Introduction
Cardiovascular diseases (CVDs), as a group of disorders of the heart and blood vessels, are the leading cause of death globally for all sex, race, and ethnicity groups; approximately 17.9 million people die each year from CVDs (1). In the United States (US), about half of adults suffer from CVDs, including hypertension (Reference Virani, Alonso and Aparicio2;3). Remote patient monitoring (RPM), as a patient-centered healthcare delivery method, has emerged for managing CVD at home (4;Reference Farias, Dagostini, Bicca, Falavigna and Falavigna5). Integrated with technology for data transition, RPM patients collect their health information, for example, weight, blood pressure (BP), blood glucose, and heart rate, at home through personal health devices and send it to healthcare facilities so that medical providers at the point of care can closely monitor the patient health status (Reference Farias, Dagostini, Bicca, Falavigna and Falavigna5;Reference Davis, Hoover, Keller and Replogle6). Many systematic reviews and meta-analyses have demonstrated short- and long-term effectiveness of RPM in improving chronic CVD care management, including better quality of life, faster clinical event detection, less re-hospitalization, and lower mortality rates (Reference Nakamura, Koga and Iseki7–Reference Thomas, Taylor and Banbury11). Recognizing the effectiveness of RPM in managing CVD, the American Heart Association (AHA) published guidance on RPM implementation to encourage the use of RPM for better CVD outcomes (4). Also, in 2018, the Center for Medicare & Medicaid Services (CMS) issued CPT codes to reimburse providers for delivering RPM services to patients, and further coverage for RPM services has been added in its recently proposed 2022 Physician Fee Schedule (12;13).
Aside from the effectiveness of managing CVD, it is critical to evaluate the related economic costs. According to an AHA report from 2018, the medical costs related to CVD are expected to more than triple by 2035 (Reference Benjamin, Virani and Callaway14), which implies that the US is experiencing an unsustainable health expenditure growth for CVD. However, though the importance of economic sustainability of RPM for CVD management has gained attention, less has been systematically reviewed and synthesized across the studies conducted. Given the lack of clear information about the cost implications of RPM for CVD management and the complexity and uniqueness of the US healthcare system, this review aims to examine the economic cost and cost-effectiveness of RPM compared to usual care for CVD management in the US.
Methods
This systematic review was conducted following the JBI methodology for systematic reviews of economic evidence in accordance with a published protocol (Reference Gomersall, Jadotte and Xue15;Reference Zhang, Peña, Fletcher, Swint and Reneker16), associated registration on PROSPERO (CRD42021270621), and written following PRISMA reporting guidelines.
Search strategy
We aimed to find both published and unpublished studies. The databases searched included PubMed (NIH), Embase (Embase.com), Web of Science (Clarivate), CINAHL (ebsco.com), and Scopus (Elsevier). Sources of unpublished studies and gray literature searched included Cochrane Central Register of Controlled Trials (Wiley), National Health Service Economic Evaluation Database (York, Centre for Reviews and Dissemination), ClinicalTrails.gov, and Cost-Effectiveness Analysis Registry. The search strategies for all searched databases and information sources are listed in Supplementary Table 1. The search strategy, including all identified keywords and index terms, was adapted for each included database and/or information source. A hand search was completed, which included a review of the included articles’ references and exploration of related articles identified.
Studies published in English from 1 January 2011 to 8 November 2021 were considered for inclusion. The limits of publication dates were based on historically impactful federal decisions. Throughout the previous decade, technologies associated with RPM development were promoted with healthcare reforms and federal legislation. The National Broadband Plan by the Federal Communications Commission in 2010 facilitated medical technology advancement and the development of technology-based health services (Reference Gruessner17). As such, the date limit of this review will be set starting from 2011.
Eligibility criteria
A PICO framework (Population, Intervention, Comparator, Outcomes) was used for study selection. Articles were eligible for inclusion if they involved a chronic CVD patient population in the US, comparing RPM, or similar health delivery models, with usual care in terms of costs or in conjunction with other health benefit outcomes. This review considered studies evaluating the costs from all time horizons, for example, short-term and long-term, and all perspectives, for example, payer, provider, and healthcare sectors (Reference Drummond and Jefferson18). Full economic evaluation studies, such as cost-effectiveness analysis (CEA), cost-utility analysis (CUA), and cost–benefit analysis (CBA), as well as partial economic evaluation studies, such as cost analysis, cost-description studies, and cost-outcome descriptions, were considered for inclusion in the review (Reference Gomersall, Jadotte and Xue15;Reference Drummond, Sculpher, Claxton, Stoddart and Torrance19).
Study selection
Following the search, all identified citations were collated and uploaded into EndNote V20 (Clarivate Analytics, PA, USA), and duplicates were removed. Titles and abstracts were screened by two independent reviewers (YZ and MTP) for assessment against the inclusion criteria. The full text of selected studies was assessed in detail against the inclusion criteria by two independent reviewers (YZ and MTP). Disagreements during any selection stage were resolved through discussion between all study members. All screenings were completed through Rayyan (Reference Ouzzani, Hammady, Fedorowicz and Elmagarmid20), a free online systematic review data management software.
Assessment of methodological quality
Eligible studies were critically appraised by two independent reviewers (YZ and MTP) at the study level for methodological quality following the detailed checklist for assessing economic evaluation from Drummond et al. (Reference Drummond, Sculpher, Claxton, Stoddart and Torrance19) and summarized using standardized critical appraisal instruments from the Joanna Briggs Institute for Economic Evaluation (Reference Gomersall, Jadotte and Xue15). Any disagreements that arose between the reviewers were resolved through discussion or with all study members.
Data extraction and analysis
Data were extracted from studies included in the review by two independent reviewers (YZ and MTP) using a modified JBI data extraction tool for economic evaluation (Reference Gomersall, Jadotte and Xue15), to consider key elements of both partial and full economic evaluations. The data extracted include specific details about the participants, study design, interventions, comparators, study perspectives, time horizons, analysis type, clinical effectiveness, and costs and cost-effectiveness outcomes of significance to the review objective (Reference Zhang, Peña, Fletcher, Swint and Reneker16). If an article reported results from multiple studies, we extracted data for all eligible studies and analyzed them separately. If a study reported multiple outcomes, we extracted the results for a broader range of costs, a more commonly used effectiveness outcome, and a longer time horizon. In conducting economic analysis, it is imperative to have a clear study perspective (Reference Drummond, Sculpher, Claxton, Stoddart and Torrance19). Two reviewers inferred the study perspective and the year of cost data, if it was not explicitly stated in the article. Any disagreements that arose between the reviewers were resolved through discussion.
All extracted cost data were converted to 2021 US dollars ($) using a web-based tool developed by the Campbell and Cochrane Economics Methods Group and the Evidence for Policy and Practice Information and Coordinating Centre (EPPI-Centre) (21). Results of included studies were synthesized by economic analysis types and were interpreted considering study perspectives, intervention, health outcomes, and time horizons. Data from full economic evaluations are summarized using JBI Dominance Ranking Matrix (Reference Gomersall, Jadotte and Xue15), which ranks studies by cost and health benefit and synthesizes them into three implication categories: reject intervention, unclear, and favor intervention.
Results
Study inclusion
As shown in the PRISMA flowchart (Figure 1), 899 records were identified from databases and registries. After the exclusion of 271 duplicates, 628 titles and abstracts were screened. Among the fifty-four potentially relevant studies, eleven clinical trial registrations did not have final reports after contacting principal investigators. Forty-three full-text reviews revealed thirty-one papers excluded for ineligible publication type, patient populations, interventions, or outcomes. One additional article was included through hand searching. One article reported two eligible independent studies, so we consider them as separate studies in the analysis (Reference Pekmezaris, Mitzner and Pecinka22). Consequently, thirteen articles, with fourteen studies, were included in the final review for data extraction and synthesis. Among them, eight conducted partial economic evaluations, in which data about treatment costs and effectiveness were presented without an integrated analysis of cost and effectiveness (Reference Pekmezaris, Mitzner and Pecinka22–Reference Margolis, Asche and Bergdall28). The remaining six studies conducted full economic evaluations, three contained CEA (Reference Dehmer, Maciosek and Trower29–Reference Williams and Wan31), two contained CUA (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33), and one contained CBA and return on investment analysis (Reference Margolis, Asche and Bergdall28).
PRISMA flowchart describing the result of the search and selection process.
Methodological quality
Overall, seventy-three percent of the quality criteria were met. Among all the included articles, full economic evaluations had higher methodological quality than partial economic evaluations; on average, full economic evaluations met eighty-nine percent of the quality criteria, while partial economic evaluations met sixty-one percent. Two partial and four full economic evaluations had a well-defined question along with a study perspective clearly stated (Reference Maciejewski, Bosworth and Olsen24;Reference Wang, Smith and Bosworth27;Reference Dehmer, Maciosek and Trower29–Reference Martinson, Bharmi, Dalal, Abraham and Adamson32). Four studies did not have a clear study perspective; therefore, it was unclear if any relevant costs or outcomes were omitted (Reference Nouryan, Morahan and Pecinka25;Reference Riley, Keberlein and Sorenson26;Reference Schmier, Ong and Fonarow33;Reference Margolis, Dehmer and Sperl-Hillen34). All included studies compared clinical effectiveness between the intervention and comparator groups with costs and effectiveness data measured accurately and credibly. Four full economic evaluations adjusted costs and outcomes for differential timing (Reference Margolis, Asche and Bergdall28;Reference Fishman, Cook and Anderson30;Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33). The detailed methodological quality assessment is provided in Supplementary Table 2.
Characteristics of included studies
Table 1 provides an overview of the study characteristics and primary results. The clinical efficacy data in the included studies were from randomized clinical trials (RCTs) (Reference Pekmezaris, Mitzner and Pecinka22–Reference Nouryan, Morahan and Pecinka25;Reference Wang, Smith and Bosworth27;Reference Dehmer, Maciosek and Trower29;Reference Fishman, Cook and Anderson30;Reference Martinson, Bharmi, Dalal, Abraham and Adamson32–Reference Margolis, Dehmer and Sperl-Hillen34) and quasi-experimental studies (Reference Pekmezaris, Mitzner and Pecinka22;Reference Riley, Keberlein and Sorenson26;Reference Williams and Wan31;Reference White-Williams, Unruh and Ward35). Generally, this systematic review included a total of 3,915 actual patients, with 2,304 in RPM intervention groups and 200,000 simulated patients with 100,000 in the RPM intervention group.
Characteristics of included studies
BP, blood pressure; CBA, cost–benefit analysis; CEA, cost-effectiveness analysis; CG, control group; CUA, cost-utility analysis; ICER, incremental cost-effectiveness ratio; IG, intervention group; NS, not significant; ~ indicates data inferred by reviewers; RCT, randomized clinical trial; RPM, remote patient monitoring; ROI, return on investment; QE, quasi-experimental study.
Though RPM served as the basic concept of all interventions in this review, studies may have additive interventional medical services. Five studies, two partial and three full economic evaluations, had an intervention group of RPM with medication management (Reference Maciejewski, Bosworth and Olsen24;Reference Wang, Smith and Bosworth27;Reference Dehmer, Maciosek and Trower29;Reference Fishman, Cook and Anderson30;Reference Margolis, Dehmer and Sperl-Hillen34). Two studies conducting partial economic evaluations based on the same RCT had intervention groups of RPM with behavioral management and RPM with behavioral and medication combined management (Reference Maciejewski, Bosworth and Olsen24;Reference Wang, Smith and Bosworth27). In addition, two studies were based on the same RCT of an implantable wireless pulmonary artery pressure remote monitor (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33).
The economic impact of RPM for a time horizon of half to two years was assessed in nine studies (Reference Pekmezaris, Mitzner and Pecinka22;Reference Nouryan, Morahan and Pecinka25–Reference Wang, Smith and Bosworth27;Reference Dehmer, Maciosek and Trower29–Reference Williams and Wan31;Reference White-Williams, Unruh and Ward35). Two partial and three full economic evaluations were conducted for a longer time horizon between two and seven years, of which three full economic evaluations were model based, consisting of two CUAs and one CBA (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32–Reference Margolis, Dehmer and Sperl-Hillen34). Moreover, the included studies were of varying perspectives, including nine studies from the payer (Reference Pekmezaris, Mitzner and Pecinka22;Reference Blum and Gottlieb23;Reference Nouryan, Morahan and Pecinka25;Reference Riley, Keberlein and Sorenson26;Reference Margolis, Asche and Bergdall28;Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33;Reference White-Williams, Unruh and Ward35), two studies from the provider (Reference Fishman, Cook and Anderson30;Reference Williams and Wan31), two studies from the Veteran Affairs (VA) healthcare system (Reference Maciejewski, Bosworth and Olsen24;Reference Wang, Smith and Bosworth27), and one study from the healthcare sector perspective (Reference Dehmer, Maciosek and Trower29). The relevant types of costs used in each study with its study perspective are summarized in Table 2. Certain types of costs were excluded in the cost aggregates if their difference was not significant between RPM and comparator groups.
Reported cost components (N = 14)
Program costs
Three studies reported program costs such as costs of equipment and medical supplies, personnel, marketing, and overhead (Reference Wang, Smith and Bosworth27;Reference Fishman, Cook and Anderson30;Reference Williams and Wan31). The equipment and supplies may consist of laptop computers and accessories, home BP monitors, and telemedicine devices for data transmission and their warranty, batteries for BP monitors, and medication containers. The personnel costs were calculated based on personnel time and relevant hourly wage, along with additional benefits. Personnel time contained nurse time spent receiving training, educating patients, implementing programs, calling patients and preparing for calls, and physician time spent reviewing medical charts and consulting with nurses. For RPM with medication management, costs were considered for pharmacist time spent receiving training, developing protocols, and providing services, such as reviewing patient progress and medication regimens, monitoring potential adverse events, and meeting with physicians.
Table 3 displays the cost and cost-effectiveness of each study inflated to 2021 US Dollars ($) by health benefit. Among the three studies that reported program costs, one study from the VA healthcare perspective found no difference in program costs and treatment efficacy between RPM and the usual care group (Reference Wang, Smith and Bosworth27). In comparison, the two studies from the provider perspective reported higher costs for the RPM-only group with no difference in treatment efficacy (Reference Fishman, Cook and Anderson30;Reference Williams and Wan31).
Cost and cost-effectiveness results by effectiveness outcomes in 2021 US dollars (N = 14)
BP, blood pressure; CG, control group; CVD, cardiovascular disease; ICER, incremental cost-effectiveness ratio; IG, intervention group; QALY, quality-adjusted life year; NS, not significant; RG, reference group.
Medical costs
Inpatient, emergency department, and outpatient costs were the most commonly considered components among included studies. Medication costs were considered in four studies (Reference Wang, Smith and Bosworth27–Reference Dehmer, Maciosek and Trower29;Reference Martinson, Bharmi, Dalal, Abraham and Adamson32). Other medical costs may include critical care, laboratory test, procedure, radiology, evaluation/management/observation service, complication, and monitoring service. As opposed to the two studies from the provider perspective that considered monitoring as a program cost (Reference Fishman, Cook and Anderson30;Reference Williams and Wan31), two studies using the implantable device considered it as a monthly cost to the payer (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33). Among studies that reported medical costs for the RPM-only intervention, seven partial economic evaluation studies reported no significant difference in costs between groups (Reference Pekmezaris, Mitzner and Pecinka22–Reference Wang, Smith and Bosworth27;Reference White-Williams, Unruh and Ward35), and two full economic evaluation studies reported that the RPM group costs more than the usual care group (details can be found in Table 3) (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33).
Cost-effectiveness
When considering costs and health outcomes jointly, the included partial economic evaluations tend to favor the RPM intervention. Maciejewsk et al. (Reference Maciejewski, Bosworth and Olsen24) and Nouryan et al. (Reference Nouryan, Morahan and Pecinka25) reported that, with the same costs, patients receiving RPMs had better BP control and improved quality of life than usual care patients. Included partial economic evaluations reported equal costs and efficacy between RPM and usual care groups for hospitalization-related outcomes, such as the number of readmission and readmission rate. In assessing costs of BP control, two partial economic evaluations based on the same RCT found no difference in associated costs among groups (Reference Maciejewski, Bosworth and Olsen24;Reference Wang, Smith and Bosworth27); however, the one with a longer time horizon identified all RPM groups as having better BP control than the usual care group (21). The two partial economic evaluations that evaluated the quality of care had differing results (Reference Blum and Gottlieb23;Reference Nouryan, Morahan and Pecinka25).
Moreover, the results of full economic evaluations are summarized using JBI Dominance Ranking Matrix. Table 4 shows the synthesized results from two CEA and two CUA studies that compared the RPM-only intervention with the usual care. The RPM-only intervention was rejected in two CEA studies from the provider perspective, due to higher costs and similar efficacy for the RPM group relative to the usual care group. Both CUA studies reported that the RPM group had higher costs and Quality-Adjusted Life-Years (QALYs) than usual care and showed unclear implications; however, at a conservative threshold of $50,000 per QALY, the CUA studies suggest that RPM relative to usual care is a cost-effective tool for CVD management (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33). Additionally, Supplementary Table 3 shows the synthesized results for RPM with medication management intervention. Two CEA studies found that RPM with medication management led to higher costs and better BP control (Reference Dehmer, Maciosek and Trower29;Reference Fishman, Cook and Anderson30), which were cost-effective at the willingness-to-pay of $150,000 per QALY, and a CBA study found that avoiding CVD events led to cost savings (Reference Margolis, Dehmer and Sperl-Hillen34). Supplementary Table 4 shows the synthesized results for studies with a time horizon over three years. Among three full economic evaluations with at least a three-year time horizon, the CBAs favored RPM with medication management, and both CUAs favored RPM at the $50,000 per QALY threshold (Reference Martinson, Bharmi, Dalal, Abraham and Adamson32;Reference Schmier, Ong and Fonarow33).
JBI dominance ranking matrix of all included full economic evaluations for RPM-only (n = 4)
Discussion
This systematic review aimed to assess the costs and cost-effectiveness of RPM for CVD management in the US. Our review included fourteen studies reported in thirteen articles comparing RPM-based interventions with usual care in terms of cost and cost-effectiveness for CVD management. Partial economic evaluations found similar costs between RPM and usual care groups, while full economic evaluations, using different outcomes and analysis methods, suggested that RPM and RPM with medication management are cost-effective in terms of QALYs, BP control, and reducing the incidence of CVD events, especially in the long run. To fully understand the economic impact, it is essential to consider long-term costs and clinical outcomes.
The present study is the first systematic review of the economic impact of RPM for CVD management, focusing on the US healthcare system. A previous systematic review involved thirty-four studies conducted in twelve countries for multiple chronic diseases (Reference De Guzman, Snoswell, Taylor, Gray and Caffery36). Their results revealed that RPM is a highly cost-effective intervention for hypertension and prevents high-cost health events in the long run from a wide variety of perspectives, which is consistent with our findings of studies from payer and healthcare perspectives (Reference De Guzman, Snoswell, Taylor, Gray and Caffery36). However, our review includes a different set of studies, including partial and full economic evaluations, invasive and non-invasive RPM, and focused on CVD management in the US context. When examining the cost-effectiveness of a program in the US healthcare system context, it is important to consider the healthcare provider perspective, which informs policymakers regarding payer–provider partnerships. Program costs, referring to costs incurred at the administrative level (Reference Johns, Baltussen and Hutubessy37), are an essential component of RPM-based interventions, especially for studies that include the provider perspective. Two included full economic evaluations revealed higher program costs of RPM compared to usual care with additional monitor and data transmission devices as well as nurse time and pharmacist time for training, service, and communication with patients. In addition, medication costs constitute an important portion of assessing the cost-effectiveness of health interventions, which is a cost borne at least partly by patients in the US, depending on the payer type. RPM with medication management can enhance medication adherence and ultimately reduce healthcare costs (Reference Simon, Kini, Levy and Ho38); therefore, it is important to consider medication costs in economic analysis. We recommend that future economic studies of RPM should be conducted rigorously with a broader perspective, such as societal perspective to include the provider perspective, considering program costs, and the patient perspective, considering medication costs (Reference Khera, Valero-Elizondo and Das39).
Nevertheless, the study of Riley et al. (Reference Riley, Keberlein and Sorenson26) was the only one with specified locations that included underserved rural communities and Native American reservations. Though the clinical efficacy of RPM has been addressed in rural areas and low-income populations (Reference Clark, Woods and Zhang40), future evidence of RPM cost-effectiveness in underserved populations is needed.
There are some limitations within our systematic review. Although fourteen studies were included in the review, eight were partial economic evaluations, providing lower quality evidence. The heterogeneity of patient populations, varying study perspectives, different health benefit outcomes, and the small number of articles included make it challenging to draw conclusions in each category and limit the generalizability of these findings.
Conclusions
This review summarizes current evidence of the economic impact of RPM on CVD management in the US. The findings suggest that RPM-based healthcare services can be more cost-effective than usual care from the payer perspective for CVD management in terms of QALYs, BP control, and fewer CVD events. This result can seem encouraging for third-party payers. Given the current evidence of clinical effectiveness, future efforts should seek to investigate the economic sustainability of RPM for CVD management, considering broader and varying perspectives with a longer-term view.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0266462323000156.
Funding statement
This work was supported by the Office for the Advancement of Telehealth, Health Resources and Services Administration, US Department of Health and Human Services under cooperative agreement award no. 2 U66RH31459‐04‐00. The information, conclusions, and opinions expressed are those of the authors, and no endorsement is intended or should be inferred.
Conflicts of interest
L.L. is an employee of ConcertAI at the time of the study. Rest of the authors do not have a conflict of interest.
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