Princess Alexandra Hospital
Woolloongabba, Queensland, 4102, Australia
Location status: Recruiting
Location contact
Gerald Holtmann, PhD
CONTACT
Natasha Koloski, PhD
CONTACT
NCT Number: NCT05274854
This research project aims to test whether early interventions delivered remotely and prior to integrated care clinic appointments are effective. Patients with chronic unexplained gastrointestinal symptoms will initially undergo structured assessment of symptoms and wheat intolerance delivered remotely. Patients who continue to experience symptoms will then be randomised to a pre-consultation intervention ((a) standardised dietician supervised intervention, b) exercise intervention, c) internet delivered cognitive behavior therapy or d) nothing) followed by randomisation to the consultation intervention ((a) consultant-led outpatient clinic or b) a integrated care clinic depending on their response to the initial intervention.
Interested in participating?
Request Info18 year–90 year
All sexes
Interventional
Not applicable
Woolloongabba, Queensland, 4102, Australia
Location status: Recruiting
Gerald Holtmann, PhD
CONTACT
Natasha Koloski, PhD
CONTACT
An Effectiveness-Implementation Hybrid Design with a two stage randomisation will be used to determine and compare efficacy and cost-effectiveness of different management approaches/interventions for patients with relevant, chronic, or relapsing gastrointestinal symptoms without concerning features and on the wait list for integrated care clinic at the Princess Alexandra Hospital. Approximately 200 patients will initially receive standardised assessment of symptoms and wheat intolerance. Those patients that continue to experience symptoms will then be randomised to a pre-consultation intervention (a) standardised dietician supervised intervention, b) exercise intervention, c) internet delivered cognitive behavior therapy or d) nothing) followed by randomisation to the consultation intervention (a) consultant-led outpatient clinic or b) an integrated care clinic conditional on their response to the initial intervention. Specific aims of the study include Aim 1: Determine efficacy (symptom improvement) and cost-effectiveness (quality adjusted life years) of a structured, digital technology enabled approach for the management of patients with severe functional gastrointestinal disorders as compared to established service models; Aim 2: Identify response-predictors for the pre-clinical dietary intervention, internet delivered cognitive behavior therapy, exercise physiology and the various clinical interventions; Aim 3: Define acceptance of consumers and staff for the new service model relative to established models of care and Aim 4. To determine the dietary patterns of people with functional gastrointestinal disorders who are presenting with symptoms necessary to access tertiary care and to further examine changes in diet after a range of interventions delivered by telehealth.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Pre consultation interventions consist of one of four intervention a)standardised dietician supervised intervention, b) exercise intervention, c) internet delivered cognitive behavior therapy or d) nothing
Consultation intervention consists of one of two interventions a) consultant-led outpatient clinic or b) a integrated care clinic
Time frame: Week 0
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 8
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 16
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 20
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 24
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 28
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 32
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 35
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 38
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 44
Structured Assessment of Gastrointestinal Symptoms score: Assesses impact of various GI symptoms. SAGIS scores will be used to measure symptom type and symptom severity. Scores can range from 0 to 88. Higher scores indicate greater severity of symptoms
Time frame: Week 0
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 8
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 16
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 20
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 24
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 28
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 32
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 35
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 38
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 44
The EQ-5D is a preference-based health related Quality of Life measure. The maximum score of 1 indicates the best health state
Time frame: Week 0
To assess the cost-effectiveness and given the expected impact of the intervention on patient quality of life, a cost-utility analysis (CUA) will be conducted. The analysis will capture direct medical and non- medical costs including out-of-pocket expenses and indirect costs (e.g., lost productivity) based upon resources consumed using unit prices from standard costing resources. Quality-adjusted life-year (QALYs) gained will be weighted by their utility score (using the EQ-5D)
Time frame: Week 8
To assess the cost-effectiveness and given the expected impact of the intervention on patient quality of life, a cost-utility analysis (CUA) will be conducted. The analysis will capture direct medical and non- medical costs including out-of-pocket expenses and indirect costs (e.g., lost productivity) based upon resources consumed using unit prices from standard costing resources. Quality-adjusted life-year (QALYs) gained will be weighted by their utility score (using the EQ-5D)
Time frame: Week 16
To assess the cost-effectiveness and given the expected impact of the intervention on patient quality of life, a cost-utility analysis (CUA) will be conducted. The analysis will capture direct medical and non- medical costs including out-of-pocket expenses and indirect costs (e.g., lost productivity) based upon resources consumed using unit prices from standard costing resources. Quality-adjusted life-year (QALYs) gained will be weighted by their utility score (using the EQ-5D)
Time frame: Week 28
To assess the cost-effectiveness and given the expected impact of the intervention on patient quality of life, a cost-utility analysis (CUA) will be conducted. The analysis will capture direct medical and non- medical costs including out-of-pocket expenses and indirect costs (e.g., lost productivity) based upon resources consumed using unit prices from standard costing resources. Quality-adjusted life-year (QALYs) gained will be weighted by their utility score (using the EQ-5D)
Time frame: Week 44
To assess the cost-effectiveness and given the expected impact of the intervention on patient quality of life, a cost-utility analysis (CUA) will be conducted. The analysis will capture direct medical and non- medical costs including out-of-pocket expenses and indirect costs (e.g., lost productivity) based upon resources consumed using unit prices from standard costing resources. Quality-adjusted life-year (QALYs) gained will be weighted by their utility score (using the EQ-5D)
Time frame: Week 0
Anxiety and Depression scores from the Hospital Anxiety and Depression Scale. Scores can range from 0 to 21 for each subscale of anxiety and depression, respectively. Higher scores indicate greater frequency of anxiety and depression.
Time frame: Week 16
Anxiety and Depression scores from the Hospital Anxiety and Depression Scale. Scores can range from 0 to 21 for each subscale of anxiety and depression, respectively. Higher scores indicate greater frequency of anxiety and depression.
Time frame: Week 28
Anxiety and Depression scores from the Hospital Anxiety and Depression Scale. Scores can range from 0 to 21 for each subscale of anxiety and depression, respectively. Higher scores indicate greater frequency of anxiety and depression.
Time frame: Week 44
Anxiety and Depression scores from the Hospital Anxiety and Depression Scale. Scores can range from 0 to 21 for each subscale of anxiety and depression, respectively. Higher scores indicate greater frequency of anxiety and depression.
Time frame: Week 0
Total abundance and relative abundance of specific phyla of the microbiome
Time frame: Week 16
Total abundance and relative abundance of specific phyla of the microbiome
Time frame: Week 28
Total abundance and relative abundance of specific phyla of the microbiome
Time frame: Week 44
Total abundance and relative abundance of specific phyla of the microbiome
Time frame: Week 16
For the pre-consultation and the 3- months intervention period, the consumer's net promotor score ('…I would recommend the service I received to a family member or friend yes/no..') will be determined and compared. With regard to the team providing services to the patients, all members providing care will respond to the following question in relation to specific treatment groups: '...I have been able to address the patient's problems yes/no..'
Time frame: Week 28
For the pre-consultation and the 3- months intervention period, the consumer's net promotor score ('…I would recommend the service I received to a family member or friend yes/no..') will be determined and compared. With regard to the team providing services to the patients, all members providing care will respond to the following question in relation to specific treatment groups: '...I have been able to address the patient's problems yes/no..'
Contact information is provided by the study sponsor or research team.
Gerald Holtmann, MD, PhD
CONTACT
Natasha Koloski, PhD
CONTACT
The University of Queensland
Other
A Practice Change for Patients With Severe Chronic, Clinically Unexplained Gastrointestinal Symptoms: A Randomised, Controlled Intervention to Assess Efficacy and Cost-effectiveness
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