Published online May 26, 2020. doi: 10.4330/wjc.v12.i5.203
Peer-review started: February 9, 2020
First decision: Mach 5, 2020
Revised: March 29, 2020
Accepted: April 23, 2020
Article in press: April 23, 2020
Published online: May 26, 2020
Newer models of cardiac rehabilitation (CR) delivery are promising and there is increasing evidence that such models can be equally effective and can be used to complement or extend traditional hospital-based CR. Highlighting this opportunity, the American Heart Association issued a presidential advisory emphasizing the importance of adopting these newer models for improving access and utilization of CR. However, effective use of these smart models depends upon patients’ ability to use technological media including Internet and smart devices. There is a dearth of knowledge on the availability of internet, ownership of smart devices, usage patterns and barriers to use specifically among CR attendees. CR attendees tend to be older than the general population or patients attending routine chronic disease management clinics. The purpose of this study was to explore the availability of such technology, current utilization and proficiency of use among older CR program attendees. This knowledge can help us understand the feasibility of such smart home-based CR programs in routine clinical practice outside of research trials.
CR is an important component in the management of patients with heart disease. Despite abundant evidence demonstrating its benefits and strong recommendations from multiple international and national associations, it remains underutilized. Potential reasons for this underuse are the need for patients to travel significant distances multiple times in a week, lack of transport, and inflexible schedules. Proposed solutions include newer models of CR delivery such as home-based CR using smart device-based instruction and monitoring. To be able to implement and deliver these home-based CR regimens, we would need to know whether CR attendees who are generally elderly have access to such tools and whether they can use them proficiently. Hence this study was designed to address some of these gaps in knowledge.
The objectives of this study were to assess access to smart devices, predictors of their use and perceived barriers to the use of smart devices among CR attendees.
This was an observational study assessing access to internet, smart device ownership and usage among attendees of 4 American Association of Cardiovascular and Pulmonary Rehabilitation-certified, hospital-based CR programs in Omaha, Nebraska, United States. This was a voluntary survey using a pilot survey tool consisting of 28 items. Subjects were recruited over a period of six months in 2018. On-site subject recruitment and survey administration were conducted by a single investigator. The survey was only available in English. Data are described using averages and percentages. Potential relationships between various items were assessed using Chi square tests for categorical data and Pearson’s coefficient for continuous data. A significance level of 0.05 was used, and all data analyses and graphics were developed using the STATA14 statistical package (College Station, TX, United States). There has been no such study focusing on CR attendees in United States with most data currently available coming from general population surveys done by the Pew research center.
We approached 376 attendees of our program, of which 169 responded (45%). Patients as expected were relatively older with a mean age of 71 years, 90% were Caucasians and ≈ 75% were males. Approximately half of the respondents had college education and had a household income of ≥ 40000 USD. Smart device ownership was 84.5% with desktop computer being the most common and preferred device for connecting to the internet. Approximately half of them owned a smart phone and 1/3rd owned multiple devices (phones, tablets etc.). On average, Internet use was 1.9 h/d. Only about 18% used their smart devices and computers for health-related purposes. Utilization of other health information modalities was low, 29.8% used mobile health applications and 12.5% used wearable devices. Of all participants, 72% reported no barriers to using Internet. Education and income were associated positively with measures of utilization and with less perceived barriers while age had a negative correlation. In this survey, we did not address the medical comorbidities that may impact patients’ ability to use smart devices for health-related applications and patients’ attitudes towards such use.
Our study demonstrates that most older patients attending CR in an urban metropolitan area have access to Internet/smart devices and do not perceive significant barriers to use. Unlike data from prior decades where elderly patients did not have access to smart devices, our study proves that access is no longer an issue. Despite this, the majority of participants did not utilize these devices for health-related applications. We hypothesize that attitudinal factors such as concern about internet privacy, physical and cognitive impairments that make it difficult to interface with smart devices such as small joint arthritis or memory impairment and lack of education on how to use the devices may be contributing to the low rates of use of smart devices for health related applications. Patient income, educational attainment and age correlated with use of smart devices in our study confirming the findings of prior studies across different age groups. Our findings have significant implications for the efforts to transition CR away from hospitals and closer to home and to create hybrid models of CR. These models not only increase access for patients, increase participation and engagement but may also prove economical and more sustainable for prolonged periods of time. More importantly, the ability to deliver CR in this fashion may be the only way to ensure safety of our patients in this current time of the corona virus 19 pandemic.
Our study demonstrates that access to smart devices is no longer a limiting factor to the implementation of smart models of home-based CR. Limited use of smart devices for healthcare applications in our elderly patients was likely a result of attitudinal factors, cognitive impairments and lack of proper education. Further research is necessary to confirm our findings in larger diverse groups of patients, sampled to account for geographic, racial and gender differences using validated survey tools. Future avenues for research include investigation into the impact of smart device and apps’ design as well as the impact of targeted education to improve technologic proficiency among older adults on the adoption of these technologies. The ultimate success of these smart models of CR will depend on their ability to improve clinical outcomes and their comparative efficacy and cost effectiveness vis-à-vis traditional hospital/center-based CR.