- Clinical content recognition software which finds patient details for you.
- Have consistent data entry with set data fields for each letter.
- Complete confidence in filing to the right patient record with a traffic light system to indicate the correct patient the letter concerns.
- Read Coding and Summarising is made easier with access to previous Read Codes without leaving Docman.
Features
Product Benefits
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Saves you time
60 seconds per document can be saved with Intellisense.
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Increase QOF points
Let Intellisense summarise your letters to help you get maximum QOF points.
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Greater accuracy
Have higher filing accuracy with Intellisense which finds patient details for you.
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Even more shortcuts
Keyboard shortcuts for even quicker filing to allow you to focus your efforts on patient care.
Technical Details
- Patient Identification – Intellisense will reduce the time it takes to file a document and improve data quality. Intellisense extracts patient demographic information from a document such as the NHS/CHI number, forename, surname and date of birth. This information is then used to match the document with the correct patient.
- Document Identification – Intellisense scans the text of a document, looks for keywords and uses pre-defined templates to assign the document with an accurate and detailed description. The information captured can include clinic date, letter type, hospital, department and consultant.
- Read Code Identification – having filed the document into the clinical record, Intellisense will search for diagnosis, procedure and value Read Codes within the document.
- Intellisense will alert you if you are trying to add a code that is already part of that patient’s record, allowing it to be added as a review of that problem instead. Intellisense will also alert you if you select a similar code to one already present in the patient’s record.
- Intellisense works with scanned documents as well, such as Microsoft Word, HTML, RTF, TXT and CSV documents. Scanned documents filed with Intellisense are automatically converted into text using Optical Character Recognition (OCR).