Phase I Amount
$1,316,275
Alara Imaging, Inc. (Alara) is seeking funding to support the development of robust, IP-protected, HIPAA- compliant commercial quality software to calculate and report on quality measures that will be reported for every radiologist and hospital group in the nation. Further, Alara is seeking funding to develop enhanced feedback that leverages machine learning, data visualization, and benchmarking to guide physicians and hospitals on safe approaches for lowering their CT radiation doses. Once implemented at scale through the support of this award, Alara's software has the potential to reduce the cancers that result from CT by up to 30%, preventing as many as 10,000 cancers annually. The use of CT has grown substantially over the last 2 decades with 90 million CT exams performed annually in the U.S. A major quality gap exists in the performance of CT as the radiation doses used for these exams are higher than needed for diagnosis and in the range where they increase a person's risk of developing cancer; it is estimated that CT use causes 36,000 cancers annually in the U.S.1 The inconsistency in how CT exams are performed represents a modifiable health risk as radiation doses can be reduced through audit and feedback, as shown in a UCSF led, NCI funded, trial.2 In 2019, UCSF was awarded a cooperative agreement from CMS to develop CT radiation dose and image quality measures for use in the agency's pay-for-performance programs. The intent of this award was to motivate radiologists and hospitals and to reduce unnecessarily high radiation doses through financial incentives. UCSF created the approach to judge each CT by combining clinical and radiology data located in disparate health data systems including the Electronic Health Record, Radiology Information System, and Picture Archiving and Communication System. These data systems communicate poorly, and properly ingesting and normalizing these data in real time was a technological challenge. Additionally, as a stipulation of the funding, CMS required UCSF to develop these measures as electronic clinical quality measures (eCQM); however, the resources required to develop and implement an eCQM at the national level were beyond what was available to Dr. Smith-Bindman from CMS. As a result, Dr. Smith-Bindman, in collaboration with UCSF as a minority equity stakeholder, worked with radiology informatics experts to create a commercial entity, Alara, to develop the eCQMs and software for national implementation. The measures are now being considered for use in CMS quality payment programs, and Alara is now seeking funding to implement the measures at scale. In addition to the CMS measure functionality, the software's architecture will represent a meaningful technological advancement and creates value beyond measure reporting by linking and providing access to combined clinical and radiology data connected to the cloud. Information technology companies that are driving care forward in radiology using novel machine learning and computer vision techniques need access to the same linked data so that they can leverage modern technology applications. Alara's software, "The Gateway", solves this integration and data access challenge, and Alara will sell access to the Gateway to technology companies, opening possibilities for technology companies to develop additional solutions that take advantage of the linked and structured data.
Public Health Relevance Statement: Project Narrative A quality gap exists in the performance of computed tomography (CT) as radiation doses are higher than needed for diagnosis and vary depending on where a patient goes for care. Alara Imaging has developed patient safety measures that are focused on the radiation dose and image quality for CT and are being considered for use in the Centers for Medicare and Medicaid Services (CMS) quality payment programs; the use of these measures has the potential to reduce the doses used for CT to make CT safer. Alara Imaging is seeking funding to support the development of commercially built software that hospitals and physicians can use to report on these measures as well as seeking funding to build software to help guide physicians to lower the doses they use for CT.
Project Terms: Adoption; Architecture; Engineering / Architecture; Automobile Driving; driving; Award; California; Malignant Neoplasms; Cancers; Malignant Tumor; malignancy; neoplasm/cancer; Certification; Communication; Computer Vision Systems; computer vision; Diagnosis; Electronics; electronic; electronic device; Feedback; Health; Healthcare Systems; Health Care Systems; Health Status; Level of Health; Hospitals; Information Systems; Data Systems; IT Systems; Information Technology Systems; Inpatients; Interview; Medical Imaging; Modernization; Persons; Outpatients; Out-patients; Patients; Physicians; Radiology Specialty; General Radiology; Radiology; Radiology Information Systems; Radiologic Information Systems; Recommendation; Resources; Research Resources; Risk; San Francisco; Computer software; Software; Standardization; Surveys; Survey Instrument; Technology; Testing; Time; X-Ray Computed Tomography; CAT scan; CT X Ray; CT Xray; CT imaging; CT scan; Computed Tomography; Tomodensitometry; X-Ray CAT Scan; X-Ray Computerized Tomography; Xray CAT scan; Xray Computed Tomography; Xray computerized tomography; catscan; computed axial tomography; computer tomography; computerized axial tomography; computerized tomography; non-contrast CT; noncontrast CT; noncontrast computed tomography; United States Centers for Medicare and Medicaid Services; Centers for Medicare and Medicaid Services; Health Care Financing Administration; United States Health Care Financing Administration; Universities; Work; Measures; Caring; Picture Archiving and Communication System; Site; Clinical; Specified; Specific qualifier value; Link; ingest; Ingestion; Funding; radiologist; Collaborations; randomized control trial; Randomized, Controlled Trials; Intellectual Property; Machine Learning; machine based learning; programs; Source; Techniques; System; Benchmarking; Best Practice Analysis; benchmark; Services; Radiation Dose Unit; Radiation Dose; cancer risk; data management; Performance; success; Informatics; Health Insurance Portability and Accountability Act; HIPAA; Kennedy Kassebaum Act; PL 104-191; PL104-191; Public Law 104-191; United States Health Insurance Portability and Accountability Act; novel; peer; payment; Graph; Categories; Report (document); Document Type; Reporting; Radiation; software development; develop software; developing computer software; cancer diagnosis; patient safety; disparity in health; health disparity; preventing; prevent; Dose; U-Series Cooperative Agreements; Cooperative Agreements; Data; Clinical Data; Clinical/Radiologic; Development; developmental; Electronic Health Record; electronic health care record; electronic health medical record; electronic health plan record; electronic health registry; electronic medical health record; Image; imaging; Information Technology; Minority; firewall; comparative; financial reward; monetary incentive; financial incentive; Secure; imaging software; data visualization; data access; Radiography; Roentgenography; radiologic imaging; radiological imaging; facilities for imaging; imaging center; imaging-related facilities; imaging facilities; service organization; FHIR; Fast Healthcare Interoperability Resources; Patient imaging; DICOM; Digital Imaging and Communications in Medicine; Visualization; structured data; Equity; electronic health data
