HOPPR’s Foundation Model allows everyone in the healthcare ecosystem to have deep conversations with the images to better gain information and insight from that the model sees that is hard for the human eye to see. Clinicians & caregivers can ask their own questions and add clinical context in order to inform decision making in near-real-time, in the OR, in billing and claims, or at the bedside. 

Radiologists can reduce cognitive and workload burden, improve accuracy and increase efficiency with applications enabled by HOPPR. Full reports with findings, measurements, scores, and impressions can be automatically pre-generated with the findings highlighted. Importantly, HOPPR allows for deep interaction with the imaging study and the generated report text via an API based conversation with HOPPR. Supporting key images, comparison studies, measurements and published papers can all be summoned to help confirm or deny pre-populated suggestions. Reports can be automatically updated to account for the radiologists adding their personal assessments or further context, then quickly signed off and approved. 

A neurosurgeon planning an aneurysm coiling procedure depends heavily on medical imaging to assess and plan. Applications powered by HOPPR’s API service can help fully characterize the aneurysm, e.g. sac size, neck orientation, etc. and also predict which vessel approach, catheter type, and coil selection and number will be most correlated with success by providing views from several modalities. These all come with statistics, prior procedures with similar anatomy, and published research can all be surfaced to help with decision making. Once a plan has been finalized, scheduling and allocating sufficient OR time, staff, and materials can be automated to help maximize outcomes and cost efficiency. 

Trauma surgeons need to prioritize high-risk patients. Applications powered by HOPPR can alert the care team immediately after a scan is completed. Critical information such as site and amount of bleeding, large fractures and solid organ damage can be automatically communicated, saving time and improving patient outcomes. After the surgeon is alerted, they can interact with the imaging study to highlight and follow up on issues to confirm and to schedule OR time and alert the care team. 

In addition to the clinical issues present at any health system, Academic Medical Centers have a special focus on research. Applications powered by HOPPR can help automate many of the tasks necessary to explore, curate, and classify patient cases and supporting information.  As clinical diagnosis, drug discovery and treatment outcomes all become increasingly dependent on imaging, the need to automate these functions will only increase. 

Millions of dollars that should be paid to medical facilities for care are lost due to inconsistencies between medical images, reports and billing. HOPPR can enable automated to flag when something is inconsistent before the claim is submitted to insurance, allowing for medical facilities to get their total value for services rendered. Furthermore, deep investigation into individual claims can be supported by applications powered by HOPPR by allowing billing and claims staff to better understand patient histories, clinical courses and outcomes.