Peripheral Arterial Disease: Harnessing Digital Health for Monitoring and Management

A digital tool was defined as any device, software, or web-based application designed for monitoring, diagnosis, or treatment of PAD. A sensitive search strategy adapted from the Cochrane Collaboration was constructed to identify all available studies regardless of publication status e.g. in-press or ahead of print. Major databases were searched from inception to January 2016. These included MEDLINE (using the OVID interface), EMBASE and the Cochrane Central Register of Controlled Trials. All titles and/or abstracts identified from the initial search strategy were independently reviewed by two authors. If no abstract was available, or if necessary, the entire manuscript was reviewed. After exclusion of clearly irrelevant studies, full texts of the remaining articles were retrieved and independently reviewed by two authors. Information was gathered into evidence tables detailing the intervention and results of each study. Due to heterogeneity in outcomes and studies, it was not feasible to perform a quantitative synthesis of evidence and qualitatively summarising results would not adequately represent the diversity of digital interventions. RP and RB were involved in all stages of the systematic review and any disagreements were resolved by consensus.

Chronic disease is now the most important global healthcare challenge. Among chronic maladies, peripheral arterial disease (PAD) separates itself from most as an interesting yet little understood area for potential improvement. Though its momentum is increasing, digital health innovation has not historically been a strong point for PAD. By describing current evidence of PAD digital health and the potential for future interventions, the goal of this review is to provide a comprehensive landscape of the use of digital tools in PAD.

Benefits of Digital Health in Monitoring Peripheral Arterial Disease

RPM services were initially aimed at patients with diabetes and heart failure, but it has now been shown to be useful in a diverse variety of health conditions, including chronic obstructive pulmonary disease and postoperative monitoring. In the case of PAD patients, RPM would allow continuous monitoring of their ABI without the need for follow-ups. Should a patient with PAD undergo treatment that may result in transient worsening of their condition, this can be monitored through the change in ABI if RPM services allowed the automatic recording of ABI data from the ABI devices. This would be particularly useful for patients with intermittent claudication who may struggle walking to health facilities and further save time in more severe cases of CLI where there are impending risks to the patient’s limb.

Remote patient monitoring (RPM) is a digital healthcare service that enables patients to monitor, record, and share their own health indicators. At some point in time, this was in the form of self-written or recorded data. In recent years, there is an emerging trend to use RPM tools, such as Bluetooth-enabled electronic devices, for the transferring and sending of health indicators to healthcare providers. This allows for continuous monitoring, which aims to reduce or substitute for time-consuming face-to-face monitoring of chronic health conditions. It is estimated that by the year 2018, 70 percent of healthcare providers in the United States will implement an RPM program.

Remote Patient Monitoring

With recent advancements in Bluetooth blood pressure and heart rate monitors for home use, these vital signs can be recorded and transmitted to a central database or directly to healthcare providers quite easily. Wireless monitoring systems can constantly collect and transmit data such as a patient’s weight, blood pressure, and walking duration without patient initiation. This provides a large amount of data on the patient’s health status and allows for the detection of long-term trends. Both methods are superior to data collected at infrequent office visits and rely on self-reporting by the patient. Although no studies have been done for PAD patients using these specific methods, it has been shown that frequent monitoring of vital signs in diabetic patients can result in early detection and treatment of adverse conditions. This has potentially large implications for PAD patients considering the high rate of coexistence between the two diseases.

Remote patient monitoring (RPM) of chronic diseases has been shown to be an effective means of improving patient care. By continuously tracking patient vital signs and other health indicators, heart failure readmission rates and all-cause mortality can be reduced. Similarly, for PAD patients, RPM can better inform clinicians of the status of their patients and allow for earlier detection and treatment of deteriorating limb ischemia. This can, in turn, reduce the need for invasive treatment or amputation and lower healthcare costs. RPM covers a wide variety of techniques, including the measuring of blood pressure and heart rate over the telephone or internet, wireless monitoring of vital signs, and self-recording of symptoms or health status. Telephone support has been shown to be effective in reducing PAD patient cardiovascular events and improving exercise capacity.

Real-Time Data Collection

An approach utilizing comprehensive data collection and analysis techniques has exciting potential to improve our understanding of disease progression and the response to treatment in PAD. Traditional measures of symptomatic PAD such as walking distance, quality of life, and time to an endpoint are relatively blunt tools, and the heterogeneity of patient response restricts the power of randomized controlled trials to detect meaningful differences between treatment groups. Comprehensive data collection, in which symptom status and daily activity are correlated with objective evidence of disease severity, may allow stratification of PAD into different ‘phenotypes’ and identify surrogate endpoints for clinical trials. This, in turn, may permit targeted treatments matched to disease severity and better assessment of new treatments in early phase studies.

Continuous digital monitoring of physiological parameters such as heart rate, blood pressure, oxygen saturation, and activity allows the collection of substantial volumes of data on the PAD patient. Over the course of a day and in different environmental or activity situations, such ‘ambulatory’ data can be collected over short or prolonged periods using automatic, non-invasive, and minimally intrusive methods. In comparison with unsupervised hospital stress testing or circulatory studies, such data is more representative of the patient’s usual functional capacity and symptom status. Since those with intermittent claudication may have a poor understanding of the relationship between their symptoms and objective evidence of functional impairment, real-time data may uncover important insights into the natural history of PAD and the relationship between transient ischemia and functional decline.

Early Detection of Complications

Digital health can greatly assist in the early detection and treatment of complications of PAD. Disease progression is often subclinical. Identification and characterization of early disease states can provide an opportunity to modify the natural history of PAD. Up to 50% of patients with PAD demonstrate limb hemodynamic deterioration in the form of decreased ankle pressures or claudication reproducibility. Unfortunately, only a small proportion of these patients seek medical help based on these symptoms. Many patients dismiss newly acquired claudication as a normal part of aging and the general public tends to underestimate the seriousness of claudication. In the absence of routine surveillance, aneurysmal disease, a limb and life-threatening condition, is often first diagnosed after rupture or acute limb ischemia. Traditional physical examination and auscultation for a femoral bruit has poor sensitivity and specificity for detection of stenosis. Segmental blood pressure measurements and pulse volume recordings are more accurate but are underutilized and unfamiliar to many clinicians. Duplex ultrasound and arterial imaging is costly to repeat frequently and has yet to be proven to alter disease morbidity. By identifying deviations from usual patterns of activity before the onset of overt symptoms, REM and real-time monitoring can provide an early warning system for acute events and limb-threatening ischemia. The strong association between changes in gait and posture with lower extremity strength and blood flow suggest that wearable monitoring devices, gait analysis, and posture recognition software may be a useful tool to assess limb function and to monitor patients for functional decline.

Challenges and Limitations of Digital Health in Managing Peripheral Arterial Disease

The usage of digital health in managing PAD may be impeded by a number of challenges and limitations. Devices and technology which are currently available may be too expensive for the average person or be too difficult for people to have access to. A significant limitation will be in the accessibility and affordability of mobile technology and wireless networks. The cost of mobile devices may prevent some patients from being able to access these tools, and the cost of wireless connectivity, though decreasing, may still be too expensive for many. This may result in an exacerbation of the digital divide in healthcare, where the poor and underprivileged have decreased access to the latest and best forms of healthcare management. This issue of the digital divide is especially relevant in the developed world, where there is an aging population with increasing prevalence of PAD. In contrast, feasibility may not be an issue in the developing world, where there is a younger population with increasing access to mobile technology, but where the burden of PAD is not as high. If mobile health tools are to be used for monitoring the health status of patients with PAD and for self-management of their condition, it is essential that the data which is collected remains secure. This is of particular importance if the devices are to be used in a healthcare system with information exchange between patients and healthcare providers. However, security is not always guaranteed with the use of mobile health technology. A recent review on the use of mobile devices in healthcare found that there is a notable lack of security in the apps which are currently available, with 61% of free apps and 41% of paid apps lacking any form of privacy policy. Apps which act as medical devices are regulated by the U.S. Food and Drug Administration, but the regulation is not always adhered to, and the security of other health apps is variable. It was also identified in the review that the data which is transmitted between a mobile device and a healthcare provider is not secure. Measures will need to be taken to ensure that the data from mobile health devices used by PAD patients is stored securely, and that there are policies in place to prevent data breaches. This is also relevant to the protection of the patient’s privacy.

Accessibility and Affordability

While the use of mobile health apps provides a useful method of recording patient data, it has been argued that digital health may not be an accessible option for lower socioeconomic groups. This can further increase health disparities as those who need it most may not be able to afford or have access to digital health technologies. There has been increasing use of mobile phones, especially in third world countries, to bypass the problem of limited access to infrastructure such as telephone lines and computers. The “mHealth” movement has great potential to progress health care in these areas, however still excludes the poorest members of society, as it relies on the availability of an expensive smartphone and mobile data plan. In developed countries, while smartphone usage is prevalent, older technology users are less likely to possess a smartphone and utilize mobile health apps. This demographic is largely comprised of PAD patients, as it is a condition of older age. Smartphone applications are often developed for newer operating systems and phones and may not be compatible with older phones. An American survey reported only 18% of adults aged 65 and older own a smartphone, making it difficult to ensure these technologies are inclusive for all age groups.

Data Security and Privacy Concerns

In accordance with these goals, further research has been funded by the US National Institutes of Health to define standards and guidelines for the development of secure and private mobile health applications. The Health on the Net Foundation Code of Conduct (HONcode) certifies medical and health websites as reliable and trustworthy sources of information. To date, over 800 sites from 56 countries have received HONcode certification. Establishing that the HONcode and similar certification processes are relevant and feasible for mobile health will help to ensure the integrity of health information and protection of patient data in the mobile environment.

The Health Insurance Portability and Accountability Act (HIPAA) created data security and privacy standards to protect patients’ medical records and other personal health information. However, our current understanding of how HIPAA applies to mobile health and how it will be enforced remain unclear. Most consumer-grade mobile devices do not contain security features to protect data that are similar to those on personal computers and may be easily lost or stolen. Adequate security standards for mobile health applications must be established and enforced, and patients should be made aware of the security measures that their health care providers and application developers are employing. With data security standards in place, the migration of paper-based medical records to mobile platforms may actually enhance the security of patient data by reducing illegible notes, the risk of lost paperwork, and the storage of sensitive information in personal dwellings.

Mobile health applications and web-based monitoring systems for PAD rely heavily on the collection and transmission of patient data from the home setting to the physician. While these data can greatly inform treatment decisions and provide real-time feedback to patients, it is imperative that such data be securely transmitted and stored. Unsecured data can be intercepted and read during transmission or while stored on a server, leading to patient identity theft, the altering of patient records, and in some countries, the denial of medical services through breaches in stored financial data.

User Acceptance and Engagement

Users’ acceptance and engagement is the first step to improving healthcare and health outcomes for all patients.

This contrasts patients who are not technologically savvy, do not have smartphones, patients who are elderly, and those living in more rural areas without mobile internet connections. It is likely that the aforementioned mobile health applications are not appropriate for the latter group of patients, thus development and implementation of these technologies to the former group should not be guided by if they can, but if they should.

By understanding users’ attitudes towards a technology before offering it, the chances of a successful implementation can be greatly improved. In the case of digital health technologies, this means there may be less emphasis on a one-size-fits-all paradigm. For example, mobile health applications have been shown to be beneficial in certain subsets of patients with chronic diseases. These include patients with frequent exacerbations of illness requiring emergency department visits or hospital admission, patients with complex medication regimens, and patients who act as informal caregivers to others with chronic diseases.

The aforementioned study could have reached a different outcome if the investigators had queried the patients on their perception of the exercise program and the use of the accelerometers at the conclusion of the study, thus providing valuable information on what they could do to make the intervention more effective for the patients in the future.

Adherence and effectiveness of the prescribed therapy in a RCT, on the other hand, is a common problem among many different trials and treatments, but similar to the pedometer study, the first step to resolving these problems is identifying the challenges and limitations faced. User acceptance will vary among different technologies and the perceived usefulness of the technology in its impact on their lives and the lives of others.

One recent example of this is a study comparing two methods of home-based walking exercise programs in patients with intermittent claudication. Even though the study was designed to test an exercise intervention, many patients perceived it as a pedometer study, where the more high-tech pedometer (an accelerometer measuring steps per day) was compared to the lower-tech pedometer (a written activity log). Since patients were not keen to use the accelerometers and adherence to their prescribed exercise was poor, there were no differences seen in the outcomes measured by the two groups.

In the modern world of rapidly expanding technology, it may be difficult to keep up with the latest devices and trends in digital health. All of these wireless technologies have the potential to offer inexpensive and easy-to-use methods to monitor and manage PAD, but they are no good if the intended users are not willing to use them.

Future Directions and Opportunities for Digital Health in Peripheral Arterial Disease Management

AI can also be used to tailor medical treatment to individual patients. One study has suggested the use of AI to optimize antiplatelet therapy by weighing the cardiovascular benefit against the risk of bleeding for each individual patient. Customized decision support tools such as this could be used to maximize the effectiveness of medical treatment while minimizing the risk of adverse events.

For example, a recent study employed machine learning techniques to construct a prediction score for the chance of PAD in a high-risk population that outperformed existing methods. In the future, similar predictive models would be used to identify patients most at risk of developing symptomatic disease or suffering adverse events, allowing for earlier intervention and thus preventing disease progression.

Artificial intelligence (AI), an area of computer science that allows technology to mimic intelligent human behavior and thought patterns, has the potential to revolutionize the management of PAD. As a starting point, data collected from previous and current patients can be used to create AI applications that assist clinicians in making diagnoses and treatment plans. This would subsequently advance to the use of AI as a means of disease prediction and risk assessment.

Artificial Intelligence and Machine Learning

By using supervised learning methods and features including clinical symptoms, functional status, and various non-invasive testing results, we could create a predictive model which provides the probability of IC versus CLI and ultimately improves clinical outcomes by ensuring that patients are getting the right treatment for the right disease state.

Another area of promise would be to use machine learning to build predictive models which optimize the classification of intermittent claudication versus critical limb ischemia at the initial presentation. While we have made significant progress in understanding the pathophysiology between these two PAD phenotypes, clinical distinction between the two can be difficult and may lead to misclassification of one or the other. This is an important distinction to make as the clinical outcomes and treatment strategies for IC and CLI are quite different.

For example, by using longitudinal data on a large cohort of PAD patients across North Carolina, we were able to develop a natural language processing and machine learning pipeline to identify PAD patients who are at high risk for lower extremity amputation. This pipeline takes advantage of various free text data within the electronic medical record to identify the presence of infection, non-healing ulcer, and other limb-threatening events and has shown to have high precision and area under the receiver operator characteristic curve. By identifying high-risk patients, we can then deploy preventive measures to decrease amputation rates in these patients.

Harnessing the potential of health information, data, clinical knowledge, and recent advances in machine learning and AI could enable the prediction of clinical events and progression in PAD patients. By understanding patterns in patient risk factors, environmental factors, and genetics on the development and progression of PAD, we might be able to identify high-risk patients in early stages and implement strategies to prevent disease progression.

Wearable Devices and Sensors

More advanced mobile gait robots and body-worn sensors seem promising but are not yet widely available for clinical or home use. With continued technological advancement and reduced costs, the use of wearable technology is likely to become more widespread and provide valuable objective measures of habitual activity and specific activities such as walking. This, in turn, will aid the assessment and monitoring of interventions to improve walking ability in PAD.

Most data on wearable device use in PAD relates to treadmill function. A recent systematic review showed that accelerometry data from wearable devices can accurately assess walking intensity in patients with PAD, and moderate and/or vigorous walking intensity has been associated with reduced leg symptoms and improved walking ability.

One large scalable example is the UK Biobank study, in which 100,000 subjects were recruited between 2006 and 2010 with the aim to examine the genetic and environmental determinants of disease in middle to late age. A subset of 500,000 participants (including original recruits) will use wrist-worn accelerometers with a 7-day wear protocol to follow up health outcomes.

Wearable devices are becoming increasingly utilized in the realm of cardiovascular health, particularly in the monitoring of physical activity. Current technologies include simple pedometers, accelerometers, and advanced multisensory devices capturing real-time data on intensity, duration, and type of activity.

Telemedicine and Virtual Care

If telehealth and virtual care can become established in PAD management, the potential benefits are substantial and far-reaching for both patients and healthcare systems. The nature of PAD as atherosclerosis in multiple vascular beds and a marker for systemic atherosclerosis makes these patients particularly well-suited for telemedicine visits using a risk factor-based approach for cardiovascular primary prevention. They often have concomitant cardiovascular risk factor management issues and other atherothrombotic disease states requiring frequent visits to multiple specialists. A coordinated approach with a ‘one-stop-shop’ telemedicine encounter can potentially reduce the burden of multiple visits to different specialty clinics. Global availability of specialist care in PAD is limited in some regions, and disparities in rural or socioeconomically disadvantaged populations with poor access to vascular specialists often result in suboptimal medical and preventive therapy. Telemedicine visits for these patients, including ‘e-visits’ organized through their primary care physician, could improve access to PAD specialists and allow monitoring of adherence to antiplatelet and statin therapy. The improvement of symptom or quality of life-based telehealth encounters in comparison to office visits has the potential to aid earlier detection of limb threat and prevent delay in treatment resulting in less limb loss. Lastly, virtual care using smartphone apps and messaging systems may improve care coordination between primary care physicians and various specialty providers in a fashion similar to clinical care pathways discussed previously.

Telemedicine (or telehealth) can be broadly defined as the use of electronic communications and software to provide clinical services to patients without an in-person visit. It was previously considered a future alternative to conventional medical practice, but the COVID-19 pandemic has forced the rapid adoption of telehealth and virtual care as traditional doctor’s office visits and outpatient clinic appointments are no longer feasible. However, the implementation of telemedicine is not an easy task as it demands a shift in the culture of healthcare practice and acceptance by patients and healthcare providers. Reimbursement structures for telehealth services have been a significant barrier but are likely to change with the increased pressure to decrease healthcare spending and modernize care delivery. Sustained efforts to prove the effectiveness and cost-savings with new evidence and guidelines that endorse telehealth options for specific conditions like PAD are required.

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