Musculoskeletal disorders (MSDs) are the leading contributors to years lived with disability worldwide and have shown an increase in disease burden over the past decade [1-3]. Musculoskeletal conditions can affect as many as 1 in 4 adults and are set to continue rising, being associated with decreased life expectancy and reduced activity [4,5]. MSDs are prevalent throughout the life span and associated with early work retirement and reduced ability to participate socially [5]. In developed countries, they present the most significant proportion of lost productivity in the workplace, leading to a significant impact on the gross domestic product and health care costs [6,7].

In the United Kingdom, this poses a financial and societal challenge, costing >£4.76 billion (US $6.35 billion) of the UK National Health Service (NHS) resources and using up to 30% of primary care physician visits annually [8,9]. A freedom of information request has revealed that the average waiting time for NHS musculoskeletal outpatient physiotherapy services exceeded 6 weeks in the year to April 2019, with some patients waiting 4 months for routine appointments [10]. Longer waiting times can result in delays to physiotherapy services, with potentially detrimental effects on pain, disability, and quality of life [11,12]. The increasing proportion of burdens on public health services because of MSDs has highlighted the need for a targeted policy response [3,13].

Access to the right person, right place, first time is considered a key factor in improving musculoskeletal condition outcomes and reducing unwarranted variation in clinical pathways, such as unnecessary secondary care consultations and investigations [14]. Musculoskeletal triage as a single point of access is effective across various outcome measures, including user satisfaction, diagnostic agreement, appropriateness of referral, and reduction in patient waiting times [15]. Importantly, triage has also shown a reduction in costs across the musculoskeletal pathway, which is particularly crucial in overburdened health care systems, where triage can be performed effectively via several methods and by a range of clinicians [16-18].

Remote triage services such as telephone and video consultations or web-based or digital applications have the potential to reduce waiting times and musculoskeletal caseload [15,19]. Direct access to these services with initial assessments by physiotherapists may be a viable, cost-effective solution for managing the growing burden of MSD demand and workloads [19-22], with recent advances being made in digital primary care triage applications [23,24]. Some research has suggested that physiotherapy-led telephone triage is shown to be clinically as effective as usual care [21,25] and broadly acceptable to patients with MSDs seeking early physiotherapy advice [26]. However, barriers include the time required to reach a triage outcome, limited patient and professional trust, and interoperability problems. It should also be noted that comparisons between studies are hampered by variations in outcome measures and lack of randomization and statistical power, making any generalizations across health care settings problematic.

Mobile health (mHealth) technology has been proposed as a cost-effective solution for improving health care delivery [27,28]; however, this requires robustly tested and validated web-based triage platforms to signpost patients with MSDs to an appropriate level of care [19,29]. Standards and guidance for safe and effective implementation of mHealth apps have been published by several national and international organizations, all specifying a requirement for evidence of clinical safety and effectiveness [30-38]. A UK evidence standards framework specifically requires as the best practice standard a high-quality randomized controlled study or studies done in settings relevant to the UK health and social care system, which compare the digital health technology with a relevant comparator and demonstrate consistent benefits, including clinical outcomes in the target population [30].

To date, there is limited evidence regarding the use of web-based or digital triage platforms for MSDs specifically, and most investigations have focused on the performance of generic symptom checkers, covering a wide range of clinical presentations. However, the evidence from these studies concerning clinical- and cost-effectiveness, signposting to appropriate services, patient compliance, and safety was found to be weak or inconsistent [29]. A review of 36 primary care generic diagnostic and triage symptom checkers on web-based or mobile platforms found that appropriate triage advice was given for only 49% of the 688 vignette cases, with appropriate triage advice being given most frequently for emergency (63%) or urgent care (56%) and nonurgent care being accurate in only 30% of cases [39]. This finding is consistent with previous literature that evaluated web-based generic symptom checkers for self-diagnosis and triage [40]. A systematic review of generic health digital and web-based symptom checkers found algorithm-based triage to be inferior and more risk averse in providing appropriate triage advice compared with doctors and health practitioners [29]. Although most system developers consider this to be a safe approach, incorrect or unnecessary clinical escalations have been shown to adversely affect user trust and system adoption [41]. It is proposed that the digital assessment routing tool (DART) may overcome the limitations of existing generic symptom checkers and triage platforms by narrowing the scope of the tool and refining clinical algorithms to specifically address MSD presentations. The potential to improve triage efficiency and timely signposting of patients with MSDs to an appropriate level of care is potentially significant.

DART (Optima Health) is the first contact mHealth system designed specifically for the management of MSDs. The clinical algorithms are configured to provide the patient with a recommendation for the correct intervention level. The patient can self-assess using a computer, tablet, or smartphone. Alternatively, the content can be delivered by a remotely situated clinician or nonclinical administrator by telephone or video call. Once the affected body region has been selected, the patient is presented with a varying number of questions, depending on the nature of their symptoms and previous responses. Serious pathology is screened for, and appropriate signposting is given at the start of the assessment, with less urgent medical referrals being identified as the patient passes through the questioning. Algorithms are configured to match the provider’s clinical services based on evidence-based practice and sector-specific referral criteria. DART can be applied across any number of health care systems, including public and private services, and typically signposts to emergency or routine medical assessment, specific condition specialists, physiotherapy, self-management programs, or psychological support services. DART has an integral reporting function that allows the analysis of individual and amalgamated patient data to assess the system and clinical pathway performance (Figure 1).

This pilot study is part of a larger project, bringing DART from concept to implementation through a series of clinical and academic research work packages.

To assess the algorithm’s clinical validity, 2 reports were commissioned by Optima Health and undertaken by a panel of 5 consultant clinicians experienced in the musculoskeletal field, which comprised a consultant rheumatologist, a consultant orthopedic surgeon, a consultant sports and exercise physician and senior clinical lecturer, an honorary general practitioner (GP) in emergency care, and a consultant physiotherapist and academic lead. The first round of desktop evaluation comprised the panel inputting symptoms from 100 clinical scenarios (including red flags and complex presentations) into DART. The DART recommendation was then assessed by the panel as being correct, arguably correct, or disagree. Feedback from the panel was incorporated into a new iteration, leading to improved DART accuracy during the second review. On the basis of their opinion, the panel recommended that clinical validity was sufficient to allow DART to proceed to further research studies.

Real-world usability testing has been completed using an iterative convergent mixed methods design incorporating patient and public involvement [42], the results of which will be reported later in 2021. This study optimized usability in the final DART iteration that will be used in this pilot study and subsequent main trial.

The aim of this study is to facilitate the delivery of a future trial by exploring key aspects of trial methodology, assessing the procedures, and collecting exploratory data to inform the design of a definitive, randomized, crossover, noninferiority trial to assess DART safety and effectiveness in an NHS primary care setting.

A pilot randomized, single-blinded, crossover, noninferiority trial will be conducted to compare the safety and efficacy of DART signposting with physiotherapy-led triage outcomes in an NHS primary care setting. This preliminary study was designed in accordance with the CONSORT guidelines for pilot and feasibility trials [43], CONSORT guidelines for equivalence and noninferiority randomized trials [44], and the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) checklist [45]. Moreover, the trial design will not influence the care or triage decisions made by the usual care clinicians. Participants will complete both a DART assessment and a physiotherapy-led triage assessment on the same day, with randomization determining the order in which this is done (Figure 2).

The outcomes available to the physiotherapist will be matched by those available within the DART, allowing direct comparison between the 2 assessment outcomes (Table 1). Following their DART assessment, the participant will use a web-based questionnaire to complete the system usability scale (SUS) [46] to measure user satisfaction.

A total of 76 participants will be recruited for this pilot study using purposive sampling from a single NHS general practice. Monthly MSD referral volumes far exceed the number required for the study, which should support the completion of data collection within the anticipated study timescale. Patients with an MSD wishing to access support from the practice, either from a GP or physiotherapist, will be recruited into the study using an advert on the practice website, posters and leaflets in the GP waiting room, and by invitation from the practice administrators if the patient telephones in to make an appointment. Interested patients will be able to access the participant information sheet on the web or through hard copies available in practice, which will provide the researcher’s contact details and a request to contact them if they wish to participate (Multimedia Appendix 1). The researcher will make contact, answer any further questions, complete eligibility screening, and gain initial verbal consent. An appointment will then be made for the next available study clinic.

The study participant inclusion criteria were as follows: (1) aged >18 years, (2) able to speak and read English, (3) registered as a patient at the primary care practice, (4) having a current musculoskeletal condition for which they are seeking treatment, and (5) able to access the internet either by themselves or with the help of a family or friend.

The study participant exclusion criteria were as follows: (1) cognitive impairments or learning disabilities that limit a participant’s ability to follow study-related procedures, (2) unwillingness or inability to follow protocol-related procedures, and (3) Optima Health or Queen Mary University of London employees.

Each participant will receive the participant information sheet (Multimedia Appendix 1), which outlines the purpose of the study and the nature of their participation. This includes information about the format of the interaction, potential risks, confidentiality and protection of their personal data, the anonymity of study findings, and their right to withdraw at any time without prejudice. The participant will be given the opportunity to raise any questions with the researcher during the formal consenting process when they attend the practice. Formal written consent will be completed by the researcher with the patient in the practice waiting room using a web-based form. Failure to provide consent will result in the participant receiving a usual care physiotherapy-led triage without a DART assessment.

Participants will be randomized to either (1) a DART assessment followed by a physiotherapist-led triage assessment or (2) a physiotherapist-led triage assessment followed by a DART assessment. This is to account for the order effects in the crossover design (Figure 2). This will be achieved by block randomization with permuted blocks of random size and without stratification factors to avoid selection bias and unequal arms [47-49]. After gaining consent, the researcher will open a sealed envelope that contains the randomization to be used for the participant. Allocation will be performed using a computer-generated list of random numbers, which will lead to a randomization sequence in Microsoft Excel 2020. The allocation ratio between the arms will be 1:1.

Blinding in this study will be ensured at 3 different points: (1) the physiotherapist leading the triage will be blinded to group allocation and DART assessment outcomes; (2) participants will be blinded to the DART assessment outcome and the physiotherapist triage outcome until they have completed both assessments and the SUS; and (3) the analysis and interpretation of the study results will be conducted by researchers blinded to the intervention group allocation.

To minimize potential bias created during the physiotherapist assessment, the physiotherapist will be required to minimize any information or advice they give to the participant until after they have completed their subjective assessment and arrived at a provisional management recommendation. This will include discussing any possible diagnoses or giving any condition management advice. Once the participant has completed both assessments and data collection is complete, they will return to the physiotherapist, who will then complete the objective assessment and continue with normal care.

Following ethics approval, 3 months will be allocated for the collection of data from the required 76 participants. The exact duration will be dependent on the volume of physiotherapy referrals entering the physiotherapy service and recruitment uptake.

This study is funded by Optima Health, the developers of DART, and therefore, is at risk of bias. The lead researcher (CL) is an employee of Optima Health and enrolled in a PhD program at the Queen Mary University of London. To mitigate bias, participants will be excluded if they are employees of Optima Health or the Queen Mary University of London. Participants will not have previously seen or used DART. Recruitment is through promotion directly to the medical center patients and not by the researcher contacting them using a database. There is no financial reward offered to people to participate in the study. After gaining of formal consent and ensuring that the participant has logged on to DART, the researcher has no further contact with participants, with data being collected through DART, by the physiotherapist, or the SUS web-based questionnaire. The expert panel will comprise senior musculoskeletal clinicians who are not employed in any form by Optima Health.

There will be no form of physical intervention during this study, and participants will have no extra travel in addition to that required for their physiotherapy appointment. Normal care, as determined by the triage physiotherapist, will be followed in all cases, and participants will have full access to all existing clinical pathways available to them. Participants will not be given the DART signposting recommendation, so there will be no conflict with the recommendation given by the physiotherapist.

Participants will have the right to withdraw from the study at any time. If they do, data collected up to the point they withdraw will be retained but not added to. Electronic and paper data will be managed and stored securely in accordance with the general data protection regulations. Study data will be collected outside the NHS firewall. Personal data collected in DART will be confined to age and sex at birth and linked to other research data using a DART system unique reference number. The data inputted by the participant during the DART assessment will be generated entirely by them, and no data will be extracted from their NHS records. DART system information security and data protection will be covered by Optima Health’s certification and compliance with Cyber Essentials Plus and ISO 27001. Data collected by the physiotherapist will comprise physiotherapist assessment recommendations and study numbers only. The web-based SUS questionnaire will only contain the participant’s study number. Research data will be stored separately to personal data and linked by a unique reference number that is only accessible to the researchers. Access to the participant’s physiotherapy assessment record forms a part of the study consenting process; however, only the assessment completed as a part of the study will be reviewed by the panel and no other part of the NHS record. The data collected during this pilot may be reused for a later definite randomized noninferiority trial in a deidentified format.

The demand for an mHealth system to correctly assess and signpost patients with MSDs has been demonstrated. Research into the patterned use of generic symptom checkers indicates that MSDs are among the most common reasons for accessing web-based or digital triage applications in primary care [59,60]. Studies regarding the effectiveness of generic symptom checkers have shown variable levels of system validity [23,24,29,40], and it cannot be assumed that these research findings translate to an mHealth system with a well-defined scope, such as DART with MSDs. To date, there are no published studies providing a proven methodology for evaluating the real-world validity of similar musculoskeletal mHealth systems. This pilot trial will explore the feasibility and study design for a future large-scale, noninferiority trial determining whether DART’s efficacy and safety are noninferior or not unacceptably worse to FCP physiotherapist-led triage, a usual practice comparator. During earlier DART development, the desktop validity of DART clinical algorithms was appraised as being good by an expert panel using vignettes; however, this is not representative of the real-world validation required for safe and effective implementation into routine clinical practice [61]. DART has demonstrated good usability through an iterative convergent mixed methods study, leading to the version to be used in this pilot trial. This pilot study protocol will give a greater understanding of how to assess the validity of an mHealth system such as DART within an NHS setting and provide a template for other researchers and developers to use across triage and referral mHealth systems.

The purpose of this pilot is to validate or provide information for improvement in the study design to underpin the successful completion of the subsequent main trial. The crossover design can create a delay in the participant receiving normal care, albeit only a few minutes, and there is an increase in the amount of service administration time required. The most common errors in crossover trials are failure to adapt stratification in the order of treatments and analysis of the group rather than separately between sequence groups [62]. This is accounted for by the permuted block randomization and the independent analysis of results per group. A washout period between interventions is normally recommended to prevent carryover effects; however, there is no therapeutic effect from either DART or the physiotherapy-led assessment. The physiotherapist being asked to refrain from giving management advice as they assess the patient may be a change in normal practice for some clinicians but should not affect their signposting recommendation. Carryover effects may involve the participant becoming primed to answer questions about their health differently after gaining more insight into their health problem from having completed the previous assessment. Data analysis comprises assessing clinical agreement between the physiotherapist and DART system management recommendations. This study is not designed to examine the impact of differing DART recommendations on individual patient management and how this may positively or negatively affect care complexity, case duration, or cost. This would form the basis of a future implementation study to assess these factors across the entire MSD pathway.

The findings from this pilot trial will constitute the design of a future noninferiority trial, as well as provide preliminary data on DART safety and effectiveness. The key benefit of a crossover design using the same participant for both arms is that differences in clinical presentation as a confounder are minimized. The large variety of MSD symptomology, patients’ general health, and psychosocial status means that using a study design where different participant results are compared, such as in a parallel study, would require an unacceptably large sample size. Assessing the participant twice within minutes reduces the risk of a change in symptoms that could lead to a different signposting recommendation between the physiotherapist and DART assessments. The use of real-world NHS participants rather than clinician testing using vignettes supports patient and public involvement, a crucial component of testing for any system designed to be used with patients. Piloting within the NHS ensures that DART is tested across a wide range of clinical presentations and patient demographics, including varying socioeconomic status, eHealth literacy, fluency of English speaking, age, and employment status.