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Artificial intelligence, such as neural networks, deep learning and predictive analytics, has the potential to transform radiology, by enhancing the productivity of radiologists and helping them to make better diagnoses. This short report from Signify Research presents 5 reasons why artificial intelligence will increasingly be used in radiology in the coming years and concludes with a list of the barriers that will first need to be overcome before mainstream adoption will occur.

Big data analytics has dominated the imaging market headlines in recent times. This emerging sector may appear tantalising and visionary, but much of the hype is based on conceptual discussion, and there is a lack of substance and evidence about how big data analytics can be applied to mainstream use in radiology.

Earlier in 2016 the Centers for Medicare & Medicaid Services' (CMS) introduced the Advancing Care Information (ACI) performance category as part of its Merit-based Incentive Payment System (MIPS). Its introduction brought patient engagement to the forefront of EHR implementation and provider re-imbursement policy.

Last week it was announced that US patient engagement platform supplier, Emmi Solutions, had entered into an agreement to become part of the Dutch information and services business, Wolters Kluwer.

Vendor Neutral Archives (VNA) have been a huge success story in the healthcare IT industry. Less than five years ago, few in the industry even knew what one was. Yet today VNA software is generating hundreds of millions of dollars annually and is rapidly becoming industry standard for storage of clinical information.

Earlier this week, Philips Healthcare and Qualcomm Life Inc. announced a strategic deal to leverage components of each firms' product offerings. Philips will benefit from enabling users of its HealthSuite cloud platform to connect to a wide array of devices that utilise Qualcomm's 2net Platform connectivity. The company claims it will allow Philips devices and third-party devices secure connectivity, data capture and transmission to the HealthSuite platform.

Since 2014, companies developing analytics for clinical diagnostics applications have received more than $260m in funding. The volume and the size of deals is increasing, with around $100m already invested this year. This includes two of the largest deals to date - UK based artificial intelligence (AI) health service provider babylon secured $25m in a series A funding round and clinical decision support company medCPU received $35m of venture funding.

The successful adoption and use of PACS was for many years a much-coveted aspect of radiology. As an early adopter of healthcare IT far ahead of other specialties, radiology was lauded for its innovation and forward thinking.

Following a tumultuous period of change in the US healthcare IT market, the US Government Centre for Medicaid and Medicare (CMS) has provided initial guidance on how the next period of e-Health adoption will be managed (https://blog.cms.gov/2016/04/27/moving-toward-improved-care-through-information/) "Meaningful Use", the much criticised multi-stage reimbursement component that led to rapid deployment and growth of the enterprise Electronic Medical Record (EMR) market, is set to be replaced by a new law, the "Medicare Access and CHIP Reauthorization Act of 2015 (MACRA)".

The recent announcement from McKesson of plans to spin-off a large portion of its health IT business came as little surprise. McKesson's health IT business has long been the side project to the $188B pharmaceuticals distribution arm; with competition in the North America market intensifying (around 90% of McKesson customer base), significant investment was going to be required to continue to compete.

The planned UK exit from the European Union will have far-ranging consequences for the medical device and healthcare IT industry. At this early stage, the detailed implications are unknown and are not possible to accurately predict.

Rapid growth in the volume and complexity of data generated in the healthcare sector is driving health providers towards adoption of cloud technology. However, adoption is being slowed by data access, security and cost concerns. With no clear standard implementation model, the diversity of cloud IT implementations in Health IT is also expanding.