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Trial registered on ANZCTR


Registration number
ACTRN12618001103257
Ethics application status
Approved
Date submitted
12/06/2018
Date registered
3/07/2018
Date last updated
18/07/2018
Type of registration
Prospectively registered

Titles & IDs
Public title
Improving cancer patients' reported pain outcomes through clinician mHealth training: a randomised controlled trial.
Scientific title
A phase III wait-listed RCT of a novel targeted inter-professional clinical education intervention to improve cancer patients’ reported pain outcomes.
Secondary ID [1] 293300 0
None
Universal Trial Number (UTN)
Trial acronym
CPAS Trial
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Cancer pain 305383 0
Condition category
Condition code
Cancer 304669 304669 0 0
Any cancer

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Clinician-focused, spaced learning pain assessment performance feedback intervention delivered via the Qstream™ platform

This mHealth intervention (‘intervention’) combines:
- an online spaced learning module that delivers authentic case-based cancer pain assessment scenarios directly to a clinician’s mobile device;
- real-time site-specific pain assessment audit and feedback, providing de-identified peer to peer comparisons; and
- online links to evidence-based pain assessment decision supports.

The intervention will be delivered via the online QStream™ platform directly to clinicians’ mobile devices (via a free app) or email. Participants will receive two cases every second day delivered via mobile app or email. Each case will take approximately 5 minutes to answer. Upon answering a case, participants will receive: immediate de-identified feedback on how they have performed compared to their peers; succinct audit and feedback data regarding site performance in the area of pain assessment; and links to additional evidence-based resources. Correctly answered cases will be re-sent after eight days, incorrectly answered cases will be re-sent every five days. Cases will no longer be sent once they have been correctly answered twice. We estimate the spaced learning module will be completed within 28 days.

Adherence to the intervention will be monitored weekly via report analytics built into the Qstream™ platform.
Intervention code [1] 299558 0
Treatment: Other
Comparator / control treatment
The control group will receive usual in-service, and be offered the intervention after 16 weeks.
Control group
Active

Outcomes
Primary outcome [1] 303881 0
Mean change in patients' pain numerical rating score ("NRS') (0–10) scores.
Timepoint [1] 303881 0
1. Immediately prior to start of intervention (T1)
2. Immediately after completion of intervention (T2) [primary timepoint]
3. 12 weeks after completion of intervention (T3)
Secondary outcome [1] 340348 0
Clinicians' pain screening/assessment adherence score
Timepoint [1] 340348 0
1. Immediately prior to start of intervention (T1)
2. Immediately after completion of intervention (T2)
Secondary outcome [2] 348059 0
Clinicians' Self-Perceived Pain Assessment Capabilities (Self-PAC) survey score
Timepoint [2] 348059 0
1. Immediately prior to start of intervention (T1)
2. Immediately after completion of intervention (T2)
Secondary outcome [3] 348058 0
Comprehensive pain assessment quality documentation score
Timepoint [3] 348058 0
1. Immediately prior to start of intervention (T1)
2. Immediately after completion of intervention (T2)
Secondary outcome [4] 348060 0
A cost-effectiveness analysis will be undertaken to evaluate the incremental resource use, cost and consequences of adding the mHealth enabled pain assessment performance feedback intervention to standard clinician CPD activities to improve cancer pain control.

A Markov decision model will be developed to estimate the cost-effectiveness of the mHealth intervention from a health care perspective.

Healthcare resource utilisation and cost data will be estimated from a systematic literature review of the direct and indirect costs of pain in cancer patients including hospitalisations, emergency department visits, outpatient clinic appointments, medications, GP visits and investigations.

Responder rates will be estimated from the project. The modelled economic evaluation will provide estimates of the incremental cost-effectiveness ratio and the incremental net monetary benefit (INMB).
Timepoint [4] 348060 0
August 1, 2018 to project completion (June 2020)

Eligibility
Key inclusion criteria
Clinicians
All medical and nursing personnel routinely caring for cancer and/or palliative care patients at a participating site are eligible to participate in the study. Participants must be willing to give written informed consent, and willing to participate to and comply with the study.

Patients
Medical records of all patients on the participating units, over 30 consecutive calendar days, will be screened for audit at each study time period (T1-T3). To be eligible, patients must: 1) have a primary diagnosis of cancer; 2) present for cancer treatment at a participating centre and/or have been referred to a specialist cancer/palliative care service; and 3) have pain at the time of first visit/appointment/admission or develop pain during the audit period.
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
Yes
Key exclusion criteria
Agency staff; casual staff who have worked less than one shift in the month before the intervention commences; Unregistered health professional who are unlikely to be undertaking and documenting patients’ pain assessment, e.g., Aged Care Workers (ACW), Personal Care Assistants (PCA), Care Support Employees (CSE) and Health Services Assistants (HSA).

Patients who: 1) are under 18 years; 2) do not have a cancer diagnosis on admission; do not have/develop cancer related pain during the audit period

Study design
Purpose of the study
Educational / counselling / training
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
The investigator(s) who determine if a subject is eligible for inclusion in the trial will be unaware, when this decision is made, to which group the subject would be allocated. Allocation will be undertaken by central randomisation by computer.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Simple randomisation using a randomisation table created by computer software
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Parallel
Other design features
Participants in the wait-listed control group will receive access to the intervention following completion of data collection in the intervention group (12 weeks post intervention).
Phase
Not Applicable
Type of endpoint/s
Efficacy
Statistical methods / analysis
Sample Size/Power Calculation
Informed by our pilot work and based on a standard RCT design, it is estimated that a sample size of 35 participants in each wait-listed arm is required. This assumes a 5% significance level and 90% power of the study with an effect size of a reduction of mean patient-reported pain rating of 1.5 (+2.0). Allowing for an attrition rate of 25%, and 5% for possible inclusion of covariates in the analyses, will increase the RCT sample size to 90 clinicians (45 in each wait-listed arm).

Statistical Analysis Plan
An intention-to-treat analysis applied to all primary and secondary outcomes. Missing data will be imputed using Multiple Imputation by Chined Equations (MICE). Should imbalance in clinicians’ characteristics be found between groups at baseline, these characteristics will be included in the final analyses as covariates to be controlled. A significance level of 5% will be adopted for refuting all test hypotheses. The intervention and wait-listed control arms will be compared on the primary and secondary outcome measures.

Interim analysis: An interim analysis will be undertaken immediately after 25 clinicians have completed the intervention with data collected at T2. At this time the corresponding 25 clinicians in the control arm will also be assessed for T2 data collection as described in the protocol. The reasons for nominating a sample of 25 in both intervention and control arms are: 1) based on the concept that an interim analysis is recommendable at the half way point of the trial (i.e. half of the RCT sample have completed the trial); 2) given that the total participants in each arm has been estimated to be 45, half of the sample will only be about 22 clinicians. This sample size would not be sufficient to support an accurate and precise comparison between groups. To ensure sufficient power for the interim analysis, a sample of 25 in each arm is considered reasonable. In order to stop the trial, we would need to demonstrate that a significant results of comparison between groups with an effect size of a reduction in mean patient-reported pain rating by at least 1.5 units in the intervention arm at an alpha level of 5% and preferably at 1%.

Primary outcome measures
Mean change in the pain NRS (0–10) scores, from admission to census date. As this is a pragmatic trial, all pain NRS scores will be captured during the chart audit process from the patients’ medical records. The NRS is the optimal brief measure of pain severity on the basis of compliance rates, responsiveness, ease of use and applicability, and is also recommended by the Australian Cancer Pain Management in Adults Guidelines. We will examine the degree of agreement between these chart auditors to determine agreement. The inter-rater reliability will be calculated using: Kappa statistics for categorical variables; and the Bland and Altman method of plots and limits of agreement for continuous variables.

Secondary outcome measures
Pain screening/assessment adherence score; comprehensive pain assessment quality documentation score; Self-Perceived Pain Assessment Capabilities (Self-PAC) survey.

Economic outcomes
Efficacy (pain score; adherence score; Self-PAC score) and resource use (intervention, i.e. clinician and administration time; Qstream platform; standard CPD, including clinician time) data.

Data analysis
1. The primary endpoint (reduction in mean pain NRS scores) will be analysed using the Linear Mixed Method (LMM) using a repeated measures approach with possible adjustments to patients’ and staff characteristics to compare the mean change in patient pain NRS scores from admission to discharge or audit date between the intervention and control groups across different time points.
The secondary endpoints will be analysed as follows:
2. The frequency of comprehensive pain assessment between the intervention and control will be determined by differences between groups. As the outcome variable is a count variable without a fixed bound, Poisson regression with possible adjustments for covariates will be applied to the data.
3. A quality score will be calculated for each audited record across time and entered into the patient’s medical records. This score will reflect the quality of the pain documentation in the medical notes and will be calculated using seven items of documentation (pain severity score, location, radiation, aggravating and alleviating factors, quality, and timing). One mark will be assigned to an item identified in the medical records and a summative quality score will then be calculated to represent the total amount of information recorded. A higher quality score represents a larger amount of pain assessment information recorded and a greater adherence to recommended pain assessment practices. The quality of pain assessment documentation will be determined by comparing the quality scores across time and between groups using a General Linear Model with repeated measures.
4. The mean scores of the three domains of the Self-PAC survey (pain assessment knowledge, pain assessment tool knowledge and pain assessment confidence) will be compared across time and between the intervention and control groups using the General Linear Model with repeated measures approach and with possible adjustments for covariates effects.
5. The primary objective of the cost-effectiveness analysis is to evaluate the incremental resource use, cost and consequences of adding the mHealth enabled pain assessment performance feedback intervention to standard clinician CPD activities to improve cancer pain control. A Markov decision model will be developed to estimate the cost-effectiveness of the mHealth intervention from a health care perspective. Healthcare resource utilisation and cost data will be estimated from a systematic literature review of the direct and indirect costs of pain in cancer patients including hospitalisations, emergency department visits, outpatient clinic appointments, medications, GP visits and investigations. Responder rates will be estimated from the project. The modelled economic evaluation will provide estimates of the incremental cost-effectiveness ratio (incremental cost per additional responder, response = a 2-point mean reduction in NRS pain score) and the incremental net monetary benefit (INMB) [monetary value of additional effects of care minus the additional costs of care] at potential threshold values for responder rates and cost-effectiveness acceptability curves. Model sensitivity to variations in individual inputs and overall decision uncertainty will be assessed through probabilistic sensitivity analyses.

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
1/08/2018
Actual
Date of last participant enrolment
Anticipated
31/07/2019
Actual
Date of last data collection
Anticipated
31/12/2019
Actual
Sample size
Target
90
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
NSW
Recruitment hospital [1] 9356 0
Neringah Hospital - Wahroonga
Recruitment hospital [2] 9952 0
Concord Repatriation Hospital - Concord
Recruitment hospital [3] 9358 0
Prince of Wales Hospital - Randwick
Recruitment hospital [4] 9357 0
Braeside Hospital - Prairiewood
Recruitment hospital [5] 9354 0
Calvary Mater Newcastle - Waratah
Recruitment hospital [6] 9355 0
Greenwich Hospital - Greenwich
Recruitment postcode(s) [1] 18032 0
2176 - Prairiewood
Recruitment postcode(s) [2] 18031 0
2076 - Wahroonga
Recruitment postcode(s) [3] 18766 0
2139 - Concord
Recruitment postcode(s) [4] 18029 0
2298 - Waratah
Recruitment postcode(s) [5] 18030 0
2065 - Greenwich
Recruitment postcode(s) [6] 18033 0
2031 - Randwick

Funding & Sponsors
Funding source category [1] 297925 0
Government body
Name [1] 297925 0
Cancer Australia: Priority-driven Collaborative Cancer Research Scheme
Country [1] 297925 0
Australia
Primary sponsor type
University
Name
University of Technology Sydney
Address
PO Box 123, Ultimo NSW 2007
Country
Australia
Secondary sponsor category [1] 296987 0
None
Name [1] 296987 0
Address [1] 296987 0
Country [1] 296987 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 298971 0
South Eastern Sydney Local Health District HREC
Ethics committee address [1] 298971 0
Ethics committee country [1] 298971 0
Australia
Date submitted for ethics approval [1] 298971 0
02/02/2018
Approval date [1] 298971 0
30/05/2018
Ethics approval number [1] 298971 0
HREC ref 17/322 (HREC/18/POWH/90)

Summary
Brief summary
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 78842 0
Prof Jane Phillips
Address 78842 0
IMPACCT – Improving Palliative, Aged and Chronic Care through Clinical Research and Translation
University of Technology Sydney
235 Jones St. Ultimo NSW 2007
PO Box 123 Broadway NSW 2007 Australia
Country 78842 0
Australia
Phone 78842 0
+61 2 9514 4862
Fax 78842 0
Email 78842 0
jane.phillips@uts.edu.au
Contact person for public queries
Name 78843 0
Nicole Heneka
Address 78843 0
IMPACCT – Improving Palliative, Aged and Chronic Care through Clinical Research and Translation
University of Technology Sydney
PO Box 123 Broadway NSW 2007 Australia
Country 78843 0
Australia
Phone 78843 0
+61 2 9514 3545
Fax 78843 0
Email 78843 0
CPAS@uts.edu.au
Contact person for scientific queries
Name 78844 0
Jane Phillips
Address 78844 0
IMPACCT – Improving Palliative, Aged and Chronic Care through Clinical Research and Translation
University of Technology Sydney
235 Jones St. Ultimo NSW 2007
PO Box 123 Broadway NSW 2007 Australia
Country 78844 0
Australia
Phone 78844 0
+61 2 9514 4862
Fax 78844 0
Email 78844 0
CPAS@uts.edu.au

No information has been provided regarding IPD availability


What supporting documents are/will be available?



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
SourceTitleYear of PublicationDOI
EmbaseA phase III wait-listed randomised controlled trial of novel targeted inter-professional clinical education intervention to improve cancer patients' reported pain outcomes (The Cancer Pain Assessment (CPAS) Trial): Study protocol.2019https://dx.doi.org/10.1186/s13063-018-3152-z
N.B. These documents automatically identified may not have been verified by the study sponsor.