Erasing borders
Lisa Fratt, Editor
Until recently, geography defined access to healthcare. Still, those of us who reside in rural communities contend with reduced access to cutting-edge medicine. For diagnostic imaging, when a clinician recommends an advanced study or the traditional option is unavailable, patients are left with several options: make a long trip to the nearest academic medical center or forego the study. Even in this rapidly evolving healthcare environment, the proper care isn’t always flowing to the patient.

In other scenarios, the technology to streamline processes is immature, which can impede workflow and patient care.

Recent work hints at how the pairing of advanced visualization with innovative thinking and other IT may blur these lines, and help clinicians deliver better healthcare to both rural residents and community hospital patients. Consider Native American communities in Arizona. The population faces in increased risk of colorectal cancer, yet screening compliance is low.

Researchers at the University of Arizona in Tucson attempted to amend the disparity by leveraging an existing teleradiology partnership with rural healthcare providers located in Fort Defiance, Ariz. and Tuba City, Ariz., which measure more than 300 miles from the academic medical center.

Two hundred eighty patients participated in virtual CT conoloscopy (CTC) screening between May 21, 2008, and June 8, 2009; and 95 percent of the studies were diagnostic quality. The model bears replicating. It weds IT and local resources to meet community needs and expand capacity. In fact, one of the communities elected to continue the CTC program even after terminating the teleradiology partnership with the university.

At RSNA 2010, presenters from Massachusetts General Hospital in Boston are profiling a program that extends MGH’s advanced visualization expertise to Staten Island University Hospital, a community hospital in New York City. Specifically, researchers are outlining workflow challenges (and preliminary solutions) associated with the use of an external 3D advanced imaging lab.

One conventional, and often employed, model requires techs to manually push images from PACS to the 3D lab and enter cases, patient history and other data. It’s not optimally efficient and is prone to human error.

Researchers developed two software tools to automate communication of patient images and data between the two sites. It’s an improved, but not yet perfect, process.

These programs offer an improved model that can expand access to essential imaging and advanced visualization solutions, extending expertise and offering new options to patients.

As always, I’m eager to hear your take.

Lisa Fratt
Editor of Health Imaging & IT