Study Design
The study is a propensity-score matched retrospective cohort analysis. Eligible AIA members were enrolled in the intervention, the CancerAid Coach Program, from October 2018 to February 2020. A comparison group was created using the below criteria and then abstracted from deidentified records of patients who did not participate in the intervention (Fig. 1).
Recruitment and eligibility criteria
From October 2018 to February 2020, during routine calls following lodgment of a disability claim for a cancer diagnosis, AIA staff had private conversations with potential participants to elicit their interest in participating in the intervention. Eligibility for a disability claim included patients who: i) were of working age (18–65); ii) held a disability insurance policy through their insurer (AIA Australia) that included coverage of a cancer diagnosis; iii) were working prior to diagnosis and were unable to work in their regular prediagnosis capacity for at least 3 months. Program enrolment involved the AIA staff member eliciting interest and completing a secure web-form, followed by automated email outreach that included consent for the use of deidentified data for research purposes [17]. Inclusion criteria were defined as: i) completing enrolment and having at least one or more calls with a health coach; ii) a minimum follow-up time from diagnosis of 34 weeks to allow for completion of the intervention (median 10 weeks) along with delays in lodgment of the claim with the insurer (median 12 weeks) and a subsequent delay in referral to the CancerAid Coach Program (median 12 weeks); iii) diagnosis from top 10 commonest cancer types to enable adequate matching. Exclusion criteria were patients whose policies were later withdrawn or did not meet the eligibility criteria of their disability insurance policy.
Intervention
The CancerAid Coach Program provides a range of integrative therapies to help manage symptoms and adverse effects during or after treatment. The CancerAid Coach Program is based upon lifestyle and psychological interventions that are well established and consistent with ASCO guidelines (e.g. diet and exercise in survivors of cancer; peer support) [18, 19] or backed by evidence from large randomized trials (e.g. digital symptom tracking) [20].
The CancerAid Coach Program consists of an online e-health app and three telephone health coaching sessions delivered over a twelve-week period. Additionally, a series of weekly messages, via email and text, are sent to participants during the period of the intervention to help reinforce key health messages on appropriate symptom tracking, exercise, diet, mindfulness and sleep strategies. The CancerAid app allows patients to coordinate their care with tools to read about their condition, treatment options and a broader community of cancer survivors. It also allows patients to monitor their condition, specifically in relation to being able to track their symptoms digitally and monitor their diet, exercise, sleep and other patient level data at home via the app.
The health-coach team includes registered nurses, doctors and allied health professionals. Coaches offer a range of interventions tailored to the needs and current stage of each patient and use principles of behavioral change theories, such as the Transtheoretical model of Stages of Change [21]. These interventions include inviting patients to consider their current behavior; helping them consider the impacts of making change; providing encouragement, support and feedback on performance; encouraging patients to set further goals once existing goals are met, and finally, providing a framework of accountability.
Matched Comparison Group
The intervention group of Coach Program participants were matched on a one-to-one basis to a control group of nonparticipating insurance plan members who were otherwise eligible to participate using propensity scores. Controls were first collected from the AIA claims database over the same time period (October 2018 to February 2020) and using the same inclusion criteria: i) working age; ii) disability claim for a cancer diagnosis; iii) unable to work in their regular capacity for at least 3 months; iv) minimum follow-up time from diagnosis of 34 weeks; v) top 10 commonest cancer types. The likelihood of participating in the Coach Program was estimated using logistic regression. Independent variables included: age, gender, cancer diagnosis, date of cancer diagnosis, time to lodgment, insurance benefit type, occupation and designated regional area from 1 (major cities) to 3 (regional centres) [22].
A logit regression model was used to calculate a propensity score for each participant, to predict the probability that they would be referred to the CancerAid group. The covariates of the propensity model included age, gender, insurance benefit type, date of cancer diagnosis and time from diagnosis to lodgment of claim. Using the propensity scores, CancerAid participants were matched on a 1:1 basis using the nearest-neighbor method without replacement, to create a matched control group. The baseline characteristics were then re-assessed for imbalance between the CancerAid and the matched control group.
Assessment and Outcomes
Outcome measures were derived from insurance-claims data as standard business practice. Primary outcomes were the rate and time from cancer diagnosis to claim closure where the reason for claim closure was the successful RTW of the patient. Death and other reasons for claim closure were assessed. Other reasons for claim closure were a single lump sum payment (compared to scheduled salary replacement), expiry of benefit period (meaning the insurance policy had expired as set out in the policy’s schedule), no longer meeting the definition of disability (ie. return to health but not work) and abandonment of the claim.
Statistical Analyses
Statistical analysis was performed in R (Version 4.0.3). Difference in final RTW rate was tested using a chi-squared test without Yates correction. Time from diagnosis to RTW claim closure was calculated using a Kaplan-Meier model with a log-rank test.