Blog
February 19, 2019

EonDirect Lung Community Case Study

Eon continues to impact patient lives and optimize provider workflows across the country. In this case study we look at how a 175 bed community hospital improved their workflow and patient tracking of incidental and lung screening patients using EonDirect.

Tracking Patient Cohort:

The case study hospital began using EonDirect in January 2018 and began using Eon’s proprietary identification model for pulmonary incidental nodule identification in August as shown in the graph below. Eon’s proprietary identification model had a 90% positive predictive value and resulted in a significant increase in incidentally identified true positive patients.

Patient Follow-Up Adherence Rate

EonDirect longitudinally tracked all future exams for both patient populations and demonstrated an increased Follow-Up adherence to 98% for both cohorts.  It is important to note that the national adherence rate for recommended clinical follow up for incidental pulmonary nodule patients is just 30%.

With and Without EonDirect Comparison

The below charts demonstrate the impact EonDirect had on the community hospital’s lung programs. To determine this information, we compared the 35 months prior to implementing EonDirect and the 10 month period following the EonDirect implementation. The chart demonstrates a 3.43 times monthly increase in lung screening exams and a 38.68 times monthly increase in incidental nodule exams.


EonDirect Increased Efficiency Between Abnormal Exam to Diagnosis to Treatment

The Journal of Oncology Practice published a multi-site study that showed a 36.5-day median time to treatment from the first abnormal radiography result to treatment (http://ascopubs.org/doi/full/10.1200/jop.2015.009605). Using EonDirect, the community hospital was able to demonstrate below average times for the same intervals. By immediately identifying patients at risk and tracking their longitudinal care, EonDirect also increases hospital efficiency by reducing time from Abnormal scan < Diagnosis < Treatment.