1.1 Introduction
In 2016, around 61 million individuals of the U.S. population (19%) were living in rural areas (U.S. Census Bureau, 2016). Residents in these areas are not always able to get routinely examined by a primary care physician and show higher prevalence of chronic health conditions, such as diabetes, cancer, or heart disease (Murray et al., 2006). The emergence of remote patient monitoring (RPM), a category of telehealth, provides a solution to handle this issue. RPM’s value shows when collecting patient health data outside of traditional clinical settings (Ahmed et al., 2016) and transmitting this data to the healthcare provider, enabling health care professionals to remotely monitor patients (Taylor et al., 2015).
Wearables and home use medical devices that are Internet-of-Things (IoT) enabled drive this capability to remotely monitor patients. These devices have become a major part of our lives (Mosenia et al., 2017) and Beaton (2017) predicts that this market will reach $37.39B in 2022 (Sellahewa et al., 2019), compared to 7.1 million in 2016. These devices include sensors that are worn on our body many times (Duval & Hashizume, 2006) and are used for capturing a variety of patient-generated data, such as step count, sleep quality or heart rate (Penzel et al., 2018) to provide insight of the patient’s health conditions.
These remote monitoring capabilities are allowing health providers to better navigate a changing reimbursement system with the shift to a value-based care system (Adarsha et al., 2019), focusing on the patient’s health, with healthcare providers getting paid based on the patient’s health outcome (Ong et al., 2017).
While this is ground-breaking technology, remotely monitoring a patient’s health during an RPM program requires the patient to be responsible for the exam outcomes, putting the burden of generating proper data in the hands of the patients or their caregiver. Therefore, there are a variety of challenges when the patient or a caregiver is responsible for the device operation at the patient’s home. This ranges from proper device operation, such as the many steps involved to receive an accurate as well as precise blood pressure reading (Muntner et al., 2019), to the need of setting up the device correctly at the patient’s home network, or the patient not being located in proper environment during data acquisition causing masked hypertension, a condition in which the patient’s blood pressure is normal at a physical doctor’s office, but elevated at home due to the patient not being in a controlled environment during the exam (Pickering et al., 2002). An important factor that could have an impact on data quality is a device that requires calibration or stopped working accurately, potentially, leading to inaccurate patient data (Gogia et al., 2016) or no data transmission at all if the device stopped working. Little to no data would be generated if the patient does not stay compliant to an RPM program and loses the motivation to adhere to the provider’s treatment plan (Baumann et al., 2019; Shin et al., 2019). The patient may start out motivated with the exams at home, but compliance to the examination schedule may drop (Shin et al., 2019).
Lastly, another factor that could the patient’s comfort in an RPM program is the secure storage and transmission of the generated data and with that the patient’s personal data. Increased reporting of security breaches may have contributed to a perception of mistrust and skepticism amongst patients and individuals in general, specifically concerning electronic health data storage and transmission (Vervoort et al., 2021). The authors highlight that 505 healthcare data breaches occurred in 2019, causing over 40 million healthcare records to be exposed. They continue illustrating the impact this has on cost and add that data breaches in the healthcare industry are incurring the highest cost to recover from, with an average cost of around $7M.
With capturing, storing, and transmitting patient-generated data comes great responsibility to safeguard patient data and to comply to healthcare ethics. When patient-generated data is captured, transmitted and then stored on the RPM provider’s platform, the RPM program should therefore also understand ethical considerations, such as the fact that the patient’s own data is providing unauthorized access to others, with the patient simply losing the ability to govern their own data (Chiruvella & Guddati, 2021).
According to Ozair et al. (2015), there are four ethical priorities for storing health data in proprietary cloud-based databases, offering increased access to the patient’s medical record. These four priorities are privacy and confidentiality, security breaches, system implementation, and data inaccuracies. The authors define each of these priorities in more detail, highlighting the fact that patient health data is considered confidential and must be protected. They also state that there is a constant need to encrypt devices that store and transmit confidential information, and stress that a constant validation of the interfaces between the user and the provider are necessary to be performed to provide an optional user experience for all involved stakeholders. Finally, a successfully implemented system needs to guarantee data integrity, ensuring the patient’s true health condition is reflected.
To overcome data privacy and ethical issues in healthcare, blockchain is an innovative technology that promises to transform many industries besides finance, due to its incorruptible digital ledger and decentralized database (Miraz & Ali, 2018). Blockchain, used originally for cryptocurrencies, such as bitcoin (Miraz & Ali, 2018) integrates strong security measures and decentralized technology, and holds promise to be applied in healthcare for the reason of its immutable database. There are many identified use-cases for blockchain in healthcare already, and this paper will investigate if this technology can be used to overcome the discussed challenges of data usability, besides data privacy, that are generated via an RPM program.