Seamless image exchange across multiple, disparate hospitals
Customer story ∙ By Philips ∙ Featuring Malaffi ∙ Oct 24, 2023 ∙ 3 min read
Malaffi is the MENA region’s first and fastest growing health information exchange (HIE) platforms, allowing public and private healthcare providers in the emirate of Abu Dhabi to exchange key patient information, including radiology images in real time. Clinicians can access a central database of unified clinical records (via their EMR), and from the same platform seamlessly review and manipulate images alongside other relevant patient information.
This vendor-agnostic technology allows clinicians to access images regardless of the hospital’s affiliation or PACS system. Using Philips unified viewing environment for all imaging studies generated in Abu Dhabi, Malaffi improves efficiency and quality of care by reducing the administrative burden and waiting time typically associated with accessing images from other facilities. In addition, clinicians can avoid duplicating unnecessary, invasive and expensive diagnostic patient tests, saving patients from unnecessary radiation and improving the overall patient safety and experience.
"Having access to the images is really important to making decisions around care delivery," said Dr Sanji de Sylva, Vice President of Clinical Engagement and Informatics, Abu Dhabi Health Data Services (Malaffi). "Instead of having to repeat expensive tests, they (clinicians) now have access to these images in real time and are delivering care in a more timely fashion."
Customer story at a glance
Building a consolidated, usable patient record while overcoming technology challenges associated with disparate hospitals
Malaffi, a strategic initiative of the Department of Health - Abu Dhabi, UAE, is the MENA region’s first health information exchange platform. It safely and securely connects public and private healthcare providers across Abu Dhabi to provide meaningful, real-time exchange of important patient health information. Malaffi, which is Arabic for “my file,” is one of the fastest implemented HIEs in the world. Malaffi currently connects 83 unique EMRs across more than 2,600 facilities and 47,000 users into one unified platform.
Due to demand from clinicians to access radiology images alongside radiology reports, the HIE was quickly extended to include Philips image exchange platform. This gives clinicians the ability to view holistic patient data from which to make better-informed clinical decisions.
“The key driver were our clinicians. They really wanted us to extend our capabilities from providing them access to radiology reports, to also seeing the images.”
Dr Sanji de Sylva
Vice President of Clinical Engagement and Informatics, Abu Dhabi Health Data Services (Malaffi)
Malaffi partnered with Philips to bring this end-to-end imaging platform to life. Philips’ innovative and award-winning Enterprise Viewer and vendor-neutral archiving solutions to link radiology systems across hospitals, regardless of technology provider, hospital affiliation or location.
The benefits of integrating the image exchange platform into Malaffi’s HIE include:
“The image exchange platform was implemented quickly with a minimal footprint. There was little to no disruption of services while bringing the solution to life.“
Mohammed Shah
Director of Project Management Office, Abu Dhabi Health Data Services (Malaffi)
The Philips imaging viewer enables the display of digital imaging and communications in medicine (DICOM) data, including X-rays, CT and MRI scans, ultrasound images, and other diagnostic images linked to the radiology reports. It provides clinicians access to a FDA-cleared image viewer supported by advanced clinical imaging tools.
In an ongoing partnership with Philips, the Malaffi platform continues to grow with the aim to connect 100% of healthcare facilities that store radiology images across Abu Dhabi by the end of 2023.
“We’ve had a lot of positive feedback about how the platform helped increase efficiency of care,” said Dr De Sylva. “Our clinicians are really looking forward to utilizing images to further add improve efficiencies in the care delivery process, improve the patient experience and to start using radiology AI and machine learning algorithms to support clinical diagnoses in the future.”
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Disclaimers
Results are specific to the institution where they were obtained and may not reflect the results achievable at other institutions. All pictures shown are for illustration purpose only. Actual product may vary due to product enhancement.
