HHE Radiology and imaging supplement 2018 | Page 8

the field of artificial imaging( AI) promises opportunities to improve the speed, accuracy, and quality of image interpretation and diagnosis in radiology. 13 Surely AI will find its way into medical imaging; however, to show how these AI products reduce costs and improve outcomes will require clinical translation and industrial-grade integration into routine workflow. 14

Value should always be defined around the patient, and in a well-functioning health care system, creating value for patients should determine the rewards for all other players in the system. 1 Creating value and contributing to patient outcome in radiology departments starts with well-organised utilisation plans, shorter waiting times, appropriateness criteria, structured and timely reporting and continuous research for better imaging, intervention and therapy. The contribution of radiologists should not be considered as a factory producing imaging examinations, and attention should not be focused on the volume of procedures performed. 4 Importantly, no false economic incentives should be set up, which primarily compensate for the volume of diagnostic or therapeutic measures.

There are different imaging value chain metrics to be considered. The most relevant ones that can be used in the daily practice could fit in five different categories, 15 namely:

• imaging appropriateness 1, 2

• patient scheduling, preparation and protocol 3 modality operations 4

• reporting

• communication. 5

Guideline compliance, adherence to CDS tools and identification of redundancy are integral parts of the first group, while in the second category, the scheduler response time, the ease of access to scanning facility, compliance with protocols or radiation limits and staff service feedback are of utmost importance. The third category comprises metrics such as on time scanning, room time and contrast reactions or extravasations. In the reporting category, the adherence to ACR incidental finding criteria, the use of standard vocabulary, the time from examination completion to finalised report and the accuracy of report to final diagnosis are the most important metrics. Finally in the fifth category, time for report availability to patient, time for closed-loop critical results reporting, ease of report access by patient and report understood by or consulted to patient are the metrics to be used.

The most important questions regarding the outcome effects induced by imaging are: Did the referring physician find the report information useful? Did results of imaging change diagnosis or therapy? Did the use of imaging eliminate need for more invasive or expensive procedures? Did the use of imaging reduce length of stay? Complications, patient and referring physician satisfaction are also examination outcomes to be borne in mind.

Conclusions In conclusion, the goal is to achieve a sustainable and affordable care, creating value, better outcomes and satisfaction to both patients and all other players in the healthcare cycle, and of course reduce waste, keeping in mind not just stratospheric amounts of potential global or nationwide money waste( like those $ 750 billion of waste spent on health care reported in US 16) but also those small amounts that we face daily in our practice, such as redundant or inappropriate emergent imaging exams, but summed on a year basis and even on a small hospital in a country such as Portugal 17 could easily equalise a radiologist annual salary. In this way, the role of radiology in healthcare management is pivotal, and radiologists, knowing the unique field of imaging as no one else, are at the forefront to become the master of a lean organisational structure.