Clinical decision support for high-cost imaging: A randomized clinical trial

"My attending really wants it!" Manual clinical decision support adjudicating the "better look" inpatient MRI at an academic medical center

OBJECTIVE

MRI utilization in the United States is relatively higher than in other parts of the world and inpatient MRI utilization is particularly difficult to manage given the lack of direct reimbursement. Body MRI studies present an opportunity to reduce inpatient MRI utilization since they are generally the least emergent. Our objective was to use a targeted questionnaire to probe the necessity of inpatient body MRI orders and present an opportunity to either cancel them or transition them to the outpatient realm METHODS: A 9-item questionnaire was devised asking questions about the urgency of the inpatient MRI order including the urgent management question, an inpatient procedure or whether it was recommended by a consultant. Peer-to-peer discussion walking through each of the questions was conducted by radiology housestaff with the ordering clinicians and responses recorded.

RESULTS

845 recorded responses reported a lack of specific clinical question in 23.9% of orders, 68.9% were recommended by a non-radiology consulting service and 16.1% were recommended by radiology studies. 17.0% orders were felt to be outpatient appropriate and 23.3% were considered possibly appropriate for the outpatient setting. 3.9% were canceled and 4.9% were transitioned to outpatient orders.

DISCUSSION

Engaging in a focused discussion about the urgency and appropriateness of an inpatient MRI body order following a list of scripted questions has the potential to reduce utilization. This approach also highlights the relatively high rate of indication uncertainty among ordering clinicians and the central role of consultants in prompting orders.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging, are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging (MRI), are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

The Otto Aufranc Award: Does Hip Arthroscopy at the Time of Periacetabular Osteotomy Improve the Clinical Outcome for the Treatment of Hip Dysplasia? A Multicenter Randomized Clinical Trial

BACKGROUND

A periacetabular osteotomy (PAO) is often sufficient to treat the symptoms and improve quality of life for symptomatic hip dysplasia. However, acetabular cartilage and labral pathologies are very commonly present, and there is a lack of evidence examining the benefits of adjunct arthroscopy to treat these. The goal of this study was to compare the clinical outcome of patients undergoing PAO with and without arthroscopy, with the primary end point being the International Hip Outcome Tool-33 at 1 year.

METHODS

In a multicenter study, 203 patients who had symptomatic hip dysplasia were randomized: 97 patients undergoing an isolated PAO (mean age 27 years [range, 16 to 44]; mean body mass index of 25.1 [range, 18.3 to 37.2]; 86% women) and 91 patients undergoing PAO who had an arthroscopy (mean age 27 years [range, 16 to 49]; mean body mass index of 25.1 [17.5 to 25.1]; 90% women).

RESULTS

At a mean follow-up of 2.3 years (range, 1 to 5), all patients exhibited improvements in their functional score, with no significant differences between PAO plus arthroscopy versus PAO alone at 12 months postsurgery on all scores: preoperative International Hip Outcome Tool-33 score of 31.2 (standard deviation [SD] 16.0) versus 36.4 (SD 15.9), and 12 months postoperative score of 72.4 (SD 23.4) versus 73.7 (SD 22.6). The preoperative Hip disability and Osteoarthritis Outcome pain score was 60.3 (SD 19.6) versus 66.1 (SD 20.0) and 12 months postoperative 88.2 (SD 15.8) versus 88.4 (SD 18.3). The mean preoperative physical health Patient-Reported Outcomes Measurement Information System score was 42.5 (SD 8.0) versus 44.2 (SD 8.8) and 12 months postoperative 48.7 (SD 8.5) versus 52.0 (SD 10.6). There were 4 patients with PAO without arthroscopy who required an arthroscopy later to resolve persistent symptoms, and 1 patient from the PAO plus arthroscopy group required an additional arthroscopy.

CONCLUSIONS

This randomized controlled trial has failed to show any significant clinical benefit in performing hip arthroscopy at the time of the PAO at 1-year follow-up. Longer follow-up will be required to determine if hip arthroscopy provides added value to a PAO for symptomatic hip dysplasia.

Environmental Sustainability and MRI: Challenges, Opportunities, and a Call for Action

The environmental impact of magnetic resonance imaging (MRI) has recently come into focus. This includes its enormous demand for electricity compared to other imaging modalities and contamination of water bodies with anthropogenic gadolinium related to contrast administration. Given the pressing threat of climate change, addressing these challenges to improve the environmental sustainability of MRI is imperative. The purpose of this review is to discuss the challenges, opportunities, and the need for action to reduce the environmental impact of MRI and prepare for the effects of climate change. The approaches outlined are categorized as strategies to reduce greenhouse gas (GHG) emissions from MRI during production and use phases, approaches to reduce the environmental impact of MRI including the preservation of finite resources, and development of adaption plans to prepare for the impact of climate change. Co-benefits of these strategies are emphasized including lower GHG emission and reduced cost along with improved heath and patient satisfaction. Although MRI is energy-intensive, there are many steps that can be taken now to improve the environmental sustainability of MRI and prepare for the effects of climate change. On-going research, technical development, and collaboration with industry partners are needed to achieve further reductions in MRI-related GHG emissions and to decrease the reliance on finite resources. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.

Features and functions of decision support systems for appropriate diagnostic imaging: a scoping review

BACKGROUND

Diagnostic imaging decision support (DI-DS) systems could be effective tools for reducing inappropriate diagnostic imaging examinations. Since effective design and evaluation of these systems requires in-depth understanding of their features and functions, the present study aims to map the existing literature on DI-DS systems to identify features and functions of these systems.

METHODS

The search was performed using Scopus, Embase, PubMed, Web of Science, and Cochrane Central Registry of Controlled Trials (CENTRAL) and was limited to 2000 to 2021. Analytical studies, descriptive studies, reviews and book chapters that explicitly addressed the functions or features of DI-DS systems were included.

RESULTS

A total of 6,046 studies were identified. Out of these, 55 studies met the inclusion criteria. From these, 22 functions and 22 features were identified. Some of the identified features were: visibility, content chunking/grouping, deployed as a multidisciplinary program, clinically valid and relevant feedback, embedding current evidence, and targeted recommendations. And, some of the identified functions were: displaying an appropriateness score, recommending alternative or more appropriate imaging examination(s), providing recommendations for next diagnostic steps, and providing safety alerts.

CONCLUSIONS

The set of features and functions obtained in the present study can provide a basis for developing well-designed DI-DS systems, which could help to improve adherence to diagnostic imaging guidelines, minimize unnecessary costs, and improve the outcome of care through appropriate diagnosis and on-time care delivery.

Effect of an algorithm for automatic placing of standardised test order sets on low-value appointments and attendance rates at four Spanish teaching hospitals: an interrupted time series analysis

OBJECTIVE

Reducing backlogs for elective care is a priority for healthcare systems. We conducted an interrupted time series analysis demonstrating the effect of an algorithm for placing automatic test order sets prior to first specialist appointment on avoidable follow-up appointments and attendance rates.

DESIGN

Interrupted time series analysis.

SETTING

4 academic hospitals from Madrid, Spain.

PARTICIPANTS

Patients referred from primary care attending 10 033 470 outpatient appointments from 16 clinical specialties during a 6-year period (1 January 2018 to 30 June 2023).

INTERVENTION

An algorithm using natural language processing was launched in May 2021. Test order sets developed for 257 presenting complaints from 16 clinical specialties were placed automatically before first specialist appointments to increase rates of diagnosis and initiation of treatment with discharge back to primary care.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes included rate of diagnosis and discharge to primary care and follow-up to first appointment index. The secondary outcome was trend in 'did not attend' rates.

RESULTS

Since May 2021, a total of 1 175 814 automatic test orders have been placed. Significant changes in trend of diagnosis and discharge to primary care at first appointment (p=0.005, 95% CI 0.5 to 2.9) and 'did not attend' rates (p=0.006, 95% CI -0.1 to -0.8) and an estimated attributable reduction of 11 306 avoidable follow-up appointments per month were observed.

CONCLUSION

An algorithm for placing automatic standardised test order sets can reduce low-value follow-up appointments by allowing specialists to confirm diagnoses and initiate treatment at first appointment, also leading to early discharge to primary care and a reduction in 'did not attend' rates. This initiative points to an improved process for outpatient diagnosis and treatment, delivering healthcare more effectively and efficiently.

Medical Imaging Decision And Support (MIDAS): Study protocol for a multi-centre cluster randomized trial evaluating the ESR iGuide

OBJECTIVES

Medical imaging plays an essential role in healthcare. As a diagnostic test, imaging is prone to substantial overuse and potential overdiagnosis, with dire consequences to patient outcomes and health care costs. Clinical decision support systems (CDSSs) were developed to guide referring physicians in making appropriate imaging decisions. This study will evaluate the effect of implementing a CDSS (ESR iGuide) with versus without active decision support in a physician order entry on the appropriate use of imaging tests and ordering behaviour.

METHODS

A protocol for a multi-center cluster-randomized trial with departments acting as clusters, combined with a before-after-revert design. Four university hospitals with eight participating departments each for a total of thirty-two clusters will be included in the study. All departments start in control condition with structured data entry of the clinical indication and tracking of the imaging exams requested. Initially, the CDSS is implemented and all physicians remain blinded to appropriateness scores based on the ESR imaging referral guidelines. After randomization, half of the clusters switch to the active intervention of decision support. Physicians in the active condition are made aware of the categorization of their requests as appropriate, under certain conditions appropriate, or inappropriate, and appropriate exams are suggested. Physicians may change their requests in response to feedback. In the revert condition, active decision support is removed to study the educational effect.

RESULTS/CONCLUSIONS

The main outcome is the proportion of inappropriate diagnostic imaging exams requested per cluster. Secondary outcomes are the absolute number of imaging exams, radiation from diagnostic imaging, and medical costs.

TRIAL REGISTRATION NUMBER

Approval from the Medical Ethics Review Committee was obtained under protocol numbers 20-069 (Augsburg), B 238/21 (Kiel), 20-318 (Lübeck) and 2020-15,125 (Mainz). The trial is registered in the ClinicalTrials.gov register under registration number NCT05490290.

Impact of Artificial Intelligence-Assisted Indication Selection on Appropriateness Order Scoring for Imaging Clinical Decision Support

PURPOSE

The aim of this study was to assess appropriateness scoring and structured order entry after the implementation of an artificial intelligence (AI) tool for analysis of free-text indications.

METHODS

Advanced outpatient imaging orders in a multicenter health care system were recorded 7 months before (March 1, 2020, to September 21, 2020) and after (October 20, 2020, to May 13, 2021) the implementation of an AI tool targeting free-text indications. Clinical decision support score (not appropriate, may be appropriate, appropriate, or unscored) and indication type (structured, free-text, both, or none) were assessed. The χ2 and multivariate logistic regression adjusting for covariables with bootstrapping were used.

RESULTS

In total, 115,079 orders before and 150,950 orders after AI tool deployment were analyzed. The mean patient age was 59.3 ± 15.5 years, and 146,035 (54.9%) were women; 49.9% of orders were for CT, 38.8% for MR, 5.9% for nuclear medicine, and 5.4% for PET. After deployment, scored orders increased to 52% from 30% (P < .001). Orders with structured indications increased to 67.3% from 34.6% (P < .001). On multivariate analysis, orders were more likely to be scored after tool deployment (odds ratio [OR], 2.7, 95% CI, 2.63-2.78; P < .001). Compared with physicians, orders placed by nonphysician providers were less likely to be scored (OR, 0.80; 95% CI, 0.78-0.83; P < .001). MR (OR, 0.84; 95% CI, 0.82-0.87) and PET (OR, 0.12; 95% CI, 0.10-0.13) were less likely to be scored than CT (; P < .001). After AI tool deployment, 72,083 orders (47.8%) remained unscored, 45,186 (62.7%) with free-text-only indications.

CONCLUSIONS

Embedding AI assistance within imaging clinical decision support was associated with increased structured indication orders and independently predicted a higher likelihood of scored orders. However, 48% of orders remained unscored, driven by both provider behavior and infrastructure-related barriers.

Population Health Management in Radiology: Economic Considerations

There is a growing emphasis on population health management (PHM) in the United States, in part because it has the worst health outcomes indices among high-income countries despite spending by far the most on health care. Successful PHM is expected to lead to a healthier population with reduced health care utilization and cost. The role of radiology in PHM is increasingly being recognized, including efforts in care coordination, secondary prevention, and appropriate imaging utilization, among others. To further discuss economic considerations for PHM, we must understand the evolving health care payer environment, which combines fee-for-service and increasingly, an alternative payment model framework developed by the Health Care Payment Learning and Action Network. In considering the term "value-based care," perceived value needs to accrue to those who ultimately pay for care, which is more commonly employers and the government. This perspective drives the design of alternative payment models and thus should be taken into consideration to ensure sustainable practice models.

Measuring appropriateness of diagnostic imaging: a scoping review

In radiology, the justification of diagnostic imaging is a key performance indicator. To date, specific recommendations on the measurement of appropriateness in diagnostic imaging are missing. To map the study literature concerning the definition, measures, methods and data used for analyses of appropriateness in research of diagnostic imaging. We conducted a scoping review in Medline, EMBASE, Scopus and the Cochrane Central Register of Controlled Trials. Two independent reviewers undertook screening and data extraction. After screening 6021 records, we included 50 studies. National guidelines (n = 22/50) or American College of Radiology Appropriateness Criteria (n = 23/50) were used to define and rate appropriateness. 22/50 studies did not provide methodological details about the appropriateness assessment. The included studies varied concerning modality, amount of reviewed examinations (88-13,941) and body regions. Computed tomography (27 studies, 27,168 examinations) was the most frequently analyzed modality, followed by magnetic resonance imaging (17 studies, 6559 examinations) and radiography (10 studies, 7095 examinations). Heterogeneous appropriateness rates throughout single studies (0-100%), modalities, and body regions (17-95%) were found. Research on pediatric and outpatient imaging was sparse. Multicentric, methodologically robust and indication-oriented studies would strengthen appropriateness research in diagnostic imaging and help to develop reliable key performance indicators.

Effect of an ultrasound-first clinical decision tool in emergency department patients with suspected nephrolithiasis: A randomized trial

INTRODUCTION

Previously, we found that the use of ultrasonography for patients with suspected nephrolithiasis resulted in similar outcomes and less radiation exposure vs. CT scan. In this study, we evaluated the implementation of an ultrasound-first clinical decision support (CDS) tool in patients with suspected nephrolithiasis.

METHODS

This randomized trial was conducted at an academic emergency department (ED). We implemented the ultrasound-first CDS tool, deployed when an ED provider placed a CT order for suspected nephrolithiasis. Providers were randomized to receiving the CDS tool vs. usual care. The primary outcome was receipt of CT during the index ED visit. Secondary outcomes included radiation dose and ED revisit.

RESULTS

64 ED Providers and 254 patients with suspected nephrolithiasis were enrolled from January 2019 through Dec 2020. The US-First CDS tool was deployed for 128 patients and was not deployed for 126 patients. 86.7% of patients in the CDS arm received a CT vs. 94.4% in the usual care arm, resulting in an absolute risk difference of -7.7% (-14.8 to -0.6%). Mean radiation dose in the CDS arm was 6.8 mSv (95% CI 5.7-7.9 mSv) vs. 6.1 mSv (95% CI 5.1-7.1 mSv) in the usual care arm. The CDS arm did not result in increased ED revisits, CT scans, or hospitalizations at 7 or 30 days.

CONCLUSIONS AND RELEVANCE

Implementation of the US-first CDS tool resulted in lower CT use for ED patients with suspected nephrolithiasis. The use of this decision support may improve the evaluation of a common problem in the ED.

TRIAL REGISTRATION

ClinicalTrials.gov#NCT03461536.

Overview of Noninterpretive Artificial Intelligence Models for Safety, Quality, Workflow, and Education Applications in Radiology Practice

Artificial intelligence has become a ubiquitous term in radiology over the past several years, and much attention has been given to applications that aid radiologists in the detection of abnormalities and diagnosis of diseases. However, there are many potential applications related to radiologic image quality, safety, and workflow improvements that present equal, if not greater, value propositions to radiology practices, insurance companies, and hospital systems. This review focuses on six major categories for artificial intelligence applications: study selection and protocoling, image acquisition, worklist prioritization, study reporting, business applications, and resident education. All of these categories can substantially affect different aspects of radiology practices and workflows. Each of these categories has different value propositions in terms of whether they could be used to increase efficiency, improve patient safety, increase revenue, or save costs. Each application is covered in depth in the context of both current and future areas of work. Keywords: Use of AI in Education, Application Domain, Supervised Learning, Safety © RSNA, 2022.

Effectiveness of Clinical Decision Support Systems on the Appropriate Use of Imaging for Central Nervous System Injuries: A Systematic Review

BACKGROUND

One of the best practices for timely and efficient diagnoses of central nervous system (CNS) trauma and complex diseases is imaging. However, rates of imaging for CNS are high and impose a lot of costs to health care facilities in addition to exposing patients with negative impact of ionizing radiation.

OBJECTIVES

This study aimed to systematically review the effects and features of clinical decision support systems (CDSSs) for the appropriate use of imaging for CNS injuries.

METHOD

We searched MEDLINE, SCOPUS, Web of Science, and Cochrane without time period restriction. We included experimental and quasiexperimental studies that assessed the effectiveness of CDSSs designed for the appropriate use of imaging for CNS injuries in any clinical setting, including primary, emergency, and specialist care. The outcomes were categorized based on imaging-related, physician-related, and patient-related groups.

RESULT

A total of 3,223 records were identified through the online literature search. Of the 55 potential papers for the full-text review, 11 eligible studies were included. Reduction of CNS imaging proportion varied from 2.6 to 40% among the included studies. Physician-related outcomes, including guideline adherence, diagnostic yield, and knowledge, were reported in five studies, and all demonstrated positive impact of CDSSs. Four studies had addressed patient-related outcomes, including missed or delayed diagnosis, as well as length of stay. These studies reported a very low rate of missed diagnosis due to the cancellation of computed tomography (CT) examine according to the CDSS recommendations.

CONCLUSION

This systematic review reports that CDSSs decrease the utilization of CNS CT scan, while increasing physicians' adherence to the rules. However, the possible harm of CDSSs to patients was not well addressed by the included studies and needs additional investigation. The actual effect of CDSSs on appropriate imaging would be realized when the saved cost of examinations is compared with the cost of missed diagnosis.

Optimization of Radiology Workflow with Artificial Intelligence

The potential of artificial intelligence (AI) in radiology goes far beyond image analysis. AI can be used to optimize all steps of the radiology workflow by supporting a variety of nondiagnostic tasks, including order entry support, patient scheduling, resource allocation, and improving the radiologist's workflow. This article discusses several principal directions of using AI algorithms to improve radiological operations and workflow management, with the intention of providing a broader understanding of the value of applying AI in the radiology department.

Interventions to reduce low-value imaging - a systematic review of interventions and outcomes

BACKGROUND

It is estimated that 20-50% of all radiological examinations are of low value. Many attempts have been made to reduce the use of low-value imaging. However, the comparative effectiveness of interventions to reduce low-value imaging is unclear. Thus, the objective of this systematic review was to provide an overview and evaluate the outcomes of interventions aimed at reducing low-value imaging.

METHODS

An electronic database search was completed in Medline - Ovid, Embase-Ovid, Scopus, and Cochrane Library for citations between 2010 and 2020. The search was built from medical subject headings for Diagnostic imaging/Radiology, Health service misuse or medical overuse, and Health planning. Keywords were used for the concept of reduction and avoidance. Reference lists of included articles were also hand-searched for relevant citations. Only articles written in English, German, Danish, Norwegian, Dutch, and Swedish were included. The Mixed Methods Appraisal Tool was used to appraise the quality of the included articles. A narrative synthesis of the final included articles was completed.

RESULTS

The search identified 15,659 records. After abstract and full-text screening, 95 studies of varying quality were included in the final analysis, containing 45 studies found through hand-searching techniques. Both controlled and uncontrolled before-and-after studies, time series, chart reviews, and cohort studies were included. Most interventions were aimed at referring physicians. Clinical practice guidelines (n = 28) and education (n = 28) were most commonly evaluated interventions, either alone or in combination with other components. Multi-component interventions were often more effective than single-component interventions showing a reduction in the use of low-value imaging in 94 and 74% of the studies, respectively. The most addressed types of imaging were musculoskeletal (n = 26), neurological (n = 23) and vascular (n = 16) imaging. Seventy-seven studies reported reduced low-value imaging, while 3 studies reported an increase.

CONCLUSIONS

Multi-component interventions that include education were often more effective than single-component interventions. The contextual and cultural factors in the health care systems seem to be vital for successful reduction of low-value imaging. Further research should focus on assessing the impact of the context in interventions reducing low-value imaging and how interventions can be adapted to different contexts.

Using Black Bone Magnetic Resonance Imaging for Fibula Free Flap Surgical Planning: A Means to Reduce Radiation Exposure with Accurate Surgical Outcomes

SUMMARY

Advances in virtual surgical planning and three-dimensionally-printed guides have enabled increased precision in vascularized free fibula flap reconstruction of the mandible and valuable preoperative planning. However, virtual surgical planning currently requires high-resolution computed tomographic scans, exposing patients to ionizing radiation. The aim of this study was to determine whether black bone magnetic resonance imaging can be used for accurate surgical planning and three-dimensionally-printed guide creation, thus reducing patient radiation exposure. This study included 10 cadaver heads and 10 cadaver lower extremities. A mock fibula free flap for mandible reconstruction was performed. Five operations were planned with guides created using black bone magnetic resonance imaging, whereas the other five were planned and performed using guides created with computed tomographic scan data. All specimens underwent a postoperative computed tomographic scan, and three-dimensional reconstruction of scans was performed and surgical accuracy to the planned surgery was assessed. Guides created from black bone magnetic resonance imaging demonstrated high accuracy to the surgical plan. There was no statistically significant difference in postoperative deviation from the plan when black bone magnetic resonance imaging versus computed tomographic scanning was used for virtual surgical planning and guide creation. Both modalities led to a postoperative positive or negative deviation from the virtual plan within 0.8 mm. This study demonstrates that virtual surgical planning and three-dimensionally-printed guide creation for free fibula flaps for mandible reconstruction can be performed using black bone magnetic resonance imaging with comparable accuracy to computed tomographic scanning. This could reduce radiation exposure for patients and enable a more streamlined imaging process for head and neck cancer patients.

Characterization of Long Non-coding RNA Signatures of Intracranial Aneurysm in Circulating Whole Blood

BACKGROUND AND OBJECTIVE

Long non-coding RNAs (lncRNAs) may serve as biomarkers for complex disease states, such as intracranial aneurysms. In this study, we investigated lncRNA expression differences in the whole blood of patients with unruptured aneurysms.

METHODS

Whole blood RNA from 67 subjects (34 with aneurysm, 33 without) was used for next-generation RNA sequencing. Differential expression analysis was used to define a signature of intracranial aneurysm-associated lncRNAs. To estimate the signature's ability to classify aneurysms and to identify the most predictive lncRNAs, we implemented a nested cross-validation pipeline to train classifiers using linear discriminant analysis. Ingenuity pathway analysis was used to study potential biological roles of differentially expressed lncRNAs, and lncRNA ontology was used to investigate ontologies enriched in signature lncRNAs. Co-expression correlation analysis was performed to investigate associated differential protein-coding messenger RNA expression.

RESULTS

Of 4639 detected lncRNAs, 263 were significantly different (p < 0.05) between the two groups, and 84 of those had an absolute fold-change ≥ 1.5. An eight-lncRNA signature (q < 0.35, fold-change ≥ 1.5) was able to separate patients with and without aneurysms on principal component analysis, and had an estimated accuracy of 70.9% in nested cross-validation. Bioinformatics analyses showed that networks of differentially expressed lncRNAs (p < 0.05) were enriched for cell death and survival, connective tissue disorders, carbohydrate metabolism, and cardiovascular disease. Signature lncRNAs shared ontologies that reflected regulation of gene expression, signaling, ubiquitin processing, and p53 signaling. Co-expression analysis showed correlations with messenger RNAs related to inflammatory responses.

CONCLUSIONS

Differential expression in whole blood lncRNAs is detectable in patients harboring aneurysms, and reflects expression/signaling regulation, and ubiquitin and p53 pathways. Following validation in larger cohorts, these lncRNAs may be potential diagnostic targets for aneurysm detection by blood testing.

Lessons From the Free-Text Epidemic: Opportunities to Optimize Deployment of Imaging Clinical Decision Support

OBJECTIVE

The Protecting Access to Medicare Act of 2014 requires clinicians to consult Appropriate Use Criteria (AUC) when ordering advanced imaging procedures. Free-text order indications are available when there is no applicable structured indication but are unscored by the AUC. We determined the proportion of free-text indications among all advanced imaging orders and the proportion of free-text indications that could be mapped to a single structured indication.

METHODS

All outpatient advanced diagnostic imaging orders placed in a large multisite health system were recorded after initial AUC deployment (November 20, 2017, to December 19, 2017). Clinicians were prompted upon order entry to select a structured indication or enter a free-text indication. We manually reviewed the two imaging examinations with the highest rate of free-text indications: enhanced CT abdomen/pelvis and unenhanced CT head. Regression analysis examined differences in patient-, imaging-, context-, and provider-level characteristics between scored and unscored examinations.

RESULTS

Among all 39,533 orders for advanced imaging procedures, 59% (23,267 of 39,533) were unscored by the system. The regression model c-statistic (0.50-0.55) demonstrated poor model fit to evaluate for differences between scored and unscored examinations. Free-text indications were found in 71% (16,440 of 23,267) of unscored examinations and 42% (16,440 of 39,533) of all examinations. Manual review of all 1,693 CT abdomen/pelvis and 1,527 CT head examinations with free-text indications revealed that 3,132 free-text indications (97%) could be mapped to a single existing structured indication.

DISCUSSION

Of all initially placed outpatient advanced imaging procedure orders, 42% included free-text indications and 97% of manually reviewed free-text indications could be mapped to a single structured indication.

Improved Appropriateness of Advanced Diagnostic Imaging After Implementation of Clinical Decision Support Mechanism

The Protecting Access to Medicare Act (PAMA) mandates clinical decision support mechanism (CDSM) consultation for all advanced imaging. There are a growing number of studies examining the association of CDSM use with imaging appropriateness, but a paucity of multicenter data. This observational study evaluates the association between changes in advanced imaging appropriateness scores with increasing provider exposure to CDSM. Each provider’s first 200 consecutive anonymized requisitions for advanced imaging (CT, MRI, ultrasound, nuclear medicine) using a single CDSM (CareSelect, Change Healthcare) between January 1, 2017 and December 31, 2019 were collected from 288 US institutions. Changes in imaging requisition proportions among four appropriateness categories (“usually appropriate” [green], “may be appropriate” [yellow], “usually not appropriate” [red], and unmapped [gray]) were evaluated in relation to the chronological order of the requisition for each provider and total provider exposure to CDSM using logistic regression fits and Wald tests. The number of providers and requisitions included was 244,158 and 7,345,437, respectively. For 10,123 providers with ≥ 200 requisitions (2,024,600 total requisitions), the fraction of green, yellow, and red requisitions among the last 10 requisitions changed by +3.0% (95% confidence interval +2.6% to +3.4%), −0.8% (95% CI −0.5% to −1.1%), and −3.0% (95% CI 3.3% to −2.7%) in comparison with the first 10, respectively. Providers with > 190 requisitions had 8.5% (95% CI 6.3% to 10.7%) more green requisitions, 2.3% (0.7% to 3.9%) fewer yellow requisitions, and 0.5% (95% CI −1.0% to 2.0%) fewer red (not statistically significant) requisitions relative to providers with ≤ 10 requisitions. Increasing provider exposure to CDSM is associated with improved appropriateness scores for advanced imaging requisitions.

Quality improvement time-saving intervention to increase use of a clinical decision support tool to reduce low-value diagnostic imaging in a safety net health system

Importance

Electronic health record (EHR) clinical decision support (CDS) tools can provide evidence-based feedback at the point of care to reduce low-value imaging. Success of these tools has been limited partly due to lack of engagement by busy clinicians.

Objective

Measure the impact of a time-saving quality improvement intervention to increase engagement with a CDS tool for low back pain imaging ordering.

Design, setting and participants

We conducted a quasi-experimental difference-in-differences analysis at (BLINDED), examining back pain imaging orders from 29 May 2015 to 07 January 2016. The intervention site was (BLINDED) Emergency Medicine/Urgent Care Center (n=5736) and control sites included all other (BLINDED) hospitals and clinics (n=1621). In May 2015, the Department of Health Services installed a CDS tool that triggered a survey when clinicians ordered an imaging test, generating an ‘appropriateness score’ based on the American College of Radiology guidelines. Clinicians often bypassed the tool, resulting in ‘unscored’ tests.

Intervention

To increase clinician engagement with the tool and decrease the rate of unscored imaging tests, a new policy was implemented at the intervention site on 15 August 2015. If clinicians completed the CDS survey and scored an appropriateness score >3, they could forego a previously mandatory telephone call for pre-imaging utilisation review with the radiology department.

Main outcomes and measures

We used EHR data to measure pre–post-intervention differences in: (1) percentage of unscored tests and (2) percentage of tests with high appropriateness scores (>7).

Results

Percentage of unscored tests decreased from 69.4% to 10.4% at the intervention site and from 50.6% to 34.8% at the control sites (between-group difference: −23.3%, p<0.001). Percentage of high scoring tests increased from 26.5% to 75.0% at the intervention site and from 17.2% to 22.7% at the control sites (between-group difference: 19%, p<0.001).

Conclusion

Workflow time-saving interventions may increase physician engagement with CDS tools and have potential to improve practice patterns.

Value of repeat CT for nonoperative management of patients with blunt liver and spleen injury: a systematic review

PURPOSE

To evaluate the effectiveness of routine repeat computed tomography (CT) for nonoperative management (NOM) of adults with blunt liver and/or spleen injury.

METHODS

We conducted a systematic review of randomized and non-randomized controlled trials (RCTs), quasi-experimental and observational studies of repeat CT in adult patients with blunt abdominal injury. We searched Medline, Embase, Web of Science, and Cochrane Central from their inception to October 2020 using Cochrane guidelines. Primary outcomes were change in clinical management (e.g., emergency surgery, embolization, blood transfusion, clinical surveillance), mortality, and complications. Secondary outcomes were hospital readmission and length of stay.

RESULTS

Search results yielded 1611 studies of which 28 studies including 2646 patients met our inclusion criteria. The majority reported on liver (n = 9) or spleen injury (n = 16) or both (n = 3). No RCTs were identified. Meta-analyses were not possible because no study performed direct comparisons of study outcomes across intervention groups. Only seven of the twenty-eight studies reported whether repeat CT was routine or prompted by clinical indication. In these 7 studies, among the 254 repeat CT performed, 188 (74%) were routine and 8 (4%) of these led to a change in clinical management. Of the 66 (26%) repeated CT prompted by clinical indication, 31 (47%) led to a change in management. We found no data allowing comparison of any other outcomes across intervention groups.

CONCLUSION

Routine repeat CT without clinical indication is not useful in the management of patients with liver and/or spleen injury. However, effect estimates were imprecise and included studies were of low methodological quality. Given the risks of unnecessary radiation and costs associated with repeat CT, future research should aim to estimate the frequency of such practices and assess practice variation.

LEVEL OF EVIDENCE

Systematic reviews and meta-analyses, Level II.

Prospective cost implications with a clinical decision support system for pediatric emergency head computed tomography

BACKGROUND

Unnecessary imaging is a potential cost driver in the United States health care system.

OBJECTIVE

Using a clinical decision support tool, we determined the percentage of low-utility non-contrast head computed tomography (CT) examinations on emergency patients and calculated the prospective cost implications of providing low-value imaging using time-driven activity-based costing at an academic quaternary pediatric hospital.

MATERIALS AND METHODS

A clinical decision support tool for imaging, CareSelect (National Decision Support Co., Madison, WI), was integrated in silent mode into the electronic health record from September 2018 through August 2019. Each non-contrast head CT order received a score from the clinical decision support tool based on the American College of Radiology Appropriateness Criteria. Descriptive statistics for all levels of appropriateness scores were compiled with an emphasis on low-utility exams. A micro-costing assessment was conducted using time-driven activity-based costing on head CT without contrast examinations.

RESULTS

Within the 11-month time period, 3,186 head CT examinations without contrast were ordered for emergency center patients. Among these orders, 28% (896/3,186) were classified as low-utility studies. The base case CT pathway time was 43 min and base case total cost was $193.35. The base case opportunity cost of these low-utility exams extrapolated annually amounts to $188,902 for our institution.

CONCLUSION

Silent mode implementation of a clinical decision support tool resulted in 28% of head CT non-contrast exams on emergency patients being graded as low-utility studies. Prospective cost implications resulted in an annual base case cost of $188,902 to Texas Children's Hospital.

Development of a Musculoskeletal Imaging Competency Examination for Physical Therapists

OBJECTIVE

The number of physical therapists with imaging ordering privileges is increasing; however, a known level of competency and knowledge is generally lacking within the profession, as is a method to determine practitioner competency. The purpose of this study was to develop a valid musculoskeletal (MSK) imaging competency examination for physical therapists.

METHODS

This 3-round Delphi method study utilized experts to reach consensus on examination content and development. Round 1 was completed by 37 experts. The last 2 rounds were completed by 35 experts. Experts rated questions on a 5-point Likert rating scale of importance (1 = not at all important, 5 = very important). Consensus was achieved with an a priori decision of (1) >75% agreement of the expert panel rating and ≥4 on the Likert scale, and (2) ≥.90 on Cronbach alpha and intraclass correlation coefficients. Experts recommended a passing score of 75%. The examination was subsequently reviewed by a panel of 5 radiologists.

RESULTS

The Delphi method and radiologist panel review resulted in the 151-question Burley Readiness Examination (BRE) for MSK Imaging Competency. Interrater agreement and internal consistency of the Delphi panel were excellent, with an average intraclass correlation coefficient and Cronbach alpha of .928 and .950, respectively.

CONCLUSIONS

The BRE is a tool that has the potential to demonstrate practitioners' level of baseline competency with MSK imaging. Additional testing among physical therapists will provide further validation and reliability of the examination.

IMPACT

The use and application of diagnostic imaging is becoming more widespread in physical therapist practice throughout the United States. The BRE could potentially have broader implications for health care utilization and cost in the area of MSK imaging.

Developing an Institute for Health Care Delivery Science: successes, challenges, and solutions in the first five years

Medical knowledge is increasing at an exponential rate. At the same time, unexplained variations in practice and patient outcomes and unacceptable rates of medical errors and inefficiencies in health care delivery have emerged. Our Institute for Health Care Delivery Science (I-HDS) began in 2014 as a novel platform to conduct multidisciplinary healthcare delivery research. We followed ten strategies to develop a successful institute with excellence in methodology and strong understanding of the value of team science. Our work was organized around five hubs: 1) Quality/Process Improvement and Systematic Review, 2) Comparative Effectiveness Research, Pragmatic Clinical Trials, and Predictive Analytics, 3) Health Economics and Decision Modeling, 4) Qualitative, Survey, and Mixed Methods, and 5) Training and Mentoring. In the first 5 years of the I-HDS, we have identified opportunities for change in clinical practice through research using our health system's electronic health record (EHR) data, and designed programs to educate clinicians in the value of research to improve patient care and recognize efficiencies in processes. Testing the value of several model interventions has guided prioritization of evidence-based quality improvements. Some of the changes in practice have already been embedded in the EHR workflow successfully. Development and sustainability of the I-HDS has been fostered by a mix of internal and external funding, including philanthropic foundations. Challenges remain due to the highly competitive funding environment and changes needed to adapt the EHR to healthcare delivery research. Further stakeholder engagement and culture change working with hospital leadership and I-HDS core and affiliate members continues.

Integration of artificial intelligence into clinical patient management: focus on cardiac imaging

Cardiac imaging is a crucial component in the management of patients with heart disease, and as such it influences multiple, inter-related parts of the clinical workflow: physician-patient contact, image acquisition, image pre- and postprocessing, study reporting, diagnostics and outcome predictions, medical interventions, and, finally, knowledge-building through clinical research. With the gradual and ubiquitous infiltration of artificial intelligence into cardiology, it has become clear that, when used appropriately, it will influence and potentially improve-through automation, standardization and data integration-all components of the clinical workflow. This review aims to present a comprehensive view of full integration of artificial intelligence into the standard clinical patient management-with a focus on cardiac imaging, but applicable to all information handling-and to discuss current barriers that remain to be overcome before its widespread implementation and integration.

Imaging Appropriateness for Neck Pain

Imaging of neck pain contributes to a significant proportion of health care costs and is expected to increase with current practices that heavily use radiologic studies as a diagnostic tool. Though consensus guidelines are available to assist physicians in selection of appropriate imaging examinations for neck pain, it is unclear if current ordering practices reflect their use and understanding. To investigate this, we analyzed the number and types of imaging examinations performed for neck pain at a university medical center over the past year. Current trends at our institution suggest that clinicians use consensus imaging guidelines, but there is still controversy in the cervical spine for when not to image. To promote appropriate imaging utilization, we developed an algorithm to guide imaging of neck pain, based upon clinical presentation, referral patterns for neck pain, and a review of the literature.

Clinical Decision Support: The Law, the Future, and the Role for Radiologists

Clinical Decision Support (CDS) was designed as an interactive, electronic tool for use by clinicians that communicates Appropriate Use Criteria (AUC) information to the user and assists them in making the most appropriate treatment decision for a patient's specific clinical condition. Policymakers recognized AUC as a potential solution to control inappropriate utilization of imaging and made CDS mandatory in the Protecting Access to Medicare Act of 2014. In the years since Protecting Access to Medicare Act, data on the potential impact of CDS has been mixed and much of the physician community has expressed concern about the logistics of the program. This article aims to review the legislation behind the AUC program, the events that have transpired since, and some of the challenges and opportunities facing radiologists in the current environment.

Diagnostic imaging: Doing the right thing

Inappropriate diagnostic imaging (DI) is a burgeoning issue and embraces its overuse and its misapplication. The obverse problem is one of underuse - that is when patients who should undergo imaging fail to do so. This article attempts to define these problems, examines the causes and effects and suggests some potential solutions.

What Physicians and Health Organizations Should Know About Mandated Imaging Appropriate Use Criteria

The Appropriate Use Criteria Program, enacted by the Centers for Medicare & Medicaid Services in response to the Protecting Access to Medicare Act of 2014 (PAMA), aims to reduce inappropriate and unnecessary imaging by mandating use of clinical decision support (CDS) by all providers who order advanced imaging examinations (magnetic resonance imaging; computed tomography; and nuclear medicine studies, including positron emission tomography). Beginning 1 January 2020, documentation of an interaction with a certified CDS system using approved appropriate use criteria will be required on all Medicare claims for advanced imaging in all emergency department patients and outpatients as a prerequisite for payment. The Appropriate Use Criteria Program will initially cover 8 priority clinical areas, including several (such as headache and low back pain) commonly encountered by internal medicine providers. All providers and organizations that order and provide advanced imaging must understand program requirements and their options for compliance strategies. Substantial resources and planning will be needed to comply with PAMA regulations and avoid unintended negative consequences on workflow and payments. However, robust evidence supporting the desired outcome of reducing inappropriate use of advanced imaging is lacking.