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Ramsoft partners with QliqSOFT Enables secure messaging of information on mobiles among doctors and patients

Amazon Comprehend Medical to bring natural language processing to healthcare A new HIPAA-eligible machine learning service

Agfa showcases rad/fluoro DR 800 system at RSNA Enhance patient and operator comfort

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Arterys touts cloud-native platform and regulatory approval in 98 countries AI capabilities with 'unmatched' security

Carestream unveils interactive multimedia and workflow enhancements Enhancing collaboration and productivity among providers and patients

Nuance launches AI Marketplace expansion with 40+ AI radiology 'app developer' network Also unveils cloud-based version of PowerScribe One reporting platform

University of Utah Health among first to leverage Philips Illumeo PACS with adaptive intelligence On display at RSNA

Siemens unveils syngo Virtual Cockpit software for CT, MR and PET at RSNA Offers remote expert technicians when needed

Intelerad acquires Clario for PACS-agnostic worklist capabilities Will ramp up presence in Seattle to leverage cloud technology expertise

Hype: Helping or hurting health care?

By Roy Smythe
From the February 2018 issue of DOTmed HealthCare Business News magazine

With new medical miracles being lauded by health care providers on a regular basis, it’s hard to differentiate between realistic benefits and overblown hype.

Promising research does not always equate to applicable clinical use in the near future. When the potential clinical effectiveness of a research endeavor is exaggerated, it may stymie the flow of financial, medical and regulatory support. Hyped-up claims can be a death sentence to once-promising work.

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If claims such as these do not pan out, those who invest in and fund medical research may be wary of supporting future ventures, and the hype ends in head-scratching as to why millions were invested in a no-show. More critically, hype can lead to heartbreaking situations for people waiting on the “next big thing” with the potential to save their lives, or the life of a loved one.

Medical advances cannot be made without research and trial and error, which often requires decades of work and significant investment to develop viable solutions. Artificial Intelligence (AI), machine learning, predictive analytics and natural language processing have great potential to help us solve some of the biggest challenges we’ve faced in health care over the past 500 years. But there is huge risk when we talk up shiny new technology and move too quickly to the health care delivery market, while the solutions themselves don’t deliver on their promise. If clinicians, providers and investors are not seeing results they may retrench. Admittedly, however, it’s also a fine line we walk, because when we don’t move quickly enough – waiting longer than necessary to bring potentially beneficial products and solutions forward – more patients lose out.

Finding the middle ground
It’s difficult to achieve the proper balance between the two extremes of such a dynamic health care innovation spectrum. We saw this same scenario play out with all the buzz around gene therapy 20 years ago. On one hand, there will always be products or technologies that promise far beyond what they’ll ever be able to deliver, leaving patients and investors at a loss. On the other, we have companies that might not seem that miraculous, but deliver on improvements and, more importantly, actually work. The middle ground may be somewhere that both gathers the interest of patients and investors and provides modest, yet successful, results. As with many aspects of life and business, finding the middle ground, if one actually even exists, can be tricky.
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