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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog

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.”

Radiology Billing and Coding Blog