**3. Critically Assessing Musculoskeletal Digital Apps**

With increasing adoption of telehealth and digital solutions comes increasing demands on clinicians to recommend and use MDAs appropriately, while avoiding dangers and pitfalls. Here, we detail methods to assess the clinical effectiveness, the functionality, and the reliability of digital health solutions.

The landscape of digital health solutions on the Internet and app stores has been likened to the Wild West, given the inability of regulators to keep up with the explosive growth of medical apps. A significant pitfall to avoid is apps that falsely claim to diagnose, prevent, or treat a disease or medical condition. Such claims require FDA review and approval prior to marketing, and digital apps have been pulled off the market for making false claims. For example, in 2011, an app developer claimed that the app could use the blue light emitted from a mobile device to cure acne. The Federal Trade Commission (FTC) intervened to prohibit marketing of the app, and the app was removed from app stores for failure to obtain regulatory approval [24]. For digital health apps that do not make diagnostic, prevention, or treatment claims, however, regulatory approval is not required. Absent fraud, such apps will not be removed from the digital marketplace. It is thus important for clinicians to be able to assess the utility of digital health solutions.

Two well-known entities that evaluate Internet resources are the Health on the Net Foundation (HON) and the Agency for Healthcare Research and Quality

#### *Evaluating the Clinical and Cost Effectiveness of Musculoskeletal Digital Health Solutions DOI: http://dx.doi.org/10.5772/intechopen.94841*

(AHRQ ). HON published a HON Code of Conduct (HONcode) in 1996 that includes 8 principles for certifying information on health and medical websites. The 8 principles include Authority, Complementarity, Confidentiality, Attribution, Justifiability, Transparency, Financial Disclosure, and Advertising [25]. AHRQ proposed similar criteria, including credibility, content, disclosure, links, design, interactivity, and caveats [26]. Hanrahan et al. recommend applying similar criteria to the evaluation of digital health apps [27].

In assessing the clinical effectiveness of an intervention, the clinician will want to consider the types of study designs used to generate evidence of effectiveness [28]. Traditionally, randomized controlled trials are considered the gold standard in evidence assessment [29], followed by observational studies such as cohort, cross-sectional, and case-control studies, and ending with descriptive studies such as surveillance, surveys, and case reports [30]. However, a nuanced that takes into account the size of the study and the rigor of the study design, recognizes that large, well-designed observational studies can yield among the highest-quality clinical evidence. Moreover, observational studies offer evidence of clinical effectiveness under real-world conditions, in contrast with randomized trials, which may have restrictive inclusion and exclusion criteria and lack generalizability beyond the highly controlled experimental study settings [31]. A commonly used system of assessing the quality of evidence generated by medical studies is The Cochrane Collaboration's GRADE approach [32].

MDAs vary widely with regard to functionality. By being aware of the different functions offered by different MDAs, the clinician can tailor recommendations to patients with different musculoskeletal monitoring or rehabilitation needs. As detailed in **Table 1**, some apps are more focused on pain management, while others are focused on restoring and improving physical function. Some apps include hardware, such as EKG and heart rate sensors and sensors over joints to track movement. Other apps focus on behavioral interventions to address pain and help patients stay on track with physical therapy plans to address musculoskeletal injuries.

Evidence based exercise-therapy is another function offered by a number of digital vendors. From gathering detailed information on movement and activity and leveraging artificial Intelligence, digital apps can deliver personalized advice and exercise programs that adapt according to the progress made by the individual. Some apps focus on preventing the development of conditions and maintaining musculoskeletal health, including access to a comprehensive library of preventative exercise programs, including Pilates, yoga, stretching and strengthening options. TrackActive is a digital application that specializes in rehabilitation of musculoskeletal conditions and acts as virtual physio enabling people to assess and self-manage injuries and common conditions from home [33]. Based on the member profile, this application tracks members activities using different surveillance techniques and provides personalized recommendations. Telehealth apps that facilitate virtual second opinions for different musculoskeletal conditions are also increasingly being utilized [34].

Many digital apps now focus on musculoskeletal injury prevention in occupational settings. Musculoskeletal injuries are the largest single category of workplace injury and account for 28% of all occupational injuries [35]. Occupational health focused digital apps thus aim to reduce muscle, joint, tendon, ligament and nerve injuries/illnesses across the workforce to improve availability and productivity [36].

With 40% of all mobile apps related to healthcare, verifying accuracy of clinical content and validating apps for intended clinical uses is critical. While assessing the clinical benefit of MDA functions, it is important to review the available evidence. For example, one randomized controlled trial (n=215) concluded that an MDA that included behavioral interventions such as medication reminders, daily

surveys of symptoms and potential adverse effects, fared no better than usual care in reducing pain scores [37].

Mobile health apps for monitoring postoperative pain are another promising frontier for MDAs. Such digital apps can provide real time monitoring and symptom management and can help improve self-management skills with post-operative pain. To alleviate pain, digital apps can provide appropriate distraction, relaxation, and guided imagery techniques. However, a critical review of digital apps focused on self-management of pain showed very limited involvement of healthcare specialists and limited evidence based self-learning content. Lalloo et al. found that of 10 mobile applications meeting inclusion criteria, none provided social support, goal setting criteria, or had scientific evaluation or end users in their development [38]. Only 50% of the apps included a provider specialist in the development. There is accordingly a need to build comprehensive pain self-management, evidence based, personalized, AI-driven mobile applications.

When assessing an MDA's functionality, the clinician will want to assess the MDA's ability to not only improve subjective pain scores, but also to improve objectively quantifiable measures of disability function. The MDAs with highest likelihood of yielding clinical benefit are those whose efficacy on objective measures have been established in peer-reviewed studies [39]. For example, two smaller randomized controlled trials demonstrated efficacy of MDAs with respect to improving both knee and back pain and disability function [40, 41]. These beneficial impacts on both chronic musculoskeletal pain and disability function were subsequently confirmed in a large 10,000 participant longitudinal cohort [42].

Moreover, some MDAs offer population health surveillance features that can be useful to health officers in organizations tracking the health of their workforce. While such features can be very useful in workforce injury surveillance and prevention, it is important to be aware of privacy issues when deploying such solutions in an organizational or work setting. In particular, the ability to leverage Artificial Intelligence (AI) focused digital health apps for population health surveillance have garnered critical attention during the COVID19 pandemic. Tools that track disease activity in real time include contact tracing applications that identify and track individuals who might have come in contact with an infected person. User consent is essential for the adoption and sustained growth of such digital health applications [43, 44].

Finally, in evaluating the utility of digital health apps, clinicians should also recognize app performance issues such as functionality, stability/reliability, and stage of development, which affect the usability of the app and the benefit to patients. The proliferation of digital health applications has led app developers to focus on functionality, stability, security, privacy, usability, reliability, and data accuracy. In evaluating performance of mobile apps, it is advisable to utilize a framework that evaluates each dimension of the application. We recommend a framework consisting of rating domains and criteria for each domain. The domains are (1) Usability, which includes functionality, visualization, ease of install and use, multi-language support and ability to customize; (2) Content (Technical), which includes performance, stability, interoperability, portability, bandwidth and application size; (3) Content (Health), which includes quality, presentation and validation of the information, literacy level, measurement and interpretation of the information and potential for harm; (4) Security/privacy/compliance, which includes data authentication, protection, tokenization, authentication and pro-active breach signaling; and (5) Transparency, which includes member consent, cost of the app and accuracy of the description in the app stores [45].

*Evaluating the Clinical and Cost Effectiveness of Musculoskeletal Digital Health Solutions DOI: http://dx.doi.org/10.5772/intechopen.94841*
