“I ask that you immediately remediate this situation, and remove the vulnerable PACS from open access to the internet.”
Senator Mark Warner (D-VA) in a letter to the U.S. Defense Health Agency calling for the agency to address continued PACS server vulnerabilities at some Army hospitals.
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PACS Vulnerability Spotlight
The spotlight on PACS server vulnerability hit a new peak last week, with new coverage of efforts to shore-up European servers, rising political pressure on the U.S. Army to improve its PACS security, and some new guidelines from the research community on how to stay out of the PACS security headlines.
Europe Reacts, Slowly – An interview with Greenbone Networks on AuntMinnieEurope.com revealed that although some European authorities have addressed the region’s unsecured PACS servers since the firm revealed widespread vulnerabilities last fall, tens of thousands of medical images are still leaking from European PACS into the public domain every week. After Greenbone revealed that there were 47 unsecured PACS servers in the EU in September 2019, the number of vulnerable PACS servers fell to 22 in November, and declined to 15 servers as of January 2020. However, these remaining servers continue to add/expose new images and studies every day.
Image Security Gets Political – Senator Mark Warner (D-VA) criticized the U.S. Defense Health Agency’s inability to address the unsecured Army PACS servers that continue to leak servicemembers’ medical images. Warner initially approached the Defense Health Agency in November for not appropriately responding to ProPublica’s revelation that millions of people’s medical data are exposed due to unsecure PACS servers, and although many servers and images have been secured since then, a number of Army facilities still have “insecure data practices” (specifically: Ft. Belvoir Medical Center, Ireland Army Health Clinic, and the Womack Army Medical Center).
Security Playbook – In light of the recent surge in medical image vulnerability, an AJR paper suggested that radiologists secure their practices/departments by following the “CIA triad” of confidentiality, integrity, and availability. More specifically, radiology practices and departments should: 1) Maintain confidentiality by encrypting all medical images on their devices/CDs and ensuring the use of secure networks; 2) Verify that imaging data has not been altered or tampered with; and 3) Guarantee that the necessary information is accessible by authorized people and can’t be blocked by ransomware.
The AHA 2020 Hospital Statistics Report revealed that U.S. hospital outpatient visits declined in 2018 for the first time in 35 years, suggesting that a notable shift in where patients seek outpatient care may be underway.
The Data – The AHA survey (n = >6,000 hospitals) revealed that U.S. hospital outpatient visits dropped by 0.9% to 879.6 million visits in 2018, however hospitals still found a way to increase net outpatient revenue by 4.5% (vs. inpatient care’s 2.1% revenue increase).
The Reason – The drop was attributed to the increased role of urgent care clinics and retail-based health clinics, which was underscored by AHA’s finding that the greatest hospital outpatient declines occurred with emergency outpatient hospital visits.
Cause for Concern – The drop in outpatient traffic should have hospitals concerned, given that many hospitals have directed millions of dollars towards new outpatient centers in recent years, many of which are still being constructed.
- Speaking of a shift towards retail clinics, a new Reaction Data survey found that provider organization employees (n = 132) were surprisingly unfamiliar with Walmart’s ambitions to open medical clinics across the U.S. (56% not familiar, 4% very familiar), and had relatively balanced opinions on whether it’s a good idea (32% bad idea, 31% good idea) and whether Walmart would execute the idea effectively (46% neutral, multi-specialty physicians most likely to be optimistic). The greatest number of respondents saw retail pharmacies as the most likely to follow Walmart’s lead and open their own clinics (31%), followed by Target (20%), and Amazon (19%).
- New research from the University of Texas at Houston reveals that the combination of noncontrast CT and CT perfusion (CTP) imaging can be effective for selecting stroke patients who are more likely to have favorable outcomes from endovascular thrombectomy (EVT). The study reviewed scans from 361 patients presenting large‐vessel occlusions (285 received EVT; 87% w/ favorable CTs, 91% w/ favorable CTPs, 81% favorable w/ CT & CTP, 16% discordant CT & CTP, and 3% both unfavorable), finding that patients with favorable profiles in both their CT and CTP scans were nearly four-times more likely to receive EVT than patients with discordant profiles. These patients were also more likely to have successful outcomes from their EVT procedure (58% favorable on both vs. 38% discordant vs. 0% when both unfavorable).
- A coalition of conservative groups are funding a series of advertisements intended to halt legislative efforts to end ‘surprise’ medical bills. Although the surprise billing legislation has bipartisan support (that’s also a surprise these days), the conservative backers of the new “Coalition Against Rate-Setting” (including Taxpayers Protection Alliance (TPA) and Heritage Action for America) view the proposal as a “rate-setting” effort that interferes in private health care decisions.
- Research from an Indiana University team found that American emergency departments continue to overuse CT pulmonary angiography (CTPA) when evaluating for pulmonary embolism, encouraging EDs to increase their use of D-dimer testing as a way to reduce low-yield CTPA. A review of 1.8 million visits across 27 emergency departments found that 5.3% of visits involved testing for PE and 2.3% included CTPA, but only 3.1% of patients who underwent a CTPA scan were diagnosed with PE.
- CB Insights reported that health AI startups raised $4 billion in funding last year across 367 deals, representing a major increase from 2018 ($2.7b, 264 deals) and surpassing AI startups in other verticals (finance was #2 at $2.2b and 198 deals). AI startups across all industries raised $26.6 billion in 2019 (2,235 deals), marking a 6.3x increase from five years ago ($4.2b, 581 deals).
- The FDA reclassified MYN-coded medical image analyzers to Class II, down from Class III, easing the regulatory process for computer-assisted/aided detection (CADe) devices for mammography and breast ultrasound as well as radiographic detection of lung nodules. With the new classification, developers no longer have to submit premarket approval applications (PMAx) for these products and will instead file an easier 510(k) premarket notification. The reclassification comes a year and a half after it was first proposed.
- New research in the Medical Care Journal found that the 2006 expansion of Massachusetts’ cancer screening coverage led to a 7% decline in the likelihood of late-stage colorectal cancer diagnosis (vs. states without expanded coverage) but no significant change in late stage breast cancer diagnosis (potentially because BC screening was already well established). If similar coverage expansion was adopted across the U.S., the researchers believe it could catch thousands of additional cases while they are still treatable.
- Intelerad Medical Systems will soon have a new private equity parent company, as UK-based PE firm HG plans to acquire Novacap’s majority stake in the imaging software company by the end of Q1 2020. Both Intelerad and HG have big goals, as Intelerad recently revealed plans to commit $75 million in R&D funding and HG has been actively expanding its healthcare portfolio (now 5 companies, $1b).
- A Stanford team developed a framework to sonographically differentiate thyroid nodules at a level comparable to expert radiologists, representing “a big step towards automating thyroid cancer triage.” The quantitative framework analyzes a range of nodule features (echogenicity, texture, edge sharpness, margin curvature) to predict nodule malignancy and achieved an AUC of 0.828 on ultrasound images of 92 biopsy-confirmed nodules (vs. 0.299 to 0.829 from six expert annotation-based classifiers). If applied to this set, the framework would have helped avoid biopsy of 20 of 46 benign nodules or identify 10 of 46 malignancies.
- Research from Brigham and Women’s Hospital reveals that millions of clinically necessary radiologic exam orders were unscheduled in EHRs at least a month after they were ordered, while many unnecessary orders were scheduled. The retrospective study found that 7% of all radiologic exam orders were unscheduled (33,546 of 494,503) and many of those unscheduled exams were clinically necessary (e.g. 87% of bone densitometric exams, 65% of mammographic studies), suggesting that this is a “major opportunity for diagnostic process improvement.”
- New analysis from the nonprofit CAQH Explorations revealed that the cost for providers to manually generate a prior authorization increased by more than 60% to $10.92 in 2019, while the cost to generate an electronic prior authorization transaction fell from $2.80 in 2018 to just $1.88 in 2019. This was enough for the Medical Group Management Association (MGMA) to announce that it is “alarmed” by the rate that prior authorization costs are increasing and call on the federal government to streamline this process by requiring a national automated approach.
- New research from UCLA found that NLP analysis of structured ultrasound reports (BI-RADS) could help identify patients who would qualify for additional genetic testing. The retrospective study of 219 breast cancer patients who previously received genetic tests analyzed BI-RADS terminology in their ultrasound reports and found that reports with abnormal ‘retrotumoral’ and mass ‘margins’ aligned with the qualifications for a pair of common genetic tests.
- A study from the LSU Health Sciences Center provided new evidence on how AI performance improves when higher-resolution images are used for training, calling on the industry to be more aware of the importance of image resolution. The retrospective study examining CNN performance using the NIH chest X-ray dataset (n = 112,120 CXRs, 30,805 patients) found that the highest AUCs were achieved using images with resolutions between 256×256 and 448×448, while certain diagnostic tests (e.g. emphysema, cardiomegaly, hernia, and pulmonary nodule detection) had the greatest improvements when changing from lower-resolution images to higher-resolution images (64×64 vs. 320×320).
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