Rates of total knee replacement (TKR) procedures have been rising steadily worldwide in recent years [1]. There has been an 80% increase in TKR procedures in Australia since 2003 [1-3], with increasing incidence and prevalence likely to continue due to factors such as the aging population, an increase in obesity and joint injury, and expectations of a continued physically active lifestyle, as well as higher demand for surgery at a younger age [1,4,5]. The mean age of TKR patients in Australia is 69 years; however, the demand for the surgery in the younger population (less than 65 years) has been increasing and is expected to double in the next decade [3,6-8].

Research has shown that a number of interventions prior to TKR surgery can improve outcomes or patient’s satisfaction [9,10]. Physiotherapy undertaken before TKR is effective in improving postoperative outcomes [10]. Quadriceps muscle stretching and upper body exercises before the procedure allow patients to be prepared for the postoperative condition and rehabilitation physiotherapy program [10]. Managing patient expectation prior to surgery has been shown to benefit the rehabilitation process and is an important predictor of postoperative outcomes [11,12]. To prepare patients for their TKR surgery and hospital stay, preoperative education may offer advantages for some patients when stratified according to their physical, psychological, and social conditions [13]. Moreover, interventions that help reduce comorbidities and obesity prior to surgery can have postoperative impact, such as improved recovery and reduced chances of adverse events [2].

Most TKR patients experience pain, joint stiffness, insufficient muscle strength, and limited physical activity after surgery [14]. Early mobility following surgery has been shown to improve functional mobility and prevent deep vein thrombosis [2,15]. Studies have shown that postoperative rehabilitation can improve short-term outcomes (3-4 months) with no significant difference between different types of treatment, however the benefits of longer term rehabilitation (4-12 months) are limited [16,17]. Postoperative physiotherapy (6-8 weeks) is common practice in Australia [1], but adherence to physiotherapy programs can be low. Adherence can be low because of pain during exercise and low levels of activity prior to surgery but also because of social and psychological issues such as low self-efficacy, depression, anxiety, and poor social support [18].

Clinicians require information from their patients for diagnosis and monitoring recovery. Many of these indicators are self-reported by the patients, such as completion of physiotherapy, functionality, pain, and sleep quality. Another key measure of progress used by physiotherapists and surgeons is range of motion (ROM), a measure of the flexibility of the knee joint [16].

We are looking at ways to motivate and assist patients to complete rehabilitation programs to realize proven benefits and improve TKR surgery outcomes. We propose a solution in the form of a digital orthopedic rehabilitation platform aimed at supporting patients and their clinicians across phases of TKR, from expectation management when considering TKR surgery right through to patient recovery and rehabilitation.

Our TKR platform comprises a mobile phone app used daily in conjunction with a wrist-worn activity tracker and a clinical Web portal. The aim is to address the challenges of engaging patients with information and physical exercise through self-managed tasks delivered via the app in surgical preparation and recovery and to bridge the communication gap between clinicians and patients via the clinical Web portal. The app is designed to assist patients in achieving meaningful behavior change around uptake, adherence, and completion of rehabilitation programs, along with meaningful education, self-monitoring, and behavior coaching through rich media content.

This paper introduces the TKR platform and details the research protocol of a study to determine the efficacy and associated impact of the platform in assisting patients in their preparation for and recovery from the TKR surgery. An Australian multisite (N=5) randomized controlled trial (RCT) will be conducted for this purpose. The duration of the study is expected to be 24 months, which includes in-hospital setup and staff training, participant recruitment, intervention delivery, and data analysis. The trial will run for 13 months for each patient.

The design and functionality of the TKR platform have been informed through a user needs analysis. The user needs analysis (paper forthcoming) included interviews and focus groups with patients (n=11), general practitioners (n=8), orthopedic surgeons (n=12), and physiotherapists (n=3). The results of the analysis from the qualitative data clearly identified different stages of the TKR journey, each with different needs and priorities, which has informed the design of our platform technology for TKR. The qualitative data was used to refine features and functionalities of the platform, which comprises a patient facing app and activity tracker and a clinical Web portal for use by clinical care teams.

The information delivered via the app been scientifically validated and all exercise videos were created in conjunction with expert physiotherapists working with TKR patients.

In order to foster motivation, the purpose-built app for iOS and Android devices includes weekly psychoeducation sessions and tasks that are delivered by a program guide via text and voice recordings. This content is also reinforced through tasks (eg, goal-setting) that the user can complete outside of the app (eg, on paper). This motivational content was developed using self-determination theory [19] and included techniques designed to foster positive emotions [20]. Tools to assist in behavior change in the app use commonly identified behavior change techniques, such as self-monitoring, goal setting and reviewing, and rewarding/recognizing achievements that appear in various behavioral models which can be broadly encompassed by social cognitive theory [21,22].

The clinical Web portal is designed for clinicians to monitor patient progress and configure physiotherapy programs. Patient data, gathered by the app, is transmitted to the portal for review by members of a patient care team. Physiotherapy programs for each patient are configured from a library of videos typically used for TKR rehabilitation. Once set, programs are available to patients in their app. Figure 1 provides sample screenshots of the TKR platform.

Data will be collected as part of a 13-month (for each participant), multisite unblinded RCT where participants are assigned to 1 of 2 study groups (1:1 allocation ratio). Both groups will undergo TKR surgery and be offered usual care and guidance from their surgeon and nominated health care team. In addition, the intervention group will receive the TKR app and a Garmin Vivosmart HR activity tracker. Patient participants will be scheduled for TKR surgery and managed through a project officer (PO), typically a member of the clinical team. Participants in the intervention group will be provided with instruction from the site PO in regard to using the technology. The aims of the study are as follows:

The study includes an active intervention period commencing when the patient is scheduled for surgery (approximately 4 weeks before surgery) and ending when the patient is 12 weeks postoperative. This is followed by a 40-week free-living period, finishing 1 year after surgery. Paper-based questionnaires will be completed by participants and the PO will be responsible for collecting responses from participants at 4 time points as illustrated in Figure 2.

All access to data will be controlled by authentication and authorization protocols designed to ensure the data is protected and only accessible by authorized persons. All information identifying the participants will be de-identified by a member of research team.

The sample size is calculated based on the primary outcome (ie, OKS), by considering 80% power (P=.05) with a 15% difference in the control group and the intervention group. The standard deviation within each group in the TKR trials can vary based on factors such as number of trial sites (eg, single-center vs multicenter) and heath care cover (eg, public patients vs private patients). Furthermore, in a repeated measure scenario or when considering multiple assessments within a trial (eg, baseline, prehabilitation, 12 weeks rehabilitation, 12 months free living), the correlation among repeated measures needs to be considered as well. Based on these factors the sample size is presented in Table 2 for a variety of scenarios. A low subject variation can be expected with participants when considering only 1 trial site or 1 type of health care cover (eg, public), and a high variation can be expected when participants are mixed. A high correlation in repeated measures can be expected for patients with big differences in the outcome measure within the assessment points.

We estimate that a total of 262 patient participants would be sufficient for this study; however, we expect a maximum of 320 participants from the 5 trial sites based on their rate of TKR surgeries during the trial timeline. A minimum sample size of 100 is suggested for using OKS as the primary outcome measure [33]. Based on the literature [1,7,34], 80% power (P=.05) with a 15% difference in the control group and the intervention group has been reported for primary outcome measure.

Statistical data analysis will be performed using an intention-to-treat approach. Mixed model analysis will be used for continuous variables (primary and secondary outcomes) measured at week 0, week 12, and week 52 for those receiving the TKR platform compared with usual care by time effects. Fixed effects will be included for the intervention, the time points, and the interaction between the 2 variables. These models will also account for relevant covariates such as baseline (4 weeks before surgery) measures, participant sex, baseline levels of motivation, etc. These covariates will be entered as fixed effects. Due to potential confounding effects between different hospitals, these will be also assessed in the mixed model as random effects. Sensitivity analysis will be used to assess the impact of these covariates before the final model is constructed. Other outcome measures of app usage, self-management (eg, physical activity), and compliance with the program (eg, physiotherapy exercise) will be analyzed using logistic or conditional logistic regression to adjust the comparisons for other variables for categorical or ordinal variables and multiple regression for continuous variables. All statistical analysis will be done using Excel (Microsoft Corp), R (R Foundation), or SPSS (IBM Corp).

It is intended that the total study will run for 24 months. This is subject to patient (ie, participants) recruitment. Data capture pertaining to each patient is required for 13 months. Figure 4 presents the expected timeline for this research.