Recent IT advances in the treatment of complex radiology interventions and diagnosis requires faster visualization, and interpretation that plays a role for positive patient outcomes.
Despite some teleradiology trends that can accelerate interpretation and reduce treatment delays, some barriers still persists that may require that patient digital imaging and communications in medicine (DICOM) format images should be transferred to a remote device for viewing before interpretation can begin this mainly is packed in a CD-ROM.
At this point patients might keep a copy of their medical records and images at home or saved in another hospital without a easy access for any physician at ER.
For instance, in a case of an Acute stroke imaging often contain several hundred megabytes (MB) of data, and any delay caused by transmission of the image may significantly reduce treatment effectiveness, Moreover any confidential information in the films of the DICOM files that needs to be anonymized, causing an additional restriction.
The value of having all images per patients in a digital endlessly footprint allows to build machine learning and extracting Artificial Intelligence tools that can be aligned with images itself to forecast relapsing or prognosis.
However many of the innovations for imaging have a lack of added value for patient’s lifes.
Many patients should when comeback at home after a period of hospitalization, mostly search over the Web for more information related with their condition, relying in Google to understand more about their disease, irrespective of their own personal medical and radiology information that define actually the trail for their disease, which is unique.
The following is a trail gap between what doctors are doing now and patient are expecting:
Doctor`s social trail:
What does currently providers offer:
What will radiology based on patient’s footprint must provide:
Radiology footprint cloud should allow to view exams before any medical physical contact.
Should provide any referring physicians and patients to send studies from anywhere.
When doctor receive exams ahead of time, can extract using ML any trail to design a better plan for their course of treatment – which can be referral to another specialist or even another clinic, or determining if the patient is a candidate for a new treatment.
Radiologist share interaction (visual design)
Radiologist metrics interaction (visual design)
Radiologist can access a cloud app for building and sharing real-time patients dashboards that helps you predict and understand better patients disease and control over a simplified visibility into the most medical important data and metrics, wherever they are.
Patient Segmentation actionable knowledge (visual design)
Based in imaging folder of each patient, they can now receive preventive information ahead of recurrences , and can be in contact based on short questions survey better plan for their information for their treatment –instead of Google alone.
Patient Reminder actionable knowledge (visual design)
Following radiology reports and progress of their disease each patient can be engaged for their reminders and treatments, and not merely downloading apps their own from Stores.
Patient Appointment actionable knowledge (visual design)
From now on each patient can book and shared images with anyone regardless of hospital worldwide.
