Diagnostic Reading #48: Five “Must Read” Articles on HIT and Radiology

Reading Time: 3 minutes read

Self-driving cars and Wikipedia are in the news this week.

This week’s articles in Diagnostic Reading include: delivering high-quality customer service in radiology; providing continuing education to radiographers; how self-driving vehicles can help radiology; ultrasound images may predict diabetes; and Wikipedia may help radiology patients.

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Diagnostic reading helps radiologists, healthcare IT and others in the medical imaging profession stay up to date.

RSNA 2018: what many radiology departments still get wrong about customer service – Radiology Business Providing high-quality customer service is a key component of any business strategy. If your customers aren’t happy, why would they use your services again or recommend you to a friend? A presentation at RSNA 2018 examined what customer service should mean to radiology professionals. Further, radiology departments have numerous customers to consider: internal customers—technologists and even the radiologists themselves—as well as the department’s patients and its ordering providers.

Continuing education in radiology contributes to patients’ quality care and well-being – Everything RadAdvances in technology impact many areas of healthcare, including diagnostic imaging. Staying current with new technology requires a commitment to continuing education for radiology. Otherwise, imaging facilities might miss advancements that could contribute to a patient’s quality care and well-being. Learn how the Ministry of Health, Oman, provides continuing education for their radiographers.

Driving AI adoption: what radiology can learn from self-driving vehicles – Radiology Today Artificial intelligence (AI) is often spoken about as a futuristic technology, but it’s already in our apps, our home voice assistants, our transportation systems, and much more. Moreover, the adoption of AI to enhance cars and navigation offers many lessons for other industries; in particular, these lessons are applicable to radiology. This article highlights how radiology can learn from the auto industry with the structure of step-by-step AI adoption.

Shoulder brightness on ultrasound predicts diabetes with 90% accuracy – Health ImagingBrightness of the shoulder’s deltoid muscle on ultrasound can identify patients with type 2 diabetes or pre-diabetes with almost 90 percent accuracy, according to a study presented at RSNA 2018. The researchers noted the reasons behind brighter-appearing shoulder muscle on ultrasound among patients with diabetes may be due to low levels of glycogen—a main source of energy for the body stored in the liver and muscles—which is commonly found in patients with diabetes whose muscle glycogen levels are decreased by up to 65 percent.

How Wikipedia may help patients understand their radiology reports – Radiology BusinessWikipedia contains a significant number of articles and images that could be incorporated into the Patient-Oriented Radiology Reporter (PORTER) initiative, according to recent research published in the Journal of Digital Imaging. This could then help patients understand the information included in their radiology reports. PORTER, a “lay-language” glossary of radiology-related terms, is used to annotate radiology reports to help patients better understand the results of their imaging procedures.

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