Currently, a vast amount of data is compiled in the electronic
patient record systems, both as numerical data (test results, etc.)
and as free-text data, and it is becoming an increasing challenge
to maintain the necessary overview of the contents of these patient
The purpose of RELIP is partly to prevent collection of data
that is already available in the patient record systems, and partly
to prevent staff from ignoring information that the patients expect
staff to be acquainted with or may be essential to patient
treatments and prognoses.
A software program (an algorithm) that provides automatic read
support will be developed as part of the project. The program can
combine selected data from patient records and thus provide
efficient staff decision support. The goal is to develop a software
program that will inform staff when patient record data reaches a
level that indicates a high probability of a complex alcohol
The Project Implementation
The project builds on an ongoing study (Relay) that
systematically collects data on diet, smoking, alcohol, and
exercise from more than 5,000 patients in selected somatic wards.
Patients who are screened as part of the Relay study and tested
positive for Alcohol Use Disorders (AUD i.e. diseases associated
with alcohol abuse), as well as those tested negative, will form
the nucleus of the RELIP project. The project will investigate
whether the patient records of the two groups differ on a number of
variables by analysing the patient log data. Text-based data will
be included and analysed using the method Natural Language
Processing. Existing biological/mathematical models and the results
obtained from the analyses will form the basis for the development
of an algorithm aimed at identifying an overconsumption of alcohol
or an addiction.
The project is divided into the following
Step 1: Data collected during the first year of the Relay study
will be analysed and AUD indicators identified by means of data
from the patient records (numeric, biological and free-text).
Step 2: Existing biological models (especially The SteatoNet
model) will be adjusted.
Step 3: The empirical findings from Step 1 and the biological
models from step 2 will be combined in an overall model.
Step 4: The overall model will be tested on patient data
achieved during the second year of the Relay study. The model's
validity and specificity will be tested.
Step 5: Development of a software program for clinical decision
Step 6: A qualitative study will be performed among patients and
staff to examine experiences and expectations in terms of using the
software program for clinical decision support.
Step 7: A protocol for implementing the software program for
clinical decision support in hospitals will be developed in
collaboration with clinicians.
Step 8: The business model will be analysed and include an
evaluation of economic and organisational perspectives of
implementing the software program.
Expectations are that the project results will lead to the
development of a prevention model that is based on advanced search
and language technology. The aim is to identify signs in the
patient records that a patient's lifestyle affects his/her medical
condition, thus paving the way for staff to actively involve the
patient and discuss how treatment can best be organised.