis of colorectal cancer or in missing high-risk adenomas. The authors' purpose was to create an electronic patient safety net for those diagnosed with rectal bleeding but who did not have colonoscopy to ensure proper detection of colonic abnormalities, including colon cancer. Methods In an integrated health delivery system serving < 4.6 million patients in Southern California, from 2014 to 2019, the authors electronically identified patients with rectal bleeding aged 45 to 80 years but with no recently documented colonoscopy. These cases were reviewed by a gastroenterologist to determine if colonoscopy was appropriate. The physician looked for known documentation as to the cause of rectal bleeding and verified no contraindications to the procedure; if indicated, testing was offered. Results Using the authors' safety net program, 1430 patients with rectal bleeding who needed and completed a colonoscopy were identified. Of those patients, 7.5% had an advanced adenoma or cancer, with a total of 20 cancers, and 34% had findings that warranted more frequent colonoscopy. Conclusions The authors designed a safety net system that was able to capture information on patients with rectal bleeding who had not had a colonoscopy and detected in 34% colonic pathology that would have otherwise gone undetected. The program did not require many resources to implement and had the ability to potentially prevent harm from reaching patients whose rectal bleeding did not get prompt workup. Other health systems and practices should consider implementing a similar system.

An Evolution of Reporting: Identifying the Missing Link

In recent years, radiologic imaging has undergone tremendous technological advances and is now a pillar of diagnostic and treatment algorithms in clinical medicine. The increased complexity and volume of medical imaging has led clinicians to become ever more reliant on radiologists to both identify and interpret patient studies. A radiologist’s report provides key insights into a patient’s immediate state of health, information that is vital when choosing the most appropriate next steps in management. As errors in imaging interpretation or miscommunication of results can greatly impair patient care, identifying common error sources is vital to minimizing their occurrence. Although mistakes in medical imaging are practically inevitable, changes to the delivery of imaging reporting and the addition of artificial intelligence algorithms to analyze clinicians’ communication skills can minimize the impact of these errors, keep up with the continuously evolving landscape of medical imaging, and ultimately close the communication gap.

Electronic Health Record Closed-Loop Communication Program for Unexpected Nonemergent Findings

Background Reliance on examination reporting of unexpected imaging findings does not ensure receipt of findings or appropriate follow-up. A closed-loop communication system should include provider and patient notifications and be auditable through the electronic health record (EHR). Purpose To report the initial design of and results from using an EHR-integrated unexpected findings navigator (UFN) program that ensures closed-loop communication of unexpected nonemergent findings. Materials and Methods An EHR-integrated UFN program was designed to enable identification and communication of unexpected findings and aid in next steps in findings management. Three navigators (with prior training as radiologic technologists and sonographers) facilitated communication and documentation of results to providers and patients. Twelve months (October 2019 to October 2020) of results were retrospectively reviewed to evaluate patient demographics and program metrics. Descriptive statistics and correlation analysis were performed by using commercially available software. Results A total of 3542 examinations were reported within 12 months, representing 0.5% of all examinations performed (total of 749 649); the median patient age was 62 years (range, 1 day to 98 years; interquartile range, 23 years). Most patients were female (2029 of 3542 [57%]). Almost half of the examinations submitted were from chest radiography and CT (1618 of 3542 [46%]), followed by MRI and CT of the abdomen and pelvis (1123 of 3542 [32%]). The most common unexpected findings were potential neoplasms (391 of 3542 [11%]). The median time between examination performance and patient notification was 12 days (range, 0-136 days; interquartile range, 13 days). A total of 2127 additional imaging studies were performed, and 1078 patients were referred to primary care providers and specialists. Most radiologists (89%, 63 of 71 respondents) and providers (65%, 28 of 43 respondents) found the system useful and used it most frequently during regular business hours. Conclusion An electronic health record-integrated, navigator-facilitated, closed-loop communication program for unexpected radiologic findings led to near-complete success in notification of providers and patients and facilitated the next steps in findings management. © RSNA, 2021 See also the editorial by Safdar in this issue.

RADAR: A Closed-Loop Quality Improvement Initiative Leveraging A Safety Net Model for Incidental Pulmonary Nodule Management

BACKGROUND

This study was conducted to assess whether patients with incidental pulmonary nodules (IPNs) received timely follow-up care after implementation of a quality improvement (QI) initiative between radiologists and primary care providers (PCPs).

METHODS

A QI study was conducted at an academic medical center for IPNs identified on chest imaging ordered by PCPs, performed between February 1, 2017, and March 31, 2019, and with at least one-year follow-up. A QI initiative, RADAR (Radiology Result Alert and Development of Automated Resolution), was implemented on March 1, 2018, consisting of (1) a novel, electronic communication tool enabling radiologist-generated alerts with time frame and modality for IPN follow-up recommendations, and (2) a safety net team for centralized care coordination to ensure that communication loops were closed. A preintervention IPN cohort was generated through a natural language processing (NLP) algorithm for radiology reports paired with manual chart review. A postintervention IPN cohort was identified using alerts captured in RADAR. The primary outcome was percentage of IPN follow-up alerts resolved on time (defined as receiving follow-up care within the recommended time frame), comparing pre- and postintervention IPN cohorts. Secondary outcomes included agreement between PCPs and radiologists on the recommended follow-up care plan.

RESULTS

A total of 218 IPN alerts were assessed following exclusions: 110 preintervention and 108 postintervention. IPN timely follow-up improved from 64.5% (71/110) to 84.3% (91/108) (p = 0.001). Postintervention, there was 87.0% (94/108) agreement between PCPs and radiologists on the recommended follow-up plan.

CONCLUSION

The RADAR QI initiative was associated with increased timely IPN follow-up. This safety net model may be scaled to other radiology findings and clinical care settings.

Closing the loop on test results to reduce communication failures: a rapid review of evidence, practice and patient perspectives

Background

Communication failures involving test results contribute to issues of patient harm and sentinel events. This article aims to synthesise review evidence, practice insights and patient perspectives addressing problems encountered in the communication of diagnostic test results.

Methods

The rapid review identified ten systematic reviews and four narrative reviews. Five practitioner interviews identified insights into interventions and implementation, and a citizen panel with 15 participants explored the patient viewpoint.

Results

The rapid review provided support for the role of technology to ensure effective communication; behavioural interventions such as audit and feedback could be effective in changing clinician behaviour; and point-of-care tests (bedside testing) eliminate the communication breakdown problem altogether. The practice interviews highlighted transparency, and clarifying the lines of responsibility as central to improving test result communication. Enabling better information sharing, implementing adequate planning and utilising technology were also identified in the practice interviews as viable strategies to improve test result communication. The citizen panel highlighted technology as critical to improving communication of test results to both health professionals and patients. Patients also highlighted the importance of having different ways of accessing test results, which is particularly pertinent when ensuring suitability for vulnerable populations.

Conclusions

This paper draws together multiple perspectives on the problem of failures in diagnostic test results communication to inform appropriate interventions. Across the three studies, technology was identified as the most feasible option for closing the loop on test result communication. However, the importance of clear, consistent communication and more streamlined processes were also key elements that emerged.

Review registration

The protocol for the rapid review was registered with PROSPERO CRD42018093316.

Imaging activity possibly signalling missed diagnostic opportunities in bladder and kidney cancer: A longitudinal data-linkage study using primary care electronic health records

INTRODUCTION

Sub-optimal use or interpretation of imaging investigations prior to diagnosis of certain cancers may be associated with less timely diagnosis, but pre-diagnostic imaging activity for urological cancer is unknown.

METHOD

We analysed linked data derived from primary and secondary care records and cancer registration to evaluate the use of clinically relevant imaging tests pre-diagnosis, in patients with bladder and kidney cancer diagnosed in 2012-15 in England. As pre-diagnostic imaging activity increased from background rate 8 months pre-diagnosis, we used logistic regression to determine factors associated with first imaging test occurring 4-8 months pre-diagnosis, considering that such instances may reflect possible missed opportunities for expediting the diagnosis.

RESULTS

1963 patients with bladder or kidney cancer had at least one imaging test in the 8 months pre-diagnosis. 420 (21%) of patients had their first imaging test 4-8 months pre-diagnosis, that being ultrasound, CT and X-ray in 48%, 43% and 9% of those cases, respectively. Factors associated with greater risk of a first imaging test 4-8 months pre-diagnosis were kidney cancer, diagnosis at stages other than stage IV, first imaging having been an X-ray, test requested by GP and absence of haematuria before the imaging request.

CONCLUSION

About 1 in 5 patients with urological cancers receive relevant first imaging investigations 4-8 months prior to diagnosis, which may represent potential missed diagnostic opportunities for earlier diagnosis.

Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression

OBJECTIVE

Electronic health record (EHR) systems contain structured data (such as diagnostic codes) and unstructured data (clinical documentation). Clinical insights can be derived from analyzing both. The use of natural language processing (NLP) algorithms to effectively analyze unstructured data has been well demonstrated. Here we examine the utility of NLP for the identification of patients with non-alcoholic fatty liver disease, assess patterns of disease progression, and identify gaps in care related to breakdown in communication among providers.

MATERIALS AND METHODS

All clinical notes available on the 38,575 patients enrolled in the Mount Sinai BioMe cohort were loaded into the NLP system. We compared analysis of structured and unstructured EHR data using NLP, free-text search, and diagnostic codes with validation against expert adjudication. We then used the NLP findings to measure physician impression of progression from early-stage NAFLD to NASH or cirrhosis. Similarly, we used the same NLP findings to identify mentions of NAFLD in radiology reports that did not persist into clinical notes.

RESULTS

Out of 38,575 patients, we identified 2,281 patients with NAFLD. From the remainder, 10,653 patients with similar data density were selected as a control group. NLP outperformed ICD and text search in both sensitivity (NLP: 0.93, ICD: 0.28, text search: 0.81) and F2 score (NLP: 0.92, ICD: 0.34, text search: 0.81). Of 2281 NAFLD patients, 673 (29.5%) were believed to have progressed to NASH or cirrhosis. Among 176 where NAFLD was noted prior to NASH, the average progression time was 410 days. 619 (27.1%) NAFLD patients had it documented only in radiology notes and not acknowledged in other forms of clinical documentation. Of these, 170 (28.4%) were later identified as having likely developed NASH or cirrhosis after a median 1057.3 days.

DISCUSSION

NLP-based approaches were more accurate at identifying NAFLD within the EHR than ICD/text search-based approaches. Suspected NAFLD on imaging is often not acknowledged in subsequent clinical documentation. Many such patients are later found to have more advanced liver disease. Analysis of information flows demonstrated loss of key information that could have been used to help prevent the progression of early NAFLD (NAFL) to NASH or cirrhosis.

CONCLUSION

For identification of NAFLD, NLP performed better than alternative selection modalities. It then facilitated analysis of knowledge flow between physician and enabled the identification of breakdowns where key information was lost that could have slowed or prevented later disease progression.

Automated Tracking of Follow-Up Imaging Recommendations

OBJECTIVE. Radiology reports often contain follow-up imaging recommendations. Failure to comply with these recommendations in a timely manner can lead to poor patient outcomes, complications, and legal liability. As such, the primary objective of this research was to determine adherence rates to follow-up recommendations. MATERIALS AND METHODS. Radiology-related examination data, including report text, for examinations performed between June 1, 2015, and July 31, 2017, were extracted from the radiology departments at the University of Washington (UW) and Lahey Hospital and Medical Center (LHMC). The UW dataset contained 923,885 examinations, and the LHMC dataset contained 763,059 examinations. A 1-year period was used for detection of imaging recommendations and up to 14-months for the follow-up examination to be performed. RESULTS. On the basis of an algorithm with 97.9% detection accuracy, the follow-up imaging recommendation rate was 11.4% at UW and 20.9% at LHMC. Excluding mammography examinations, the overall follow-up imaging adherence rate was 51.9% at UW (range, 44.4% for nuclear medicine to 63.0% for MRI) and 52.0% at LHMC (range, 30.1% for fluoroscopy to 63.2% for ultrasound) using a matcher algorithm with 76.5% accuracy. CONCLUSION. This study suggests that follow-up imaging adherence rates vary by modality and between sites. Adherence rates can be influenced by various legitimate factors. Having the capability to identify patients who can benefit from patient engagement initiatives is important to improve overall adherence rates. Monitoring of follow-up adherence rates over time and critical evaluation of variation in recommendation patterns across the practice can inform measures to standardize and help mitigate risk.

Test results management and distributed cognition in electronic health record-enabled primary care

Managing abnormal test results in primary care involves coordination across various settings. This study identifies how primary care teams manage test results in a large, computerized healthcare system in order to inform health information technology requirements for test results management and other distributed healthcare services. At five US Veterans Health Administration facilities, we interviewed 37 primary care team members, including 16 primary care providers, 12 registered nurses, and 9 licensed practical nurses. We performed content analysis using a distributed cognition approach, identifying patterns of information transmission across people and artifacts (e.g. electronic health records). Results illustrate challenges (e.g. information overload) as well as strategies used to overcome challenges. Various communication paths were used. Some team members served as intermediaries, processing information before relaying it. Artifacts were used as memory aids. Health information technology should address the risks of distributed work by supporting awareness of team and task status for reliable management of results.