Effect of Evidence-based Clinical Decision Support on the Use and Yield of CT Pulmonary Angiographic Imaging in Hospitalized Patients

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.

Turning radiology reports into epidemiological data to track seasonal pulmonary infections and the COVID-19 pandemic

OBJECTIVES

To automatically label chest radiographs and chest CTs regarding the detection of pulmonary infection in the report text, to calculate the number needed to image (NNI) and to investigate if these labels correlate with regional epidemiological infection data.

MATERIALS AND METHODS

All chest imaging reports performed in the emergency room between 01/2012 and 06/2022 were included (64,046 radiographs; 27,705 CTs). Using a regular expression-based text search algorithm, reports were labeled positive/negative for pulmonary infection if described. Data for regional weekly influenza-like illness (ILI) consultations (10/2013-3/2022), COVID-19 cases, and hospitalization (2/2020-6/2022) were matched with report labels based on calendar date. Positive rate for pulmonary infection detection, NNI, and the correlation with influenza/COVID-19 data were calculated.

RESULTS

Between 1/2012 and 2/2020, a 10.8-16.8% per year positive rate for detecting pulmonary infections on chest radiographs was found (NNI 6.0-9.3). A clear and significant seasonal change in mean monthly detection counts (102.3 winter; 61.5 summer; p < .001) correlated moderately with regional ILI consultations (weekly data r = 0.45; p < .001). For 2020-2021, monthly pulmonary infection counts detected by chest CT increased to 64-234 (23.0-26.7% per year positive rate, NNI 3.7-4.3) compared with 14-94 (22.4-26.7% positive rate, NNI 3.7-4.4) for 2012-2019. Regional COVID-19 epidemic waves correlated moderately with the positive pulmonary infection CT curve for 2020-2022 (weekly new cases: r = 0.53; hospitalizations: r = 0.65; p < .001).

CONCLUSION

Text mining of radiology reports allows to automatically extract diagnoses. It provides a metric to calculate the number needed to image and to track the trend of diagnoses in real time, i.e., seasonality and epidemic course of pulmonary infections.

CLINICAL RELEVANCE

Digitally labeling radiology reports represent previously neglected data and may assist in automated disease tracking, in the assessment of physicians' clinical reasoning for ordering radiology examinations and serve as actionable data for hospital workflow optimization.

KEY POINTS

• Radiology reports, commonly not machine readable, can be automatically labeled with the contained diagnoses using a regular-expression based text search algorithm. • Chest radiograph reports positive for pulmonary infection moderately correlated with regional influenza-like illness consultations (weekly data; r = 0.45; p < .001) and chest CT reports with the course of the regional COVID-19 pandemic (new cases: r = 0.53; hospitalizations: r = 0.65; p < 0.001). • Rendering radiology reports into data labels provides a metric for automated disease tracking, the assessment of ordering physicians clinical reasoning and can serve as actionable data for workflow optimization.

Influence of research evidence on the use of cardiovascular clinical prediction rules in primary care: an exploratory qualitative interview study

BACKGROUND

Cardiovascular clinical prediction rules (CPRs) are widely used in primary care. They accumulate research evidence through derivation, external validation, and impact studies. However, existing knowledge about the influence of research evidence on the use of CPRs is limited. Therefore, we explored how primary care clinicians' perceptions of and experiences with research influence their use of cardiovascular CPRs.

METHODS

We conducted an exploratory qualitative interview study with thematic analysis. Primary care clinicians were recruited from the WWAMI (Washington, Wyoming, Alaska, Montana and Idaho) region Practice and Research Network (WPRN). We used purposeful sampling to ensure maximum variation within the participant group. Data were collected by conducting semi-structured online interviews. We analyzed data using inductive thematic analysis to identify commonalities and differences within themes.

RESULTS

Of 29 primary care clinicians who completed the questionnaire, 15 participated in the interview. We identified two main themes relating to the influence of clinicians' perceptions of and experiences with cardiovascular CPR research on their decisions about using cardiovascular CPRs: "Seek and judge" and "be acquainted and assume." When clinicians are familiar with, trust, and feel confident in using research evidence, they might actively search and assess the evidence, which may then influence their decisions about using cardiovascular CPRs. However, clinicians, who are unfamiliar with, distrust, or find it challenging to use research evidence, might be passively acquainted with evidence but do not make their own judgment on the trustworthiness of such evidence. Therefore, these clinicians might not rely on research evidence when making decisions about using cardiovascular CPRs.

CONCLUSIONS

Clinicians' perceptions and experiences could influence how they use research evidence in decisions about using cardiovascular CPRs. This implies, when promoting evidence-based decisions, it might be useful to target clinicians' unfamiliarity, distrust, and challenges regarding the use of research evidence rather than focusing only on their knowledge and skills. Further, because clinicians often rely on evidence-unrelated factors, guideline developers and policymakers should recommend cardiovascular CPRs supported by high-quality evidence.

Electronic Health Record Order Entry-Based Interventions in Response to a Global Iodinated Contrast Media Shortage: Impact on Contrast-Enhanced CT Utilization

BACKGROUND. Radiology informatics systems and clinical decision support tools in the electronic health record (EHR) can be leveraged to help impact ordering patterns in response to the ongoing global iodinated contrast media shortage. OBJECTIVE. The purpose of our study was to assess the impact of EHR order entry-based interventions, implemented as part of a health system's response to the global contrast media shortage, on contrast-enhanced CT utilization. METHODS. This retrospective study included 79,259 patients who underwent CT at a large multisite health system between April 1, 2022, and July 3, 2022. Two EHR-based interventions were implemented as part of the health system's response to the global contrast media shortage. A first EHR-based intervention on May 10, 2022, entailed creating an alert that appeared in a sidebar after any contrast-enhanced body CT orders, indicating the present shortage and recommending alternate imaging modalities. A second EHR-based intervention on May 16, 2022, required referrers to enter detailed clinical information for all contrast-enhanced body CT orders, which radiologists used when protocoling examinations. Data regarding CT orders and examinations performed were extracted from the electronic data warehouse. RESULTS. During the preintervention, first postintervention, and second postintervention periods, the mean number of patients who underwent contrast-enhanced CT per weekday was 726, 689, and 639, respectively (p for preintervention vs second postintervention periods, < .001). During the three periods, the mean number of patients who underwent CT per weekday was 1350, 1323, and 1314 (p < .001). During the three periods, the mean number of patients who underwent contrast-enhanced body CT per weekday was 561, 532, and 492 (p < .001). During the three periods, the mean number of orders for CT with IV contrast media per weekday was 154, 143, and 131 (p < .001). During the three periods, the mean number of orders for CT without IV contrast media per weekday was 196, 202, and 221 (p < .001). CONCLUSION. EHR order entry-based interventions implemented in response to the global contrast media shortage significantly reduced contrast-enhanced CT utilization in a large health system. CLINICAL IMPACT. The findings indicate the ability to rapidly achieve changes in ordering clinician behavior and subsequent clinical practice using systemwide EHR changes.

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.

Decision support for computed tomography in the emergency department: a multicenter cluster-randomized controlled trial

OBJECTIVES

Clinical decision support may facilitate evidence-based imaging, but most studies to date examining the impact of decision support have used non-randomized designs which limit the conclusions that can be drawn from them. This randomized trial examines if decision support can reduce computed tomography (CT) utilization for patients with mild traumatic brain injuries and suspected pulmonary embolism in the emergency department. This study was funded by a competitive public research grant and registered on ClinicalTrials.gov (NCT02410941).

METHODS

Emergency physicians at five urban sites were assigned to voluntary decision support for CT imaging of patients with either head injuries or suspected pulmonary embolism using a cluster-randomized design over a 1-year intervention period. The co-primary outcomes were CT head and CT pulmonary angiography utilization. CT pulmonary angiography diagnostic yield (proportion of studies diagnostic for acute pulmonary embolism) was a secondary outcome.

RESULTS

A total of 225 physicians were randomized and studied over a 2-year baseline and 1-year intervention period. Physicians interacted with the decision support in 38.0% and 45.0% of eligible head injury and suspected pulmonary embolism cases, respectively. A mixed effects logistic regression model demonstrated no significant impact of decision support on head CT utilization (OR 0.93, 95% CI 0.79-1.10, p = 0.31), CT pulmonary angiography utilization (OR 0.98, 95% CI 0.88-1.11, p = 0.74) or diagnostic yield (OR 1.23, 95% CI 0.96-1.65, p = 0.10). However, overall CT pulmonary diagnostic yield (17.7%) was almost three times higher than that reported by a recent large US study, suggesting that selective imaging was already being employed.

CONCLUSION

Voluntary decision support addressing many commonly cited barriers to evidence-based imaging did not significantly reduce CT utilization or improve diagnostic yield but was limited by low rates of participation and high baseline rates of selective imaging. Demonstrating value to clinicians through interventions that improve workflow is likely necessary to meaningfully change imaging practices.

Machine learning applications in radiation oncology

Machine learning technology has a growing impact on radiation oncology with an increasing presence in research and industry. The prevalence of diverse data including 3D imaging and the 3D radiation dose delivery presents potential for future automation and scope for treatment improvements for cancer patients. Harnessing this potential requires standardization of tools and data, and focused collaboration between fields of expertise. The rapid advancement of radiation oncology treatment technologies presents opportunities for machine learning integration with investments targeted towards data quality, data extraction, software, and engagement with clinical expertise. In this review, we provide an overview of machine learning concepts before reviewing advances in applying machine learning to radiation oncology and integrating these techniques into the radiation oncology workflows. Several key areas are outlined in the radiation oncology workflow where machine learning has been applied and where it can have a significant impact in terms of efficiency, consistency in treatment and overall treatment outcomes. This review highlights that machine learning has key early applications in radiation oncology due to the repetitive nature of many tasks that also currently have human review. Standardized data management of routinely collected imaging and radiation dose data are also highlighted as enabling engagement in research utilizing machine learning and the ability integrate these technologies into clinical workflow to benefit patients. Physicists need to be part of the conversation to facilitate this technical integration.

A systematic review of natural language processing applied to radiology reports

BACKGROUND

Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to radiology is of significance but recent reviews on this are limited. This study systematically assesses and quantifies recent literature in NLP applied to radiology reports.

METHODS

We conduct an automated literature search yielding 4836 results using automated filtering, metadata enriching steps and citation search combined with manual review. Our analysis is based on 21 variables including radiology characteristics, NLP methodology, performance, study, and clinical application characteristics.

RESULTS

We present a comprehensive analysis of the 164 publications retrieved with publications in 2019 almost triple those in 2015. Each publication is categorised into one of 6 clinical application categories. Deep learning use increases in the period but conventional machine learning approaches are still prevalent. Deep learning remains challenged when data is scarce and there is little evidence of adoption into clinical practice. Despite 17% of studies reporting greater than 0.85 F1 scores, it is hard to comparatively evaluate these approaches given that most of them use different datasets. Only 14 studies made their data and 15 their code available with 10 externally validating results.

CONCLUSIONS

Automated understanding of clinical narratives of the radiology reports has the potential to enhance the healthcare process and we show that research in this field continues to grow. Reproducibility and explainability of models are important if the domain is to move applications into clinical use. More could be done to share code enabling validation of methods on different institutional data and to reduce heterogeneity in reporting of study properties allowing inter-study comparisons. Our results have significance for researchers in the field providing a systematic synthesis of existing work to build on, identify gaps, opportunities for collaboration and avoid duplication.

Utilization of serum D-dimer assays prior to computed tomography pulmonary angiography scans in the diagnosis of pulmonary embolism among emergency department physicians: a retrospective observational study

Background

A variety of evidence-based algorithms and decision rules using D-Dimer testing have been proposed as instruments to allow physicians to safely rule out a pulmonary embolism (PE) in low-risk patients.

Objective

To describe the prevalence of D-Dimer utilization among emergency department (ED) physicians and its impact on positive yields and utilization rates of Computed Tomography Pulmonary Angiography (CTPA).

Methods

Data was collected on all CTPA studies ordered by ED physicians at three sites during a 2-year period. Using a chi-square test, we compared the diagnostic yield for those patients who had a D-Dimer prior to their CTPA and those who did not. Secondary analysis was done to examine the impact of D-Dimer testing prior to CTPA on individual physician diagnostic yield or utilization rate.

Results

A total of 2811 CTPAs were included in the analysis. Of these, 964 CTPAs (34.3%) were ordered without a D-Dimer, and 343 (18.7%) underwent a CTPA despite a negative D-Dimer. Those CTPAs preceded by a D-Dimer showed no significant difference in positive yields when compared to those ordered without a D-Dimer (9.9% versus 11.3%, p = 0.26). At the individual physician level, no statistically significant relationship was found between D-Dimer utilization and CTPA utilization rate or diagnostic yield.

Conclusion

This study provides evidence of suboptimal adherence to guidelines in terms of D-Dimer screening prior to CTPA, and forgoing CTPAs in patients with negative D-Dimers. However, the lack of a positive impact of D-Dimer testing on either CTPA diagnostic yield or utilization rate is indicative of issues relating to the high false-positive rates associated with D-Dimer screening.

Use of interrupted time series methods in the evaluation of health system quality improvement interventions: a methodological systematic review

BACKGROUND

When randomisation is not possible, interrupted time series (ITS) design has increasingly been advocated as a more robust design to evaluating health system quality improvement (QI) interventions given its ability to control for common biases in healthcare QI. However, there is a potential risk of producing misleading results when this rather robust design is not used appropriately. We performed a methodological systematic review of the literature to investigate the extent to which the use of ITS has followed best practice standards and recommendations in the evaluation of QI interventions.

METHODS

We searched multiple databases from inception to June 2018 to identify QI intervention studies that were evaluated using ITS. There was no restriction on date, language and participants. Data were synthesised narratively using appropriate descriptive statistics. The risk of bias for ITS studies was assessed using the Cochrane Effective Practice and Organisation of Care standard criteria. The systematic review protocol was registered in PROSPERO (registration number: CRD42018094427).

RESULTS

Of 4061 potential studies and 2028 unique records screened for inclusion, 120 eligible studies assessed eight QI strategies and were from 25 countries. Most studies were published since 2010 (86.7%), reported data using monthly interval (71.4%), used ITS without a control (81%) and modelled data using segmented regression (62.5%). Autocorrelation was considered in 55% of studies, seasonality in 20.8% and non-stationarity in 8.3%. Only 49.2% of studies specified the ITS impact model. The risk of bias was high or very high in 72.5% of included studies and did not change significantly over time.

CONCLUSIONS

The use of ITS in the evaluation of health system QI interventions has increased considerably over the past decade. However, variations in methodological considerations and reporting of ITS in QI remain a concern, warranting a need to develop and reinforce formal reporting guidelines to improve its application in the evaluation of health system QI interventions.

Effect of COVID-19 on computed tomography usage and critical test results in the emergency department: an observational study

BACKGROUND

The effect of the coronavirus disease 2019 (COVID-19) pandemic on new or unexpected radiologic findings in the emergency department (ED) is unclear. The aim of this study was to determine the effect of the COVID-19 pandemic on the number of computed tomography (CT) critical test results in the ED.

METHODS

We performed a retrospective observational study of ED CT usage at 4 Ontario hospitals (1 urban academic, 1 northern academic, 1 urban community and 1 rural community) over 1 month during the COVID-19 pandemic (April 2020) and over the same month 1 year earlier (April 2019; before the pandemic). The CT findings from 1 of the 4 hospitals, Hamilton Health Sciences, were reviewed to determine the number of critical test results by body region. Total CT numbers were compared using Poisson regression and CT yields were compared using the χ² test.

RESULTS

The median number of ED CT examinations per day was markedly lower during the COVID-19 pandemic than before the pandemic (82 v. 133, p < 0.01), with variation across hospitals (p = 0.001). On review of 1717 CT reports from Hamilton Health Sciences, fewer critical test results were demonstrated on CT pulmonary angiograms (43 v. 88, p < 0.001) and CT examinations of the head (82 v. 112, p < 0.03) during the pandemic than before the pandemic; however, the yield of these examinations did not change. Although the absolute number of all CT examinations with critical test results decreased, the number of CT examinations without critical results decreased more, resulting in a higher yield of CT for critical test results during the pandemic (46% [322/696] v. 37% [379/1021], p < 0.01).

INTERPRETATION

Emergency department CT volumes markedly decreased during the COVID-19 pandemic, predominantly because there were fewer examinations with new or unexpected findings. This suggests that COVID-19 public information campaigns influenced the behaviours of patients presenting to the ED.

Predictive Value of Noncontrast Head CT with Negative Findings in the Emergency Department Setting

BACKGROUND AND PURPOSE

Noncontrast head CTs are routinely acquired for patients with neurologic symptoms in the emergency department setting. Anecdotally, noncontrast head CTs performed in patients with prior negative findings with the same clinical indication are of low diagnostic yield. We hypothesized that the rate of acute findings in noncontrast head CTs performed in patients with a preceding study with negative findings would be lower compared with patients being imaged for the first time.

MATERIALS AND METHODS

We retrospectively evaluated patients in the emergency department setting who underwent noncontrast head CTs at our institution during a 4-year period, recording whether the patient had undergone a prior noncontrast head CT, the clinical indication for the examination, and the examination outcome. Positive findings on examinations were defined as those that showed any intracranial abnormality that would necessitate a change in acute management, such as acute hemorrhage, hydrocephalus, herniation, or interval worsening of a prior finding.

RESULTS

During the study period, 8160 patients in the emergency department setting underwent a total of 9593 noncontrast head CTs; 88.2% (7198/8160) had a single examination, and 11.8% (962/8160) had at least 1 repeat examination. The baseline positive rate of the "nonrepeat" group was 4.3% (308/7198). The 911 patients in the "repeat" group with negative findings on a baseline/first CT had a total of 1359 repeat noncontrast head CTs during the study period. The rate of positive findings for these repeat examinations was 1.8% (25/1359), significantly lower than the 4.3% baseline rate (P < .001). Of the repeat examinations that had positive findings, 80% (20/25) had a study indication that was discordant with that of the prior examination, compared with only 44% (593/1334) of the repeat examinations that had negative findings (P < .001).

CONCLUSIONS

In a retrospective observational study based on approximately 10,000 examinations, we found that serial noncontrast head CT examinations in patients with prior negative findings with the same study indication are less likely to have positive findings compared with first-time examinations or examinations with a new indication. This finding suggests a negative predictive value of a prior noncontrast head CT examination with negative findings with the same clinical indication.

Clinical Decision Support for Ordering CTA-PE Studies in the Emergency Department-A Pilot on Feasibility and Clinical Impact in a Tertiary Medical Center

PURPOSE

To determine the feasibility and impact of Clinical Decision Support for imaging ordering.

METHODS

A survey of 231 emergency providers identified Computed tomography angiography (CTA)-Pulmonary embolism (PE) as an overutilized study. We developed an algorithm that combined established risk scores to stratify patients for PE work-up (recommendations: CTA, D-dimer or no further testing); the algorithm was integrated into the Epic Radiology Information Ordering System.

RESULTS

Among 872 studies requested, 479 (55%) received a recommendation to change their order: 6 (1.3%) were cancelled; 13 (2.7%) changed to a D-dimer, and 460 (96%) proceeded with CTA. Of the 853 studies conducted, 8.2% were positive for PE. The algorithm had good discriminatory power with positivity rates of 12.0% (CT), 10.0% (D-dimer), and 2.6% (no further testing). Compliance with the recommendation ranged from 12%-68% (mean 45%) with 10% correlation between compliance and positivity rates.

CONCLUSION

While the CDS algorithm was accurate, it had only a minimal impact on ordering practices, in part due to heterogeneity in physician adherence.

Evaluation of Cancer Patients With Suspected Pulmonary Embolism: Performance of the American College of Physicians Guideline

BACKGROUND

Accurate risk stratification of pulmonary embolism (PE) can reduce unnecessary imaging. We investigated the extent to which the American College of Physicians (ACP) guideline for evaluation of patients with suspected PE could be applied to cancer patients in the emergency department of a comprehensive cancer center.

MATERIALS AND METHODS

Data from cancer patients who underwent CT pulmonary angiography (CTPA) between August 1, 2015, and October 31, 2015, were collected. We assessed each patient's diagnostic workup for its adherence to the ACP guideline in terms of clinical risk stratification and age-adjusted d-dimer level and the degree to which these factors were associated with PE.

RESULTS

Of the 380 patients identified, 213 (56%) underwent CTPA indicated per the ACP guideline, and 78 (21%) underwent CTPA not indicated per the guideline. Only one of the patients who underwent nonindicated CTPA had a PE. Fifty-seven patients underwent unnecessary d-dimer evaluation, and 71 patients with negative d-dimer test results underwent nonindicated CTPA. PEs were found in 6 of 108 (6%) low-risk patients, 22 of 219 (10%) intermediate-risk patients, and 13 of 53 (25%) high-risk patients. The ACP guideline had negative predictive value of 99% (95% confidence interval: 93%-100%) and sensitivity of 97% (95% confidence interval: 86%-100%) in predicting PE.

CONCLUSION

The ACP guideline has good sensitivity for detecting PE in cancer patients and thus can be applied in this population. Compliance with the ACP guideline when evaluating cancer patients with suspected PE could reduce the use of unnecessary imaging and laboratory studies.

Fast Healthcare Interoperability Resources, Clinical Quality Language, and Systematized Nomenclature of Medicine-Clinical Terms in Representing Clinical Evidence Logic Statements for the Use of Imaging Procedures: Descriptive Study

Background

Evidence-based guidelines and recommendations can be transformed into “If-Then” Clinical Evidence Logic Statements (CELS). Imaging-related CELS were represented in standardized formats in the Harvard Medical School Library of Evidence (HLE).

Objective

We aimed to (1) describe the representation of CELS using established Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT), Clinical Quality Language (CQL), and Fast Healthcare Interoperability Resources (FHIR) standards and (2) assess the limitations of using these standards to represent imaging-related CELS.

Methods

This study was exempt from review by the Institutional Review Board as it involved no human subjects. Imaging-related clinical recommendations were extracted from evidence sources and translated into CELS. The clinical terminologies of CELS were represented using SNOMED CT and the condition-action logic was represented in CQL and FHIR. Numbers of fully and partially represented CELS were tallied.

Results

A total of 765 CELS were represented in the HLE as of December 2018. We were able to fully represent 137 of 765 (17.9%) CELS using SNOMED CT, CQL, and FHIR. We were able to represent terms using SNOMED CT in the temporal component for action (“Then”) statements in CQL and FHIR in 755 of 765 (98.7%) CELS.

Conclusions

CELS were represented as shareable clinical decision support (CDS) knowledge artifacts using existing standards—SNOMED CT, FHIR, and CQL—to promote and accelerate adoption of evidence-based practice. Limitations to standardization persist, which could be minimized with an add-on set of standard terms and value sets and by adding time frames to the CQL framework.

Impact of a Multifaceted Information Technology-Enabled Intervention on the Adoption of ACR White Paper Follow-Up Recommendations for Incidental Adnexal Lesions Detected on CT

OBJECTIVE. The objective of our study was to improve adherence to American College of Radiology (ACR) white paper follow-up imaging recommendations for incidental adnexal lesions seen on pelvic CT (herein referred to as "adherence rate to recommendations"). MATERIALS AND METHODS. This quality improvement project was conducted at a large academic teaching hospital. The baseline adherence rate to recommendations was assessed by screening all pelvic CT reports for the period from October 22, 2016, through December 22, 2016, for incidental adnexal findings, followed by manual review. Forty abdominal and cancer imaging radiologists were surveyed to understand the barriers to adoption of the recommendations. Interventions to address the most common identified barriers were implemented on December 23, 2016. The postintervention adherence rate was assessed from December 23, 2016, through February 15, 2017, by again screening CT pelvis reports for incidental adnexal lesions followed by manual review. The change in pre- and postintervention adherence rates was assessed using the Fisher exact test and statistical process control (SPC) p-chart with 3-sigma control limits. RESULTS. The adherence rate to recommendations at baseline was 67% (121/181). Of the 28 of 40 (70%) radiologists who completed the survey, only 29% (8/28) often or consistently used the recommendations. Not remembering the details of the recommendations or not having time to look them up accounted for 83.3% of the barriers cited by radiologists. Interventions consisted of radiologist education and creation of an easily accessible clinical decision support tool incorporated into radiology reporting workflow. The adherence rate to recommendations after the intervention increased to 87% (129/148; p < 0.0001), as also shown by the SPC chart. CONCLUSION. The rate of adherence to follow-up imaging recommendations significantly increased after radiologist education and incorporation of recommendations into the radiologist workflow.

A Computerized Method for Measuring Computed Tomography Pulmonary Angiography Yield in the Emergency Department: Validation Study

Background

Use of computed tomography pulmonary angiography (CTPA) in the assessment of pulmonary embolism (PE) has markedly increased over the past two decades. While this technology has improved the accuracy of radiological testing for PE, CTPA also carries the risk of substantial iatrogenic harm. Each CTPA carries a 14% risk of contrast-induced nephropathy and a lifetime malignancy risk that can be as high as 2.76%. The appropriate use of CTPA can be estimated by monitoring the CTPA yield, the percentage of tests positive for PE. This is the first study to propose and validate a computerized method for measuring the CTPA yield in the emergency department (ED).

Objective

The objective of our study was to assess the validity of a novel computerized method of calculating the CTPA yield in the ED.

Methods

The electronic health record databases at two tertiary care academic hospitals were queried for CTPA orders completed in the ED over 1-month periods. These visits were linked with an inpatient admission with a discharge diagnosis of PE based on the International Classification of Diseases codes. The computerized the CTPA yield was calculated as the number of CTPA orders with an associated inpatient discharge diagnosis of PE divided by the total number of orders for completed CTPA. This computerized method was then validated by 2 independent reviewers performing a manual chart review, which included reading the free-text radiology reports for each CTPA.

Results

A total of 349 CTPA orders were completed during the 1-month periods at the two institutions. Of them, acute PE was diagnosed on CTPA in 28 studies, with a CTPA yield of 7.7%. The computerized method correctly identified 27 of 28 scans positive for PE. The one discordant scan was tied to a patient who was discharged directly from the ED and, as a result, never received an inpatient discharge diagnosis.

Conclusions

This is the first successful validation study of a computerized method for calculating the CTPA yield in the ED. This method for data extraction allows for an accurate determination of the CTPA yield and is more efficient than manual chart review. With this ability, health care systems can monitor the appropriate use of CTPA and the effect of interventions to reduce overuse and decrease preventable iatrogenic harm.

Information overload: when less is more in medical imaging

In medicine, data collection and analysis provide the information needed to reduce diagnostic uncertainty. An examination of how medical imaging data is collected and then transformed into diagnostic information provides testable ideas for better managing this dynamic process. In other fields, process data is systematically assessed for differences between observed and predicted values. For studies that expose patients to the potentially harmful effects of ionizing radiation, monitoring imaging studies/illness, images/imaging study and radiation exposure/image would be steps towards developing radiation dose budgets for the diagnosis and treatment of common conditions. Random variation within the expected range would signal a high quality process. Conversely, single outlying cases or nonrandom variation within the expected range would trigger an investigation for a possible underlying cause. Such investigations would provide insights into how to continually improve this important aspect of healthcare.

Long-Term Experience With a Mandatory Clinical Decision Rule and Mandatory d-Dimer in the Evaluation of Suspected Pulmonary Embolism

PURPOSE

This study evaluated the long-term effectiveness of mandatory assignment of both a clinical decision rule (CDR) and highly sensitive d-dimer in the evaluation of patients with suspected pulmonary embolism (PE).

MATERIALS AND METHODS

Institutional guidelines with a CDR and highly sensitive d-dimer were embedded in an order entry menu with mandatory assignment of key components before ordering a CT pulmonary angiogram (CTPA). Data were retrospectively extracted from the electronic health record.

RESULTS

This was a retrospective review of 1,003 CTPA studies (905 patients, 845 male and 60 female patients, age 63.7 ± 13.5 years). CTPAs were positive for PE in 170 studies (17%), representing an average yield of 15% (year [average]; 2007 [15%], 2008 [18%], 2009 [15%], 2010 [15%], 2011 [17%], 2012 [15%], 2013 [23%]). The increased yield represented efforts of mandatory order entry assignments, educational sessions, and clinical champions. Different d-dimer thresholds with or without age adjustments in combination with the CDR identified about 10% of patients who may have been managed without CTPA.

CONCLUSION

Mandatory assignment of a CDR and highly sensitive d-dimer clinical decision pathway can be successfully incorporated into an order entry menu and produce a sustained increase in CTPA yield of patients with suspected PE.

Compliance with evidence-based guidelines for computed tomography of children with head and abdominal trauma

INTRODUCTION

Recently, two large prospective clinical trials developed and validated prediction rules for children at very low risk for clinically important traumatic brain injuries (ciTBI) or abdominal injury for whom CT is unnecessary. Specific criteria/guidelines were identified which if met would obviate the need for CT scanning. The purpose of this study was to assess compliance at a level one pediatric center with these guidelines as a tool for quality improvement.

METHODS

Records of children admitted to our pediatric trauma center one year before and two years after publication of head (Kuppermann '09) and abdominal trauma (Holmes '13) CT imaging guidelines were reviewed. Data collected included demographics, Glasgow coma score, (GCS), injury severity score (ISS), mechanism of injury, and indication for imaging based on criteria/guidelines from the prediction rule including history, symptoms, and physical exam findings.

RESULTS

There were 296 total patients identified. Demographic data, GCS, ISS, and mechanism of injury were similar between both groups before and after guideline publication. Prior to publication of head trauma imaging guidelines, 20.7% of head trauma patients had no indication for head CT prior compared with 19.5% after publication of imaging guideline (p=0.85). Prior to publication of abdominal trauma imaging guidelines, 28.9% of patients had no indication for abdominal CT compared with 31.5% after publication of imaging guidelines (0.76). The rate of ciTBI requiring intervention was 4.6% before and 1.1% after guideline publication (p=0.4). The rate of abdominal injury requiring intervention was 7.9% before and 1.8% post guideline publication (p=0.2). None of the children at very low risk for ciTBI or abdominal injury required surgical intervention.

CONCLUSION

At our institution compliance with evidence-based guidelines for CT of children with head and abdominal trauma is poor with a significant number of patients undergoing unnecessary imaging. This provides an opportunity for quality improvement with evidence based methods to reduce unnecessary imaging for trauma.

LEVEL OF EVIDENCE

III TYPE OF STUDY: Clinical Research Paper.

Interventions to Reduce the Overuse of Imaging for Pulmonary Embolism: A Systematic Review

BACKGROUND

Imaging use in the diagnostic workup of pulmonary embolism (PE) has increased markedly in the last 2 decades. Low PE prevalence and diagnostic yields suggest a significant problem of overuse.

PURPOSE

The purpose of this systematic review is to summarize the evidence associated with the interventions aimed at reducing the overuse of imaging in the diagnostic workup of PE in the emergency department and hospital wards.

DATA SOURCES

PubMed, MEDLINE, Embase, and EBM Reviews from 1998 to March 28, 2017.

STUDY SELECTION

Experimental and observational studies were included. The types of interventions, their efficacy and safety, the impact on healthcare costs, the facilitators, and barriers to their implementation were assessed.

DATA SYNTHESIS

Seventeen studies were included assessing clinical decision support (CDS), educational interventions, performance and feedback reports (PFRs), and institutional policy. CDS impact was most comprehensively documented. It was associated with a reduction in imaging use, ranging from 8.3% to 25.4%, and an increase in diagnostic yield, ranging from 3.4% to 4.4%. The combined implementation of a CDS and PFR resulted in a modest but significant increase in the adherence to guidelines. Few studies appraised the safety of interventions. There was a lack of evidence concerning economic aspects, facilitators, and barriers.

CONCLUSIONS

A combined implementation of an electronic CDS and PFRs is more effective than purely educational or policy interventions, although evidence is limited. Future studies of high-methodological quality would strengthen the evidence concerning their efficacy, safety, facilitators, and barriers.

Standard Anatomic Terminologies: Comparison for Use in a Health Information Exchange-Based Prior Computed Tomography (CT) Alerting System

Background

A health information exchange (HIE)–based prior computed tomography (CT) alerting system may reduce avoidable CT imaging by notifying ordering clinicians of prior relevant studies when a study is ordered. For maximal effectiveness, a system would alert not only for prior same CTs (exams mapped to the same code from an exam name terminology) but also for similar CTs (exams mapped to different exam name terminology codes but in the same anatomic region) and anatomically proximate CTs (exams in adjacent anatomic regions). Notification of previous same studies across an HIE requires mapping of local site CT codes to a standard terminology for exam names (such as Logical Observation Identifiers Names and Codes [LOINC]) to show that two studies with different local codes and descriptions are equivalent. Notifying of prior similar or proximate CTs requires an additional mapping of exam codes to anatomic regions, ideally coded by an anatomic terminology. Several anatomic terminologies exist, but no prior studies have evaluated how well they would support an alerting use case.

Objective

The aim of this study was to evaluate the fitness of five existing standard anatomic terminologies to support similar or proximate alerts of an HIE-based prior CT alerting system.

Methods

We compared five standard anatomic terminologies (Foundational Model of Anatomy, Systematized Nomenclature of Medicine Clinical Terms, RadLex, LOINC, and LOINC/Radiological Society of North America [RSNA] Radiology Playbook) to an anatomic framework created specifically for our use case (Simple ANatomic Ontology for Proximity or Similarity [SANOPS]), to determine whether the existing terminologies could support our use case without modification. On the basis of an assessment of optimal terminology features for our purpose, we developed an ordinal anatomic terminology utility classification. We mapped samples of 100 random and the 100 most frequent LOINC CT codes to anatomic regions in each terminology, assigned utility classes for each mapping, and statistically compared each terminology’s utility class rankings. We also constructed seven hypothetical alerting scenarios to illustrate the terminologies’ differences.

Results

Both RadLex and the LOINC/RSNA Radiology Playbook anatomic terminologies ranked significantly better (P<.001) than the other standard terminologies for the 100 most frequent CTs, but no terminology ranked significantly better than any other for 100 random CTs. Hypothetical scenarios illustrated instances where no standard terminology would support appropriate proximate or similar alerts, without modification.

Conclusions

LOINC/RSNA Radiology Playbook and RadLex’s anatomic terminologies appear well suited to support proximate or similar alerts for commonly ordered CTs, but for less commonly ordered tests, modification of the existing terminologies with concepts and relations from SANOPS would likely be required. Our findings suggest SANOPS may serve as a framework for enhancing anatomic terminologies in support of other similar use cases.

Clinical decision support increases diagnostic yield of computed tomography for suspected pulmonary embolism

OBJECTIVE

Determine effects of evidence-based clinical decision support (CDS) on the use and yield of computed tomographic pulmonary angiography for suspected pulmonary embolism (CTPE) in Emergency Department (ED) patients.

METHODS

This multi-site prospective quality improvement intervention conducted in three urban EDs used a pre/post design. For ED patients aged 18+years with suspected PE, CTPE use and yield were compared 19months pre- and 32months post-implementation of CDS intervention based on the Wells criteria, provided at the time of CTPE order, deployed in April 2012. Primary outcome was the yield (percentage of studies positive for acute PE). Secondary outcome was utilization (number of studies/100 ED visits) of CTPE. Chi-square and statistical process control chart assessed pre- and post-intervention differences. An interrupted time series analysis was also performed.

RESULTS

Of 558,795 patients presenting October 2010-December 2014, 7987 (1.4%) underwent CTPE (mean age 52±17.5years, 66% female, 60.1% black); 34.7% of patients presented pre- and 65.3% post-CDS implementation. Overall CTPE diagnostic yield was 9.8% (779/7987 studies positive for PE). Yield increased a relative 30.8% after CDS implementation (8.1% vs. 10.6%; p=0.0003). There was no statistically significant change in CTPE utilization (1.4% pre- vs. 1.4% post-implementation; p=0.25). A statistical process control chart demonstrated immediate and sustained improvement in CTPE yield post-implementation. Interrupted time series analysis demonstrated the slope of PE findings versus time to be unchanged before and after the intervention (p=0.9). However, there was a trend that the intervention was associated with a 50% increased probability of PE finding (p=0.08), suggesting an immediate rather than gradual change after the intervention.

CONCLUSIONS

Implementing evidence-based CDS in the ED was associated with an immediate, significant and sustained increase in CTPE yield without a measurable decrease in CTPE utilization. Further studies will be needed to assess whether stronger interventions could further improve appropriate use of CTPE.

Medicare Imaging Demonstration: Assessing Attributes of Appropriate Use Criteria and Their Influence on Ordering Behavior

OBJECTIVE

Persistent concern exists about the variable and possibly inappropriate utilization of high-cost imaging tests. The purpose of this study is to assess the influence of appropriate use criteria attributes on altering ambulatory imaging orders deemed inappropriate.

MATERIALS AND METHODS

This secondary analysis included Medicare Imaging Demonstration data collected from three health care systems in 2011-2013 via the use of clinical decision support (CDS) during ambulatory imaging order entry. The CDS system captured whether orders were inappropriate per the appropriate use criteria of professional societies and provided advice during the intervention period. For orders deemed inappropriate, we assessed the impact of the availability of alternative test recommendations, conflicts with local best practices, and the strength of evidence for appropriate use criteria on the primary outcome of cancellation or modification of inappropriate orders. Expert review determined conflicts with local best practices for 250 recommendations for abdominal and thoracic CT orders. Strength of evidence was assessed for the 15 most commonly triggered recommendations that were deemed inappropriate. A chi-square test was used for univariate analysis.

RESULTS

A total of 1691 of 63,222 imaging test orders (2.7%) were deemed inappropriate during the intervention period; this amount decreased from 364 of 11,675 test orders (3.1%) in the baseline period (p < 0.00001). Of 270 inappropriate recommendations with alternative test recommendations, 28 (10.4%) were modified, compared with four of 1024 inappropriate recommendations without alternatives (0.4%) (p < 0.0001). Seventy-eight of 250 recommendations (31%) conflicted with local best practices, but only six of 69 inappropriate recommendations (9%) conflicted (p < 0.001). No inappropriate recommendations that conflicted with local best practices were modified. All 15 commonly triggered recommendations had an Oxford Centre for Evidence-Based Medicine level of evidence of 5 (i.e., expert opinion).

CONCLUSION

Orders for imaging tests that were deemed inappropriate were modified infrequently, more often with alternative recommendations present and only for appropriate use criteria consistent with local best practices.

Creation of a simple natural language processing tool to support an imaging utilization quality dashboard

BACKGROUND

Testing for venous thromboembolism (VTE) is associated with cost and risk to patients (e.g. radiation). To assess the appropriateness of imaging utilization at the provider level, it is important to know that provider's diagnostic yield (percentage of tests positive for the diagnostic entity of interest). However, determining diagnostic yield typically requires either time-consuming, manual review of radiology reports or the use of complex and/or proprietary natural language processing software.

OBJECTIVES

The objectives of this study were twofold: 1) to develop and implement a simple, user-configurable, and open-source natural language processing tool to classify radiology reports with high accuracy and 2) to use the results of the tool to design a provider-specific VTE imaging dashboard, consisting of both utilization rate and diagnostic yield.

METHODS

Two physicians reviewed a training set of 400 lower extremity ultrasound (UTZ) and computed tomography pulmonary angiogram (CTPA) reports to understand the language used in VTE-positive and VTE-negative reports. The insights from this review informed the arguments to the five modifiable parameters of the NLP tool. A validation set of 2,000 studies was then independently classified by the reviewers and by the tool; the classifications were compared and the performance of the tool was calculated.

RESULTS

The tool was highly accurate in classifying the presence and absence of VTE for both the UTZ (sensitivity 95.7%; 95% CI 91.5-99.8, specificity 100%; 95% CI 100-100) and CTPA reports (sensitivity 97.1%; 95% CI 94.3-99.9, specificity 98.6%; 95% CI 97.8-99.4). The diagnostic yield was then calculated at the individual provider level and the imaging dashboard was created.

CONCLUSIONS

We have created a novel NLP tool designed for users without a background in computer programming, which has been used to classify venous thromboembolism reports with a high degree of accuracy. The tool is open-source and available for download at http://iturrate.com/simpleNLP. Results obtained using this tool can be applied to enhance quality by presenting information about utilization and yield to providers via an imaging dashboard.

Evidence-Based Cancer Imaging

With the advances in the field of oncology, imaging is increasingly used in the follow-up of cancer patients, leading to concerns about over-utilization. Therefore, it has become imperative to make imaging more evidence-based, efficient, cost-effective and equitable. This review explores the strategies and tools to make diagnostic imaging more evidence-based, mainly in the context of follow-up of cancer patients.

JOURNAL CLUB: Predictors of Provider Response to Clinical Decision Support: Lessons Learned From the Medicare Imaging Demonstration

OBJECTIVE

The efficacy of imaging clinical decision support (CDS) varies. Our objective was to identify CDS factors contributing to imaging order cancellation or modification.

SUBJECTS AND METHODS

This pre-post study was performed across four institutions participating in the Medicare Imaging Demonstration. The intervention was CDS at order entry for selected outpatient imaging procedures. On the basis of the information entered, computerized alerts indicated to providers whether orders were not covered by guidelines, appropriate, of uncertain appropriateness, or inappropriate according to professional society guidelines. Ordering providers could override or accept CDS. We considered actionable alerts to be those that could generate an immediate order behavior change in the ordering physician (i.e., cancellation of inappropriate orders or modification of orders of uncertain appropriateness that had a recommended alternative). Chi-square and logistic regression identified predictors of order cancellation or modification after an alert.

RESULTS

A total of 98,894 radiology orders were entered (83,114 after the intervention). Providers ignored 98.9%, modified 1.1%, and cancelled 0.03% of orders in response to alerts. Actionable alerts had a 10 fold higher rate of modification (8.1% vs 0.7%; p < 0.0001) or cancellation (0.2% vs 0.02%; p < 0.0001) orders compared with nonactionable alerts. Orders from institutions with preexisting imaging CDS had a sevenfold lower rate of cancellation or modification than was seen at sites with newly implemented CDS (1.4% vs 0.2%; p < 0.0001). In multivariate analysis, actionable alerts were 12 times more likely to result in order cancellation or modification. Orders at sites with preexisting CDS were 7.7 times less likely to be cancelled or modified (p < 0.0001).

CONCLUSION

Using results from the Medicare Imaging Demonstration project, we identified potential factors that were associated with CDS effect on provider imaging ordering; these findings may have implications for future design of such computerized systems.

Natural Language Processing Technologies in Radiology Research and Clinical Applications

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively "mine" these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. "Intelligent" search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications.

Yield of CT Pulmonary Angiography in the Emergency Department When Providers Override Evidence-based Clinical Decision Support

Purpose To determine the frequency of, and yield after, provider overrides of evidence-based clinical decision support (CDS) for ordering computed tomographic (CT) pulmonary angiography in the emergency department (ED). Materials and Methods This HIPAA-compliant, institutional review board-approved study was performed at a tertiary care, academic medical center ED with approximately 60 000 annual visits and included all patients who were suspected of having pulmonary embolism (PE) and who underwent CT pulmonary angiography between January 1, 2011, and August 31, 2013. The requirement to obtain informed consent was waived. Each CT order for pulmonary angiography was exposed to CDS on the basis of the Wells criteria. For patients with a Wells score of 4 or less, CDS alerts suggested d-dimer testing because acute PE is highly unlikely in these patients if d-dimer levels are normal. The yield of CT pulmonary angiography (number of positive PE diagnoses/total number of CT pulmonary angiographic examinations) was compared in patients in whom providers overrode CDS alerts (by performing CT pulmonary angiography in patients with a Wells score ≤4 and a normal d-dimer level or no d-dimer testing) (override group) and those in whom providers followed Wells criteria (CT pulmonary angiography only in patients with Wells score >4 or ≤4 with elevated d-dimer level) (adherent group). A validated natural language processing tool identified positive PE diagnoses, with subsegmental and/or indeterminate diagnoses removed by means of chart review. Statistical analysis was performed with the χ² test, the Student t test, and logistic regression. Results Among 2993 CT pulmonary angiography studies in 2655 patients, 563 examinations had a Wells score of 4 or less but did not undergo d-dimer testing and 26 had a Wells score of 4 or less and had normal d-dimer levels. The yield of CT pulmonary angiography was 4.2% in the override group (25 of 589 studies, none with a normal d-dimer level) and 11.2% in the adherent group (270 of 2404 studies) (P < .001). After adjustment for the risk factor differences between the two groups, the odds of an acute PE finding were 51.3% lower when providers overrode alerts than when they followed CDS guidelines. Comparison of the two groups including only patients unlikely to have PE led to similar results. Conclusion The odds of an acute PE finding in the ED when providers adhered to evidence presented in CDS were nearly double those seen when providers overrode CDS alerts. Most overrides were due to the lack of d-dimer testing in patients unlikely to have PE. ^© RSNA, 2016.

Outcomes after inappropriate nuclear myocardial perfusion imaging: A meta-analysis

BACKGROUND

The relationship between inappropriate MPI and cardiovascular outcomes is poorly understood. We sought to systematically review the literature on appropriate use criteria (AUC) for MPI, including temporal trend of inappropriate testing and resulting cardiovascular outcomes.

METHODS

We searched the MEDLINE database for studies related to AUC and MPI. The co-primary outcomes were abnormal test results and the presence of cardiac ischemia. Random effects odds ratios (OR) were constructed using DerSimonian-Laird method.

RESULTS

A total of 22 studies with 23,443 patients were included. The prevalence of inappropriate testing was 14.8% [95% confidence interval (CI) 11.6%-18.7%]. Inappropriate MPI studies were less likely to be abnormal (OR 0.41 95% CI 0.35-0.49, P < .0001) and to demonstrate ischemia (OR 0.40, 95% CI 0.24-0.67, P < .0001) compared to appropriate testing. No difference in the rate of inappropriate tests was detected based on the midpoint of the enrollment year (P = .54). The pattern of ordering inappropriate studies was not different between cardiology and non-cardiology providers (OR 0.74, 95% CI 0.51-1.06, P = .10).

CONCLUSION

Inappropriate MPI studies are less likely to yield abnormal results or demonstrate myocardial ischemia. The rate of inappropriate MPI has not decreased over time.

Neuroimaging Wisely

Diagnostic imaging is the most rapidly growing physician service in the Medicare and privately insured population. The growing share of medical costs devoted to imaging procedures has led to increasing concerns among the key federal agencies and private payers. In an attempt to educate health care providers, patients, and families on the importance of making optimal clinical decisions, the American Board of Internal Medicine Foundation organized the Choosing Wisely initiative with strong collaboration from specialty societies representing nearly all medical disciplines. Among 45 tests and treatments listed on the Choosing Wisely Web site, 24 are directly related to imaging. Eleven of the 24 are associated with neuroimaging. The listing of imaging tests in the Choosing Wisely program by multiple medical societies other than the radiology societies acknowledges that appropriate use of medical imaging is a shared responsibility between radiologists and referring physicians. In this article, we highlight why radiologists are uniquely positioned to support the appropriate use of imaging. We review some of the strategies that radiologists can use to help their referring physicians with appropriate ordering of neuroimaging in real-world practice and address some the challenges and pitfalls in implementing patient-centered imaging decision-making and shifting to a value-based focus in radiology.

Limited Hospital Variation in the Use and Yield of CT for Pulmonary Embolism in Patients Undergoing Total Hip or Total Knee Replacement Surgery

Purpose To evaluate the variation among U.S. hospitals in overall use and yield of in-hospital computed tomographic (CT) pulmonary angiography (PA) in patients undergoing total hip replacement (THR) or total knee replacement (TKR) surgery. Materials and Methods Patients in the Premier Research Database who underwent elective TKR or THR between 2007 and 2011 were enrolled in this HIPAA-compliant, institutional review board-approved retrospective observational study. The informed consent requirement was waived. Hospitals were categorized into low, medium, and high tertiles of CT PA use to compare baseline patient- and hospital-level characteristics and pulmonary embolism (PE) positivity rates. To further investigate between-hospital variation in CT PA use, a hierarchical logistic regression model that included hospital-specific random effects and fixed patient- and hospital-level effects was used. The intraclass correlation coefficient (ICC) was used to measure the amount of variability in CT PA use attributable to between-hospital variation. Results The cohort included 205 198 patients discharged from 178 hospitals (median of 734.5 patients discharged per hospital; interquartile range, 316-1461 patients) with 3647 CT PA studies (1.8%). The crude frequency of CT PA scans among the hospitals ranged from 0% to 6.2% (median, 1.6%); more than 90% of the hospitals performed CT PA in less than 3% of their patients. The mean hospital-level PE positivity rate was 12.3% (median, 9.1%); there was no significant difference in PE positivity rate across low through high CT PA use tertiles (11.3%, 11.9%, 12.9%, P = .37). After adjustment for hospital- and patient-level factors, the remaining amount of interhospital variation was relatively low (ICC, 9.0%). Conclusion Limited interhospital variation in use and yield of in-hospital CT PA was observed among patients undergoing TKR or THR in the United States. ^© RSNA, 2016 Online supplemental material is available for this article.

The actionable imaging report

The goal of a diagnostic imaging examination is to provide the referring provider with an actionable imaging report that can be used to impart information to determine optimal clinical management for the patient. An actionable imaging report not only conveys the findings of the examination accurately, but does so in a timely and safe manner for an imaging examination that was performed appropriately and using the correct technique. The use of information technology tools has been paramount in improving the value of the imaging report and continues to play a prominent role in this process. The diversity of abdominal imaging, in both the variety of imaging modalities available and the organ systems evaluated, makes it well-suited to adopt these information technology solutions to improve report quality, including increased consistency in reports and in follow-up recommendations. This review discusses the components of the imaging chain involved in optimizing the imaging report with specific emphasis on the role of information technology applications to address the challenges that are frequently encountered. Specific abdominal imaging examples are presented to provide practical guidance and clinical context.

JOURNAL CLUB: Radiologists' Perceptions of Computerized Decision Support: A Focus Group Study From the Medicare Imaging Demonstration Project

OBJECTIVE

The purpose of this study was to discern radiologists' perceptions regarding the implementation of a decision support system intervention as part of the Medicare Imaging Demonstration project and the effect of decision support on radiologists' interactions with ordering clinicians, their radiology work flow, and appropriateness of advanced imaging.

SUBJECTS AND METHODS

A focus group study was conducted with a diverse sample of radiologists involved in interpreting advanced imaging studies at Medicare Imaging Demonstration project sites. A semistructured moderator guide was used, and all focus group discussions were recorded and transcribed verbatim. Qualitative data analysis software was used to code thematic content and identify representative segments of text. Participating radiologists also completed an accompanying survey designed to supplement focus group discussions.

RESULTS

Twenty-six radiologists participated in four focus group discussions. The following major themes related to the radiologists' perceptions after decision support implementation were identified: no substantial change in radiologists' interactions with referring clinicians; no substantial change in radiologist work flow, including protocol-writing time; and no perceived increase in imaging appropriateness. Radiologists provided suggestions for improvements in the decision support system, including increasing the usability of clinical data captured, and expressed a desire to have greater involvement in future development and implementation efforts.

CONCLUSION

Overall, radiologists from health care systems involved in the Medicare Imaging Demonstration did not perceive that decision support had a substantial effect, either positive or negative, on their professional roles and responsibilities. Radiologists expressed a desire to improve efficiencies and quality of care by having greater involvement in future efforts.