No Patient Left Behind
Radiation oncologists and radiologists are changing the face of lung cancer screening for veterans.
Each year, more people die of lung cancer than of colon, breast, and prostate cancers combined.1 Active duty and veteran military members have a significantly higher risk of developing lung cancer — due to exposure from carcinogenic chemicals on military bases and in the field of battle, as well as a higher rate of smoking.2 From 2006 through 2015, 77,930 veterans were diagnosed with non-small cell lung cancer. Unfortunately, the majority presented with advanced stages, which are often incurable and carry a survival rate of only 2–13%.2
The ACR is working with Congress to find a solution to the problem of surprise medical bills.
Lawmakers return to Capitol Hill this month and will resume their efforts to address the problem of surprise billing. Predominantly defined as a patient receiving an unanticipated medical bill from an out-of-network provider or facility, surprise bills can be financially catastrophic for the patient. The ACR has been working with Congressional leadership and other medical societies to enact equitable legislation that will spare the patient from being part of the reimbursement equation — while ensuring that physicians and insurers continue to have the ability to negotiate fair and reasonable agreements and maintain the ability to resolve payment disputes that may arise.
Appropriate Use Criteria:
Claims and Billing Guidance Arrives
CMS is committed to advancing AUC, motivating radiologists to implement the program.
On July 26, CMS released two documents updating the Appropriate Use Criteria (AUC) program, mandated by PAMA.1,2 The document restates the implementation timeline from previous CMS communications, including last year’s Medicare Physician Fee Schedule Final Rule. The anticipated guidance on billing claims is provided below. The education and operations testing period begins on Jan. 1, 2020, with full implementation of the AUC program expected Jan. 1, 2021.
The College’s latest survey included a deep dive into members’ perceptions of machine learning — and how it will affect their practices.
The ACR is committed to empowering its members to advance the practice, science, and professions of radiologic care. The College works to equip members with the tools they need to succeed — while actively promoting and advocating for the profession before Congress, federal and state regulatory agencies, and state legislatures.
A new initiative out of SCARD and GE Healthcare involves radiology leaders helping their female peers rise in the ranks.
Rachel Gilbreath and Cheri L. Canon, MD, FACR, connected over what they could do to make the path to leadership easier to navigate for their female peers in healthcare.
Two years ago, Cheri L. Canon, MD, FACR, and Rachel Gilbreath, vice president at Hillrom, attended the Radiology Leadership Institute® Summit in Wellesley, Mass., and found themselves bonding over their experiences as leaders in their respective fields — and what they could do to make the path forward easier to navigate for their female peers in healthcare. Although they had different backgrounds — Canon is a professor and chair of radiology at the University of Alabama at Birmingham School of Medicine, while at the time Gilbreath led GE Healthcare’s strategy for academic medical centers across the U.S. — they found they’d encountered many of the same challenges on their rise to leadership positions.
What is the effect of surprise billing on patients?
The Right Tools
Radiologists can improve the appropriateness of image ordering, transforming patient care and driving down costs.
Appropriate diagnostic imaging is a key element of high-value healthcare. Careful selection of imaging exams can expedite diagnoses, reduce unnecessary testing,
decrease radiation exposure and other risks, and diminish healthcare costs. A 2018 analysis of healthcare spending in the United States compared to other countries concluded that high healthcare costs in this country may trace in part to an overuse of diagnostic imaging.
Experiencing Artificial Intelligence
Machine learning will result in even greater improvements in efficiency and accuracy, while at the same time reducing work fatigue.
Artificial intelligence was a major emphasis at RSNA in 2017, and I had an opportunity to check out the latest technology from several AI start-ups. Hands-on experiences with simulated PACS workstations quickly convinced me that AI technology could improve our accuracy and efficiency and reduce turnaround time.
Learning from Patients
An innovative teaching initiative at Indiana University positions patients to drive care improvements.
“A patient presents …” The medical community uses this phrase frequently when discussing patients’ symptoms. However, the idea of a patient presenting has taken on new meaning in the radiology department at Indiana University (IU).
Charting a Course
Keeping up and moving forward in machine learning means having a roadmap for success.
Gauging the practical implementation of day-to-day, timesaving AI in medical imaging is no simple calculation. Setting your group’s compass to ensure quality care doesn’t have to be an arduous endeavor.