Assessment of a Large-Scale Peer Learning Program's Value by Manual Review of Case Submissions.

OBJECTIVE: Prior studies used submission numbers or report addendum rates to measure peer learning programs' (PLP) impact. We assessed the educational value of a PLP by manually reviewing cases submitted to identify factors correlating with meaningful learning opportunities (MLOs). METHODS: This institutional review board-exempted, retrospective study was performed in a large academic radiology department generating >800,000 reports annually. A PLP facilitating radiologist-to-radiologist feedback was implemented May 1, 2017, with subsequent pay-for-performance initiatives encouraging increasing submissions, >18,000 by 2019. Two radiologists blinded to submitter and receiver identity categorized 336 randomly selected submissions as a MLO, not meaningful, or equivocal, resolving disagreements in consensus review. Primary outcome was proportion of MLOs. Secondary outcomes included percent engagement by subspecialty clinical division and comparing MLO and report addendum rates via Fisher's exact tests. We assessed association between peer learning category, pay-for-performance interventions, and subspecialty division with MLOs using logistic regression. RESULTS: Of 336 PLP submissions, 65.2% (219 of 336) were categorized as meaningful, 27.4% (92 of 336) not meaningful, and 7.4% (25 of 336) equivocal, with substantial reviewer agreement (86.0% [289 of 336], κ = 0.71, 95% confidence interval 0.64-0.78). MLO rate (65.2% [219 of 336]) was five times higher than addendum rate (12.9% [43 of 333]) for the cohort. MLO proportion (adjusted odds ratios 0.05-1.09) and percent engagement (0.5%-3.6%) varied between subspecialty divisions, some submitting significantly fewer MLOs (P < .01). MLO proportion did not vary between peer learning categories. CONCLUSION: Educational value of a large-scale PLP, estimated through manual review of case submissions, is likely a more accurate measure of program impact. Incentives to enhance PLP use did not diminish the program's educational value.

Peer Learning in Radiology: Effect of a Pay-for-Performance Initiative on Clinical Impact and Usage.

OBJECTIVE. The purpose of this article is to assess the effects of a pay-for-performance (PFP) initiative on clinical impact and usage of a radiology peer learning tool. MATERIALS AND METHODS. This retrospective study was performed at a large academic hospital. On May 1, 2017, a peer learning tool was implemented to facilitate radiologist peer feedback including clinical follow-up, positive feedback, and consultation. Subsequently, PFP target numbers for peer learning tool alerts by subspecialty divisions (October 1, 2017) and individual radiologists (October 1, 2018) were set. The primary outcome was report addendum rate (percent of clinical follow-up alerts with addenda), which was a proxy for peer learning tool clinical impact. Secondary outcomes were peer learning tool usage rate (number of peer learning tool alerts per 1000 radiology reports) and proportion of clinical follow-up alerts (percent of clinical follow-ups among all peer learning tool alerts). Outcomes were assessed biweekly using ANOVA and statistical process control analyses. RESULTS. Among 1,265,839 radiology reports from May 1, 2017, to September 29, 2019, a total of 20,902 peer learning tool alerts were generated. The clinical follow-up alert addendum rate was not significantly different between the period before the PFP initiative (9.9%) and the periods including division-wide (8.3%) and individual (7.9%) PFP initiatives (p = .55; ANOVA). Peer learning tool usage increased from 2.2 alerts per 1000 reports before the PFP initiative to 12.6 per 1000 during the division-wide PFP period (5.7-fold increase; 12.6/2.2), to 25.2 in the individual PFP period (11.5-fold increase vs before PFP; twofold increase vs division-wide) (p < .001). The clinical follow-up alert proportion decreased from 37.5% before the PFP initiative, to 34.4% in the division-wide period, to 31.3% in the individual PFP period. CONCLUSION. A PFP initiative improved radiologist engagement in peer learning by marked increase in peer learning tool usage rate without a change in report addendum rate as a proxy for clinical impact.

Radiology Patient Outcome Measures: Impact of a Departmental Pay-for-Performance Initiative on Key Quality and Safety Measures.

OBJECTIVE: Assess impact of a multifaceted pay-for-performance (PFP) initiative on radiologists' behavior regarding key quality and safety measures. METHODS: This institutional review board-approved prospective study was performed at a large, 12-division urban academic radiology department. Radiology patient outcome measures were implemented October 1, 2017, measuring report signature timeliness, critical results communication, and generation of peer-learning communications between radiologists. Subspecialty division-wide and individual radiologist targets were specified, performance was transparently communicated on an intranet dashboard updated daily, and performance was financially incentivized (5% of salary) quarterly. We compared outcomes 12 months pre- versus 12 months post-PFP implementation. Primary outcome was monthly 90th percentile time from scan completion to final report signature (CtoF). Secondary outcomes were percentage timely closed-loop communication of critical results and number of division-wide peer-learning communications. Statistical process control analysis and parallel coordinates charts were used to assess for temporal trends. RESULTS: In all, 144 radiologists generated 1,255,771 reports (613,273 pre-PFP) during the study period. Monthly 90th percentile CtoF exhibited an absolute decrease of 4.4 hours (from 21.1 to 16.7 hours) and a 20.9% relative decrease post-PFP. Statistical process control analysis demonstrated significant decreases in 90th percentile CtoF post-PFP, sustained throughout the study period (P < .003). Between 95% (119 of 125, July 1, 2018, to September 30, 2018) and 98.4% (126 of 128, October 1, 2017, to December 31, 2017) of radiologists achieved >90% timely closure of critical alerts; all divisions exceeded the target of 90 peer-learning communications each quarter (range: 97-472) after January 1, 2018. DISCUSSION: Implementation of a multifaceted PFP initiative using well-defined radiology patient outcome measures correlated with measurable improvements in radiologist behavior regarding key quality and safety parameters.

Radiologists' Self-Assessment Versus Peer Assessment of Perceived Probability of Recommending Additional Imaging.

OBJECTIVE: Determine radiologist ability to accurately select the probability of recommendation of additional imaging (RAI) for themselves and colleagues when arrayed in a feedback report. METHODS: In this institutional review board-approved study, we analyzed 318,366 diagnostic imaging reports from examinations performed in the radiology department of a large quaternary teaching hospital during calendar year 2016. A validated machine learning algorithm identified reports containing RAI. A multivariable logistic regression model was then used to determine the probability of RAI. In 2018, an e-mailed survey asked radiologists to identify their own RAI probability and that of their colleagues from a report arrayed lowest to highest. Radiologists were grouped into quartiles based on their RAI probability. χ2 Analysis compared self-assessment and assessment of colleagues between quartiles. RESULTS: Forty-eight of 57 radiologists completed the survey (84.2%). Fourteen (29.2%) accurately self-identified their RAI probability (chose the correct quartile); 34 (70.8%) did not. There was no statistically significant difference between quartiles of radiologists and their ability to self-identify their RAI probability (ie, radiologists in the bottom or top quartile of RAI probabilities did not correctly predict their RAI probability). However, radiologists were better able to identify the RAI probability of their colleagues who were in the top and bottom quartiles. DISCUSSION: Radiologists were unable to estimate their own RAI probability but were better at predicting the RAI probability of colleagues. Given that radiologists, and physicians in general, may be poor evaluators of their own performance, objective assessment tools are likely needed to help reduce unwarranted variation.

Report of the ACR's Economics Committee on Value-Based Payment Models.

A major outcome of the current health care reform process is the move away from unrestricted fee-for-service payment models toward those that are based on the delivery of better patient value and outcomes. The authors' purpose, therefore, is to critically evaluate and define those components of the overall imaging enterprise that deliver meaningful value to both patients and referrers and to determine how these components might be measured and quantified. These metrics might then be used to lobby providers and payers for sustainable payment solutions for radiologists and radiology services. The authors evaluated radiology operations and services using the framework of the imaging value chain, which divides radiology service into a number of discrete value-added activities, which ultimately deliver the primary product, most often the actionable report for diagnostic imaging or an effective outcome for interventional radiology. These value activities include scheduling and imaging appropriateness and stewardship, patient preparation, protocol design, modality operations, reporting, report communication, and clinical follow-up (eg, mammography reminder letters). Two further categories are hospital or health care organization citizenship and examination outcome. Each is discussed in turn, with specific activities highlighted.

Academic Medical Centers and Community Hospitals Integration: Trends and Strategies.

Academic medical centers are widely recognized as vital components of the American health care system, generally differentiated from their community hospital peers by their tripartite mission of clinical care, education, and research. Community hospitals fill a critical and complementary role, serving as the primary sites for health care in most communities. Health care reform initiatives and economic pressures have created incentives for hospitals and health systems to integrate, resulting in a nationwide trend toward consolidation with academic medical centers leveraging their substantial assets to merge, acquire, or establish partnerships with their community peers. As these alliances accelerate, they have and will continue to affect the radiology groups providing services at these institutions. A deeper understanding of these new marketplace dynamics, changing relationships and potential strategies will help both academic and private practice radiologists adapt to this ongoing change.

Radiology Malpractice Claims in the United States From 2008 to 2012: Characteristics and Implications.

PURPOSE: The aim of this study was to compare the frequency and liability costs associated with radiology malpractice claims relative to other medical services and to evaluate the clinical context and case disposition associated with radiology malpractice claims. METHODS: This HIPAA-compliant study was exempted from institutional review board approval. The Comparative Benchmarking System database, a repository of more than 300,000 medical malpractice cases in the United States, was queried for closed claims over a five-year period (2008-2012). Claims were categorized by the medical service primarily responsible for the claim and the paid total loss. For all cases in which radiology was the primary responsible service, the case abstracts were evaluated to determine injury severity, claimant type by setting, claim allegation, process of care involved, case disposition, modality involved, and body section. Intracategory comparisons were made on the basis of the frequency of indemnity payment and total indemnity payment for paid cases, using χ(2) and Wilcoxon rank-sum tests. RESULTS: Radiology was the eighth most likely responsible service to be implicated in a medical malpractice claim, with a median total paid loss (indemnity payment plus defense cost plus administrative expense) per closed case of $30,091 (mean, $205,619 ± $508,883). Radiology claims were most commonly associated with high- and medium-severity injuries (93.3% [820 of 879]; 95% confidence interval [CI], 91.7%-94.95%), the outpatient setting (66.3% [581 of 876]; 95% CI, 63.0%-69.2%), and diagnosis-related allegations (ie, failure to diagnose or delayed diagnosis) (57.3% [504 of 879]; 95% CI, 54.0%-60.6%). A high proportion of claims pertained to cancer diagnoses (44.0% [222 of 504]; 95% CI, 39.7%-48.3%). A total of 62.3% (548 of 879; 95% CI, 59.1%-65.5%) of radiology claims were closed without indemnity payments; 37.7% (331 of 879; 95% CI, 34.5%-40.9%) were closed with a median indemnity payment of $175,000 (range, $112-$6,691,762; mean $481,094 ± $727,636). CONCLUSIONS: Radiology malpractice claims most commonly involve diagnosis-related allegations in the outpatient setting, particularly cancer diagnoses, with approximately one-third of claims resulting in payouts to the claimants.

ACR white paper on teleradiology practice: a report from the Task Force on Teleradiology Practice.

Teleradiology services are now embedded into the workflow of many radiology practices in the United States, driven largely by an expanding corporate model of services. This has brought opportunities and challenges to both providers and recipients of teleradiology services and has heightened the need to create best-practice guidelines for teleradiology to ensure patient primacy. To this end, the ACR Task Force on Teleradiology Practice has created this white paper to update the prior ACR communication on teleradiology and discuss the current and possible future state of teleradiology in the United States. This white paper proposes comprehensive best-practice guidelines for the practice of teleradiology, with recommendations offered regarding future actions.

Radiologist report turnaround time: impact of pay-for-performance measures.

OBJECTIVE: Expedited finalized radiologist report turnaround times (RTAT) are considered an important quality care metric in medicine. This study was performed to evaluate the impact of a radiologist pay-for-performance (PFP) program on reducing RTAT. MATERIALS AND METHODS: A radiologist PFP program was used to assess its impact on RTAT for all departmental reports from 11 subspecialty divisions. Study periods were 3 months before (baseline period) and immediately after (immediate period) the introduction of the program and 2 years later after the program had terminated (post period). Three RTAT components were evaluated for individual radiologists and for each radiology division: examination completion (C) to final signature (F), C to preliminary signature (P), and P to F. RESULTS: Eighty-one radiologists met the inclusion criterion for the study and performed a final signature on 99,959 reports during the baseline period, 104,673 reports during the immediate period, and 91,379 reports during the post period. Mean C-F, C-P, and P-F for all reports decreased significantly from baseline to immediate to post period (p < 0.0001), with the largest effect on the P-F component. Similarly, divisional C-F, C-P, and P-F also significantly decreased (p < 0.0001) for all divisions except the C-F for nuclear and neurovascular radiology from baseline to immediate period and the C-P component from baseline to post period for cardiac radiology. CONCLUSION: A radiologist PFP program appears to have a marked effect on expediting final report turnaround times, which continues after its termination.

ACR White Paper: Task Force to Evaluate the Value Add Impact on Business Models.

Radiology practices are seeing both evolutionary and revolutionary changes in their business models. The Task Force to Evaluate the Value Add Impact on Business Models was charged with considering how radiologists and their practices add value in these novel settings. Both traditional and novel forms of added value were considered. Types of new business models that were evaluated included hybrid groups of radiologists and other practitioners, regional or national megagroups, and novel services both within and beyond the traditional purview of radiology practice. Recommendations for both how to measure and how to capture this value were considered at both the practice and national levels.

The evolving radiology landscape: the importance of effective leadership.

Advances in technology and imaging techniques have propelled radiology into the centre of diagnostic and therapeutic medicine. However, all this success has come at a price, with radiology departments persistently struggling to keep up with increasing demand. In response, radiologists in many countries are giving up an increasing proportion of their traditional workload, often driven by teleradiology, causing them to become less visible within their organizations. As such, radiologists now risk being viewed as commodities by their peers. The failure to meet the increasing stakeholder expectations is, at least in part, due to lack of radiology leadership. While the drivers for the radiology profession and the organizational structures for radiologists vary from country to country, this article will discuss the characteristics of good leadership and how these can be used to ensure radiologists remain centre stage in the provision of high-quality clinical care in any healthcare environment.

Maximizing outpatient computed tomography productivity using multiple technologists.

PURPOSE: A key radiology stakeholder demand is to increase patient access to computed tomography (CT) and reduce waiting lists. However, the number of patients that a single technologist can scan is limited because of the many tasks required to process a patient through a CT scan. However, many tasks could be performed simultaneously by using additional personnel. This study evaluated how many additional patients can be scanned using a 2- or 3-technologist model with outpatient multidetector CT and its impact on CT capacity. METHODS: The number and type of individual technologist tasks were initially evaluated. The time to perform these tasks was then measured using 1-, 2-, and 3-technologist models, including the time a patient was within the CT scanner room, to determine the hourly patient throughput on a CT scanner. Two theoretic CT operations were then developed to evaluate the impact on CT capacity. RESULTS: Thirty-four technologist workflow tasks were identified. A total of 205 outpatients were evaluated. The total time to perform all tasks for 1-, 2-, and 3-technologist models was 27, 23, and 22 minutes, respectively. CT room time per patient for 1-, 2-, and 3-technologist models was 12, 9.7, and 8.0 minutes, respectively. However, the number of patients scanned per hour for 1-, 2-, and 3-technologist models was 2.2, 5.2, and 7.5, respectively. There was an increase of more than 12,000 potential patient CT slots made available using 2 technologists 7 days per week and 22,000 additional slots for a 3-technologist model when compared with a single-technologist model on weekdays only. CONCLUSION: A single-technologist model for outpatient multidetector CT is inefficient with limited opportunity for increased patient throughput. The use of multiple technologists (or other key personnel) optimizes CT throughput and capacity, particularly with a 3-technologist model, which can yield a greater than three-fold increase in CT productivity.