A recent study aimed at calculating follow-up recommendations in radiology reports and comparing the efficacy of various methods to identify patients in need of follow-up suggests the usefulness of technologies that can take action on those recommendations. The study that was conducted by Dr. Emmanuel Carrodeguas and his colleagues, published on December 29, 2018 in the Journal of the American College of Radiology and reported by AuntMinnie.com, concludes in part that “Automatic identification of follow-up recommendations could have wide implications for establishing and timely performance of collaboratively developed follow-up care plans for actionable findings in radiology reports to improve quality and experience of care for patients.”
A study reported in the September 2018 American Journal of Roentgenology concludes, “A semi-automated approach to tracking patients with IVC filters can facilitate care coordination and clinical decision-making for a device with known potential complications.” The study followed 293 IVC filter recipients over a 6-month period, and found that the use of a tracking system improved the filter retrieval rate from 23% to 34% over the same period of the previous year.
Our recent article How Radiology Practices Can Drive True Quality of Care describes how the use of clinical data can be integrated with a business process to provide benefits for both patient care and practice value. Expanding this concept to the next level triggers the imagination – what other types of cases in the practice need follow-up within specific time periods? Thus came the idea for the second iteration of HAP’s clinical analytics solution deployment that involved patients with implanted inferior vena cava (IVC) filters.