The Promises and Pitfalls of Leveraging Mobile Health Technology for Pain Care

Introducing Mobile Health

Mobile health technology (mHealth) includes cell phones, smartphones, and wearable sensors that offer several putative advantages over customary approaches when generating and/or communicating personal data from patients with acute, cancer, and non-cancer pain. Due to their flexibility, simplicity, and increasing affordability, mHealth devices represent a new generation of tools with the potential to improve pain management by reliably and safely collecting pain, function, and activity data outside of the clinical setting and facilitate delivery of interventions (e.g., instruction in cognitive-behavioral methods of pain management).

mHealth is defined as “handheld [or wearable] transmitting device[s] with multi-functional capabilities [that can be] used to store, transmit and receive health information and has user control over the access to the health information.” [1] The growing popularity of mobile devices among patients means that clinical data can be collected while patients engage in their usual daily activities. These data have substantial potential to impact patient care in a number of ways to include informing clinician decision-making for symptom management, promoting positive patient behavior change through real-time feedback, and providing supplemental data that enrich patient–provider communication. In the near future, collecting and sharing mHealth data between patients and multiple authorized stakeholders will produce new and perhaps revolutionary models of health care delivery including pain care [2].

The promise of mHealth does not come without potential pitfalls. The design of mHealth devices may have significant effects on data quality and accuracy. Design issues are of particular concern for older patients as many experience functional (e.g., physical and cognitive) changes with age. Other considerations include the ways in which mHealth-derived data can be optimally presented to health care providers and caregivers, and protecting them from being overwhelmed by a sea of data. Indeed, a review of 111 pain apps for patient use (released on the market in 2009 and 2010) found that there was very low involvement of health care providers in the development of the apps, raising concerns about the utility of the information generated from the health care providers’ perspective [3]. Over 50% of the apps provided some type of education for patients, about one quarter included a function that allowed patients to enter and track symptoms over time, while about one in five apps provided relaxation skills training. Perhaps of most concern, many of the apps suggested that device use could lead to pain relief without citing any evidence of device efficacy or effectiveness [3].

In this article, we describe how the devices might be used in the area of pain management, and present several promises and potential pitfalls associated with mHealth in this area. In addition, we highlight areas in need of research that could enhance the development of practical mHealth devices for use in pain care.

Active, Passive, and Hybrid mHealth: Pain Monitoring

Patients employ active mHealth when choosing to take an action such as launching an application (“app”) and self-reporting pain or associated symptoms. For example, the WebMD Pain Coach app, which has yet to be independently evaluated, offers users a variety of features that enable users to track their levels of pain over time, journal their pain episodes, and set goals related to areas such as diet and activity. The app also provides educational and motivational resources including text and video, as well as “physician-reviewed” tips to support pain self-management.

In a recent study of active mHealth for pain care, investigators in Norway evaluated a smartphone-based intervention for use among women with widespread musculoskeletal pain [4]. Following completion of a 4-week, inpatient rehabilitation program, participants randomized to the active intervention group were asked to complete three diary entries daily over a 4-week period. These participants provided diary entries regarding their pain, pain beliefs, and use of self-management activities designed to encourage patient self-monitoring and reflection. Responses were posted on a secure website where therapists could review them and then provide individualized patient feedback along with positive reinforcement. Control participants received standard care along with access to a non-interactive website with information regarding the use of self-management strategies for pain. At the 5-month follow-up, participants randomized to the active treatment group were found to have significant reductions in catastrophizing and symptom levels, along with greater pain acceptance and overall functioning [4]. These findings support the notion that mHealth devices can lead to improved pain outcomes at the patient level.

Passive mHealth refers to devices that run in the background on a smartphone or a wearable device and do not require active engagement on the user’s part. The data generated by these devices can be transmitted to an authorized source such as the patient’s health care provider or a family member. Unlike active mHealth that relies on users to purposefully engage a device, passive mHealth may be worn on the body or embedded into a smartphone, thereby enabling users to engage in daily activities with little (or no) notice of the data being collected. Over the last 5 years, various forms of passive mHealth have been applied in an effort to improve patient care [5,6] for an array of health outcomes, including monitoring heart rates [7] and detecting falls among older adults [8,9]. This research holds promise for pain care in that health care providers can better track patients’ daily physical activity levels and better detect actual (or potential) adverse events, e.g., falls or unsteady gait in an older patient on a pain medication. Finally, passive collection of data could be a valuable tool in the treatment of older pain patients, many of whom may have difficulty actively interacting with mHealth devices.

Swiss researchers offer a recent example of passive mHealth for pain care in a small experimental study [10]. They evaluated wearable sensor devices among patients with chronic pain and controls with no reported pain problem. The sensors passively collected axiometric and accelometric data using built-in gyroscopes and accelerometers to track movements. After subjects wore the sensors 8 hours a day for 5 days, researchers detected patients with chronic pain spent significantly fewer hours performing daily physical activities (sitting, standing, and walking) than patients without chronic pain. Given that most, if not all, smartphones possess gyroscope and accelerometer functionalities, this type of passive monitoring for activities of daily living could soon be employed by many pain patients.

mHealth can potentially take a hybrid approach that uses aspects of active and passive functions together. A hypothetical example of this would be to passively collect physical activity while patients actively enter diary data to determine any associations between function and patient distress. We have been unable to identify any peer-reviewed research that evaluates a hybrid mHealth approach in the area of pain care, but we believe that utilizing both active and passive functions to collect objective and subjective data together offers exciting novel approaches to improve pain management (Table 1).

Table 1.

Active, passive, and hybrid mHealth interventions monitor or intervene on a user’s behalf

mHealth Type	Purpose	Hypothetical Example
Active	Device data input requires a user’s focused attention.	A user types into a smartphone application using its keypad to describe how pain is affecting her mood.
Passive	Device data input does not require a user’s focused attention.	A digital pedometer in a shoe captures a user’s number of steps per day, then automatically transmits the data to an application that logs over time the total number of steps taken on a daily basis.
Hybrid	Device data input does not require a user’s focused attention up to a defined threshold, beyond which, the device alerts a user for focused attention.	A smartphone’s gyroscope monitors a user’s postural sway, then alerts the user and user’s caregiver when the degree of sway registers as abnormal.

mHealth = mobile health technology.

The Promise of mHealth to Improve Pain Care

There are many potential promises associated with using mHealth devices to inform pain treatments and overall patient health. Some of the most important putative benefits are described briefly below.

Potential Promise #1: More Effective Monitoring

mHealth has the potential to improve objective measures of pain by providing the means to monitor daily pain levels, assess for associated symptoms (e.g., fatigue, mood, anorexia, sleep disturbance), capture treatment-related side effects, improve medication adherence to analgesic medications, deliver educational materials, and facilitate timely interactions with health care providers. For example, we found that aside from pain itself, focus groups of primary care providers would most value mHealth that could monitor bowel function of patients newly prescribed opioids [11]. The potential for monitoring is being welcomed in fields such as neurorehabilitation [10], and pain medicine might benefit, too, by using mHealth devices that monitor the gait quality of older patients newly started on opioid treatment. This type of monitoring could alert providers, families, and patients themselves to take action before the risk of a fall becomes too great.

Potential Promise #2: More Accurate Reporting

mHealth has the potential to improve the reliability of patients’ pain reporting by way of interactive reporting features made possible by ubiquitous availability. Because people often carry cell phones and smartphones with them wherever they go [12], this means that pain diaries and measures of associated symptoms (e.g., fatigue, depressive symptoms) can be captured at home and in other settings as well. For example, mHealth interventions under development at Cornell University demonstrate that ecological momentary assessments with mHealth improve patients’ recall and therefore generate more reliable data [13]. One experimental technology platform, called MobiScale, can support apps that present time-appropriate surveys to users to capture subjective symptoms and transmit those data back to patients or to providers in real time [13]. This platform is in the testing phases for use in pain management.

The approach that MobiScale and others like it offers is one that can enable patients to share data with providers, families, and friends. These patient-reported data can be aggregated and subsequently offer providers a richer view of a patient’s status that could lead to more timely changes in medication and other treatment regimens. Our research into older pain patients’ attitudes around mHealth suggests that most older adults with chronic pain would welcome the opportunity for greater surveillance in the home environment, providing that surveillance led to improved treatment outcomes [11].

Potential Promise # 3: Improving Patient–Provider Communication

Using mHealth to promote patient–provider communication in the context of pain management constitutes an exciting opportunity to deliver patient-centered information and services. Because mHealth devices have the ability to integrate active, passive, and hybrid monitoring with bidirectional communication between patients and their health care providers, these tools may promote connectedness and social interactivity. Connectedness and interactivity can be of particular importance to older adults with pain who often times also suffer from social isolation [14]. There are exciting research opportunities to understand whether and the extent to which mHealth positively impacts perceptions of connectedness and security among patients with pain and their providers. We have much to learn as to how best to meet each party’s communication and information needs [15].

Potential Promise #4: Innovative Treatment Delivery Mechanisms

mHealth offers new ways to deliver pain treatments and therapies to patients. We have already noted Kristjánsdóttir et al.’s randomized controlled trial in which women who used smartphone-based diaries along with receiving standard care reported significantly increased physical function and pain acceptance along with significantly reduced catastrophizing as compared with control subjects [4]. The Center for Connected Health in Boston, MA, is embarking on research to test if mHealth-delivered feedback using text messaging and “interactive voice response (IVR)” can help patients with cancer-related pain better manage their pain and pain care [16]. These mHealth projects offer hope for delivering effective and patient-centered pain care.

Potential Promise #5: Enabling Research

The National Institutes of Health support mHealth research in a number of ways, from workshops on using smartphones to track disease [17], training [18], and disseminating mHealth evaluation best practices [19]. These efforts are critically important for pain medicine because mHealth data could provide ample opportunities to gain more insights than ever before about pain, its impact, and potential solutions for reducing pain in diverse patient populations. One such approach could involve the development of pain registries where mHealth device users voluntarily upload their deidentified data so that researchers can electronically discover new associations between pain, medications, and patient outcomes. An example of one such resource is PatientsLikeMe, a website that consumers use to track their personal health data and then share those data with other patients. Researchers are beginning to use data from PatientsLikeMe to determine clinical outcomes [20] as well as online social behaviors [21]. Other disciplines such as bioinformatics [22–24] and neuroscience [25,26] are collecting and making deidentified clinical data available for research. Using their work as examples, the field of pain medicine could follow suit and make available deidentified mHealth patient data so that researchers may reuse those data to investigate novel research questions.

Potential Pitfalls of Using mHealth to Improve Pain Care

There are many potential pitfalls associated with using mHealth to manage patients with pain. Several of the most important potential pitfalls are outlined briefly below.

Potential Pitfall #1: mHealth that is Not User-Centered

To promote patient adoption of mHealth, the devices must be patient-centered and help patients achieve four pillars of patient-centered care: 1) caring for the whole person; 2) promoting communication and coordination; 3) empowering patients; and 4) improving access to health care [27]. However, mHealth must be useful and easy to use or patients will likely fail to adopt the technology. Public and private entities should be encouraged to fund research that generates empirical evidence regarding how patients’ perspectives and needs can be effectively integrated into mHealth designs. Our preliminary work with older patients [28], in addition to other research [29,30], shows that design features that accommodate their functional abilities are critically important.

Patients may not adopt mHealth interventions for other reasons such as a dislike or distrust of continuous passive and active monitoring. If that were to be the case, might patients be more amenable to monitoring if it were for defined time periods, such as the period immediately following a new analgesic trial (e.g., starting an opioid medication). An additional set of questions includes whether or not continuous monitoring “should” occur. These questions lead to unresolved issues around data security and privacy that are addressed next.

Designers and developers must work in tandem with patients and providers to translate user needs into safe, effective, and practical mHealth technological interventions [31]. Additional research is needed to develop and test effective designs of software tools, such as device usability [32], that better address the needs of both patients and providers in order to improve pain management. To date, few efforts have employed evidence-based approaches to insure that the methods by which mHealth software is developed meet patient, provider, and regulatory requirements. There is still much to be learned as to how much trust patients will place in mHealth technologies and whether these technologies will appropriately meet (or fail to meet) patients’ needs.

Potential Pitfall #2: mHealth Data could Overwhelm Health Care Providers

Given that mHealth has the potential to generate large amounts of patient-level data, and that health care providers would be responsible for interpreting and in certain cases taking action based on these data, mHealth has the potential to profoundly impact the ways health care providers practice medicine. The potential “tsunami” of patient data will no doubt affect health care providers’ abilities to respond to patients in a timely manner. Providers in focus groups that we have conducted lent confirmatory evidence about this concern [11,28]. The participants’ proposed solution was to have a care manager or nurse synthesize the data first and then transmit only the most pertinent information that would likely require a health care provider intervention (e.g., pain score remains above 7 despite initiating a new therapy 48 hours earlier). Although potentially valuable, this approach could require human resources that are beyond the scope of many practices. Automated tools that have yet to be developed could help identify concerning trends or discrete patterns (such as unstable gait due to opioids, or potential opioid abuse) and alert providers sooner in the titration period as compared with current approaches.

Understanding how mHealth impacts health care providers’ practice patterns, including the ability to respond effectively to mHealth-generated data, constitutes a critically important area in need of investigation. Collaborations between health care providers, informaticians, mHealth usability experts, and end users (i.e., patient with chronic pain) are strongly encouraged. These types of collaborations could help to identify the most salient symptoms and other outcomes to monitor and develop effective graphical representations of mHealth-derived patient data for optimal use by patients, as well as their providers that could help with decision making. In addition, there will be a need for the health care system as a whole to develop reimbursement strategies to better insure that providers are properly remunerated for engaging with patients who provide health information via mHealth devices.

Potential Pitfall #3: mHealth could Fragment Care Delivery

Interoperability between electronic health record (EHR) systems and mHealth-generated data currently remains the exception rather than the rule. Few, if any vendors, have linked patient data generated from mHealth devices with EHRs so that providers can readily access the data. Although standard bodies such as The Institute of Electrical and Electronics Engineers, Open mHealth, and the Continua Health Alliance (an industry-led consortium) are promoting mHealth interoperability, standards have yet to take hold to a significant degree [33]. We call on industry representatives, researchers, and policy makers to develop and disseminate standards that enable mHealth data interoperability.

Lastly, health care systems must develop and implement policies that specify the ways mHealth-derived pain data are incorporated into clinical care. Policies must provide guidance as to the ways patients can decide to make mHealth data available to family, health care providers and/or other stakeholders (e.g., paid caregivers). Currently, the Health Information Portability and Accountability Act (HIPAA) does not apply to mHealth data that reside on mobile devices, but would apply if those were interfaced into a provider’s electronic health record system. In addition, there are currently no federal or state policies that regulate how mHealth data are stored on devices or specify the security measures that should be in place such as password protection or data encryption. An alphabet soup of federal agencies currently have a stake in mHealth, including the Federal Trade Commission, the Federal Drug Administration, and the Department of Health and Human Services Office for Civil Rights Division that oversees HIPAA [1]. However, Happtique is a private entity that recently offers mHealth certification but its degree of influence remains to be seen [34].

To mHealth and Beyond!

In conclusion, the current literature demonstrates a growing interest in how mHealth technologies can be designed and implemented to improve health and health outcomes of patients with a diverse array of pain disorders [35–38]. Research in this area could potentially translate into better models of pain care delivery and improve treatments and associated outcomes among patients with acute, chronic, and/or cancer-related pain. An important gap that must be addressed involves developing effective ways to incorporate pain patients’ perspectives to inform safe, reliable, and effective mHealth technologies that promote sustainable communication loops with health care providers. We welcome and encourage future research in the design, development, and use of mHealth technologies to improve pain care.