Why LightSpeed Technologies
- Iris and facial fusion with patient ID error rate (0.00%) outperforms the best existing error rate of >7%
- 100% ID accuracy for large scale populations including regional & national ID
- Twins and all look-alikes are uniquely distinguished at national scale
- Instant ID proof of transaction with non-repudiation traceability
- Miniature camera can be instantly clipped to a monitor or embedded into device via USB
- Comfortable user interface with non-contact 3-second process
- Easy ergonomic design captures image zone from 14”~20”
- Stable iris patterns over life supports periodic facial template updates
- Cloud matching with search speeds of billions of records per second
- System compatible with 3rd party 2FA verification software by cell phone
Secure and Private
- Data is protected using multiple strong layers of security
- Separation and isolation of all your private demographic data from your biometric identity
- Privacy protected by PrivateID architecture (no demographic data used)
- ID fraud protection for all connected apps
Why Patient Identification Is Needed
Medical patient identification errors jeopardize patient safety, impede patient engagement, and result in serious financial inefficiencies for healthcare providers. A patient identification crisis is gripping hospitals’ EMPI and EHR systems. Patient identification errors threaten to harm patient safety, impact revenue cycle efficiency, and reduce profit margin and market share.
HIPAA has called for the creation of a national patient identifier to improve efficiency and safety. While patient-matching technology and processes have improved tremendously since HIPAA was enacted, a national patient identifier would still offer considerable efficiency and safety benefits and would remove a barrier to seamless interoperability.
Below are just a few statistics to further quantify this problem.
Annual patient deaths in the U.S. due to preventable medical errors
Percent of patient identification errors resulting in duplicate health records caused by inpatient registration mistakes, according to Johns Hopkins Hospital.
Percent of all records that have blank or default values in one of the key data fields of first name, last name, date of birth, gender, or Social Security Number
Studies show that 7-10% of patients are misidentified during health record searches and that 6% of identification errors result in an adverse event.