This study aims to investigate computer based symptom assessment in an outpatient cancer population, and the use of a computer based decision support system to facilitate the diagnosis and treatment of cancer related pain. Primary hypothesis is, that this approach improves pain control and pain management in an unselected group of cancer patients in an outpatient setting. * Improvement of average pain last 24 hours by at least 1.5 points on a 0-11 scale * Improvement of worst pain last 24 hours by at least 1.5 points on a 0-11 scale * An alteration in the prescribing dose of opioids in equipotent opioid dosage Secondary hypothesis is, that this system improves overall symptom control and symptom management in an unselected group of cancer patients in an outpatient setting.
The traditional way of symptom assessment is by the paper-and-pen method, which suffers from several limitations. The assessment items are not individually adjusted to each patient and his/her subjective symptoms, the collected data is rarely used in clinical practice, and decision-support for the physician is not possible. Although the body of evidence is accumulating regarding the benefits of computerised symptom assessment in cancer patients, there is still insufficient knowledge of the impact of computerised assessment tools on the management of cancer pain and other cancer related symptoms. The COMBAT study aims to investigate if a computer based assessment of cancer related symptoms, and a computerized decision support can improve treatment of pain and other symptoms in cancer patients. This is an open, comparative study with a sequential design with two consecutive study periods, the non-intervention period and the intervention period. The computer-based clinical decision support system will utilize the following data to generate one or several treatment options: 1. Data from self assessment of cancer related symptoms 2. Data from relevant variables reported by the physician 3. Revisited guidelines on treatment of cancer pain
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
255
Department of Oncology outpatient clinic, St Olavs Hospital
Trondheim, Norway
average and worst pain during the last 24 hours
\- The Brief Pain Inventory (BPI, a self-reported pain assessment tool aiming to quantify two aspects of cancer pain: Pain intensity and the functional disability as a result of cancer pain.
Time frame: 1 week
average and worst pain during the last 24 hours
\- The Brief Pain Inventory (BPI, a self-reported pain assessment tool aiming to quantify two aspects of cancer pain: Pain intensity and the functional disability as a result of cancer pain.
Time frame: 3 weeks
average and worst pain during the last 24 hours
\- The Alberta Breakthrough Pain Assessment Tool for cancer patients (ABPAT), a questionnaire developed in order to measure several dimensions of cancer-related breakthrough pain. It contains 15 questions, and was translated into Norwegian by our research group according to EORTC's rules for translation.
Time frame: 1 week
average and worst pain during the last 24 hours
\- The Alberta Breakthrough Pain Assessment Tool for cancer patients (ABPAT), a questionnaire developed in order to measure several dimensions of cancer-related breakthrough pain. It contains 15 questions, and was translated into Norwegian by our research group according to EORTC's rules for translation.
Time frame: 3 weeks
symptoms
\- The Edmonton Symptom Assessment System (ESAS), a validated standardized questionnaire consisting of 10 items, which evaluate physical and psychological symptoms as well as general wellbeing.
Time frame: 1 week
symptoms
\- The Edmonton Symptom Assessment System (ESAS), a validated standardized questionnaire consisting of 10 items, which evaluate physical and psychological symptoms as well as general wellbeing.
Time frame: 3 weeks
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