CDA-Compliant Section Annotation of German-Language Discharge Summaries: Guideline Development, Annotation Campaign, Section Classification

We present the outcome of an annotation effort targeting the content-sensitive segmentation of German clinical reports into sections. We recruited an annotation team of up to eight medical students to annotate a clinical text corpus on a sentence-by-sentence basis in four pre-annotation iterations and one final main annotation step. The annotation scheme we came up with adheres to categories developed for clinical documents in the HL7-CDA (Clinical Document Architecture) standard for section headings. Once the scheme became stable, we ran the main annotation campaign on the complete set of roughly 1,000 clinical documents. Due to its reliance on the CDA standard, the annotation scheme allows the integration of legacy and newly produced clinical documents within a common pipeline. We then made direct use of the annotations by training a baseline classifier to automatically identify sections in clinical reports.

Rationale for Quantification in Nursing Services Using the International Council of Nurses Nurse-Patient Summary

This review provides evidence that new data from nurses meets criteria that explains variation in hospital charges, length of hospital stay and end results of hospital care compared with ICD data; that nurses' data can be used to evaluate assignments of nurses to patients; that new data properly distinguishes patients' human needs within ICD categories. These new data are derived from the professional literature indexed and synthesized by Henderson. It is proposed to adopt the ICN-NPSum to standardize quantification in nursing services.

Enrich classifications in psychiatry with textual data: an ontology for psychiatry including social concepts

We propose a modular approach to develop an ontology of psychiatry, ONTOPSYCHIA, based on Patient Discharges Summaries (PDS) and divided into three modules (i.e. social, mental disorders and treatments). We decided to take into account the social aspects of the patient life described in PDS to consider information such as family history, social environment or education.

Are we talking about the same patient?

The objective of this study is to determine the degree of similarities between the clinical terms used by physicians and nurses in their documentation.

Design, development and first validation of a transcoding system from ICD-9-CM to ICD-10 in the IT.DRG Italian project

In Italy, ICD-9-CM is currently used for coding health conditions at hospital discharge, but ICD-10 is being introduced thanks to the IT-DRG Project. In this project, one needed component is a set of transcoding rules and associated tools for easing coders work in the transition. The present paper illustrates design and development of those transcoding rules, and their preliminary testing on a subset of Italian hospital discharge data.

Construction of the integrated multicentre discharge summary database

We started a multi-year project to collect discharge summaries from multiple hospitals and create a big text database to build a common document vector space, and develop various applications such as the autoselection of the disease. As the first step, we extracted discharge summary from two hospitals. Using a text mining method, we carried out a DPC selection. There was a difference in term structure and number of terms between the discharge summaries from both hospitals. Nevertheless, the selection rate of the disease is resembled closely.

A rule-based method for continuity of care identification in discharge summaries

Discharge summaries are an important clinical narrative as they include the continuity of care information. Identification of data contained in their text is a difficult task due to its freeform text and lack of consensus on essential content. This research proposes a rule-based method to verify the presence of information about continuity of care in Portuguese texts, applying Natural Language Processing (NLP) techniques, and based on an annotated medical corpus. After the experiments, 4 rules were defined and applied in the text of 200 summaries to identify if they have or not the continuity of care information. This process had resulted in Precision value of 84%, Recall value of 70%, Specificity value of 97% and F-Measure value of 76% related to algorithm evaluation.