The ease in which protected health information (PHI) is shared, accessed, and analyzed has a direct impact on clinical productivity, patient care coordination, and health outcomes. Today, clinicians still spend a considerable amount of time typing in, clicking through, and editing electronic health records (EHR). Manually keying-in patient data into fields is not only time-consuming and inefficient, but it can also lead to medical errors if any of the information is typed incorrectly.
This is a huge concern. Data must be accurate and up to date in order to be reliably used. Any delay in accessing, extracting, and exporting patient data can also prevent test results, prescriptions, and insurance information from being processed efficiently. Failure to submit clinical documentation in a timely manner to support authorization requests could result in insurance claim denials and delayed treatment.
Healthcare organizations searching for an innovative solution to enhance workflows and clinical decision-making should consider utilizing cognitive services for automated data extraction.
Leveraging artificial intelligence (AI) technology, automated data extraction enables organizations to quickly transform content locked in unstructured documents such as PDFs and paper-based forms into structured, searchable data ready to be integrated into workflows, applications, or EHRs. Extracted data can then be mapped to third-party systems, allowing tasks such as indexing patient records, scheduling, and referrals to be automated. This virtually eliminates error rates associated with manual data entry and improves data quality throughout the entire organization.
Paul Banco, CEO and co-founder of ETHERFAX, discussed the benefits of automated data extraction in HIT Consultant. Read his article here.
