| Radiology Digest: News from the week of March 28, 2023. |
| Here Are the 20 Highest Paid Specialties in 2022 as Average Physician Pay Drops 2.4%: Doximity By Heather Landi | March 23, 2023 | Included in Radiology Digest – March 28, 2023 Physicians are facing the same economic and compensation pressures as the broader workforce with inflation putting a squeeze on doctors’ real income. Average physician pay fell by 2.4% from 2021 to 2022, and that decline in physician compensation comes at a time when U.S. healthcare workers are facing significant challenges, including economic strains, a growing physician shortage issue and high rates of work-related burnout, according to the sixth annual Physician Compensation Report from professional medical network Doximity. The average pay for doctors increased by 3.8% from 2020 to 2021, which was up from a nominal increase of 1.5% in 2020. This year’s study was based on self-reported compensation data from 31,000 full-time U.S. physicians. Doximity claims it is also the largest study to provide six years of year-over-year trends data, gathered from surveys of over 190,000 physicians, nurse practitioners and physician assistants from 2017 to 2022. In 2023, physicians will also experience a 2% Medicare payment cut after two decades of flat payments. Many doctors experienced a decline in real income as inflation ran rampant. Inflation reached a 40-year high of 9.1% in June, as measured by the Consumer Price Index. According to the American Medical Association, when adjusted for inflation, Medicare physician payment declined 22% from 2001 to 2021. These economic and financial pressures also are impacting physicians’ job satisfaction, according to Amit Phull, M.D., Doximity’s medical director and senior vice president of strategy. To read more, go to Fierce Healthcare. |
CMS Fully Resumes Dispute Resolutions Under No Surprises Act Following Pressure From Radiologists By Marty Stempniak | March 22, 2023 | Included in Radiology Digest – March 28, 2023 CMS has resumed the process, spelled out in the No Surprises Act, for resolving out-of-network payment disputes between providers and insurers, a move praised by radiologists and other docs. The federal government had partially halted this key activity in February in response to a Texas judge’s order, decreeing that portions of the framework violate federal rules. Physician groups including the American College of Radiology have since pressured the feds to resume this process and address a growing stack of unresolved cases, and CMS has now obliged. With the March 17 relaunch, the agency has revised its guidance for independent dispute resolution, taking into account the Feb. 6 court order. This includes stipulating that arbiters must take into account all evidence presented by both parties, and not weigh the “qualifying payment amount” more heavily. “At last, the guidance seems to closely reflect what the No Surprises Act statute actually says,” the American College of Emergency Physicians, which has pushed for the resumption alongside the ACR, said in an announcement. “This is a major advancement in ACEP’s advocacy push to make the arbitration process more fair and balanced … Hopefully now since the IDR process is reopened, arbiters can start working through the significant backlog.” CMS previously instructed arbiters to resume dispute resolutions at the end of February. But that applied only to services furnished before Oct. 25, which were not impacted by the Texas judge’s order. ACR, ACEP and the American Society of Anesthesiologists sent a letter to the Center for Consumer Information and Insurance Oversight last month, urging officials to address cases that have accumulated since October. “The letter stated that delays in payment determinations were exacerbating the existing IDR backlogs and harming members’ practices by holding up payments for services provided to patients,” ACR said in a Tuesday, March 21, news update announcing the resumption. To read more, go to Radiology Business. |
Healthcare Has Yet to Feel Full Impact of Physician Retirements By Jacqueline LaPointe | March 22, 2023 | Included in Radiology Digest – March 28, 2023 Healthcare organizations need to prepare for a wave of physician retirements, according to a new survey from the physician, physician leader, and advanced practice provider recruitment firm Jackson Physician Search. The firm polled nearly 400 physicians and 60 healthcare administrators to understand their views on physician retirement and readiness. The survey showed that 62 percent of physicians have not changed their retirement plans because of the economy, including recent inflation, stock market volatility, and recession fears. Additionally, of the physicians delaying retirement because of the economy, most plan (27 percent) to postpone retirement by one to four years. COVID-19 is also still a factor when it comes to physician retirement. In a 2021 survey, more than half of physicians said the virus had changed their employment plans, with one in five of those respondents seriously considering early retirement. Of the 24 percent of physicians in this year’s survey who plan to retire early because of COVID-19, the majority (60 percent) still expect to do so. Overall, the findings indicate that most physicians will retire as soon as they are financially able, meaning healthcare organizations are slated to lose key members of their workforce in the near future. Almost half of practicing physicians were already over the age of 55 in 2021, according to a 2022 report from the Association of American Medical Colleges (AAMC). “It all comes down to the question of when – not if – the healthcare industry will feel the full impact of forthcoming physician retirements,” Tony Stajduhar, president of Jackson Physician Search, said in a statement. Healthcare organizations need to have a plan to withstand physician retirements, according to Stajduhar. That means recruiting and retaining physicians differently than they have done so in the past. Physicians indicated in the survey that offering part-time work and flexible schedules would delay their retirement plans. Many physicians also cited reducing or eliminating on-call requirements as a factor in their retirement plans. To read more, go to Revcycle Intelligence. |
Price For a Brain MRI Actually Cheaper at For-profit Hospitals than Their Nonprofit Counterparts By Marty Stempniak | March 22, 2023 | Included in Radiology Digest – March 28, 2023 The price for a brain MRI is actually cheaper at a for-profit hospital than its nonprofit or government-operated counterpart, according to a new analysis published Tuesday in JAMA Network Open [1]. Rural hospitals also were discovered to be pricier than urban ones, findings that may contradict conventional wisdom and show the “strong revenue-maximizing efforts of these hospitals,” one of the study’s authors told Radiology Business. “My takeaway: Commercial negotiated price reflects hospitals’ market power,” said Ge Bai, PhD, CPA, a professor of health policy and management at the Johns Hopkins Bloomberg School of Public Health. “To bring affordable brain MRI for commercial patients, competition from for-profit hospitals and other types of facilities, such as radiologist-owned imaging centers, are needed.” For the research letter, Bai et al. obtained information on commercial negotiated prices for brain MRI, as of June 2022, using data from Turquoise Health. They also pinpointed characteristics of those who did (and those who did not) disclose prices for the exam, including ownership type, health system affiliation, location, teaching status, profit margin, payer mix, etc. Altogether, the search produced a total of 2,630 hospitals meeting the criteria. Hospitals that publicly disclose prices for brain MRIs are typically larger, more profitable, nonprofit, system-affiliated, teaching hospitals, and located in more urban, affluent areas compared to nondisclosing institutions. They also have a higher charge markup, treat a lower number of Medicare beneficiaries, and are more likely to employ clinicians in the MRI department, the authors noted. On average, the commercial pricing for a brain exam was about $2,268 (interquartile range of $1,024 to $3,197), with hospitals contracting with an average of 16 commercial plans (range of 6-20). State, referral region and health system characteristics also appeared to impact price variation. Nonprofit and government hospitals charged higher commercial prices than other institution types, the analysis found, and this bore true both nationwide and in the same states or regions. “Across the nation and within the same state, referral region, or health system, hospitals located in rural areas, contracting with more health plans, or treating more Medicare patients had higher prices, potentially reflecting these hospitals’ stronger bargaining power compared with insurers in their local markets,” Bai and co-authors noted. To read more, go to Radiology Business. |
CMS Resumes IDR Payment Determinations Under No Surprises Act By Jacqueline LaPointe | March 21, 2023 | Included in Radiology Digest – March 28, 2023 CMS has instructed certified independent dispute resolution (IDR) entities to resume payment determinations for disputes involving items or services furnished on or after Oct. 25, 2022, according to the American Hospital Association (AHA). Payment determinations for the disputes were paused earlier this year after a court rule against the federal agency. A Texas judge ruled on Feb. 6, 2023, that a revised IDR process skews arbitration results in favor of payers, which violated Congress’ intent for the No Surprises Act. In the ruling, the judge vacated the regulations nationwide. CMS stopped all payment determinations under the IDR process following the Texas court’s decision. Late last month, certified IDR entities could make payment determinations for disputes involving out-of-network items and services before Oct. 25, 2022, using the standards from October 2021 interim final rules. This month, CMS dropped additional guidance for payment determinations made on or after Feb. 6, 2023, for items and services furnished on or after Oct. 25, 2022, for plan years beginning on or after Jan. 1, 2022. The AHA also said CMS announced that starting Mar. 17, 2023, disputing parties will start getting most of their payment determination notices from the IDR portal, specifically from auto-reply-federalidrquestions@cms.hhs.gov. Professors in a new Health Affairs Forefront blog post say that it remains unclear how the Texas judge’s decision to vacate the IDR regulation will be appealed or what comes next for the process. “[I]t obviously represents a wild card that could change the IDR balance of power in the direction of providers at the expense of insurers,” wrote research professors Jack Hoadley, PhD, and Kevin Lucia, JD, MHP, from the Center on Health Insurance Reforms at Georgetown University’s McCourt School of Public Policy. Meanwhile, the IDR process is currently facing a backlog. The federal government expected about 22,000 IDR cases for all of 2022, per the interim final rule establishing the process. By the end of September, payers and providers had filed 90,078 cases. A December update notice reported 164,000 cases filed as of Dec. 5, 2022. The high volume of disputes submitted to the IDR process — even though upwards of 40 percent of disputes are deemed ineligible — could signal provider frustration over payments they receive from payers for out-of-network claims, Hoadley and Lucia state. A recent survey of medical group leaders found that the No Surprises Act is a top source of provider regulatory burden, trailing prior authorizations. To read more, go to Revcycle Intelligence. |
How NLP Can ‘Revolutionize’ Structured Reporting By Hannah Murphy | March 20, 2023 | Included in Radiology Digest – March 28, 2023 The continued emergence of natural language processing (NLP) has caught the eye of experts in radiology recently, with some suggesting its use could streamline the process of integrating structured reporting across the specialty. A new paper published in Insights into Imaging proposes that the use of NLP could be the solution to the woes of structured reporting (SR) by integrating speech recognition features—a known hindrance to the implementation of structured reporting. Corresponding author of the new paper Tobias Jorg, with the Department of Diagnostic and Interventional Radiology at the University Medical Center of the Johannes Gutenberg in Germany, and colleagues explained why SR uptake remains low, despite its known benefits. “SR templates must be laboriously completed using a mouse and keyboard, which may explain why SR use remains limited in clinical routine, despite its advantages,” the group wrote. In short, they suggested that SR templates can interrupt workflows by slowing radiologists down when navigating through their dictation. To address the dilemma, the experts developed a tool that utilizes NLP speech recognition to convert dictated free text into a structured report. The system extracts structured content and then enters it into an SR template in RadLex terms. The system was first tested on the reporting of urolithiasis CTs using both fake text about the condition and actual reports from patients with the diagnosis. It performed well on both sets, achieving F1 scores ranging from .90 to .98, respectively. The group suggested that their system can help to address the “so-called look away problem” of structured reporting. “As imaging data sets become increasingly large and complex, most of the radiologist’s cognitive effort should be focused on the images, rather than on complicated reporting templates that require the use of a mouse and keyboard for completion,” the experts noted, adding that NLP avoids the shortcomings of traditional free text reporting and known issues with speech recognition in structured reporting. The authors concluded by suggesting that NLP has the potential to “revolutionize” structured reporting in the future. The study can be viewed here. To read more, go to Health Imaging. |
Traditional Methods Continue to Outperform AI in Some Orthopedic Scenarios By Hannah Murphy | March 17, 2023 | Included in Radiology Digest – March 28, 2023 AI algorithms have proven themselves beneficial in predicting outcomes based on imaging, but a new meta-analysis suggests that when it comes to hip fractures, these tech tools do not always live up to their hype. A new paper published in JAMA on March 17 details experts’ review of 39 different studies involving AI algorithms said to identify hip fractures and predict postoperative outcomes using X-rays alone. Although the analysis revealed the algorithms to be an effective tool for detecting these fractures, their performance in predicting patient-specific outcomes did not earn the researchers’ endorsement over expert radiologists [1]. “The performance of AI in diagnosing hip fractures was comparable with that of expert radiologists and surgeons,” corresponding author of the new paper Johnathan R. Lex, MB, ChB, with the Division of Orthopaedic Surgery at the University of Toronto, and colleagues noted. “However, current implementations of AI for outcome prediction do not seem to provide substantial benefit over traditional multivariable predictive statistics.” For the meta-analysis, experts compared traditional statistical models used to predict surgical outcomes to various machine learning models applied to the same out-of-sample dataset. Mortality and length of hospital stay were the most predicted outcomes in studies included in the analysis. For fracture detection accuracy, ML models rendered performances similar or superior to that of human readers and frequently improved their performances when used as an assistive tool. However, when it came to accurately predicting post-operative outcomes, the ML models did not offer additional benefits over traditional prediction methods, as 60% of relevant studies did not report significant differences in outcomes between the techniques. The analysis only included studies that utilized plain radiographs, a possible limitation, the authors noted. While hip fractures are often diagnosed via X-ray, it is common for readers to overlook nondisplaced fractures using this method alone. The group explained that most AI models are trained to maximize sensitivity and specificity; they suggested that taking steps to put more emphasis on false negatives could be more beneficial in reducing missed diagnoses when reviewing plain radiographs. The potential for AI to help diagnose hip fractures in the future is “promising,” but more research with more quality data is needed first, the authors noted. The study abstract can be viewed here. To read more, go to Health Imaging. |
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