Overview
Ethics, privacy and confidentiality
This research has been approved by the University of Calgary Conjoint Health Research Ethics Board (REB20-0543) and the University of Alberta Health Research Ethics Board Biomedical Panel (Pro00107116). Any protocol deviations will be approved in advance by the Board and updated in the clinical trials registry. All participants will provide written, informed consent prior to data collection (Additional file 1). Participant data will be anonymized and stored on a password protected University server. Only the Principal Investigators and Research Coordinators will have access to identifiable participant information and the final trial datasets.
Setting
This research will take place in Alberta, Canada. Participants will be recruited through primary care and diabetes specialty clinics located in urban and rural communities, including clinics with an explicit focus on serving people identifying as Indigenous.
Study oversight
Scientific Steering Committee
A Scientific Steering Committee will oversee all aspects of the research, receive and review reports from the study’s Advisory Boards and Subcommittees, and will have final decision-making authority. It will be comprised of the study’s five co-Principal Investigators (DLO, ES, RFB, LL, DJTC).
Advisory Board
A multi-stakeholder Advisory Board will provide high-level oversight for the research and will advise the Scientific Steering Committee on study conduct. Members will include policymakers, academic experts, representatives from Alberta Health Services (the provincial health authority), an Indigenous public health expert and a patient.
Indigenous Advisory Board
An Indigenous Advisory Board will ensure that research activities within Indigenous clinics proceed in a culturally sensitive, relevant, responsive, equitable and reciprocal manner that is guided by OCAP (Indigenous Ownership, Control, Access and Possession of data) principles [67] and complies with Government of Canada guidance for Indigenous Research [68, 69]. The Board will include Indigenous Elders and patients, along with academic experts, policymakers, managers and front-line practitioners from the public health and healthcare sectors who are themselves Indigenous, or who work closely with Indigenous peoples.
Primary Care Clinic Subcommittee
The Primary Care Clinic (PCC) Subcommittee will include PCC managers, staff and patients. As participant recruitment and implementation of the intervention unfolds, PCC managers and staff will collect feedback from their respective clinics and will share it with the larger group as a learning tool and to inform ongoing adaptations.
Implementation Support Team
The Implementation Support Team will consist of Research Coordinators and Assistants who will execute the daily tasks required to administer, plan, support, monitor and evaluate the subsidized healthy food prescription program.
Patient and public involvement
This research has been informed by substantial prior [70-74] and ongoing engagement with patients experiencing financial barriers to chronic disease care. Patients (who are not study participants) will help to pilot test infrastructural supports (e.g. healthy food prescription pamphlet, usability of the subsidy list), care pathways and implementation processes, and will be members of the Advisory Boards and PCC Subcommittee. Patients who are study participants will provide continuous program feedback via a dedicated study help-line/email, and by completing implementation fidelity checklists. At the conclusion of the study, participants will be invited to describe their program experiences via a post-intervention questionnaire and during in-depth, semi-structured interviews.
Lands and food hold deep cultural, symbolic and spiritual significance for Indigenous peoples [75]. Staff and patients from Indigenous PCCs will co-design clinical care pathways and other procedures that are context-specific and culturally appropriate for Indigenous patients, and that respect and promote Indigenous worldviews, particularly those surrounding food procurement and consumption. We will ensure that representatives from Indigenous clinics are involved at all stages of the research, including study design, pilot testing infrastructural supports, interpreting results and formulating conclusions, and that their agreement is obtained prior to communicating any research findings that pertain to them. As previously described, the Indigenous Advisory Board will also oversee all aspects of the research.
Evaluation framework and theory of change
RE-AIM [65, 66] will provide a structured means of integrating data from the RCT, modelling and implementation studies to understand the reach, effectiveness, adoption, implementation and maintenance of the subsidized healthy food prescription program.
Our theory of change draws on Barnard et al’s [76] conceptual model linking material needs insecurities with diabetes outcomes, and posits that reduced food insecurity and improved diet quality will be key mediators of improved blood glucose levels, which will help to reduce diabetes complications, and healthcare resource use and costs. Each construct will be examined to affirm or disprove the proposed pathway (Figure 1).
Randomized controlled trial
The RCT protocol adheres to the SPIRIT and TIDieR reporting guidelines (Table 1; Additional File 2-4).
Study design and objectives
A 6 month, parallel-group RCT will examine the effectiveness of a subsidized healthy food prescription program, compared to a healthy food prescription alone, in improving the following outcomes among 404 adults who are experiencing food insecurity and persistent hyperglycemia (i.e. A1C 8-12%):
1) Primary outcome: Average blood glucose levels measured by A1C
2) Secondary outcomes:
- Blood glucose levels: Proportion of patients with elevated A1C (i.e. ≥ 9%); blood glucose measured by fructosamine
- Dietary intake: Diet quality; skin carotenoids
- Intermediate clinical outcomes: Blood lipids; blood pressure; body mass index (BMI); waist circumference; need for diabetes medication/insulin
- Patient-reported outcomes: Psychosocial well-being; self-rated health; diabetes self-efficacy; diabetes self-management; diabetes distress; diabetes competing demands; perceived financial barriers to chronic disease care; hypoglycemic episodes; household food insecurity
3) Exploratory outcomes: Subjective social status; perceived income adequacy; work productivity and activity impairment; medication and physical activity adherence
Primary care clinics
PCCs will be recruited, including urban, rural and Indigenous clinics. To be eligible, clinics must serve lower-income patients, agree to allow their physicians, Registered Dietitians and/or nurses to dispense healthy food prescriptions, appoint a staff member to liaise with the Implementation Support Team, and be willing to receive training. The final list of study sites, currently projected at 30 clinics, will be available in the clinicaltrials.gov registry.
Participants
PCCs will use information from electronic medical records to identify patients with T2DM and persistent hyperglycemia (i.e. A1C 8-12%), including patients living in rural and urban areas, and those who identify as Indigenous. Potentially eligible patients will be invited to complete a brief screening questionnaire, including the validated two-item hunger vital sign, which is 97% sensitive and 83% specific for food insecurity [77-79]. Eligible patients will be adults (18-85 years) with persistent hyperglycemia (i.e. A1C 8-12%) who are experiencing food insecurity, who are not currently on intensive insulin therapy (multiple daily injections or continuous subcutaneous insulin infusion), do not reside in a facility that provides meals (e.g. shelter, long term care, prison), and can communicate in English or have someone to translatePatients will be excluded if they have an A1C < 8% or > 12% (given the recommendation for anti-hyperglycemic treatment escalation for those with A1C > 12%), have signs/symptoms of metabolic decompensation, have an eating disorder, are functionally dependent, have limited life expectancy (< 2 years), have experienced diabetic ketoacidosis or a hyperglycemic hyperosmolar emergency in the past 2 years, have a history of recurrent severe hypoglycemia or hypoglycemic unawareness, or if they have been diagnosed with dementia. Patients will also be excluded if they are pregnant or trying to conceive, breastfeeding, participating in other clinical trials, if someone in their household is currently or has previously participated, if they will no longer reside within 100km of a participating supermarket in the next 6 months, if they plan to leave Canada for more than 2 weeks in the next 6 months, or if they will not be able to complete data collection at 6 months (e.g. due to moving).
Eligible patients will be asked to provide consent to their healthcare provider to be contacted by the research team. A Research Assistant will contact patients to confirm all eligibility criteria have been met, obtain informed consent and provide instructions for collection of baseline data. Participants may elect to report baseline patient-reported data immediately over the telephone, or independently via the study’s online data collection platforms. Any patients identified as food insecure at screening using the two-item hunger vital sign, but who do not respond affirmatively to any of the items on the full 18-item Household Food Security Survey Module during baseline data collection will be excluded. Participants will have biochemical and physical measurements performed at a community laboratory or at their PCC. Participants with an A1C outside the 8-12% range will be excluded at that point. All participants will subsequently receive a healthy food prescription pamphlet from their healthcare provider (i.e. physician, nurse, Registered Dietitian) and a brief, high-level overview of its contents using standardized teaching guidelines, either virtually or in-person during a clinic visit.
Sample size calculation
Based on local administrative data, we expect a mean baseline A1C of 9.1% (SD=1.0%) in our sample (i.e. individuals with A1C 8-12%) [80]. Assuming 5% type I error, 35% attrition [81] and potential design effects based on sampling in different clinics (25% inflation), 403 participants are required for 95% power to detect a difference in A1C of 0.5%, which is often considered a minimally important clinical difference [17].
Randomization and blinding
Following baseline data collection and delivery of the healthy food prescription pamphlet, participants will be randomized to a subsidized healthy food prescription intervention (n=202) or a healthy food prescription comparison group (n=202) with a 1:1 allocation ratio using a computer-generated, concealed, blocked randomization sequence created by an independent statistician. Blocking variables will include gender, clinic type location (urban, rural, Indigenous) and baseline A1C (8-9%, 9-12%). Allocation concealment will be ensured via secure storage of the randomization sequence separately from the participant database, which will only be accessible by the statistician. To ensure researcher blinding, randomization will be operationalized via REDCap (Research Electronic Data Capture) following completion of baseline data collection. Intervention assignment will be communicated by Research Assistants via a telephone call. Participants cannot be blinded to treatment allocation, however details of the healthy food subsidy, including its monetary value and the types of foods that are eligible, will not be divulged to participants in the comparison group. Care providers and individuals who collect biochemical and physical measurements will be blinded to group allocation.
Intervention
Development of the subsidized healthy food prescription program was informed by the social prescribing literature, EQUIP (Research to Equip Primary Healthcare for Equity) principles of equity-oriented healthcare [82], initiatives elsewhere (e.g. Wholesome Wave [83]), and stakeholder consultation. The comparison group will receive a one-time healthy food prescription pamphlet. The intervention group will receive a one-time healthy food prescription pamphlet and a 6 month subsidy of $1.50/day/household member (e.g. household of four receives $42/week) to purchase healthy foods in study-affiliated supermarkets. Thus, the study is designed to test the impact of a healthy food subsidy, which is an intervention that targets economic rather than knowledge-related barriers to healthy eating. Aside from labelling the nutritional advice delivered as a “prescription” (which may have some independent impact on participants’ behaviour), the healthy food prescription closely mimics current care (i.e. nutrition counselling) and is unlikely to substantially change dietary intake in the context of severe economic constraints [84-89]. The subsidy amount exceeds the benefit provided by similar US programs (e.g. [56, 83]) in order to more closely bridge the gap in food spending between food secure and insecure households in Canada [90]. In their systematic review, Rao et al (2013) demonstrated that a subsidy of $1.50/day was associated with greater compliance with a Mediterranean style dietary pattern. The subsidy amount that each household receives will be determined based on household size at baseline; this amount will remain consistent throughout the intervention regardless of changes in household size. A household member is defined as a partner or a dependent child or adult who resides at the same location at least 50% of the time. Finally, the intervention will be delivered over 6 months to allow sufficient time for dietary changes to be reflected in approximately two A1C cycles [91].
The healthy food prescription pamphlet was designed by Registered Dietitians and modelled after a previous food prescription program to be a visually appealing, low literacy resource [92] (Additional File 5). The cover page contains the following pre-printed prescription “I prescribe a healthy eating pattern of minimally processed foods that have little to no added fat, sugar or salt,” with space for the care provider to add their signature, date, and patient information. The inner pages outline an evidence-based healthy dietary pattern, with key messages to consume a variety of whole, minimally processed foods from all food groups with little to no added fat, sugar or salt, to spread carbohydrate foods over the day, to satisfy thirst with water, and to avoid sugary drinks, refined grains, sweets, confectionary and desserts [7, 93]. A diabetes-appropriate recipe is provided along with links to connect patients with sources of free/lower-cost food, additional recipes, nutrition information, other helpful community services and sources of emergency food assistance. Feedback from PCC staff and patients and the Advisory Boards was incorporated into the final version of the pamphlet.
The healthy food subsidy can be used to purchase whole, minimally processed foods with little to no added fat, sugar or salt from all food groups [7, 93] (Table 2). Ineligible items include beverages (except white milk), refined grains, sweets and other foods with excess fat, sugar or salt. A pilot-tested PDF booklet was created with pictures of eligible items to assist participants to locate eligible items and Research Assistants will review the list of subsidized foods and subsidy redemption procedures with participants prior to the intervention. Participants in the intervention group can redeem their food subsidies at participating supermarkets located throughout Alberta. Subsidies will be loaded onto participants’ store loyalty card weekly, and dollars-off discounts will be automatically applied on subsidy-eligible foods at the point-of-purchase. The entire food subsidy must be spent during a single shop, either in-person or using a pick-up service. Subsidies not redeemed within the week will expire. To minimize potentially stigmatizing experiences, all participants in the intervention group will receive a one-time unrestricted grocery gift card valued at $30. The grocery gift card can be used in the event that participants inadvertently exceed their subsidy amount and lack funds to cover the additional costs. Participants will also have access to a study email and telephone help-line where they can ask study-related questions.
Table 2
Foods that qualify for the healthy food subsidy
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Food group
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Eligible items
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Vegetables and fruits
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Fresh vegetables and fruit
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Frozen vegetables and fruit
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Canned vegetables
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Meat, poultry and fish
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Fresh meat, poultry and fish
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Canned fish
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Meat alternatives
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Dried or canned lentils, chickpeas or beans
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Whole eggs
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Whole almonds
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Dairy products
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White cow’s milk
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Unsweetened fortified soy beverage
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Plain yogurt
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Hard cheddar cheese
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Whole grain foods
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Whole grain pasta
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Brown rice
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Large flake rolled oats
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100% whole wheat bread
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Bran Flakes cereal
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Data collection
To support retention, all participants (regardless of treatment allocation) will receive $100 following completion of data collection at baseline (0 months) and again at follow-up (6 months).
Questionnaires
Electronic questionnaires will encompass sociodemographic and health-related items, dietary intake in the previous 24 hours, and a variety of patient-reported outcomes. The final questionnaires will be reviewed by the Advisory Boards and Scientific Steering Committee to establish face and content validity, and will be pre-tested with patients.
Sociodemographic and health-related variables will be recorded in REDCap using existing items from the Canadian Community Health Survey where available [94], including date of birth, sex at birth, gender identity, race/ethnicity, years lived in Canada, household size and composition, number of household members with T2DM, educational attainment, employment status, marital status, annual household income, main income source, access to extended health benefits, participation in income support programs, smoking status, housing status, medication/insulin type and dose, duration of diabetes and physical activity level [95].
Patient-reported outcomes will be assessed using the following validated scales: World Health Organization well-being scale [96], Stanford Diabetes Self-Efficacy Scale [97, 98], Diabetes Self-Management Questionnaire [99, 100], Problem Areas in Diabetes Scale-5 to assess diabetes distress [101], EQ-5D-5L to assess self-rated health [102], hypoglycemic episodes [30], Work Productivity and Activity Impairment Questionnaire [103], Health Canada’s Household Food Security Survey Module to assess experiences of marginal, moderate and severe household food insecurity in the past 6 months [104-106] and medication adherence [107]. We will also assess diabetes competing demands [108] and perceived financial barriers to chronic disease care, the latter of which has undergone testing via focus groups and cognitive interviews [109]. Subjective social status will be assessed using the MacArthur Scale of Subjective Social Status national and community ladders [110, 111]. Participants will report perceived income adequacy by answering the question: “Thinking about your total monthly income, how difficult or easy is it for you to make ends meet?” [112-114].
Quality of dietary intake will be assessed using the online Automated Self-Administered 24-hour Dietary Recall for Canada (ASA24-Canada-2018) whereby all participants will report all foods and beverages consumed from midnight to midnight the previous day, including location of consumption and dietary supplements [115-117]. The ASA24 has demonstrated good correspondence with standardized interviewer administered dietary recalls and with true intakes [116, 118]. Participants will receive an unannounced email/text 2-4 days later prompting them to complete a second dietary recall to provide a more precise estimate of usual intake [119]. Dietary intake data will be used to calculate a Healthy Eating Index-2015 score from 0-100 for each participant, which provides a valid assessment of overall diet quality consistent with recommendations in the healthy food prescription pamphlet [120, 121].
To reduce missing data, REDCap will be configured to require a response prior to proceeding to the next question, although ‘don’t know’ and ‘refuse to answer’ will be response options. Research Assistants will also review all completed questionnaires and will telephone participants within 24 hours to request responses to any unanswered questions.
Clinical measurements
Biochemical measurements will include quantification of blood glucose levels via A1C (standardized to the Diabetes Complications and Control Trial [122-125]) and fructosamine, as A1C can be unreliable for some patients and fructosamine is more sensitive to acute changes [126]. Blood lipids (total-, HDL- and LDL-cholesterol, triglycerides, apolipoprotein B), serum creatinine (to calculate estimated glomerular filtration rate), albumin-to-creatinine ratio and hemoglobin concentration will also be quantified. Participants will provide a urine sample to detect albuminuria. All samples will be analyzed by Alberta Precision Laboratories and DynaLIFE Medical Labs.
Physical measurements will adhere to standardized measurement protocols and will be performed a minimum of two times by trained researchers/clinicians, including weight and height to calculate BMI, waist circumference, systolic and diastolic blood pressure (using oscillometric devices approved by Hypertension Canada) and heart rate. Skin carotenoids will be assessed using Pharmanex Biophotonic Scanners as biomarkers of fruit and vegetable intake [127].
Administrative health data
A1C levels and information on comorbidities and diabetes complications will be obtained from Alberta Health Services’ Analytics, Data Integration, Measurement and Reporting database. The secondary outcome of need for diabetes medication/insulin will be quantified by monitoring changes in medication/insulin use (i.e. initiation or discontinuation), type (i.e. Metformin, Sulfonylureas, Repaglinide, DPP-4 inhibitors, GLP1 receptor agonists, SGLT2-inhibitors, Acarbose, Thiazolidinediones, Statins or other lipid-lowering agents, Renin-angiotensin aldosterone antagonists and other anti-hypertensive agents) and dosage recorded in the Pharmaceutical Information Network Database [128]. We will also collect administrative data on health events and healthcare use on an ongoing basis post-intervention to support understanding of longer-term outcomes.
Implementation fidelity
Implementation fidelity will be continuously assessed using a combination of quantitative and qualitative measures as part of the implementation study (described below).
Data monitoring and adverse events
We have not established stopping guidelines or a data monitoring committee as the intervention is low-risk. In addition, physicians will be free to adjust patients’ medication regimens to achieve improved glycemia, although they will be asked to initiate or uptitrate insulin therapy only when absolutely necessary. Given that serious adverse events are unlikely, adverse events will not be monitored and no provisions have been made for compensation. Interim analyses will not be conducted. At the conclusion of the study, participants will continue to be followed by their care providers.
Data analysis
Mixed-effects linear and multinomial logistic/ordinal regression will assess group differences in outcomes at follow-up, adjusted for baseline values of each outcome, blocking variables and covariates (specific to each outcome), with subgroup analyses by gender, rural and Indigenous status, baseline A1C (8-9%, 9-12%) and insulin use. Participant- and PCC-specific variations will be modeled using random effects. A dose-response analysis will examine whether outcomes depend on the value of food subsidies redeemed. Missing data will be handled using full information maximum likelihood under a missing at random assumption. Analyses will be intention-to-treat using all available data.
For the primary outcome of blood glucose levels, covariates will include the following: age, gender, race/ethnicity, educational attainment, years lived in Canada, number of children living in the home, marital status, change in number of household members since baseline, access to extended health benefits, participation in other income support programs, diabetes duration, and physical activity level.
Sensitivity analyses
Sensitivity analyses will examine outcomes among patients whose diabetes medication/insulin regimen was unchanged during the 3 months prior to the study, throughout the study period, and when patients taking insulin are excluded. We will also examine the impact of excluding patients who were started on lipid-lowering or anti-hypertensive therapy from models assessing impact on blood lipids and blood pressure, respectively. Additional sensitivity analyses will consider the impact on findings when food insecurity is modelled as a continuous, rather than as a categorical outcome [129], and when an indicator of energy intake misreporting (i.e. the ratio of reported energy intake to estimated energy expenditure) is included in models assessing impact on diet quality.
We will also consider the impact on findings when models are adjusted for changes in medication/insulin type and dosage that occurred between baseline and follow-up. We propose to use a novel scoring system that attempts to match the changes made with the expected clinical impact on A1C [130]. The following changes will be assigned 1 point (expected change in A1C of ~0.5%): less than full dose of Metformin (< 2000mg/day), Sulfonylureas (Gliclazide < 60mg/day, Glyburide < 10mg/day), or Repaglinide (<5mg/day); any dose of DPP-4 inhibitor, SGLT2-inhibitor or Acarbose; initiation of basal insulin or insulin adjustment by < 20% of total daily dose. Two points (expected change in A1C of ~1%) will be assigned for: full dose of Metformin, Sulfonylureas or Repaglinide; any dose of GLP1 receptor agonists or Thiazolidinedione; initiation of bolus insulin or insulin adjustment of > 20% of total daily dose. Points will be attributed cumulatively for all medication/insulin changes. Addition of medication/insulin will be scored positively and reductions scored negatively to arrive at a final cumulative medication/insulin adjustment score for each participant.
Markov chain Monte Carlo multiple imputation, inverse probability weighting and available case analysis will be used to investigate the impact of different assumptions about missing data on estimated program impacts [131-133]. Pattern mixture methods models [134] will be used to explore the robustness of study findings to the assumption that data were missing not at random [135].
Implementation study
Study design and objectives
A mixed methods implementation study will evaluate the RE-AIM [65, 66] of the subsidized healthy food prescription program, including contextual influences, patients’ experiences in the program and perceived outcomes, reasons behind program successes and failures, implementation fidelity, mechanisms of impact and the likelihood of sustainability (Table 3). The Consolidated Framework for Implementation Research (CFIR) consolidates determinants of effective implementation into five domains (intervention characteristics, inner setting, outer setting, characteristics of individuals, implementation process), and will accordingly structure our investigation of determinants of effective implementation, including barriers and facilitators, within RE-AIM’s implementation domain [136].
Table 3
Logic model for the implementation of a subsidized healthy food prescription program
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Inputs
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Activities
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Outputs
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Short-term outcomes
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Longer-term outcomes
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Impact
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· Patient-oriented research, with patients as partners
· A type 2 hybrid effectiveness-implementation study design
· Scientific Committee, Advisory Boards, and PCC Subcommittee
· PCC support and infrastructure
· Organizational champions
· Funding and in-kind support from Alberta Innovates, Alberta Blue Cross, Alberta Health Services and Nu-Skin
· Implementation Support Team
· Technical support
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· Development of partnership agreements
· Readiness, capacity, barriers/facilitators and implementation assessments
· Co-customization of care pathways and implementation strategies
· Education and training, including booster training
· Ongoing monitoring and evaluation
· Regular communication, including continuous implementation feedback
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· # and % of subsidies redeemed
· # and % of subsidies redeemed for eligible/ineligible items
· # and type of PCCs and care providers that participate
· # and % of staff who participate in training
· # and % of patients who participate
· Patient experiences
· Implementation fidelity
· Cost-effectiveness analysis
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· Successful integration of care pathways within PCC workflows
· Increased awareness of effective strategies to reduce food insecurity
· Increased empowerment for patients and care providers
· Increased care provider motivation to sustain care pathways
· Improved diet quality
· Reduced food insecurity
· Improved diabetes management
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· Improved quality of care
· Improved patient satisfaction
· Improved glycemia
· Reduced chronic diabetes complications
· Commitments from Alberta Health Services, PCCs, Alberta Blue Cross and supermarkets to collaborate for longer-term sustainability
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· Decreased acute care usage
· Decreased acute care costs
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PCC: Primary care clinic
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GOAL: To support adults who are experiencing food insecurity and persistent hyperglycemia to manage their diabetes with a healthy diet.
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SITUATION: In Alberta, more than 54,000 adults are experiencing food insecurity and type 2 diabetes, including 13,600 Indigenous individuals who bear a disproportionately high burden [166-169] This group of Albertans incurs $842 million/year in healthcare costs, with a small subset of 9,600 individuals with persistent hyperglycemia incurring nearly one-quarter of these costs [20, 24, 165, 166, 170]. Nevertheless, although it is well known that food insecurity is a primary driver of acute care usage and costs, primary care providers often lack effective strategies to address it.
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Implementation process
The implementation process will unfold according to the four phases and action-oriented steps in the Quality Implementation Framework (QIF) [137, 138].
QIF phase 1: Initial considerations regarding the host setting
- Stakeholder buy-in: Partnership agreements will be finalized with all stakeholders.
- Implementation Support Team: An Implementation Support Team will be formed to administer, plan, support, monitor and evaluate implementation of the intervention.
- Training: Study personnel will be trained in principles of equity-oriented care [82, 139, 140] and study procedures.
- Assess needs, fit, capacity, readiness and adaptations: Implementation strategies will be tailored by clinic using a theory-informed modified conjoint analysis [141] in which PCC staff will complete a questionnaire to identify potential implementation barriers and facilitators within the five domains of CFIR. Researchers will use the CFIR-ERIC (Expert Recommendations for Implementing Change compilation) matching tool to identify strategies to mitigate the barriers and leverage the facilitators identified by each clinic [136, 141-145].
- Pre-Implementation planning and adaptations: The Implementation Support Team will develop a pre-implementation plan and timeline and will execute it, including co-developing infrastructural supports, training modules, and care pathways with PCC staff and patients. The Indigenous Advisory Board will progress relationship building with Indigenous PCCs and will work with them to adapt infrastructural supports and care pathways as required.
- Capacity building and supportive organizational climate: PCC staff will be trained in principles of equity-oriented care [82, 139, 140] and study procedures. Training sessions and co-design processes will enhance buy-in and readiness to change. One staff designate per organization will liaise with the Implementation Support Team weekly and will serve as an organizational champion.
- Study planning: The Implementation Support Team will develop study protocols and procure materials for all three studies.
QIF phase 2: Creating a structure for implementation
- Implementation planning and adaptations: The Implementation Support Team will use findings from the modified conjoint analysis to develop a detailed implementation plan and timeline, co-customize it with PCCs, and assign specific roles and responsibilities. Subsidy redemption procedures will be finalized.
QIF phase 3: Implementation and ongoing implementation structure
- Program implementation and data collection: The subsidized healthy food prescription program will be implemented and data collection for the RCT and modelling study will proceed (Figure 2).
- Technical support and communication: The Implementation Support Team will provide ongoing support to PCC staff, including via weekly meetings with staff designates. Booster training sessions will be held when new/modified processes are introduced and for new staff.
- Implementation study and feedback mechanisms: The Implementation Support Team will collect data continuously for the implementation study. Ongoing monitoring and provision of feedback to PCCs will support continuous quality improvement.
QIF phase 4: Improving future applications
- Data analysis: The research team will analyse and integrate data from all three studies.
- Knowledge translation and learning from experience: The research team and Advisory Boards will jointly interpret and disseminate findings. Outcomes from a deliberative dialogue [146, 147] knowledge translation event will inform sustainability planning.
Data collection
Implementation processes and outcomes related to all five RE-AIM domains, and determinants of effective implementation within CFIR domains, will be repeatedly measured via quantitative and qualitative data collected by trained Research Assistants. Participants will receive $30 for participating in interviews and $5 for completing questionnaires.
Quantitative data
Quantitative data will be collected via administrative records of the numbers and characteristics of PCCs and patients that do and do not participate (reach and adoption), the number and types of healthcare providers who receive training (implementation), healthy food prescription and subsidy allocation data (implementation), audits of supermarket subsidy transaction data (implementation), and implementation fidelity checklists completed by patients (implementation). Quantitative data will also encompass the aforementioned questionnaire pertaining to barriers/facilitators completed as part of the modified conjoint analysis. A post-intervention questionnaire will be distributed to PCC staff and patients to explore all five RE-AIM domains, including barriers/facilitators.
Qualitative data
Qualitative data pertaining to program effectiveness, implementation (including barriers and facilitators) and maintenance will be continuously collected via weekly meetings with PCC staff liaisons and through interviews with patients. The latter will entail post-intervention semi-structured interviews with 30 purposively selected patients to understand their overall experience of participating in the program, including fidelity of intervention delivery, barriers/facilitators, and how the program influenced the medical management of their T2DM. An additional 30 patients will be recruited to participate in longitudinal (pre- and post-subsidy), shop-along, think aloud qualitative interviews to understand the experience of redeeming food subsidies and how they influenced patients’ food purchasing patterns. We will also record and collect qualitative observations of Indigenous Advisory Board meetings and interview Board members to understand how the program unfolded from their perspective.
Implementation fidelity
From the measures summarized above, objective measures of implementation fidelity will include subsidy allocation data and audits of supermarket subsidy transaction data. Perceived measures of implementation fidelity will be reported by patients via quantitative checklists and semi-structured interviews.
Data analysis
Quantitative data
Quantitative findings pertaining to all five RE-AIM domains will be summarized using descriptive statistics and will inform areas for subsequent in-depth qualitative exploration. We will stratify our analyses by clinic type (urban, rural, Indigenous) to examine any meaningful differences between them.
Qualitative data
Qualitative data will be coded by two trained researchers using directed content analysis [148], whereby development of an initial coding scheme for each set of interviews will be informed by RE-AIM, CFIR and other frameworks as appropriate. Concurrent data collection and analysis and regular meetings between researchers will permit iterative adjustments to the interview questions and coding schemes, and continuous evaluation of the adequacy of the samples [149]. Sampling will end when new concepts are no longer being identified in the data.
Data integration
Quantitative and qualitative data will be integrated during the analysis stage for the purposes of expansion (e.g. qualitative data will help to elaborate and explain quantitative findings) and convergence (e.g. to examine whether quantitative and qualitative fidelity ratings correspond) [150].
Modelling study
Study design and objectives
A modelling study will estimate longer-term effectiveness of the subsidized healthy food prescription program on diabetes-related complications, resource use and costs.
Data collection
The individual-level data required as inputs for the model will be captured in the baseline and follow-up assessment phase of the RCT, as previously described. Model inputs required to estimate program impact on longer-term resource use and costs will be obtained from Alberta Health Services’ Analytics, Data Integration, Measurement and Reporting database, including emergency department, inpatient, specialist, general practice and urgent care costs. The costs of the intervention will include administrative costs associated with implementing the program and the costs of food subsidies at a household level. The time to administer the program will be based on the non-research hours of the study personnel and unit costs will be obtained from the Alberta Wage and Salary Survey [151].
Data analysis
The potential longer-term health and economic impacts of the subsidized healthy food prescription program will be modelled using the validated UK Prospective Diabetes Study outcomes simulation model-2 [152]. Health-related model outputs will include differences between the intervention and comparison groups in cardiovascular events, amputation, blindness, renal failure, diabetic foot ulcers, and mortality over 1 year, 5 year and lifetime scenarios. Model outputs related to the economic impacts of the intervention will include the incremental difference in costs and quality adjusted life years [153] between the intervention and comparison groups, the incremental cost-effectiveness ratio and the net benefit. A budget impact analysis will explore the difference in costs (e.g. prescriptions, physician visits, hospitalizations) considering the RE-AIM domains, and return on investment from the public payer perspective over 1 year, 5 year and lifetime scenarios.
Data integration and dissemination
Data from each of the three studies will be published separately, with an additional final publication that will integrate and synthesize findings for all RE-AIM domains to examine the following specific outcomes:
Reach will be assessed by calculating the: a) absolute number and proportion of adults who are experiencing food insecurity and persistent hyperglycemia In Alberta who participate; b) absolute number and proportion of individuals experiencing household food insecurity who are potentially reached by the intervention (by virtue of living in the household of a participant); c) absolute number and proportion of eligible adults who are invited who participate (i.e. participation rate).
Effectiveness will be assessed via: a) impact on primary and secondary outcomes; b) perceived positive and negative program experiences, mechanisms of impact and outcomes reported by PCC staff and patients; and c) impact on longer-term health outcomes, resource use and costs.
Adoption will be assessed by calculating the: a) absolute number and proportion of PCCs that participate, and their representativeness; b) absolute number and proportion of care providers who participate, and their representativeness; and c) reasons why PCCs and care providers decline to participate.
Implementation will be assessed by determining: a) the absolute number, type and proportion of care providers who receive training; b) the number of healthy food prescriptions prescribed; c) the value of food subsidies allocated; d) the proportion and value of food subsidies redeemed (i.e. dose); e) implementation fidelity; f) PCC staff and patient-reported barriers, facilitators and contextual influences on program implementation and uptake; and g) PCC staff and patient-perceived quality of infrastructural supports.
Maintenance will be assessed via: a) PCC staff-reported longer-term program feasibility, acceptability, organizational fit and willingness to deliver it; b) patient-reported longer-term program acceptability and willingness to participate; c) evidence of successful program integration within PCC and supermarket workflows; d) how aspects of the program are sustained or change over time; e) PCC staff and patient suggestions for program improvement; f) reasons for drop-out; and g) commitments from study partners, including Alberta Health Services, PCCs, Alberta Blue Cross and participating supermarkets to collaborate on research to assess program scale-up and longer-term sustainability.
These fully integrated data will be disseminated via technical reports, lay summaries, infographics, policy briefs, academic publications and oral/poster presentations.