Summary
Background: Clinical information is often stored as free text, e.g. in discharge summaries or
pathology reports. These documents are semi-structured using section headers, numbered
lists, items and classification strings. However, it is still challenging to retrieve
relevant documents since keyword searches applied on complete unstructured documents
result in many false positive retrieval results.
Objectives: We are concentrating on the processing of pathology reports as an example for unstructured
clinical documents. The objective is to transform reports semi- automatically into
an information structure that enables an improved access and retrieval of relevant
data. The data is expected to be stored in a standardized, structured way to make
it accessible for queries that are applied to specific sections of a document (section-sensitive queries) and for information reuse.
Methods: Our processing pipeline comprises information modelling, section boundary detection
and section-sensitive queries. For enabling a focused search in unstructured data, documents are automatically structured
and transformed into a patient information model specified through openEHR archetypes.
The resulting XML-based pathology electronic health records (PEHRs) are queried by
XQuery and visualized by XSLT in HTML.
Results: Pathology reports (PRs) can be reliably structured into sections by a keyword- based
approach. The information modelling using openEHR allows saving time in the modelling
process since many archetypes can be reused. The resulting standardized, structured
PEHRs allow accessing relevant data by retrieving data matching user queries.
Conclusions: Mapping unstructured reports into a standardized information model is a practical
solution for a better access to data. Archetype-based XML enables section-sensitive retrieval and visualisation by well-established XML techniques. Focussing the retrieval to
particular sections has the potential of saving retrieval time and improving the accuracy
of the retrieval.
Keywords
Standardized electronic health record - electronic health record system - medical
infor - matics applications - openEHR - information retrieval - section boundary detection
