Radiology experts propose new framework to capture true value of diagnostic imaging
As healthcare spending climbs ever higher, radiology departments are faced with quantifying the value of diagnostic imaging exams. But measuring the impact of these tests is more complex compared to other medical tools.
That’s partly because many frameworks are centered around quantitative, rather than qualitative, analyses like cost-effectiveness assessments, experts explained Friday in a JACR opinion piece.
With this in mind, the experts—which include Ruth C. Carlos, MD, MS, editor-in-chief of the ACR’s flagship journal—called for wider adoption of what’s known as the "net health benefit."
“NHB is a summary statistic that describes the impact on a patient’s health after the new intervention is introduced,” the authors wrote, adding the technique reflects both life expectancy and quality. “When used to calculate the value of a diagnostic imaging test, a positive value indicates that the patient gains health benefits (either in extended life years or improved quality), and a negative value indicates that the patient’s health worsens as a result of the new diagnostic imaging test."
Another benefit, the authors added, is that NEB incorporates the comparison of a test to another test or the absence of one, known as the incremental cost-effectiveness ratio. This is a useful way to capture the value of imaging exams, the authors noted.
At the same time, NEB cannot directly account for two important factors: patient-reported outcomes and patient preference information.
PPI ensures patients understand the risks and benefits of imaging prior to undergoing testing. And PRO, for example, can compare the morbidity of one exam with another. Both have become more important in recent years but require more research to integrate into NHB.
Calculating the net health benefit requires heavy lifting, including modeling various treatment decisions and disease progressions for any one condition. Building a model to account for all potential care pathways and corresponding tasks would be time-consuming, to say the least.
The authors stress the need for such modeling to be freely available.
“Such open-source models are public goods; therefore, we call for public funding for [the] creation of such models,” they added. “We also call for broad cooperation between public and private payers, diagnostic, medical device and pharma companies, and clinical societies on development of such models.”
Read the full opinion piece here (paywall).
Matt joined Chicago’s TriMed team in 2018 covering all areas of health imaging after two years reporting on the hospital field. He holds a bachelor’s in English from UIC, and enjoys a good cup of coffee and an interesting documentary.