Determining the Impact of a New Physiotherapist-led Primary Care Model for Hip and Knee Pain - A Cluster Randomized Controlled Trial
Phase: NA
Conditions: Hip Osteoarthritis, Knee Osteoarthritis
Sponsor: Queen's University

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Study Title:  Determining the Impact of a Physiotherapist-Led Primary Care Model  
For Hip and Knee Pain: Study Protocol and Analysis Plan for a Cluster Randomized Controlled Trial 
and Process Evaluation 
 
Authors:  
Jordan Millera,b, jordan.miller@queensu.ca 
Catherine Donnellya,b, catherine.donnelly@queensu.ca  
Chad McClintocka,b, cwm2@queensu.ca 
Kevin Varettea,b, varettek@queensu.ca 
Yeimi Camargo a,b, yeimi.c@queensu.ca 
Jacquelyn Marshc, jmarsh2@uwo.ca  
Monica Taljaardd,e, mtaljaard@ohri.ca  
Mir Sanim Al Mamuna, mirsanimal.mamun@queensu.ca 
Geneviève Bacchusa, 20gkb1@queensu.ca 
David Barberf, barberd@queensu.ca 
Lynn Cooperg, lkcooperbes@rogers.com 
Simon Frencha,h, simon.french@mq.edu.au  
Michael Greenb,f,i, mgreen@nosm.ca  
Jonathan Hillj, j.hill@keele.ac.uk 
Joy MacDermidc, jmacderm@uwo.ca 
Kathleen Normana, kn4@queensu.ca 
Julie Richardsonk, jrichard@mcmaster.ca  
Joan Tranmerb,l, tranmerj@queensu.ca 
Timothy Widemanm, timothy.wideman@mcgill.ca 
 
aSchool of Rehabilitation Therapy, Queen’s University, Louise D Acton Building, 31 George Street, 
Kingston, Ontario, Canada, K7L 3N6 
bHealth Services and Policy Research Institute, Queen’s University, Abramsky Hall, 21 Arch Street, 
K7L 3N6 
cSchool of Physical Therapy, Western University, Elborn College, 1201 Western Rd, London, Ontario, 
Canada, N6G 1H1 
dOttawa Hospital Research Institute, Ottawa Hospital, Civic Campus, 1053 Carling Ave, Ottawa, 
Ontario, Canada, K1Y 4E9 
eEpidemiology and Public Health, University of Ottawa, 75 Laurier Avenue East, Ottawa, Ontario, 
Canada, K1N 6N5 
fDepartment of Family Medicine, Queen’s University, 220 Bagot Street, Kingston, Ontario, Canada, 
K7L 3G2 
gCanadian Injured Workers Alliance, 127 Ravenwood Avenue, Thunder Bay, Ontario, P7B 4H7  
hDepartment of Chiropractic, Macquarie University, Level 2/75 Talavera Road, Sydney, New South 
Wales 2109, Australia 
iNorthern Ontario School of Medicine, 955 Oliver Road, Thunder Bay, Ontario P7B 5E1 
jSchool of Allied Health Professionals, Keele University, MacKay Building, Newcastle-under-Lyme, 
United Kingdom, ST5 5BG 
kSchool of Rehabilitation Science, McMaster University, Institute for Applied Health Sciences Building, 
1400 Main Street West, Hamilton, Ontario, Canada, L8S 1C7 
lSchool of Nursing, Queen’s University, Cataraqui Building, 92 Barrie Street Kingston, Ontario K7L 
3N6, Canada 
mSchool of Physical and Occupational Therapy, McGill University, Hosmer House, 3630 prom Sir-

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William-Osler, Montreal, Quebec, Canada, H3G 1Y5 
 
Corresponding author:  
Jordan Miller, Associate Professor 
School of Rehabilitation Therapy, Queen’s University, Louise D Acton Building, 31 George Street, 
Kingston, Ontario, Canada, K7L 3N6 
Jordan.miller@queensu.ca 
 
Version date: November 20, 2025 
 
Results: Our internal pilot cluster randomized trial was registered prospectively in February 2023 
(NCT05736133). Recruitment of primary care sites (clusters) was completed in June 2023 and cluster 
randomization was performed in July 2023. Patient recruitment began in October 2023. When 
progression criteria for patient participant recruitment rate, assessment completion rate, and treatment 
fidelity were met at the 20-week time-point; the decision was made to progress directly into the fully 
powered trial without performing any preliminary analysis of the outcome data collected during the pilot 
phase with the plan to incorporate this data in the full trial analysis. The fully powered trial was 
registered at ClinicalTrials.gov (NCT06358521) at the end of the pilot phase (April 2024). Participant 
recruitment was completed in November 2024. At the time of publishing this protocol and analysis plan, 
data collection is ongoing and expected to be completed by December 19, 2025. Analysis will be 
conducted as outlined in this pre-specified analysis plan starting after all data collection is complete. No 
interim analysis was planned or completed. The findings are anticipated to be published in 2026.   
 
 
 

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Introduction 
 
Hip and knee pain are leading contributors to reduced functioning. Osteoarthritis (OA) alone is one of 
the leading causes of pain, disability, and reduced quality of life in patients1, and the hip and knee are 
the most common body regions2,3. Arthritis currently affects one in five Canadians, and this is expected 
to rise to nine million people by 20402. OA places a substantial burden on society in terms of both direct 
and indirect costs, including reduced work productivity and missed work2,3. 
 
Hip and knee pain and other musculoskeletal (MSK) conditions are among the most common reasons 
for a patient to access primary care4-6. Due to the rise in patients seeking support at the primary care 
level for many chronic conditions and a growing shortage of primary care providers, patients often do 
not receive timely access to the care they require7-10. Additionally, for patients without primary care 
providers, their first point of contact for their pain is often the emergency department (ED), which 
contributes to long wait times and overcrowding of the EDs11. 
 
There is an urgent need for evidence-informed and patient-centred interprofessional primary care models 
to meet the needs of patients with hip and knee pain. In Canada, federal and provincial governments 
have identified that interprofessional teams with complementary skillsets are required to address 
patients’ multiple needs and to improve the effectiveness, efficiency, and sustainability of the healthcare 
system12,13. Research from other health conditions suggests that team-based primary care can improve 
access to appropriate care, coordination of care, and patient outcomes14-16. One example of such an 
integrated model of care is having a physiotherapist (PT) integrated within primary care teams and 
available as the first point of contact 17 (PT-led primary care).  Physiotherapists can provide 
comprehensive and efficient management of patients seeking primary care for musculoskeletal 
conditions such as hip and knee pain, and evidence suggests that PTs are able to provide collaborative 
care in a primary care setting18-21.    
 
Previous studies on PTs working in primary care for MSK disorders have demonstrated that PTs provide 
equal or improved care compared to physicians or nurse practitioners (NPs) and that patient satisfaction 
is high when being managed by a PT22-24. Studies conducted in the UK concluded that PTs working in 
primary care resulted in freeing up primary care practitioners’ time, reduced referrals to secondary and 
tertiary care, fewer requests for diagnostic imaging, increased patient satisfaction, and potential for cost 
savings25,26. 27,28 
 
The impact of a PT-led primary care model for patients with hip and knee pain has not been examined in 
the Canadian context.  High quality evidence is needed to assess the effects of the PT-led primary care 
model on the following: patient health outcomes; access to care; health service utilization; and society 
(e.g. occupational productivity, costs).  Additionally, there is a need to assess how this model of care is 
implemented, potential mechanisms of the model, and patients’ experiences with the model of care.  
 
The goal of publishing this protocol and analysis plan for our cluster trial and embedded process 
evaluation is to transparently communicate our design and methods in enough detail to be reproduced 
and to communicate the analytic plan in advance of analysis to reduce risk of analytic or reporting bias. 
 
Research Objectives: 
 
1) To determine the effectiveness of a PT-led primary care model for people with hip and knee pain at 

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improving function (primary outcome), pain intensity, quality of life, global rating of change, patient 
satisfaction, and adverse events compared to usual physician-led primary care, when evaluated over a 
one-year period from the initial consultation. 
 
2) To assess the impact of a PT-led primary care model for patients with hip and knee pain on the health 
system and society (healthcare access, primary care physician workload, healthcare utilization, missed 
work, cost-effectiveness), evaluated over a one-year period from initial consultation. 
 
Methods  
 
Design: The trial is a parallel arm cluster randomized controlled trial (RCT) conducted across 14 
primary care sites in Ontario, Canada. Participating sites were randomized 1:1 to either a PT-led primary 
care model or the usual physician-led primary care model for hip and knee pain. Randomizing at the 
practice level, rather than the patient level, enabled full integration of PTs within the primary care team 
and minimized the risk of contamination between providers29. This protocol and analysis plan is 
according to the Standard Protocol Items: Recommendations for Interventional Trial (SPIRIT) reporting 
guidelines30,31. See Table 1 for an overview of the schedule of enrolment, interventions and assessments 
as recommended in the SPIRIT guidelines.  
 
Table 1.  Schedule of enrolment, interventions, and assessments. 
 
 
STUDY PERIOD 
 
Enrolment 
or clusters 
Allocation of 
clusters 
Enrolment 
of patient 
participants 
Post-allocation 
Close-
out 
TIMEPOINT 
Pre-
intervention 
Pre-
intervention 
0  
(baseline) 
3 mo. 
6 mo. 
9 mo. 
12 mo. 
ENROLMENT OF PRIMARY CARE SITES: 
Eligibility screen 
X 
 
 
 
 
 
 
Informed consent  
X 
 
 
 
 
 
 
Allocation to study 
group 
 
X 
 
 
 
 
 
ENROLMENT OF PATIENT PARTICIPANTS: 
Eligibility screen 
 
 
X 
 
 
 
 
Informed consent 
 
 
X 
 
 
 
 
INTERVENTIONS: 
PT-led primary care 
 
 
 
 
 
 
 
Usual care 
 
 
 
 
 
 
 
ASSESSMENTS: 

5 
 
Participant 
characteristics and 
demographic 
information 
 
 
X 
 
 
 
 
Participant health 
and experiences 
outcomes (LEFS, 
pain intensity, EQ-
5D-5L, PSEQ, PCS, 
TSK-11, PHQ-2) 
 
 
X 
X 
X 
X 
X 
Participant health 
and experiences 
outcomes (GROC, 
satisfaction, adverse 
events) 
 
 
 
X 
X 
X 
X 
Health system and 
societal outcomes 
(provider encounters, 
EHR utilization, 
healthcare utilization, 
missed occupational 
activities, assistance 
required) 
 
 
 
X 
X 
X 
X 
Implementation 
measures (timely 
access, PT as first 
point of contact, 
access to PT, 
hip/knee 
management) 
 
 
X 
X 
X 
X 
X 
Implementation 
measures (patient 
adherence) 
 
 
 
X 
 
 
 
QUALITATIVE INVERVIEWS: 
Patient participants 
 
 
 
X 
 
 
 
 
The trial includes a multi-methods process evaluation, guided by the United Kingdom Medical Research 
Council (MRC) framework for developing and evaluating complex interventions32,33. The process 
evaluation is exploring how the intervention is being implemented, differences in primary care provided 
to people with hip and knee pain receive in the PT-led primary care model in comparison to the usual 
care model, potential mechanisms of the model of care, and experiences of patients with this model of 
care. This is essential for interpreting trial results; for example, understanding why the intervention may 
fail, yield unintended effects, or succeed — and can help guide future implementation of this model of 
care in the future if effective33,34.  
 
This cluster randomized trial is being run along-side another cluster randomized trial (clinicaltrials.gov 
NCT04287413) that aims to determine the impact of a PT-led primary care model for people with low 
back pain. The trial focused on hip and knee pain (the protocol and analysis plan presented here) is 
being carried out at 14 of the 20 sites participating in the low back pain trial (14 sites located in Ontario 
are included, six sites in BC are not included). We used the existing randomization schedule created for 
the low back pain trial to be able to efficiently assess the impact of a PT-led primary care model for 
people with hip and knee pain by leveraging the PTs and research staff already hired for the low back 

6 
 
pain study. The multi-methods process evaluation for the low back pain trial includes a mixed-methods 
exploration of how the context influences implementation of a PT-led primary care model and a 
qualitative exploration of the perspectives of primary care team members. These elements were 
intentionally not included or replicated in the process evaluation plan for the hip and knee trial in this 
trial. However, we anticipate findings related to the perspectives of primary care team members and 
contextual factors influencing implementation of the PT-led primary care model explored as part of the 
process evaluation in the low back pain trial will be informed by experiences implementing a PT-led 
primary care model for both people with low back pain and people with hip or knee pain.  
 
The process evaluation will provide an understanding of how the PT-led primary care model for patients 
with hip and knee pain was implemented, explore the potential mechanisms of the interventions, and 
capture the experiences of patients who received care through this model. 
 
Patient and Public Involvement: A person with lived experience was involved throughout this study, 
contributing to the conceptualizing the study, study design, and selection of outcomes important to 
people with lived experience. Their ongoing involvement included pre-testing data collection tools, 
supporting the interpretation of process evaluation results, and co-developing knowledge mobilization 
supports such as tailored summaries that will be distributed through patient organizations. 
 
Enrollment and Randomization of Sites: We enrolled all 14 Ontario sites from the 20 sites included in 
our cluster-RCT testing a similar model of care for people with low back pain in Ontario and British 
Columbia. We used the existing randomization schedule17, with a 1:1 ratio of the intervention and 
comparison arms. Covariate constrained randomization35 was used by an independent statistician to 
reduce the risk of baseline imbalances across study arms; the number of active patients and rural versus 
urban clinic setting were used as covariates. Each cluster name was concealed with a deidentified code 
prior to randomization. The maximum tolerable difference for rural/urban was 1. The strata balancing 
criteria was 10% for number of active patients. 
 
Strategies to Mitigate Bias: Given the nature of the trial design and the interventions being compared, 
blinding was not feasible for the PTs, patient participants, primary care team members, or research 
assistants. While this limitation is inherent to the study design, we implemented several measures 
recommended for cluster randomized trials to reduce potential bias36. 
 
 A common concern in cluster RCTs is the risk of selection and recruitment bias, particularly when 
patient enrollment occurs after cluster assignment37. To address this, we took efforts to invite 
consecutive patients with hip or knee pain to participate in the study, to ensure RAs who handled 
recruitment and consent were not familiar with the patients, and to apply inclusion and exclusion criteria 
consistently across all sites. We also provided identical trial information to all potential participants 
before obtaining consent, regardless of cluster. This meant that we did not reveal which study arm 
participants were in until after obtaining their consent. 
  
Patient Participant Recruitment: During patient participant recruitment, medical secretaries screened 
patients to be invited to participate when they booked an appointment for hip or knee pain. As an 
additional strategy, potential participants were also identified any healthcare provider (HCP) when they 
sought care for their hip or knee pain during a clinical visit. Potential participants who were agreeable to 
being invited to participate were contacted by a study research assistant (RA) to explain the details of 
the study. Those who were interested in participating were asked to complete a consent form that was 
built into the baseline surveys in a secure data collection platform (REDCap, Research Electronic Data 

7 
 
Capture). If a potential participant requested to do this in-person, arrangements were made to meet with 
the RA who provided detailed written and verbal information about the study and obtained consent for 
participation from those patients who were interested. A verbal consent process was in place for those 
who preferred to do this over the phone or in a virtual meeting.  
 
Inclusion/Exclusion: All adult (≥19 years) patients who sought primary care for their hip or knee pain 
of any duration at participating sites were invited to meet with the RA to discuss participating in the 
study. Potential participants were excluded if: they reported not being able to understand, read, and write 
English; they had known cancer causing their hip or knee pain; or they reported being unable to 
complete the scheduled follow-up surveys over the one-year study period. The inclusion criteria for 
primary care sites were to have at least 1,500 rostered patients and two or more family physicians. Those 
sites that already had physiotherapy services or not enough space to include the physiotherapist were 
excluded. 
 
Study Power: Participants were recruited over a 13-month period at all 14 primary care sites (7 PT-led 
arm, 7 usual care arm). Our power calculation is based on methods described by Hemming et al.38 Our 
sample size calculation is targeted to detect a clinically meaningful mean difference of 9 points on the 
Lower Extremity Functional Scale (LEFS) using a two-sided alpha of 0.05, assuming a conservative 
standard deviation of 16, a conservative intracluster correlation coefficient of 0.1, a cluster 
autocorrelation coefficient of 0.5, an individual autocorrelation coefficient of 0.6, and a coefficient of 
variation of 0.7.39-41  Allowing for an attrition of 20% of patient participants at the 12-month follow-up, 
we require a sample size of 560 participants to achieve >80% power. Pilot work for this study suggested 
we would recruit 1 patient per week per site; as such, we planned and prepared resources to recruit 
approximately 728 participants. 
  
Interventions:  
PT-Led Primary Care Model for Hip and Knee Pain: The index intervention incorporates a PT within the 
primary care team as an option for the first point of contact for people presenting with hip or knee pain 
for one year from the time of enrolment. Patients in this model are given the choice of seeing the PT or 
primary care provider first. There are four key components of the PT-led intervention: 1) initial 
assessment and screening; 2) brief individualized intervention at first visit; 3) health services navigation; 
4) and providing additional PT care for people with an unmet need (e.g., no insurance coverage for PT).  
Physiotherapist training: During two consecutive days, seven registered physiotherapists received 
training on this new model of care to apply across the seven sites randomized to the PT-led primary care 
model for hip or knee pain. 
 
1) Initial assessment and screening: the PT provides a comprehensive patient assessment according 
to established clinical practice guidelines. The assessment includes taking a detailed clinical 
history; screening for potential pathology and the need to refer to another HCP; physical 
examination; and using a validated patient reported outcome measure (LEFS39) to guide clinical 
decision-making. 
2) Brief individualized intervention at first visit: the PT intervention is at the discretion of the PT to 
reflect real-world PT practice. 
3) Health services navigation: where applicable, patient participants are provided with options 
available to them in their community for rehabilitation programs or other health or social 
services. For example, they may be referred to community PT for ongoing management or 
presented with options for group exercise programs. Patients are assessed regarding the need for 
specialist referrals or resources available to manage complex clinical presentations such as 

8 
 
comorbidity, frailty, or the need for surgical consult. Patients are referred to the primary care 
provider if specialized services are needed or when the PT cannot provide a direct referral. In 
addition, patients are referred back to their primary care provider when it is deemed that their 
clinical needs fall outside of the PT’s scope of practice (i.e., medication advice, pathology 
requiring medical attention) or they identify factors that require mental health intervention.  
4) Providing additional PT care: patient participants who require PT but do not have the appropriate 
access to community-based services are managed by the PT who provided the assessment in the 
primary care setting. Individuals with private or government health coverage are referred to 
services outside of the primary care practice when they are accessible to the patient in order to 
avoid duplication of available services. The amount of care provided is decided on a case-by-
case basis in alignment with the health needs for each individual.  
  
Usual Care Model: The physician- or nurse practitioner -led primary care intervention is unstandardized 
to best reflect the usual primary care clinical practice in Ontario. Patients in the usual care group are 
seen by either a primary care physician or a nurse practitioner as their first point of contact, depending 
on the current practice at the clinic. Participants in both groups are permitted to seek additional care 
from interprofessional team members within their primary care team or health services outside of the 
primary care clinic as needed.  
 
Duration of Treatment Period: 
The intervention is being carried out over a one-year period from the time of consent. All participants in 
the intervention arm are offered an initial assessment with the PT. While some participants in the 
intervention arm may be recommended to seek community health services if they have access to 
comprehensive health insurance, they have access to the PT as a member of their primary care team 
throughout the one-year follow-up period if they require additional support for their hip or knee pain. 
The frequency and duration of visits is determined by the PT and patient participant. The usual care 
model is ongoing and involves continuing as usual, and process outcomes are being collected from the 
date of consent to one-year post enrollment. 
 
Intervention Modifications: 
We do not expect any safety-related issues that would necessitate removing a participant from either the 
PT-led or usual physician-led primary care pathway. In line with routine care practices for hip or knee 
pain, the primary care team will adjust the intervention as needed to prioritize participant well-being. 
Adjustments may be made in response to factors such as increased pain, limited mobility, poor tolerance 
to treatment, changes in clinical status, or adverse reactions to medications or exercises. As the risks are 
minimal and did not compromise participants’ well-being, a data monitoring committee was not 
established. 
 
Data Collection and Management: 
All baseline measures have been collected from participants and follow-up data collection is ongoing. 
We used several approaches to support participant retention at all time points. Research assistants 
maintained regular contact, sending reminders every two to three days via personalized emails, phone 
calls, and text messages to encourage survey completion. When preferred by participants, surveys were 
completed in person or by phone to enhance engagement and reduce the likelihood of attrition.  
All data at baseline and follow-up timepoints is being collected through online surveys using REDCap42 
(Research Electronic Data Capture), a secure online survey and data capture tool that is hosted at 
Queen’s University.   

9 
 
 
Electronic health record (EHR) data is being extracted by trained research assistants at the end of the 
one-year intervention period directly into a securely stored database to capture all primary care provided 
related to the hip or knee pain. Unique study identifiers are used to link responses from the surveys with 
data obtained in the EHRs.   
 
At the end of the study, survey responses will be exported from REDCap into encrypted, password-
protected datasets and securely stored in Microsoft OneDrive. Data extracted from the EHR, as well as 
the master list linking participant identifiers to study IDs, will also be kept in encrypted, password-
protected files on OneDrive. Audio recordings from qualitative interviews are being transcribed, de-
identified, and stored in a secure OneDrive environment at Queen’s University. 
 
1. Baseline Characteristics Used to Describe the Population  
We collected the following baseline information from participants through REDCap: age, sex, gender, 
education, duration of hip/knee pain, locations of pain, medications, comorbidities, employment status, 
income, rurality, and ethnicity. Comorbidities are assessed using the Functional Comorbidity Index43-45 
(a list of comorbidities that are associated with physical functioning. The presence of a comorbidity is 
assigned a score of 1 and the total score is the sum of the comorbidity element with a maximum score of 
18). 
  
2. Individual Health and Experience Outcomes  
The following individual health and experience measures are being collected through REDCap with 
repeat surveys at baseline, 3-, 6-, 9-, and 12-months post enrollment. Patient satisfaction, global rating of 
change, and adverse events are being collected at all follow-up time points only. 
• 
Self-reported functioning: using the LEFS39– a validated  20-item patient-reported outcome 
measure used to assess functional status related to lower extremity conditions. Each item is 
scored on a 5-point scale, with higher scores indicating better function.  
• 
Pain intensity: measured using a Numeric Pain Rating Scale (NPRS)46 where 0 is no pain and 10 
is the worst possible pain. 
• 
Health-related quality of life: using the EuroQOL-5D (EQ-5D-5L), which is suitable for 
economic evaluations47,48. The EQ-5D-5L score will also be converted to quality-adjusted life 
years (QALY)47.    
• 
Global rating of change: using an 11-point global rating of change (GROC) scale to assess 
perceived overall change in health status, symptoms, or function over time, with anchors of a 
great deal better (+5) to a great deal worse (-5).49.  
• 
Patient satisfaction: using an 11-point scale with anchors of very dissatisfied (-5) and very 
satisfied (+5).  
• 
Adverse events: using an adverse events questionnaire aligned with reporting guidelines27,28. The 
questionnaire determines: 1) adverse events experienced as a result of any of the interventions 
received; 2) a description of the adverse event; 3) duration of the adverse event; and 4) severity 
of the adverse event. Serious adverse events are identified if the participant requires 
hospitalization or an emergency department as a result of the adverse event, the adverse event 
leads to significant and persistent disability beyond 72 hours, or the adverse event is life-
threatening. The study team monitored these responses to ensure ongoing patient participant 
safety. 
• 
Potential mechanisms of the intervention: 

10 
 
o Self-efficacy: confidence in abilities to participate in usual activities using the Pain Self-
Efficacy Questionnaire (PSEQ)50,51. 
o Psychosocial risk factors for persistent pain and disability: The Pain Catastrophizing 
Scale (PCS)52-54, Tampa Scale of Kinesiophobia (TSK-11) 55-57, and 2-item Patient Health 
Questionnaire (PHQ-2)58 will measure psychosocial factors associated with pain-related 
disability.  
 
3. Health System Outcomes  
 
Primary care physician or nurse practitioner visits: the total number of patient visits, both initial and 
follow-up, related to hip or knee pain. This metric is being used to explore whether involving PTs in 
care delivery helps alleviate demand on primary care providers, potentially allowing them to allocate 
more time to patients with other health concerns. 
 
Healthcare utilization within the primary care team: consultations with all primary care team members 
(e.g., physicians, nurse practitioners, nurses, social workers, and occupational therapists), including the 
PT in the intervention sites, and group programming accessed within the organization. This data is being 
collected from the EHR abstraction process. 
 
Healthcare utilization outside of the primary care team: medications used; walk-in clinic visits; ED 
visits; inpatient hospital stays; diagnostic imaging; surgeries, injections, and other interventional 
procedures; visits to specialist physicians; and visits to other health professionals outside the primary 
care team (e.g., chiropractors, massage therapists, occupational therapists, physiotherapists, chronic pain 
clinics). These outcomes are being collected from the self-report surveys at each follow-up assessment 
and verified, whenever possible, in the EHR. 
 
Missed Occupational Activities: self-reported time lost from paid employment, volunteer, homemaking, 
or educational activities.  
 
Assistance required: self-reported paid and unpaid assistance required. For example, self-care (e.g., 
taking medications, dressing/undressing, going to the bathroom, bathing/showering, grooming), 
shopping/groceries, meal preparation, housework, managing finances, or transportation (e.g., to a 
medical appointment). 
 
Costs: Total per-person costs include both direct and indirect healthcare costs, with indirect costs 
estimated using a human capital approach based on time missed from work or other daily activities59. 
 
Direct costs incorporate intervention-related expenses (e.g., physiotherapist salary and training), publicly 
funded healthcare services (sourced from the Ontario Ministry of Health Schedule of Benefits60), 
medication costs (using the Ontario Drug Benefit formulary), and participant-reported expenses for 
privately funded services or out-of-pocket supports (e.g., self-care, household help, transportation). 
Resource use will be multiplied by relevant unit costs to estimate total expenditures, which will be 
summed over each follow-up interval and used to calculate both time-specific and overall costs. 
 
Indirect costs reflect productivity losses due to time away from paid work, valued using the provincial 
average wage from Statistics Canada for participants not engaged in paid employment (e.g., retirees, 
homemakers, caregivers, students). Lost time from unpaid activities will be valued using the minimum 
wage in Ontario. 

11 
 
 
Implementation: 
Consistent with the UK MRC guidelines33, we are collecting the following implementation measures as 
part of our process evaluation:  
 
Timely access to care: determined by the percentage of patients with hip or knee pain who are assessed 
within 48 hours of calling for an appointment. Only participants who were invited to participate at the 
time of calling for an appointment for their hip or knee pain will be included in this analysis. 
Participants who were invited to participate at the time of an appointment with another primary care 
provider will not be included. 
 
First contact care by the PT: using the percentage of patients with hip or knee pain in the PT-led primary 
care arm who visited a PT as their first point of contact for the current episode of hip or knee pain.   
 
Hip and knee pain management provided: visits to the primary care site related to hip and knee pain  are 
being collected from the EHR, along with indicators for the following process measures: education 
provided; exercises prescribed; psychological interventions provided; referrals made to internal primary 
care team members; referrals made to external HCPs; medications prescribed, deprescribed, and 
suggested; diagnostic imaging ordered; notes sent to employers or insurers; messages sent to internal 
primary care team members; and other interventions provided.  
 
Patient adherence to recommendations: adherence to PT activity and exercise recommendations is being 
collected at the 3-month follow-up survey. We will also be able to determine if participants accessed 
community PT as part of each follow-up survey timepoint.   
 
Qualitative Interviews:  
Qualitative interviews are being conducted with patient participants following an interpretive description 
approach120 to explore their experiences with the PT-led model of care for hip and knee pain, and their 
perspectives towards the model of care. A purposive sampling strategy is being used61. We are aiming to 
recruit 8-12 patients representing diversity in age, gender, race, income, employment status, pain 
duration and intensity, baseline function, and primary care clinic. We are using the concept of 
information power62 to determine sample size adequacy within each group—ending recruitment once 
sufficient depth and breadth of data have been obtained to meet the study objectives. During the 
consenting process for the main part of the study, patient participants were asked if they were willing to 
be contacted for qualitative interviews exploring their experiences and perspectives of the PT-led model 
of care. Using the purposive sampling approach, agreeable patients are being contacted, approximately 
2-3 months after enrollment, to explain the purpose of the interviews, discuss the consenting process and 
letter of information, and schedule an interview time. At the beginning of the interview, the researcher 
completing the interview confirms that the participant has read the consent form and answer any 
questions they may have before obtaining verbal consent. 
 
Protocol Amendments: any protocol modifications will be documented through updates to the 
ClinicalTrials.gov registry and described in the final trial publication. Investigators and participants will 
be informed as needed, depending on the nature of the changes. 
 
 
Data Analysis Plan  
 

12 
 
All analyses will be by intention to treat principle. Descriptive statistics will be provided for baseline 
characteristics and outcomes using means (standard deviation) or medians (interquartile range) for 
continuous variables and frequencies (percent) for categorical variables. We will compare arms using 
linear mixed models and generalized estimating equations (GEE) to account for clustering and present 
the corresponding p-values. Analyses will be performed using SAS, version 9.4 (SAS Institute Inc; 
Cary, NC). 
 
The estimand for patient health outcomes will be the time-specific patient participant treatment effect, 
adjusting for clustering by primary care site. The primary outcome (LEFS) will be analyzed using linear 
mixed regression with restricted maximum likelihood (REML) estimates under the assumption of 
Missing at Random (MAR), which will allow the use of all available data without the need for multiple 
imputation. The Kenward-Rogers degrees of freedom correction will be used to account for a small 
number of clusters63. The 12-month timepoint will provide the intervention effect as the adjusted least 
square mean difference between arms with 95% confidence intervals. Secondary comparisons will be 
made using adjusted least square mean differences between arms at all intermediate time-points. Fixed 
effects in the mixed model will include time, intervention group by time interaction (omitting the group 
main effect), pre-specified covariates associated with hip and knee function (patient participant age, sex, 
duration of current episode of hip or knee pain, income, highest level of education, and comorbidity 
score), and primary care site rurality and number of active patients (the covariates from the covariate-
constrained allocation procedure). Repeated measures will be modeled using a covariance structure 
determined by information criteria (AIC/BIC). Clinic site will be included as a random effect to account 
for site clustering. We will assess for potential risk of bias associated with missing data by comparing 
the characteristics of those who participated. We plan to carry out a sensitivity analysis for a potential 
departure of our MAR assumption using a delta-adjusted imputation pattern mixture model approach64-
66. This approach will allow us to investigate the robustness of our trial outcomes with regard to the 
missing values of the LEFS. 
 
We plan a secondary analysis using our primary outcome (LEFS) to compare the proportion of 
participants who experience a meaningful improvement in each arm (responder analysis67). We will 
define a meaningful change as an improvement of greater than or equal to 9 points on the LEFS (the 
minimally important change39,40). We will present the proportion of participants who experience a 
meaningful improvement in each arm and compare, using relative risk, between groups using robust 
Poisson regression, accounting for clustering130.  We will use empirical covariance (“sandwich”) bias-
adjusted (residual-based) estimators, and apply the Fay and Graubard correction for the small number of 
clusters68. 
 
Pain intensity (NPRS), quality of life (EQ-5D-5L), self-efficacy (PSEQ), catastrophic thinking (PCS), 
pain-related fear (TSK)-11, and depressive symptoms (PHQ-2) will be analyzed using the same analytic 
approach as described for our primary LEFS analysis, adjusted for the same covariates. We will use 
simple mean imputation to fill in missing individual items on surveys as described by Chavance66. 
Patient satisfaction and global rating of change do not include a baseline measure and will be assessed 
using ordinal logistic regression with random effects and adjusting for the same covariates as above.   
 
Incidence rates for minor adverse events (yes or no) will be calculated using robust Poisson regression 
and compared by calculating relative risks with confidence intervals using GEE-type robust covariance 
estimators (PROC GLIMMIX, EMPIRICAL option in SAS) to account for clustering69.  In our models 
comparing incidence rates, we will use an exchangeable working correlation matrix, empirical 
covariance (“sandwich”) bias-adjusted (residual-based) estimators, and the Fay and Graubard correction 

13 
 
to account for small number of clusters68. Given that we have only included 14 clusters and adverse 
events are expected to be rare, we anticipate there may be issues of non-convergence or instability in our 
models. Should the model for adverse events not converge or demonstrate instability, we would attempt 
to fit the model using an independent working correlation matrix. If there are still issues of non-
convergence or instability, we will reduce the model by removing covariates, beginning with duration of 
pain and income. Severity and duration of minor adverse events will be presented descriptively. We do 
not anticipate many, if any, serious adverse events; as such, we plan to present these data descriptively. 
 
Visits with primary care physicians or nurse practitioners, time (days) lost from occupational activities, 
and assistance required (hours) will be presented as rates and compared by calculating rate ratios using 
GEE-type covariance estimators with an adjusted Poisson or negative binomial model, accounting for 
clustering, and assuming an exchangeable working correlation matrix. Incidence rates will be used to 
present visits to other health professionals within the primary care team, participation in group programs 
offered by the primary care team, and health care services received outside of the primary care team 
(medications, diagnostic imaging, walk-in clinic visits, ED visits, specialist physician visits, , hospital 
admissions, interventional procedures, surgeries, other health provider visits). Comparisons between 
groups for each of these variables will be made by calculating relative risk using robust Poisson 
regression130. These models will incorporate empirical covariance (“sandwich”) bias-adjusted (residual-
based) estimators, and the Fay and Graubard correction due to the small number of clusters68,70,71. These 
models will use time as an offset to account for variable follow-up times. All of the healthcare utilization 
and lost time from occupational activity models will control for the same covariates as the patient health 
outcomes analyses  Similar to our analyses for adverse events, in the case of model non-convergence or 
instability, we will attempt to fit the model using an independent working correlation matrix and if the 
model still does not converge and demonstrate stability, we will reduce the model by removing 
covariates. 
 
Our cost utility analysis will be carried out from societal (primary) and health payer (secondary) 
perspectives. We will calculate total costs by multiplying the quantity of resource use by the 
corresponding unit cost, summing the total cost over each follow-up interval to determine total costs at 
each follow-up time point as well as across the entire study period. Total and mean costs (overall and at 
each time point) will be presented by aggregated and disaggregated costs. We will estimate quality 
adjusted life year (QALYs) for every participant using area under the curve and assuming linear 
interpolation between assessment time points. Bivariate multilevel modelling, accounting for clustering, 
will be used to analyze the incremental cost per Quality-Adjusted Life Year (QALY) gained and 
describe the incremental net benefit at various values of willingness-to-pay. We will model treatment 
group as a fixed effect and account for site clustering. We will adjust for the same covariates as the 
primary analyses. We will use a probabilistic sensitivity analysis with Monte Carlo simulations to 
explore the uncertainty in our cost-effectiveness estimates. The results will be illustrated on cost-
effectiveness planes, and cost-effectiveness acceptability curves will be presented to demonstrate the 
likelihood that the PT-led care model is cost-effective across various willingness-to-pay thresholds.  
 
 
We also plan a subgroup analysis based on sex for each of our effectiveness outcomes, as recommended 
in the sex and gender equity in research (SAGER) guidelines33. We will include an interaction term with 
sex and group, and group by time in order to assess this. We will present the data using forest plots and 
95% confidence intervals. 
 
Process Evaluation 

14 
 
 
Implementation 
Timely access to care: the percentage of patients with hip or knee pain who are assessed within 48 hours 
of calling for an appointment will be reported descriptively and compared between arms by calculating 
relative risks with robust Poisson regression, using GEE-type covariance estimators to account for 
clustering, assuming an exchangeable working correlation matrix. Empirical covariance (“sandwich”) 
bias-adjusted (residual-based) estimators and the Fay and Graubard correction will be used68. We will 
incorporate the same covariates as with our effectiveness analysis.  
 
First contact care by the PT: the percentage of patients with hip or knee pain in the PT-led primary care 
arm who visited a PT as their first point of contact for the current episode of hip or knee pain will be 
reported descriptively.   
 
Hip and knee pain management provided: the proportion of patient participants who receive the 
following will be reported descriptively: education; exercises; psychological interventions; referrals to 
internal primary care team members; referrals to external HCPs; medications prescribed, deprescribed, 
and suggested; diagnostic imaging ordered; notes to employers or insurers; messages sent between 
internal primary care team members. Comparison between arms will be made using robust Poisson 
regression.  Comparison between arms will be made using relative risks and confidence intervals using 
GEE-type covariance estimators, accounting for clustering, and assuming an exchangeable working 
correlation matrix. Empirical covariance (“sandwich”) bias-adjusted (residual-based) estimators and the 
Fay and Graubard correction to account for small number of clusters will be used131-133. 
 
Patient adherence to recommendations: adherence to PT activity and exercise as reported at 6-week 
follow-up will be reported descriptively. The proportion of people accessing PT in the community will 
be reported descriptively and compared using robust Poisson regression, accounting for clustering.  
 
Potential Mechanisms 
If the intervention is effective (i.e., The PT-led primary care model results in greater patient functioning 
than the usual care group), we will carry out mediation analyses137 to assess potential mechanisms. 
Specifically, we will assess whether changes in self-efficacy (PSEQ) or changes in psychosocial risk 
factors (PHQ-2, PCS, TSK-11) explain or partially explain changes in patient functioning (LEFS score). 
We will conduct a separate mediation analysis for each potential variable (PSEQ, PHQ-2, PCS, TSK-
11). We will use a stepped approach proposed by Beril and colleagues138 to investigate temporal and 
dynamic trends of the treatment effect across repeated measures using theoretical insights about the 
mediation effect to choose the appropriate mediation model. The intervention effect explained by the 
mediator (indirect effect) will be calculated as the difference between the total effect (the effect 
calculated in the primary analysis) of the PT-led primary care model on the LEFS score and the direct 
effect of the intervention139,140. We will evaluate the possibility of mediation using the significance of 
this effect141,142. We will use the LEFS outcome at the 12-month follow-up timepoint as the outcome 
variable143,144. This analysis will provide effect measures that allow us to report the proportion of the 
total effect that is mediated through each of the potential mediator variables.145. Our causal/associated 
conceptual model has considered, and controlled for where needed, mediation analysis assumptions that 
there is no intervention-outcome, mediator-outcome, or intervention-mediator confounding or mediator-
outcome confounding that is influenced by the intervention itself140,146,147. To explore potential 
mechanisms of cost differences in our cost analysis, we will report the proportion of cost differences 
between arms that are healthcare utilization costs and the proportion of costs associated with missed 
occupational activities. 

15 
 
 
Patient Experiences 
We will explore the experiences of patient participants with hip or knee pain who have participated in 
the PT-led primary care model for hip or knee pain using in-depth qualitative interviews conducted and 
analyzed in an interpretive description tradition72,73. Interpretive description is a qualitative approach 
that is founded on naturalistic inquiry and involves focusing on identifying applied and clinically 
relevant themes that can inform healthcare or health service delivery. Interpretive description, therefore, 
is well suited to helping us achieve our process evaluation goal to understand experiences and 
perspectives with the PT-led primary care model for people with hip or knee pain. The experiences and 
perspectives of patients are expected to lead to refinements how the model of care is implemented if 
effective. Strategies to support rigour will include use of two independent coders for the first two to 
three manuscripts to ensure reliability and consistency in coding, use of reflexive journaling and 
reflexive dialogue amongst team members throughout the analytic process, incorporation of detailed 
field notes and written memos, long and deep engagement with the qualitative interview data, and 
maintaining an audit trail to document the analytic decisions throughout the research process74-78. 
 
Ethics  
Ethics approval for this study has been obtained from the Queen’s University Health Science and 
Affiliated Teaching Hospitals Research Ethics Board (HSREB #6040471). Written consent was obtained 
from all participants willing to participate.   
 
Discussion: The results of this pragmatic trial and accompanying mixed methods process evaluation 
will provide comprehensive evidence to guide health system leaders and primary care teams regarding 
the implementation of a new PT-led primary care model of hip and knee pain in Ontario, with relevance 
for health systems across Canada and around the world. Our approach combines quantitative analyses of 
patient health outcomes and healthcare costs with in-depth qualitative inquiries into how the model of 
care was experienced and implemented. This design allows us not only to assess effectiveness and cost 
implications, but also to understand contextual factors, barriers, and facilitators that shape real-world 
uptake. The evaluation has been co-developed with knowledge users—including individuals living with 
hip and knee pain and health care professionals engaged in the intervention—to ensure that study 
outcomes are meaningful and aligned with current health system priorities.  
 
We will share out findings through peer-reviewed manuscripts on: the effectiveness of the PT-led 
primary care model for people seeking primary care with hip or knee pain, the cost-effectiveness of the 
model, how the model of care was implemented (including differences in care provided between arms), 
potential mechanisms (if the intervention is effective) and the experiences of patients.  
Acknowledgements: Not applicable. 
 
Funding  
This study protocol was supported by Canadian Institutes of Health Research (CIHR) Institute of 
Musculoskeletal Health and Arthritis (grant reference number 185253) and the Arthritis Society of 
Canada (agreement number 02360-00). Neither funder took part in the writing of this protocol and 
analysis plan.  
 
Competing Interest  
The authors declare that they have no competing interests, including: no support from any organization 
for this work, no financial relationships with any organizations that might have an interest in our study 

16 
 
in the previous three years, no other relationships or activities that could appear to have influenced this 
work.    
 
Data Availability   
For access to the data, please contact the corresponding author. 
 
Abbreviations:  
 
CCI: Canadian Classification of Health Interventions 
ED: Emergency Department 
EHR: Electronic health record 
GEE: Generalized estimating equation 
GROC: global rating of change 
HCP: healthcare provider 
LEFS: Lower Extremity Functional Scale 
MAR: Missing at random 
MRC: Medical Research Council (UK) 
MSK: musculoskeletal 
NPRS: Numeric Pain Rating Scale 
OA: Osteoarthritis  
OHIP: Ontario Health Insurance Program 
PSEQ: Pain Self-Efficacy Questionnaire 
PT: Physiotherapist 
QALY: Quality-adjusted life years 
RA: Research assistant 
REDCap: Research Electronic Data Capture 
REML: Restricted maximum likelihood 
RCT: Randomized controlled trial 
 
 
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