Autoscriber provides an AI-powered clinical documentation solution that automatically captures and structures patient encounters, including relevant medical codes like ICD10 and SNOMED. This technology significantly reduces administrative burden for healthcare practitioners, allowing them to focus more attention on patient care during consultations. The platform integrates directly with major Electronic Health Record (EHR) systems to streamline workflow and improve data quality.
Funding
$1.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Medical practitioners spend significant time on administrative tasks, manually typing notes into electronic health records (EHRs) after patient consultations. This administrative burden reduces the time available for patient care and can lead to healthcare worker burnout. Incomplete or unstructured data capture during consultations can also negatively impact data quality and patient outcomes.
Solution
Autoscriber offers an AI-powered EHR extension that automates medical note taking by converting patient consultations into structured summaries in real-time. The AI engine extracts discrete medical data from conversations and automatically incorporates SNOMED-CT and ICD-10 codes for accurate data capture at the source. By minimizing administrative time, Autoscriber enables medical practitioners to focus more on patients, reduces follow-up calls, and improves overall data quality for research and better patient outcomes. The platform adheres to ISO27001 and NEN7510 guidelines and cloud security best practices, ensuring secure and GDPR-compliant operation.
Target Audience
The primary target audience includes doctors, medical practitioners, neurologists, and CMIOs seeking to minimize administrative time, improve data quality, and enhance patient care within hospitals and healthcare organizations.
Features
- Real-time conversion of patient consultations into structured clinical notes
- Automatic extraction of discrete medical data, including medications and allergies
- Integration of SNOMED-CT and ICD-10 codes for accurate data capture
- Compliant with ISO27001, NEN7510, and GDPR guidelines
- Regular penetration testing to ensure security
- Utilizes Natural Language Processing (NLP), large language models, and Generative Pre-trained Transformers (GPT)