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

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.

COVID-Necessitated Online Radiology Elective Improves Student Imaging Appropriateness in Clinical Case Vignettes

RATIONALE AND OBJECTIVES

The use of imaging in medicine has increased considerably over the previous decades, contributing to significant inefficiency of use. Radiology education varies amongst institutions without standardized learning objectives. Consequently, many physicians and student doctors are unprepared to make appropriate choices regarding imaging. In response to COVID-19-engendered restrictions, we created a fully online, image-intensive radiology curriculum to introduce students to clinical radiology and appropriate imaging usage.

MATERIALS AND METHODS

A 2-week radiology elective curriculum was created that adopted accessible, free, online-based learning to foster student education and patient safety while upholding academic standards. Each unit included an emphasis on imaging appropriateness. Students assembled an elective portfolio including self-assessments and prepared a clinical radiology conference to present as a radiologist in training. Two final assessments were required. One consisted of clinical vignettes based on American College of Radiology (ACR) Appropriateness Criteria (AC). The second was an MRI safety quiz.

RESULTS

Third and fourth year students at five institutions (N = 97) completed the elective. Examination scores on an assessment adapted from the ACR AC were significantly improved compared to previously published scores of medical students who took ACR AC-based assessments without taking a radiology course. The course was published and shared with medical schools worldwide.

CONCLUSION

The elective successfully educated students in radiology through a virtual platform and introduced them to the concept of appropriateness in medical imaging. These goals were accomplished using a free, online, easily accessible curriculum. Incorporation of additional topics within the discipline of radiology should be included in the curriculum in the future.

Analytics to monitor local impact of the Protecting Access to Medicare Act's imaging clinical decision support requirements

OBJECTIVE

This study aimed is to: (1) extend the Integrating the Biology and the Bedside (i2b2) data and application models to include medical imaging appropriate use criteria, enabling it to serve as a platform to monitor local impact of the Protecting Access to Medicare Act's (PAMA) imaging clinical decision support (CDS) requirements, and (2) validate the i2b2 extension using data from the Medicare Imaging Demonstration (MID) CDS implementation.

MATERIALS AND METHODS

This study provided a reference implementation and assessed its validity and reliability using data from the MID, the federal government's predecessor to PAMA's imaging CDS program. The Star Schema was extended to describe the interactions of imaging ordering providers with the CDS. New ontologies were added to enable mapping medical imaging appropriateness data to i2b2 schema. z-Ratio for testing the significance of the difference between 2 independent proportions was utilized.

RESULTS

The reference implementation used 26 327 orders for imaging examinations which were persisted to the modified i2b2 schema. As an illustration of the analytical capabilities of the Web Client, we report that 331/1192 or 28.1% of imaging orders were deemed appropriate by the CDS system at the end of the intervention period (September 2013), an increase from 162/1223 or 13.2% for the first month of the baseline period, December 2011 (P = .0212), consistent with previous studies.

CONCLUSIONS

The i2b2 platform can be extended to monitor local impact of PAMA's appropriateness of imaging ordering CDS requirements.

Retrospective Evaluation of Artificial Intelligence Leveraging Free-Text Imaging Order Entry to Facilitate Federally Required Clinical Decision Support

OBJECTIVE

The Protecting Access to Medicare Act mandates clinical decision support (CDS) at imaging order entry, necessitating the use of structured indications to map CDS scores. We evaluated the performance of a commercially available artificial intelligence (AI) tool leveraging free-text order entry to facilitate provider selection of the necessary structured indications.

METHODS

Our institution implemented an AI tool offering predicted structured indications based upon the ordering provider's entry of a free-text reason for examination. Providers remained able to order via the traditional direct search for structured indications. Alternatively, they could take the new free-text-AI approach allowing them to select from AI-predicted indications, perform additional direct searches, indicate no matching indication, or exit CDS workflow. We hypothesized the free-text-AI approach would be elected more often and the AI tool would be successful in facilitating selection of structured indications. We reviewed advanced imaging orders (n = 40,053) for the first 3 months (February to May 2020) since implementation.

RESULTS

Providers were more likely (P < .001) to choose the free-text-AI approach (23,580; 58.9%) to order entry over direct search for structured indications (16,473; 41.1%). The AI tool yielded alerts with predicted indications in 91.7% (n = 21,631) of orders with free text. Ultimately, providers chose AI-predicted indications in 57.7% (n = 12,490) of cases in which they were offered by the tool.

DISCUSSION

Providers significantly more often elected the new free-text-AI approach to order entry for CDS, suggesting provider preference over the traditional approach. The AI tool commonly predicted indications acceptable to ordering providers.

Disproportionate Use in Minor Trauma Is Driving Emergency Department Cervical Spine Imaging: An Injury Severity Score-Based Analysis

PURPOSE

Clinical practice guidelines intended to reduce unnecessary cervical spine imaging have yielded mixed results. We aimed to assess evolving emergency department (ED) cervical spine imaging utilization in patients with trauma by injury severity.

METHODS

Using 2009 to 2018 IBM MarketScan Commercial Databases, we identified ED trauma encounters, associated cervical spine imaging, and related diagnosis codes. We classified encounters by injury severity (minor, intermediate, major) using an International Classification of Disease code-derived Injury Severity Score algorithm and studied evolving imaging utilization using multivariable Poisson regression models.

RESULTS

Of all 11,346,684 ED visits for trauma, 7,753,914 (68.3%), 3,524,250 (31.1%), and 68,520 (0.6%) involved minor, intermediate, and major injuries, respectively. Overall cervical spine imaging increased 5.7% annually (incidence rate ratio [IRR] 1.057, P < .001) with radiography decreasing 2.7% annually (IRR 0.973, P < .001) and CT increasing 10.5% annually (IRR 1.105, P < .001). Radiography utilization remained unchanged for minor injuries (IRR 0.994, P = .14) but decreased for intermediate (IRR 0.928 versus minor, P < .001) and major (IRR 0.931 versus minor, P < .001) injuries. Increases in CT utilization were greatest for minor injuries (IRR 1.109, P < .001) with smaller increases in intermediate (IRR 0.960 versus minor, P < .001) and major (IRR 0.987 versus minor, P = .022) injuries.

CONCLUSIONS

Recent increases in cervical spine imaging in commercially insured patients with trauma seen in the ED have been largely related to increases in CT for patients with only minor injuries, in whom imaging utilization has been historically low. Further study is necessary to assess appropriateness, implications on costs and population radiation dose, and factors influencing ordering decision making.

Trends in the Evaluation and Management of Back Pain in Emergency Departments, United States, 2007-2016

OBJECTIVE

Back pain is one of the most common pain syndromes in the United States, but there has been limited recent description of the role of emergency departments (EDs) in caring for patients with back pain. We investigated trends in the evaluation and management of back pain in U.S. EDs from 2007 to 2016.

METHODS

We performed a retrospective analysis of the National Hospital Ambulatory Medical Care Survey, a nationally representative annual survey of ED visits, which includes data on patient-, hospital-, and visit-level characteristics. We evaluated trends among adult ED visits for back pain, including demographics, resource utilization, and disposition. Trends were assessed through the use of survey-weighted analyses.

RESULTS

Visit rates as a proportion of overall ED visits were stable from 2007 to 2016 (9.1% [95% confidence interval (CI): 8.5-9.6] vs. 9.3% [95% CI: 8.6-10.0]; P = 0.44). Admission rates declined from 6.4% (95% CI: 5.1-8.0) to 5.0% (95% CI: 3.5-6.9; P < 0.001). Imaging utilization increased from 51.7% (95% CI: 49.3-54.1) to 57.6% (95% CI: 53.3-61.7; P = 0.023), with an increase of 58.3% in computed tomography. Overall opioid utilization declined from 53.5% (95% CI: 49.4-57.5) to 46.5% (95% CI: 43.2-49.8; P < 0.001). Tramadol use increased over the study period (4.1% [95% CI: 3.0-5.8] vs. 8.4% [95% CI: 6.6-10.7]; P < 0.001).

CONCLUSIONS

Opioid utilization during ED visits for back pain decreased from 2007 to 2016, whereas tramadol use more than doubled. Care intensity increased significantly despite declining admission rates. Further research into optimal strategies for back pain management in the ED is needed.

Can emergency department provider notes help to achieve more dynamic clinical decision support?

OBJECTIVE

Assess whether clinical data were present in emergency department (ED) provider notes at time of order entry for cervical spine (c-spine) imaging that could be used to augment or pre-populate clinical decision support (CDS) attributes.

METHODS

This Institutional Review Board-approved retrospective study, performed in a quaternary hospital, included all encounters for adult ED patients seen April 1, 2013-September 30, 2014 for a chief complaint of trauma who received c-spine computed tomography (CT) or x-ray. We assessed proportion of ED encounters with at least 1 c-spine-specific CDS rule attribute in clinical notes available at the time of imaging order and agreement between attributes in clinical notes and data entered into CDS.

RESULTS

A portion of the clinical note was submitted before imaging order in 42% (184/438) of encounters reviewed; 59.2% (109/184) of encounters with note portions submitted before imaging order had at least 1 positive CDS attribute identified supporting imaging study appropriateness; 34.8% (64/184) identified exclusion criteria where CDS appropriateness recommendations would not be applicable. 65.8% (121/184) of encounters had either a positive CDS attribute or an exclusion criterion. Concordance of c-spine CDS attributes when present in both notes and CDS was 68.4% (κ = 0.35 95% CI: 0.15-0.56; McNemar P = 0.23).

CONCLUSIONS

Clinical notes are an underutilized source of clinical attributes needed for CDS, available in a substantial percentage of encounters at the time of imaging order. Automated pre-population of imaging order requisitions with relevant clinical information extracted from electronic health record provider notes may: (1) improve ordering efficiency by reducing redundant data entry, (2) help improve clinical relevance of CDS alerts, and (3) potentially reduce provider burnout from extraneous alerts.

Changes in Hospital Outpatient Quality Reporting Program Brain CT Efficiency Performance, 2013 to 2018

BACKGROUND AND PURPOSE

Inefficient imaging practices merit renewed attention in preparation for full implementation of the Appropriate Use Criteria Program. This study's purpose is to quantify changes in outpatient brain CT imaging efficiency from 2013 to 2018, including changes in relative efficiency by hospital category.

MATERIALS AND METHODS

Imaging efficiency data were obtained from the Medicare Hospital Compare website. Summary statistics were calculated for rates of unnecessarily combined brain and sinus CT scans from 2013 to 2018. Relative performance was compared by hospital Medicare payment structure, type of ownership, and affiliation with a radiology residency program. The predictive value of these hospital characteristics on brain CT efficiency was determined using linear regression analysis.

RESULTS

From 2013 to 2018, the mean frequency of unnecessarily combined brain and sinus CT scans decreased by 1.82% (95% confidence interval, 1.74%-1.90%). Proprietary and physician-owned hospitals exhibited a higher mean frequency of combined scans than other hospitals in 2013 (P < .001), and government-owned hospitals exhibited a lower mean frequency of combined scans than other hospitals in 2018 (P < .001). Radiology residency-affiliated hospitals exhibited no significant difference in 2013 but exhibited a higher mean frequency in 2018 (difference: 0.45%; 95% confidence interval, 0.29%-0.61%). Critical access hospital status and nonaffiliation with a radiology residency program were the strongest predictors of brain CT efficiency in the regression model.

CONCLUSION

Recent changes in hospitals' relative brain CT efficiency suggest category-specific differences in responsiveness to quality improvement efforts and may foreshadow similar trends under forthcoming initiatives.

Fecal Bile Acid Testing in Assessing Patients With Chronic Unexplained Diarrhea: Implications for Healthcare Utilization

INTRODUCTION

Bile acid (BA) diarrhea is the cause in ∼26% of chronic unexplained (nonbloody) diarrhea (CUD) based on SeHCAT testing. To assess fecal BA excretion and healthcare utilization in patients with CUD.

METHODS

In a retrospective review of 1,071 consecutive patients with CUD who completed 48-hour fecal BA testing, we analyzed the symptoms, diagnostic tests performed, and final diagnoses.

RESULTS

After 135 patients were excluded because of mucosal diseases, increased BA excretion was identified in 476 (51%) of the 936 patients with CUD: 29% with selective increase in primary BA and 22% with increased total BA excretion (35% with normal primary BA excretion). There were no differences in demographics, clinical symptoms, or history of cholecystectomy in patients with elevated total or selective primary fecal BA excretion compared with patients with normal excretion. Before the 48-hour fecal BA excretion test was performed, patients completed on average 1.2 transaxial imaging, 2.6 endoscopic procedures, and 1.6 miscellaneous tests/person. Less than 10% of these tests identified the etiology of CUD. Total fecal BAs >3,033 µmol/48 hour or primary BAs >25% had a 93% negative predictive value to exclude mucosal disease. Among patients with increased fecal BA excretion, >70% reported diarrhea improved with BA sequestrant compared with 26% with normal fecal BA excretion. Patients with selective elevation in primary fecal BAs were 3.1 times (95% confidence interval, 1.5-6.63) more likely to respond to BA sequestrant therapy compared with those with elevated total fecal BAs.

DISCUSSION

Increased fecal BA excretion is frequent (51%) in patients with CUD. Early 48-hour fecal BA evaluation has the potential to decrease healthcare utilization in CUD.

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.

Introducing Artificial Intelligence Training in Medical Education

Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillful medicine-machine interaction. As the rate of medical knowledge grows, technologies such as AI are needed to enable health care professionals to effectively use this knowledge to practice medicine. Medical professionals need to be adequately trained in this new technology, its advantages to improve cost, quality, and access to health care, and its shortfalls such as transparency and liability. AI needs to be seamlessly integrated across different aspects of the curriculum. In this paper, we have addressed the state of medical education at present and have recommended a framework on how to evolve the medical education curriculum to include AI.