Value-Based Healthcare: Institute of Health Economics Evaluation of densitas intelliMammo A.I. Platform

Jan 27, 2021

Categories: General

Think of breast cancer screening as a funnel: 90% of women participating in breast screening have only a screening mammogram, and the remaining 10% go on to diagnostic mammography. Efficient patient and process management are critical in determining the effectiveness of breast cancer screening and are impacted by a woman’s breast density, her breast cancer risk, and the clinical image quality of her mammogram. Optimizing patient and process management in screening mammography impacts the effectiveness of diagnostic mammography and can cost-effectively improve breast cancer screening service delivery quality and clinical outcomes, supporting value-based healthcare models.

To date, the majority of healthcare services have operated on fee-for-service delivery models which drive high healthcare costs. These models focus on quantity of service, promoting the treatment of patients for increased testing and billing.

The global shift from fee-for-service to value-based care models of healthcare service delivery demands striking a delicate balance between quality, clinical outcomes, and cost.

Rather than considering all treatments as individual siloed events for billing, value-based care models reward efficiency and effectiveness in patient care management.

Breast Density Stratification and Mammography Quality Assurance as Key Considerations for Value-Based Care

Dense breasts both mask and are a risk factor for breast cancer. Stratifying women according to their breast density identifies those who may benefit from tailored follow-up screening protocols such as adjunctive imaging, including ultrasound and MRI, to improve the sensitivity of breast cancer screening.

Inadequate mammography clinical image quality is associated with unnecessary radiation exposure, delays in regularly scheduled mammography screening exams, technical recalls, increased breast cancer risk, and missed cancers. Flagging inadequate clinical image quality provides opportunities to improve radiological technologist positioning techniques and reduce positioning error rates.

Population-wide assessment of breast density and clinical image quality on every mammogram can significantly reduce the number of missed cancers and enable earlier detection and treatment, improving quality of care and reducing costs associated with morbidity and mortality. Using precise, standardized, and reliably reproducible measures for breast density classification and clinical image quality assessments enables tailored breast screening protocols and continuous mammography quality assurance supporting value-based healthcare delivery.


Cost Savings Achievable for a Health System using densitas® intelliMammo™

Consider a health system in the USA with 100,000 women who start annual screening at 50 years old and regularly participate in a breast cancer screening program for the whole of their lives. A health economics headroom analysis shows that the following lifetime cost savings are achievable as a result of better stratification of high-density patients, improving clinical image quality and test accuracy.

Bullseye clipart – Value-based healthcare + breast density + breast cancer risk

Save $300 Million with better stratification of high-density patients

The greatest savings per patient can be made if all patients are better stratified by breast density such that their invasive disease can be identified at an earlier stage should it occur. For women with dense breasts, this has the biggest impact, providing average cost savings of $300 million.


Checkmark clipart – Value-based healthcare + quality

Save $70 Million by improving clinical image quality

High image quality is associated with increased sensitivity and specificity, which provides better patient outcomes. Eliminating image quality errors could lead to a total cost savings of $70 million.


Stopwatch clipart – Valuebased healthcare + technical recalls

Save $9.8 Million by eliminating technical recalls

Automated clinical image quality assessments flag poor quality clinical images at point-of-care. Such images can be repeated while the patient is still in the exam room to avoid recalling patients for repeat mammograms at a later date. In standard operating conditions where technical recalls are at 3%, elimination of these would provide average cost savings of $9.8 million.


Improve Patient Outcomes Across a Health System

In a population with 100,000 women who started screening at age 50 and participated fully in a breast cancer screening program for the whole of their lives, using densitas® intelliMammo has the potential to significantly improve patient outcomes, increasing the average number of years lived in perfect health.

Checkmark clipart – Value-based healthcare + quality

Additional 2000 years by improving clinical image quality

Obtaining 100% good quality images impacts both the sensitivity and specificity of mammograms, thus improving patient outcomes. Such improvements of image quality could result in an average of 2000 extra years lived in perfect health over the course of their lifetimes.


Stopwatch clipart – Value-based healthcare + technical recalls

Additional 959 years by eliminating technical recalls

A 100% reduction in technical recalls could result in an average of 959 extra years lived in perfect health over the course of their lifetimes.


How Densitas® Supports Value-Based Healthcare

Healthcare systems struggle to deliver quality care and good patient outcomes at a sustainable cost. Attempts to prioritize quality and patient outcomes with less resources have typically come at an increased cost, added to the growing administrative burden on the clinical care team and increased radiologist burnout.

With COVID-19 restrictions increasing the backlog of breast screening services, depleted resources, and projections of burnout among clinical care teams, mammography facilities are in need of effective patient and process management that aligns with value-based care service models.

Densitas® designs A.I. solutions to optimize operational and workflow efficiencies and support business continuity for mammography facilities. By focusing on automation and standardization of routine, tedious, and time-consuming tasks in the radiology workflow, and providing actionable information on-demand, densitas®
intelliMammo™
enables radiologists to focus on the more challenging tasks associated with breast cancer diagnosis.

With an estimated 40 million mammography procedures performed annually in the United States, densitas®
intelliMammo™
has the potential to significantly reduce health system costs and improve the health outcomes for many women.

Reach out to learn how Densitas® can help you, especially in the context of the COVID-19 pandemic impact on healthcare service delivery and the accelerated shift to value-based-care.


Let’s Stay Connected, Subscribe for Updates

Join our email list to stay up to date on the latest advancements in breast health technology.

Sign Me Up

 

Sutton A, Palfrey D, Corabian P, Tjosvold L. Early Economic Evaluation of densitas® intelliMammo™ enables radiologists to focus on the more challenging tasks to assist mammography in the screening of women for breast cancer. Edmonton (AB): Institute of Health Economics; 2020.