Overview

A large majority of medical data is stored as text, usually across a number of document types and storage locations. This unstructured content embedded in patient records can be tapped for a wealth of greater knowledge with HLA’s deep-dive search and analytics engines.

HLA technology has been developed to utilise unstructured clinical text through a range of functions including:

Report Classifying
Content Extraction
Inferencing
Keyword & Concept Search
Hot Key Abstracting & Coding

HLA’s technology uses semantics (i.e. the meaning of a word, phrase, sentence) and context (document structure and surrounding text) to identify a broad range of medical concepts within medical documents.

Our unique “Knowledge Discovery – Knowledge Reuse” methodology ensures that all knowledge captured in the creation of a client’s solution is integrated immediately into their technology. This enables rapid iteration to an optimal solution for their needs.

The HLA Wheel diagram shows the structure of our technology hub and the Language Technology Hub Applications table expands on the clinical and business uses of the various segments of the wheel.

Service Type	Application	Description/Example
Report Classifier	Document Separation	Separating documents based on defined classes (e.g. separating cancer from non-cancer reports).
	Work Streaming	Filter documents and route to correct staff or user-groups for processing (e.g. filter breast cancer reports from other tumour streams).
	Case Identification	Identifying a report that is needed for a particular task, e.g. identifying a reportable cancer case to send it to the cancer registry.
Inferencing	Cancer Staging	Convert tumour descriptions to stage.
Inferencing	Data Integration	Identify risks and automatically raise alarms.
Content Extraction	Risk Analysis	Automate extraction of content required to compute risk analysis profiles for patients.
	Convert Unstructured text to Structured data	Supply categorised data for BIG Data analytics, and quality audit databases.
	Epidemiology	Deliver and codify data for storage in population-based databases.
	Patient Safety Notifications	Daily extraction from pathology, imaging and other lab reports of diagnoses requiring clinical attention.
Concept Search	Cohort Identification	Find records with certain characteristics (e.g. All patients with prostate cancer).
	Case Studies	Identify patients who are current problematic cases so as to make comparisons.
	Case Review	Find specific cases without having to know their demographics (e.g. Clinician retrieving a certain case with a known medical history but no recollection of the patient’s identity).
	Content Retrieval	Ad-hoc general-purpose search for text-based records with given content.
	Multi-Disciplinary Team Meetings (MDTM)	Search for radiology, pathology, and other text notes in preparation for Oncology Multi-Disciplinary Team Meetings.
Report Completion Validation	Medical Record Coding	Ensure that all content that forms a complete record is included and flag missing content (e.g. flagging that “Plan” has not been included in a particular discharge summary).
Report Consistency Validation	Billing Errors & Omissions	Automatic computation of billing codes lowers errors and increases the number of chargeable items.
Report Consistency Validation	Unexpected Results	Ensure that content is consistent across a report (e.g. alerting a radiology report that has a diagnosis that is unexpected in the context of the requested investigation).
Hot Key Coding & Classification	Medical Records Coding	Add-on application that automatically suggests clinical codes for any on-screen content (e.g. suggesting codes in a pop up for a Discharge Summary in an EMR system).
Hot Key Coding & Classification	GP Coding	Code specific types of content (e.g. codifying reason for attendance at a General Practice or Emergency Department).