Adherence is a crucial factor for treatments involving all medical braces. Adherence is defined as the percentage of actual wear time compared with that of prescribed wear time of a medical brace.1 It is the active decision of the patient to comply with treatment and is a behavior that can be influenced. In comparison, compliance is defined as a passive behavior.1 Thus, the rest of our discussion will use the term adherence to describe brace wear. Length of brace wear has tremendous effects on therapeutic outcome. Without proper adherence to brace protocol, satisfactory end results are difficult, if not impossible to achieve. The clinical solution may be excellent, but with lack of adherence, the projected results might not be seen.
Brace adherence has been studied for the past several years, and adherence rates among all devices are markedly low (i.e., orthopedic, orthodontic).2,3 Bracing can help facilitate favorable outcomes, and a study comparing bracing versus observation in scoliosis published in the New England Journal of Medicine (NEJM) was stopped early due to the efficacy of bracing.4 Irrespective of age group and disease state, the theme of inadequate adherence is consistent, which is indicated in the following summarized results. One study found patient adherence to orthodontic headgear wear to be 56.7% ± 22.1%.5 Nonadherence is a well-known problem in scoliosis bracing, and two different studies show nonadherence rates of 27%6 and 45%.7 A more recent study with adolescent idiopathic scoliosis (AIS) bracing used the Cricket, a temperature sensor, to quantify adherence between visits. Adherence rates gathered from these data indicated that 85.5% of patients did not comply with the prescribed wear time, furthering the idea of decreased adherence in scoliosis bracing.8 Clubfoot braces in young children follow a similar pattern with an estimated nonadherence rate of 30% to 41%.2
The above statistics give a sample of the low wear rate problem that plagues many medical devices. Later on in this article, we will argue that decreased wear rates increase the need for further therapeutic medical procedures. Moreover, The International Research Society of Spinal Deformities (IRSSD), a society of spine deformity experts created specifically to address the understanding of spinal deformities, has said that the outcome of spinal scoliosis bracing is incumbent on risk of progression, the in-brace correction, and the adherence.9
This review aimed to explore the low adherence rate among several medical braces and the negative effects of decreased adherence on individual health and the larger health care system. It includes the entire spectra of device usage, with both parental adherence for their children and self-adherence data, to highlight that poor adherence exists independent of the age group. In contributing to the low adherence, several factors have been shown to play an integral role. Among these include the long duration of treatment, social stigma, body image, expectations for treatment, and the treatment team used. Each of these factors will be discussed subsequently in more detail; however, being able to identify and quantify adherence more accurately is integral in elucidating factors of low adherence. Only in this way can steps be taken to address them to improve clinical outcomes.
Furthermore, research has also shown that decreased adherence leads to adverse outcomes that need further medical intervention down the line. For example, failed scoliosis bracing leads to surgical correction, indicating, as with other medical bracing, the link between low adherence and increased medical intervention. As a result, increased medical expenditure arises, further burdening our health care system. In addition, this article emphasizes the lack of adequate models to accurately quantify brace adherence. Earlier than 2000, we did not have the compact modalities to effectively gather patient adherence data. We will focus on these newer modalities and sensors to understand the need for further validation. Encouraging data from fitness trackers have shown that wearables have the ability to influence behavior. Individuals using the FitBit One for 6 weeks had a 1266-step increase by week 1 and a 4.3-min/wk increase in physical activity (PA) by the end (P < 0.02).10 Other studies have shown that using pedometers on smartphones along with multimodal engagement strategies with SMS texting have helped sedentary women increase their step count by 800 steps/d (P < 0.001) over 2 weeks.11,12 These results indicate the potential to bring about similar trends among brace wear in orthotics by transferring the techniques used in commercial trackers.
This article will delve deeper into the factors of nonadherence, highlight the impact of nonadherence on clinical outcomes and health care expenditure, and survey studies that have used sensors as a proxy for adherence. We will then introduce real-time monitoring as a solution to address some of the pitfalls of current adherence monitoring and introduce studies of fitness trackers to show how such technology has already been successful in other realms.
Searches were conducted on PubMed and Cochrane databases using the following terms individually or in combination: adherence, compliance, remote monitoring, brace treatment, scoliosis, mini magnetic mover 3MP, Pectus Excavatum, fitness trackers, activity trackers, FitBit, JawBone, and Nike FuelBand. In addition, references found in these articles were reviewed and used if applicable. The goal was to assess brace adherence monitoring platforms across different age groups and disease states. Because many of the modalities used to quantify adherence arose after the year 2000, we focused on this year range due to availability of better sensors and data validation. From this method, articles on adherence rates and monitoring systems in scoliosis, clubfoot, ankle, and knee immobilizer bracings were reviewed to analyze the low adherence. Commercial fitness trackers were assessed for their ability to monitor daily fitness metrics and use goal setting as a way to bolster adherence in relation to medical brace monitoring.
FACTORS THAT CONTRIBUTE TO NONADHERENCE
Patient cooperation with treatment is a crucial factor for nonadherence. There are several reasons why patients may not cooperate.
- 1) Long duration of treatment: The average duration of the brace treatment for scoliosis is between 1 and 2 years. There is a range of prescribed wear times, with the highest being around 23 hrs/d.9 Similar wear times exist for other braces, and for the pediatric population, it is challenging to adhere to this lengthy treatment.
- 2) Social stigma: Brace wear may make patients feel different and socially isolated from their peers. Thus, they might try to hide their brace and decrease brace wear altogether. Patients who have positive social experiences and interactions with peers and family are less likely to be nonadherent.5
- 3) Body image: Patients may try to hide their brace from their peers by wearing clothing that is several sizes bigger. Engaging in this behavior can become cumbersome and may serve as an additional barrier to adherence. A study conducted on AIS by Lindeman et al. showed the impact of psychosocial effects on adherence. These impacts differed based on patient's sex and duration of treatment. Among women, the most predictive factors for nonadherence were decreased expectations in success with treatment, low self-esteem, and decreased motivation to seek social support. Among men, predictive factors for nonadherence were optimism for the success of treatment and high self-esteem. These factors also changed with the duration of brace treatment.13
- 4) Attitude toward treatment: Patient's perceptions toward treatment also impacts adherence. Patients initially motivated to seek treatment may have better outcomes.5 In addition, younger patients may not be able to comprehend the long-term consequences of nonadherence.14,15
- 5) Treatment team: Adherence to prescribed treatment is affected by the patient, the treatment team, and the interaction between the two. According to the Clinical Guidelines Consensus on Brace Treatment Management, there are specific recommendations within the following domains: experience/competence, behaviors, prescription, construction, brace check, and follow-up.16 Interprofessional team care can positively affect adherence.17 Therefore, the lack of such a team dynamic may contribute negatively to brace adherence.
THE PROBLEM: IMPACTS OF NONADHERENCE AND DIFFICULTIES IN MEASURING ADHERENCE
This section will be broken up into three parts. The first part will focus on the impact of nonadherence on clinical outcomes, the second will delve into its impacts on health expenditure, and the third will discuss studies using sensor validation for adherence.
Impact of Nonadherence on Clinical Outcomes
In our previous discussion, we have already reviewed the low rates of adherence among several different orthotic systems. We have also examined several factors that may contribute to these low rates of brace wear. Consequently, low wear rates can negatively impact clinical outcomes, decreasing treatment success and increasing rates of recurrence. This next section will examine the results of several studies that analyzed low adherence and clinical outcomes.
The BrAIST trial was conducted on 242 adolescents with AIS to assess the benefit of bracing and its role in preventing curve progression. The trial found a 72% success, defined as limited curve progression, in bracing compared with just 48% with observation. Because the trial allowed some of the patients to choose bracing versus observation, an intention-to-treat analysis was completed, and it showed similar results: 75% versus 42% treatment success in the brace group compared with the observation group, respectively. The study also found an association between the number of hours of wear and likelihood of successful outcome.4 A different scoliosis study analyzed patients with adolescent idiopathic scoliosis for brace adherence and found a dose-dependent outcome of curve progression depending on how often the brace was worn. The study team validated the use of a temperature sensor to quantify adherence. There was 35% adherence in patients prescribed with 16 hrs/d brace wear and 28.6% adherence in the group prescribed with 23 hrs/d. Patients who wore the brace more than 12 hrs/d had a successful rate of 82%, in which they had a curve progression less than 6 degrees. However, those who wore the brace less had increased rates of curve progression. A 61% success rate was seen in patients who wore the brace 6 to 7 hrs/d and only 31% success in those wearing it less than 7 hrs/d. A total of 46.1% of the patients who adhered to the prescribed treatment had a successful outcome, whereas only 28.6% of patients who did not adhere to the prescribed wear time had a successful outcome.18
The data from this cohort were reanalyzed with the end point of curve progression defined as greater than 50%, which was defined as surgical range. Under these new parameters, patient adherence was stratified and the following results ensued. A total of 27% of the adolescents enrolled wore their brace for less than 2 hrs/d. Of these patients, 44% progressed to need surgical correction. However, in comparison, only 22% of the patients who had worn the brace for more than 2 hrs/d progressed to surgery.6 In addition, when scoliosis patients were stratified according to their brace wear, research showed that bracing for 8 or 16 hrs/d was less effective than for 23 hrs/d.6
Furthermore, similar results of decreased adherence leading to negative outcomes with clubfoot bracing have been shown.19 This method involves two phases, the first of which is a correction phase and the second is a maintenance phase. Nonadherence with either one was shown to have a higher risk of reappearance of the deformity, a need for rebracing, and a progression to surgery.19 Several other studies have linked decreased adherence with bracing to increased rates of clubfoot recurrence after orthotic treatment. Haft et al.20 found that the nonadherent group (49%) was 5 times more likely to have a recurrence. Dobbs et al.21 calculated nonadherent individuals (41%) to have a 183 times higher chance of relapse. Nonadherent children (36%) in the study of Avilucea et al.22 were, similarly, 120 times more likely to have a relapse. Although these specific statistics differ from study to study, the general trend is the same. Relapsed patients must seek further treatment for clubfoot correction, increasing the total health care expenditure.
Moreover, a study conducted by Janssen et al.23 studied the effects of ankle bracing in athletes at high risk of primary and recurrent ankle sprains. The 384 athletes were split into three groups. The control group received an 8-week home-based neuromuscular training program that consisted of triweekly exercises lasting 30 minutes. This program had been previously validated as having a 35% reduction in ankle sprain recurrence risk.24 The intervention group received a semirigid ankle brace that was to be worn during all athletic activities for 12 months. The last group received combination therapy with an 8-week neuromuscular training program in addition to an ankle brace that was to be worn during the athletic activities during these 8 weeks. At the end of the follow-up period, the brace group (risk ratio [RR], 0.53; 95% confidence interval [CI], 0.29-0.97) and the combination group (RR, 0.71; 95% CI, 0.41-1.23) both had significant decreases in ankle sprains compared with the control group.23 These results indicate how additional interventions (i.e., neuromuscular training, bracing) may lead to further improvement in outcomes because patients are engaged in multiple manners. The study by Janssen et al. demonstrates the therapeutic benefit a medical brace can have on decreasing the recurrence of negative outcomes, thereby decreasing net health expenditure.
Impact of Nonadherence on Health Care Expenditure
In many ways, medical brace adherence parallels the statistics of medication nonadherence, which contributes to a staggering $300 billion per year to health care costs.25,26 In addition, clinicians expect only 50% of patients to follow through with chronic medical therapy for 1 year, while only 65% of these 50% achieve therapeutic outcomes.27 Device nonadherence has a similar cost profile with decreased adherence rates leading to therapeutic loss. Scoliosis braces have some of the lowest adherence rates with two different studies showing nonadherence rates of 27%6 and 45%.7 In the study by Sanders et al. regarding AIS, 44% of the patients in the nonadherent brace group had progression to surgery, a preventable measure that is more invasive and expensive.6 Nonadherent individuals with clubfoot bracings were 5 to 183 times more likely to have a recurrence, which indicated repeat bracing or surgery.20–22 Both of these interventions add to the total costs and burden of the health care system. The study by Janssen et al. regarding the use of neuromuscular bracing in addition to training exercises hints that the idea of several interventions, with proper adherence, can mitigate negative outcomes and decrease costs.23
Furthermore, a study conducted by Cui et al. illustrated how early interventions with medical braces can decrease the rate of unfavorable outcomes, thereby saving hospital costs. This study determined that the use of knee immobilizer braces after total knee arthroplasty (TKA) decreased the number of falls experienced by patients. Twenty-two (3.7%) of the 600 TKA patients who did not receive a knee brace met with a fall. Conversely, only 8 (1.6%) of the 502 TKA patients who did receive a brace experienced a fall. The difference in the rates of falls was found to be significant with a P value of 0.04. Furthermore, patients who did not experience a fall did not have to be hospitalized and undergo imaging or follow-up procedures, saving more than $4000 in hospitalization costs per patient.28
SELF-REPORTED VERSUS SENSOR-REPORTED ADHERENCE
This low adherence rate has been postulated to be the cause of treatment failures leading to increased expenditure. However, poor outcomes were also observed among patients who self-claimed to have a high adherence rate. To assess the validity of these claims and shed light on the disconnection, researchers have used the use of sensors for an objective measure of adherence. Force, pressure, and temperature sensors have been the main types of sensors used to assess adherence in orthotic systems. These sensors have been integrated into braces used mainly in scoliosis, clubfoot, and obstructive sleep apnea. Temperature sensors measure brace wear by measuring the difference in temperature between the atmosphere and body. Pressure and force sensors use the compressive forces generated by brace wear to assess the amount of active brace wear. These sensors have all been validated in preliminary experiments in which braces equipped with sensors were trialed on healthy patients. Wear time was validated by cross-referencing the times the brace was recorded as being worn or off based on diaries kept by the individuals.2,8,15,29,30 The presence of the sensor also did not seem to affect the overall adherence to the brace.2
Regardless of the type of sensor, a force, pressure, or temperature measurement is obtained in equal intervals and stored in a data logger. These data are then downloaded at clinic visits by clinicians to ascertain brace wear adherence. This approach provides a much more objective understanding of brace wear compared with subjective questionnaires patients filled out previously. However, they only provide a very stochastic view of brace wear outside of the office visit and offer time-lagged adherence information available only at discrete moments during treatment. The sensor modality also comes with its own advantages and disadvantages. With pressure or force sensors, interpreting a reading of zero is challenging because it may indicate that the brace is not being worn or the fact that no pressure or force is being applied. However, temperature measurements do not yield a sense of the quality of the bracing, which may be better ascertained by a force or pressure measurement.31 They also create discrepancy depending on the weather condition, depending on whether the sensor is in direct contact with the body or on the garment. To further this discussion, we will highlight studies that each used different sensors to obtain objective adherence. We will also discuss a smart orthosis system that uses a pressure sensor to assess quality of wear.
The next several studies compare self-reported versus sensor-reported adherence in brace wearers. A study with 67 clubfoot patients compared self versus sensor-reported adherence in a foot abduction orthosis (FAO). All of the children in the study were younger than 3 years. The sensor used pressure as a proxy for measuring wear time in the patients. The study participants were split into three groups: 1) patients with a functional pressure-based sensor (FPS) in their brace; 2) patients with a nonfunctional pressure-based sensor (NFPS) in their brace; and 3) patients with no sensor (NS) in their brace. In addition, for subjective adherence, researchers assessed wear time through diaries of the patients' caregivers. Diaries were turned in at monthly clinic visits, which was also the case when data from the sensor was manually downloaded. Data logger data from the patients in the FPS group resulted in the following statistically different adherence rates for the first, second, and third month, respectively: 94.5%, 84.3%, and 77.1%.2 Adherence ascertained from the diaries resulted in the following adherence rates for the first, second, and third month, respectively: 94.9%, 95.6%, and 94.8%. Diary data from the NFPS group resulted in 95.5%, 95.8%, and 89.4% adherence for the first, second, and third months, respectively.2 The NS group had adherence rates of 94.8%, 94.9%, and 94.2% for the 3 months based on the diary recordings.2 Sensor-based adherence waned after the first month and was statistically different from the self-reported wear rate (P < 0.0001).2 These results highlight the disconnect between self-reported and sensor-based adherence, and indicate that patients and caregivers may not be a reliable historians.
A similar study comparing self-reported and temperature sensor-based adherence was conducted among AIS patients. The study included 61 patients between the ages of 6 and 16 years, all who had a 20° to 45° Cobb angle. Average time of follow-up after monitoring began was 17 months (range, 4–31 months). Sensor-reported adherence was 75% ± 27%, whereas patient-reported adherence based on verbal responses at clinic visits was 85% ± 24%. Patient-reported adherence was significantly higher (P = 0.01), reaffirming the idea from the previous study that patient-based adherence may not be an accurate indication of true brace wear.30
A study conducted in Hong Kong further investigated the self-reported versus sensor-based adherence enigma. This study was aimed to determine the correlation between brace adherence, in-brace correction, and quality of life (QoL) of patients with AIS. In order to do so, self-reported brace wear was collected in daily log sheets. Patients were asked to indicate if the brace was worn 0 to 8 hrs/d, 8 to 16 hrs/d, or 16 to 24 hrs/d. Objective brace wear was determined through the orthosis monitoring system on the brace that used the use of a force sensor. Patients' wear time was followed objectively and subjectively for 39 to 120 days. Patients returned to the clinic every 4 to 6 months, where the data from the sensor was downloaded onto a computer, and log sheets were reviewed by the provider. The subjective wear time per day as indicated by the log sheets was 10.7 hrs (±1 SD; 5.8; range, 0–21).32 The objective wear time indicated by the force sensor was also 10.7 hrs (±1 SD; 5.5; range, 2.3–19).32 The average difference between log sheet and sensor-based wear time was −0.1 hr (±1 SD; 3.3; range, −4 to 6.4), and the correlation between these two measures was significant (r = 0.83, P = 0.000).32 In addition, the team did further studies to correlate brace wear to in-brace correction. As expected from previously reported studies, subjects in the lower brace wear group showed a low in-brace correction and lower QoL.32 This study affirms the use of sensors as an objective measure of patient brace wear time and serves as a verification tool for subjective wear data. The association between brace wear and QoL brings up the social and emotional ramifications of low brace wear. In addition, these results further support the idea of using sensors in other brace-indicated syndromes as tools for validating adherence.
Moreover, a treatment model to use a smart orthosis system in scoliosis patients has been validated by Lou et al.33 Although we define a smart orthosis system as one that uses sensors to actively monitor patient's brace wear time and alert the patient and care team of progress, this particular system uses the use of a feedback loop to enable device actuation for better overall quality wear by tailoring the pressure applied without patient or care team notification. This study looked at five scoliosis patients (12.6 ± 2.2 years) to see if their designed monitor could enhance the quality of the wear time of the device. The device used a force transducer to measure the pressure the brace was applying and used an automatic air bladder to correct the pressure if it was outside of the prescribed range. This treatment model ensured that the brace was worn effectively while it was used on the patient. The patients wore their brace with the air bladder disengaged for 2 weeks and engaged for 2 weeks. The results indicated that the time during which the pressure was below, in-range, and above when the air bladder was engaged was 17% ± 13%, 68% ± 14%, and 15% ± 11%, respectively. When the air bladder was inactive, the time that the pressure level was below, in-range, and above was 30% ± 11%, 53% ± 9%, and 16% ± 7%, respectively. Adherence during this time was 72% ± 15% of the prescribed 17.5 ± 3.8 hrs/d.33 This model takes advantage of the instant pressure feedback to ensure quality brace wear time.
The above studies impress upon the need for continued development of objective measures of adherence to be able to address specific factors leading to low brace wear rates and unreliable self-reported data. They also introduce the idea of using sensors to better characterize quality in addition to quantity of brace wear.
POTENTIAL SOLUTION: REAL-TIME MONITORING FOR BRACE WEAR
In a $2.9 trillion health care system with projected rapidly increasing costs,34 interventions to prevent costly outcomes are crucial. Medical braces carry out this role by hindering and slowing down disease progression, hospital stays, and diagnostic/therapeutic procedures, as evidenced by scoliosis, clubfoot, ankle, and TKA braces.2,3,6 A major pitfall of all of the present monitoring systems used in previous studies have relied on downloading data at interval periods (e.g., weekly or monthly). A potential solution would be a system that integrates real-time smart sensor data with the clinical team to allow for a more connected and effective care delivery. In the smart orthosis system discussed above, feedback data from the pressure sensor ensured quality wear during the duration of brace wear.33 Introducing a similar system that uses novel sensor modalities for real-time monitoring of brace wear time daily or weekly allows clinicians to have adherence data earlier. This ensures earlier conversations between patients and physicians about behavior changes, elucidating a better outcome. It also allows providers to be able to characterize the degree of nonadherence among individuals and their adherence trends overtime. Clinical decisions guiding management will be different among patients that are only mildly nonadherent versus severely nonadherent. A brace wear of 1 hr less per day occurring every few days may not be as clinically significant. However, if this occurs daily and goes on a downtrend to even more decreased adherence, then these data will become more clinically significant. Thus, the degree of nonadherence overtime may be a more meaningful indicator of clinical outcome than just the degree of nonadherence itself.
In addition, patients can also self-monitor their progress and make improvements as needed. A study conducted by Miller et al. illustrated the power of being cognizant of adherence monitoring and its effect on individual brace wear time. The study divided a group of 21 patients with scoliosis into two groups. Both groups were subscribed to a corrective brace treatment plan; however, one group knew that they were being monitoring for adherence via a temperature probe, whereas the other group did not. At the end of 14 weeks, the group who knew they were being monitored had a statistically higher adherence rate than the other group (85.7% vs. 56.5%, P = 0.029). This corresponded to a difference of 5.24 hrs of daily brace wear.35 The study of Miller et al. demonstrates the power of adherence monitoring and how it can practically lead to behavioral modifications. Patient knowledge of being monitored for adherence by the care team serves as a motivation for brace adherence. The study of Miller et al. does not incorporate self-monitoring systems that enable patients to have an objective measure of their own progress and modify their adherence to meet their goals. A very close approach for self-monitoring systems was met by a study that used the Cricket sensor for adherence measurements. The brace included an LCD readout on daily wear and accumulated usage. Although the study itself did not focus on the impact of the LCD, it did report that the parents found it useful to encourage their children to use their brace more regularly.8 Such self-monitoring methods are part of the next frontier, which will allow for real-time changes to better individual health outcomes and decrease health care costs.
Another part of the solution includes incorporating other modalities of engagement platforms to brace wear monitoring. Currently, the technology for real-time health monitoring exists in the market. Consumer companies have been successful in driving adoption of self-monitoring fitness products such as FitBit, JawBone, Nike FuelBand, and others. Individuals are able to monitor their own fitness through the number of steps taken per day, calorie intake, and heart rate, and assess progress toward milestones. This approach allows for instant personalized behavior and lifestyle changes. These fitness trackers have behavior change techniques built into their platforms. They use goals, automated prompts, social communities for support and comparison, rewards, and focus on past success to generate automatic notifications and graphs of the individual's progress.36 Patel et al.37 stresses the importance of these engagement strategies (individual encouragement, social competition and collaboration, and effective feedback loops) over tracking for behavior change. Among individuals that track their weight, diet, exercise, blood pressure, and other health indicators in some form, 46% indicated that tracking changed their approach to their own health and the health of someone they took care of. In addition, 40% were also able to use the tracking knowledge to ask doctors appropriate questions for managing their health. Tracking also affected 34% of them when making a decision about treating an illness or health condition.38 Fukuoka et al. conducted a study with 41 sedentary adult women and analyzed the use of pedometers with smartphones that received daily messaging and prompts regarding the benefits and barriers for continuing PA. This engagement platform helped create a mean increase of 800 steps/d (P < 0.001) over 2 weeks.11,12
To further assess the ability of wearables to impact behavior change, a study looked at the effect of tracking fitness levels with FitBit and text messaging prompts. One hundred seventy-seven overweight and obese subjects were split into 2 different groups. Both groups were assigned to wear a FitBit for 6 weeks; however, only one of the groups was also sent daily SMS texts reminding them to engage in daily PA. Outcomes measured were steps and time of PA, stratified by the intensity level. The study found that SMS texting was able to cause a statistically significant increase in PA between the groups during week 1 (P < 0.02) during which step count increased by 1266 (SE = 491; P = 0.01), fairly/very active minutes per week by 17.8 (SE = 8.5; P = 0.04), and total active minutes per week by +38.3 (SE = 15.9; P = 0.02). However, even without the SMS messages, the control group had an increased baseline PA by 4.3 min/wk (SE = 2) at the end of 6 weeks. This group also reported viewing their FitBit trackers “very often” or “often,” and it was these same individuals that had a higher PA at the end of 6 weeks.10 The short-term effect of text messages on PA needs to be further investigated to understand how best to influence behavior change and, later on, adherence. In addition, text messaging as a mechanism of early intervention for chronic disease management has also shown benefits in diabetes management, smoking cessation, and weight loss.39 The first step to be able to translate these effects to medical braces is to design accurate monitoring systems.
Fitness tracking systems are cost friendly and readily available to the public; however, a similar clinical analog for brace adherence does not yet exist. A related device in obstructive sleep apnea treatment has recently received US Food and Drug Administration (FDA) approval to integrate a microrecording device for compliance measurement. SomnoDent devices are wearables for patients undergoing continuous open airway therapy (COAT) for sleep apnea. With the use of the integrated DentiTrac microrecorder, real-time adherence can be wirelessly measured. Preliminary tests have shown an adherence rate of 95% for a prescribed wear time of 21 nights a month. Such a system translated to other medical and orthotic braces would have a tremendous impact in the ability to remotely monitor adherence.29
Related systems to fitness trackers and SomnoDent have been reported on, but none of them used real-time monitoring of brace adherence with an independent user interface. In addition, currently, any sensor data from a brace measuring wear time needs be manually downloaded at clinical visits and analyzed. Only at these times can physicians make recommendations on future brace use.2,6,18 There is no system in place for remote monitoring of patient brace wear, which prevents real-time and continuous guidance from the care team. The future of monitoring, in addition, should not just focus on the ability to monitor adherence but also on the ability to gather data in real-time with the advent of new sensor modalities, so that we can intervene between clinical visits. We can then study the impact of these interventions to understand their impact on adherence. A comprehensive table of the studies discussed in this article is listed in Table 1 in chronological order.
We can augment this approach with a social engagement platform for the patients to interact with other patients experiencing the same disease or condition. Interaction among peers could be a more effective approach to encourage the patients to adhere to the treatment. The system will also use notifications to encourage patients to increase their brace wear if goals are not met, while reinforcing positive behavior with congratulatory messages. A study conducted on obese patients with serious mental illnesses used activity monitoring devices such as FitBit, Nike Fuelband, and smartphones to test the feasibility of m-Health in activity tracking. The results indicated that patients found the ability to set goals and self-monitor their progress as motivational. In addition, patients were able to see the progress of other patients and found this social connectivity and competition to be particularly engaging for their own improvement.40 Studies that combined fitness tracking with engagement platforms with daily messages, goal setting, and progress visuals on smartphones found an 800 to 1100 mean increase in daily step counts.11,12,41
With real-time monitoring, physicians will also have the ability to contact patients in between visits to investigate reasons for low brace adherence so barriers can be addressed and overcome in a more direct manner. Open communication addressing these concerns can encourage personalized treatment plans that are in line with both the provider's and the patient's priorities. As shown in previous studies, earlier interventions combating lower adherence can decrease disease progression and assist a favorable outcome of a corrected chest.2,3,6 The current medical bracing field lacks systems to accurately monitor real-time adherence. The addition of technology-enhanced real-time adherence monitoring will elicit patient behavior modifications and establish a closer partnership between patients and clinicians. Such an approach would facilitate a program to faster assess clinical progress in patients and intervene if needed earlier. This will also enable more research on real-time monitoring and its affect on adherence, which is currently lacking in the literature.
Brace treatments are proven to be effective if patient adherence is comparable to prescribed dosage. Methods should be developed to help patients adhere to brace treatment. Real-time monitoring is the next direction for medical device adherence. It can help close the gap between self-reported and actual adherence data, while facilitating a more therapeutic outcome with the ability to intervene with earlier health interventions from the care team. With more studies to assess the impact of being able to intervene earlier, we can also understand the role of real-time monitoring in improving adherence. The ability to generate accurate adherence data will also enable us to assess and validate existing and new medical braces. The technology to create such a system already exists in the market as evidenced by the consumer health monitors; however, it has yet to be translated to the clinical realm. An approach taking advantage of wireless remote adherence monitoring system can be applied to other brace systems to enable accurate monitoring across other medical braces, allow early intervention in case of nonadherence, and encourage increased adherence.
1. Negrini S, Hresko TM, O'Brien JP, et al. Recommendations for research studies on treatment of idiopathic scoliosis: consensus 2014 between SOSORT and SRS non-operative management committee. Scoliosis
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3. Rowe DE, Bernstein SM, Riddick MF, et al. A meta-analysis of the efficacy of non-operative treatments for idiopathic scoliosis. J Bone Joint Surg Am
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5. Bartsch A, Witt E, Sahm G, Schneider S. Correlates of objective patient compliance with removable appliance wear. Am J Orthod Dentofacial Orthop
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8. Rahman T, Sample W, Yorgova P, et al. Electronic monitoring of orthopedic brace compliance. J Child Orthop
9. Bagnall KM, Grivas TB, Alos N, et al. The International Research Society of Spinal Deformities (IRSSD) and its contribution to science. Scoliosis
10. Wang JB, Cadmus-Bertram LA, Natarajan L, et al. Wearable sensor/device (FitBit One) and SMS text-messaging prompts to increase physical activity in overweight and obese adults: a randomized controlled trial. Telemed J E Health
11. Fukuoka Y, Vittinghoff E, Jong SS, Haskell W. Innovation to motivation—pilot study of a mobile phone intervention to increase physical activity among sedentary women. Prev Med
12. Bort-Roig J, Gilson ND, Puig-Ribera A, et al. Measuring and influencing physical activity with smartphone technology: a systematic review. Sports Med
13. Lindeman M, Behm K. Cognitive strategies and self-esteem as predictors of brace-wear noncompliance in patients with idiopathic scoliosis and kyphosis. J Pediatr Orthop
14. Fällström K, Cochran T, Nachemson A. Long-term effects on personality development in patients with adolescent idiopathic scoliosis. Influence of type of treatment. Spine (Phila Pa 1976)
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