Abstract
Introduction: Uncontrolled hypertension (blood pressure (BP) ≥130/80) is the most prevalent reversible risk factor for cardiovascular disease. Remote patient monitoring (RPM) can be an effective way to improve BP control and was further incentivized by the COVID-19 pandemic, which necessitated remote chronic disease management. We report on a natural experiment involving federal funding for virtual care expansion, which included home BP kits (BP cuffs, smartphones, cellular data) to facilitate RPM.
Methods: We performed a mixed methods analysis of 18 health centers that requested and received BP kits, assessing device distribution, patient use, and facilitators/barriers to RPM implementation. Electronic health record (EHR) data were investigated from 2020 to 2023. Qualitative data included semistructured interviews with health center staff, patients, and programmatic staff and field notes from observations of implementation meetings. Data were analyzed following a framework-informed thematic approach.
Results: 10 of 18 health centers (56%) initiated RPM with ≥ 5 patients during the study period. A total of 1,748 patients had EHR orders to initiate RPM, of which 780 (45%) responded with any BP data and 271 (16%) with meaningful BP data. There was no correlation between RPM distribution/use and health center size or number of BP kits received. The biggest barriers to RPM uptake were inadequate health center resources and the complexity of operationalizing an RPM program in general and the BP kits specifically.
Conclusions: Supplying free RPM hardware and cellular data plans in the absence of adequate support resources is insufficient to successfully augment care among hypertensive patients at community-based health centers.
- Blood Pressure
- Disease Management
- Electronic Health Records
- Hypertension
- Patient Monitoring
- Smartphone
- Telemedicine
Introduction
Hypertension is a focus of primary care because of its high prevalence and negative impact on cardiovascular outcomes.1 Although it is well known that reducing blood pressure (BP) leads to lower cardiovascular morbidity and mortality, fewer than half of patients with diagnosed hypertension have controlled BP (<130/80).2 Putting hypertension monitoring into patients’ hands, via remote patient monitoring (RPM), could improve rates of BP control.3
Portable electronic BP machines allow patients to measure and record BP independently, outside of the clinic. Home BP measurement improves BP control,4–6 can reduce complications from hypertension,7,8 and can be cost-effective.9,10 Although clinical guidelines recommend incorporating RPM into routine care for hypertension,11,12 large gaps persist in the systematic incorporation of RPM into hypertension management.13
Starting in 2020, in response to the COVID-19 pandemic, there has been a vast increase in telehealth usage: phone and video visits have dramatically increased,14 and there is intensified interest in gathering RPM data to enable chronic disease self-monitoring.15,16 Little is known about RPM use for hypertension control during and since the pandemic, especially in community-based health centers (CHCs), which care for socioeconomically vulnerable patients with high rates of complicated chronic disease. Patients receiving care at CHCs have many care access barriers that could be mitigated through RPM, but at the same time, they may also face increased challenges to RPM adoption.17
The 2020 Coronavirus Aid, Relief, and Economic Security (CARES) Act included funding for the Federal Communications Commission (FCC) to increase capacity for telehealth in CHCs, including the provision of connected RPM devices in clinics that desired them. Funds could not be used for clinic infrastructure, staffing improvements, or assessment of program implementation or outcomes. CARES Act funding created a natural experiment on how eliminating material resource barriers (ie, providing free devices, phones, and broadband access) impacts RPM implementation in CHCs. To take advantage of this, we examined the extent of RPM use for hypertension management among 18 CHCs that requested and received devices through the FCC program, as well as barriers and facilitators to RPM use.
Methods
Design and Conceptual Frameworks
Our observational, mixed-methods study used an explanatory sequential approach to data collection and analysis.18–20 Quantitative data about device distribution and use informed the evolution of our qualitative research approach, and qualitative findings are presented to help interpret quantitative results. The Consolidated Framework for Implementation Research (CFIR)21 informed study conceptualization and was used to guide qualitative data collection and analysis. Our qualitative analyses focused on intervention characteristics, intervention processes, organizational and external contexts, and characteristics of participating individuals. However, based on early indications of challenges associated with RPM implementation, we subsequently incorporated the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) Framework22 into qualitative data collection and analysis. NASSS consists of 7 domains relating to health technology adoption and focuses on assessing whether each is simple, complicated, or complex. Increasing complexity is theorized to decrease the likelihood of technology adoption.
The study was approved by the Kaiser Permanente Interregional Institutional Review Board (IRB# 00000405).
Setting
OCHIN (not an acronym) is a nonprofit health information technology (IT) consultancy that hosts a single, centralized EHR system serving a national network of CHCs. OCHIN’s EHR platform is used by more than 33,000 clinicians caring for over 6 million people in rural and medically underserved communities in 39 states.
In 2020, using the FCC funding, OCHIN invited its 111 member CHCs to apply for hardware, including RPM devices and smartphones with data plans to enable digital integration between the RPM devices and the EHR. Following competitive award processes, 30 CHCs were selected to receive hardware; of those, 18 requested hypertension management kits. RPM devices and data plans were allocated to participating CHCs in 2 waves, occurring in 2020 (“wave 1”) and 2022 (“wave 2”), with participating CHCs expected to distribute the devices to eligible patients. OCHIN offered technical support in the form of workflow recommendations, educational videos, twice monthly office hours, and an on-call help desk, but these resources were very lightly utilized by CHCs.
Quantitative Data Sources and Analysis
BP and heart rate data collected from RPM devices were extracted from the OCHIN Epic EHR data flowsheets that store input biomedical data. To record data from an RPM device in the EHR, a patient must receive an electronic order for a flowsheet and have an activated health portal account to which the order can be sent. Once the RPM data collection is set up, BP data are either automatically recorded via digital integration from the patient’s smartphone, or if preferred by the patient, manually entered onto the flowsheet by the patient via the health portal.
Using the EHR, we analyzed for RPM flowsheet orders and resulting BP data from participating CHCs. For “wave 1” clinics (provided with devices and smartphones/data plans from October 2020 to September 2021), we examined RPM flowsheet orders from October 2020 to December 2022 and BP data from these flowsheets from October 2020 to June 2023. Because of delays in device distribution to some awardees in wave 1, we extended our follow-up period for 3 additional months beyond what had been planned. For “wave 2” clinics (provided with devices and smartphones/data plans from January 2022 to December 2022), we examined RPM flowsheet orders from January 2022 to December 2023 and BP data from these flowsheets from January 2022 to March 2024. We also gathered information on device distribution from available OCHIN FCC project distribution records. Although data plans only lasted 11 months, we were able to continue to gather flowsheet data beyond this time frame because the phones still worked with Wi-Fi connections, and the flowsheets also worked with the patients’ personal devices.
We aggregated data on frequencies of flowsheet orders and data intake at the CHC level. As there were no substantial changes in RPM equipment, smartphone integration, workflows, or technical assistance between waves, data from waves 1 and 2 were combined for analyses. Using scatterplots and Pearson correlation coefficients, we explored the relationships between the intended outcome of the FCC program (reduction in BP) and CHC factors (number of hypertensive patients, and number of clinicians, number of RPM devices received, number of patients with RPM flowsheet orders).
Qualitative Data Sources and Analysis
We conducted exploratory, semistructured interviews with a purposive sample of people with in-depth experience of RPM implementation and use, including CHC staff, patients, and OCHIN staff responsible for distributing devices to CHCs (see supplement table). We also observed virtual implementation meetings between OCHIN and CHC staff.
We invited all 18 CHCs that received FCC-funded BP devices to participate in interviews. If they agreed to participate, a CHC contact identified clinic staff who had a role in the RPM program to participate in interviews. Three CHCs from the first wave of distribution participated in interviews in June-July 2022 and 6 CHCs from the second wave participated in October-December 2023. In total, we interviewed 14 individuals working at these 9 CHCs (5 from the first wave; 9 from the second). Data from the first group of interviews were used to inform revisions to interview questions for the second group.
We recruited and interviewed patients who had experience using the connected RPM devices, as identified by CHC contacts, though few patients used the devices regularly. Because uptake and use was low, we did not have enough data for analysis of patient interview data.
To understand the impact of OCHIN’s efforts to support program implementation, we interviewed 4 OCHIN FCC Program staff in January-February 2023. Interviews asked about device distribution, EHR interoperability, and interviewee experiences working with the CHCs that received the devices (See Appendix).
We also observed implementation meetings between OCHIN FCC program staff and CHC staff. Field notes from 16 virtual meeting observations that occurred from May 2022 through May 2023 were included in our analysis.
Interviews were audio recorded, transcribed, and uploaded to NVivo (release 1.7) for analysis along with fieldnotes. Qualitative data were analyzed thematically,23 primarily by RG, an experienced Masters-level qualitative researcher with expertise in health information technology adoption. CM, a PhD-trained anthropologist with expertise in health services and medical informatics and Principal Investigator of the project, guided the analysis. An initial code list developed based on CFIR constructs (eg, inner setting, intervention characteristics), with inductive codes created during the coding process, was expanded to include codes based on the NASSS framework. This helped explicate complexities of the technology implementation. RG and CM met regularly to review coding, discuss unusual or outlying data, and engage in ongoing reflections on emerging themes. Developing findings were regularly shared with the multi-disciplinary research team and with qualitative participants to enhance trustworthiness and foster interpretation through multiple lenses.
Results
RPM Device Distribution and Use
Eighteen CHCs requested and received a total of 1,261 hypertension management packages (Table 1). These included Bluetooth-enabled iHealth Track BP cuffs and iPhone 11 smartphones preloaded with a one-year data plan and applications to electronically transfer BP values into the EHR, chosen for greater connectivity options verses Android platform phones and devices. One CHC received an additional 25 BP measuring devices without an accompanying smartphone. In total, 1,286 BP measuring devices were distributed.
Hypertension (HTN) and Remote Patient Monitoring (RPM) Information from Participating Clinics
Of the 18 CHCs, during their respective data plan periods, 14 (78%) ordered at least 1 flowsheet requesting that a patient record their BPs via the patient portal, but only 2 sites ordered BP flowsheets for more than 5% of hypertensive patients, suggesting very low uptake by clinicians (see Table 1). Among 1,748 total patients who received flowsheets via the portal, 780 (45%) sent in at least 1 BP and 271 (16%) sent in BP data for at least 16 different days in a one-month period (the minimum needed for Medicare reimbursement).24
There was no correlation at the CHC level between the number of patients with hypertension or number of RPM devices received and the number of patients providing RPM data (R2 = 0.241 and 0.011, respectively; Figure 1). However, there was a strong correlation between the extent of clinicians’ RPM adoption (measured by the number of patients with RPM flowsheet orders) and the number of patients providing RPM data (R2 = 0.786).
Associations between population served, Remote Patient Monitoring (RPM) device availability, orders for RPM and collection of RPM data at participating health centers (N = 18).
Barriers and Facilitators of RPM Implementation: NASSS Domains
Qualitative analyses identified several themes regarding facilitators and barriers to RPM use by CHCs and patients. While themes could span multiple NASSS framework domains, we present them in the context of their most relevant domain. For simplicity, we combined the health care organizational and adopter system domains because comments on these were so intertwined.
Technology Domain
Barrier: Complexity of RPM Kits
Interviewees noted technical issues with using the RPM devices and the apps required to send data. The suite of devices was from a single manufacturer but used multiple apps to link device data to an iPhone, which then transmitted device data to the EHR via the patient portal. CHC staff who tested the connections described it as a complicated process.
As devices were distributed to patients, CHC interviewees noted difficulties in teaching patients how to use them. Teaching often occurred at a 45 to 60-minute appointment, but even with that support, patients struggled to sync devices to their iPhone and take measurements at home. CHC staff noted that the patients who could most benefit from RPM devices were also often older, had never used an iPhone, and/or spoke a language other than English. This exacerbated the digital divide for patients, many of whom opted not to use the devices.
Value Proposition Domain
Facilitator: Potential Impact on Patients’ Health
In initial training meetings with OCHIN’s FCC Program team, CHC staff conveyed excitement about distributing the RPM devices and expressed being motivated by the potential benefit to their patients. Teams in CHCs that subsequently implemented their RPM program in the first year stated that using the RPM devices helped patients learn more about their chronic condition and how to accurately take measurements, thus improving overall self-management. CHC staff appreciated being able to monitor device home readings to inform care plan adjustments, especially to medications.
Organization and Adopter System Domains
Barrier: Limited Capacity and Complexity of Implementation
All participating CHCs reported that competing priorities hindered RPM program implementation. This was most pronounced in CHCs that delayed RPM or used it infrequently. Staffing capacity was cited as a critical reason for not being able to distribute the equipment. One CHC specifically mentioned challenges related to hiring qualified staff, others referred to staff time being used for higher-priority initiatives or general patient care; frequent staff turnover added to these barriers. In some cases, without a designated implementation team or project champion, RPM planning was placed on hold.
Another barrier reported by all participating CHCs was the complexity of implementing an RPM program. The systems and workflows that the RPM was designed to leverage were not in common use at many participating CHCs. Though OCHIN provided some training and educational materials to interested participants, CHCs were still responsible for developing an implementation plan specific to their context. CHCs had to make many decisions before distributing RPM devices to their patients, including defining appropriate patient recipients; creating processes for device distribution, EHR documentation, patient education, and technical troubleshooting; and deciding how they would monitor RPM data. The process of making these decisions and implementing the resulting workflows were further exacerbated by capacity constraints. Most CHCs had no prior experience implementing this model of remote care, which resulted in some clinicians’ reluctance to try RPM.
Facilitator: Systematic Implementation Planning
All CHCs that implemented any RPM use took an organized approach supported by a member of their leadership team. With leadership support, time was allocated for CHC staff to plan for implementation. RPM implementation teams had project champions with allocated time to make decisions and prepare for implementation. Implementation efforts were largely propelled by clinical staff directly involved in RPM. These staff members collaborated with others, including information technology staff, quality improvement staff, and a clinical champion such as a chief medical officer, to finalize implementation plans. Implementation initially started with a small pilot, in which the clinical champion oversaw testing of associated workflows as well as of the technical features of the RPM devices.
Wider System Domain
Barrier: Regulatory and Legal Implications of RPM
Many CHCs raised concerns regarding potential liability if CHCs were collecting data during off-hours when it would not be systematically acted on. Another regulatory concern was shifting telehealth reimbursement policies. CHC staff also noted competing demands, in part due to state Medicaid requirements and related quality measures, that left limited bandwidth to support additional programs like RPM.
Mixed-Methods/Confirmatory Analysis
As a final analytic step, qualitative results were compared between the 4 clinics that adopted RPM (ie, had more than 10 RPM flowsheet orders) and the 14 clinics that did not. Results, shown in Table 2, show distinct experiences of implementers versus nonimplementers and confirm that the NASSS framework clarifies factors relating to implementation of RPM.
Qualitative Findings by Non-adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework Domain and Clinic RPM Adoption Status
Discussion
Even when free BP measuring devices and smartphones with data plans were provided to a set of requesting CHCs during the COVID-19 pandemic, there was little RPM distribution or patient use, with some CHCs not distributing a single RPM kit. This finding adds to the literature documenting serious barriers to RPM implementation in CHCs, including the key barriers of RPM complexity and inadequate CHC resources.25,26 While lack of necessary devices is also frequently cited as a barrier to RPM implementation,27 our findings show that providing the necessary devices for RPM was insufficient to ensure use in the CHC setting. Fewer than half of the study’s 18 participating CHCs received meaningful BP data during the study period, despite receiving an adequate number of devices and having sufficiently large hypertensive populations. Less than half of the patients who were sent a BP flowsheet request through the patient portal provided any data. Patient adherence might have improved through more support and engagement from CHC staff,28 but their ability to do so was limited given the complexities of the technology and its implementation at the organizational level.
The overarching challenge to implementation cited by all interviewees was limited clinic capacity to support this effort, typically due to a lack of available staff and staff time. Resource constraints were evident at multiple steps, as the unexpected complexity of implementing a program increased resource demands. CHCs provide care to vulnerable patients who are disproportionately poor, un-, or underinsured, and have high rates of social risks and medical complexity.29 As such, available staff often needed to focus on standard elements of care delivery, and options are very limited for obtaining funding for additional staff,30 a situation exacerbated by the COVID-19 pandemic.31
We found that the intervention had high levels of complexity in multiple NASSS domains,32 including poor organization preparedness, inadequate staff adoption, and complex technology. RPM provision is new to many clinical settings, and organizations are often not prepared or resourced to address the challenges involved in developing new workflows and educational materials, providing training, and addressing liability concerns, all which staff in this study named as barriers. The RPM technology itself was reported to be too complicated for many patients and staff, especially the process of integrating BP measurements into the EHR. This can lead to frustration and poor patient adoption. Extra time and effort were often needed to directly assist patients with the technology.
We reported elsewhere on 1 CHC that successfully implemented RPM during wave 1.32 This success was driven by recognizing staffing needs early and ensuring that the project was adequately resourced throughout the program period.33 The success of this CHC aligns with prior findings showing that systematic implementation and planning can facilitate success of RPM programs.25,26 However, this success should be considered an exception, offering a model of what is possible. Future research should explore other successful RPM implementations, including those making use of innovative features such as automated support6 and self-titration of medication,34 which could decrease demand on staff resources. Expanding use of digital health modalities in patient care and medical education,35,34 plus technology innovations,25,25 should foster broader uptake of this important chronic disease management modality over time. However, during this expansion period, it is critical to address any unintentional inequities in access to RPM.36–38
Limitations
Our study has a few key limitations. First, RPM use may have been underestimated if patients shared BP values from the devices with the CHC outside of the portal (eg, delivered on a sheet of article rather than the EHR flowsheet). Given the small and skewed sample of participating patients, an accurate analysis of patient characteristics associated with RPM orders could not be performed. In addition, CHCs are a unique health care environment, and care should be taken extrapolating these results outside of that setting. We also note that the COVID-19 pandemic, even in its later phases, was a unique time in health care, with additional staffing and resource challenges; and it is unknown if RPM adoption would be significantly different today. Finally, the qualitative patient participant sample size was smaller than anticipated due to the challenges associated with implementation and device use, and thus we were not able to make use of patient interviews in our analysis. Future work in this area should incorporate more patient perspectives.
Conclusion
While RPM for hypertension management addresses a clear clinical need in a well-defined population, significant complexities associated with RPM implementation severely limited its integration into CHC settings in this study. While some technological complexity could be reduced with optimized RPM/EHR integration and a simplified user experience, this study demonstrates that hardware and broadband access alone are not enough to overcome the barriers to adoption caused by human resource constraints in a challenging environment. Nonetheless, with adequate resources and implementation planning, RPM holds promise for improving hypertension management.
Qualitative Participant Engagement
Acknowledgments
The research reported in this work was powered by PCORnet®. PCORnet has been developed with funding from the Patient-Centered Outcomes Research Institute® (PCORI®) and conducted with the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Research Network (CRN). ADVANCE is a Clinical Research Network in PCORnet led by OCHIN in partnership with Health Choice Network, Fenway Health, University of Washington, and Oregon Health & Science University. ADVANCE’s participation in PCORnet is funded through the PCORI Award RI-OCHIN-01-MC. We also acknowledge the final editing assistance from Jill Pope.
Appendices
Notes
This article was externally peer reviewed.
Funding: This work was supported by the National Institute of Nursing Research grant award number R01NR020305. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funder.
Conflict of interest: There are no conflicting or competing interests to disclose.
- Received for publication December 16, 2024.
- Revision received March 31, 2025.
- Accepted for publication April 14, 2025.
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