Published on in Vol 10, No 5 (2022): May

Preprints (earlier versions) of this paper are available at, first published .
Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review

Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review

Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review


1ECRI, Plymouth Meeting, PA, United States

2Division of General Internal Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

3Center for Evidence-based Practice, University of Pennsylvania Health System, Philadelphia, PA, United States

Corresponding Author:

Jonathan R Treadwell, PhD


5200 Butler Pike

Plymouth Meeting, PA, 19462

United States

Phone: 1 6108256000 ext 5379


Background: In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains unclear whether such devices can improve health outcomes.

Objective: We performed a systematic review of the literature on consumer BP monitors that collect PGHD for managing hypertension to summarize their clinical impact on health and surrogate outcomes. We focused particularly on studies designed to measure the specific effect of using a BP monitor independent of cointerventions. We have also summarized the process and consumer experience outcomes.

Methods: An information specialist searched PubMed, MEDLINE, and Embase for controlled studies on consumer BP monitors published up to May 12, 2020. We assessed the risk of bias using an adapted 9-item appraisal tool and performed a narrative synthesis of the results.

Results: We identified 41 different types of BP monitors used in 49 studies included for review. Device engineers judged that 38 (92%) of those devices were similar to the currently available consumer BP monitors. The median sample size was 222 (IQR 101-416) participants, and the median length of follow-up was 6 (IQR 3-12) months. Of the included studies, 18 (36%) were designed to isolate the clinical effects of BP monitors; 6 of the 18 (33%) studies evaluated health outcomes (eg, mortality, hospitalizations, and quality of life), and data on those outcomes were unclear. The lack of clarity was due to low event rates, short follow-up duration, and risk of bias. All 18 studies that isolated the effect of BP monitors measured both systolic and diastolic BP and generally demonstrated a decrease of 2 to 4 mm Hg in systolic BP and 1 to 3 mm Hg in diastolic BP compared with non–BP monitor groups. Adherence to using consumer BP monitors ranged from 38% to 89%, and ease of use and satisfaction ratings were generally high. Adverse events were infrequent, but there were a few technical problems with devices (eg, incorrect device alerts).

Conclusions: Overall, BP monitors offer small benefits in terms of BP reduction; however, the health impact of these devices continues to remain unclear. Future studies are needed to examine the effectiveness of BP monitors that transmit data to health care providers. Additional data from implementation studies may help determine which components are critical for sustained BP improvement, which in turn may improve prescription decisions by clinicians and coverage decisions by policy makers.

JMIR Mhealth Uhealth 2022;10(5):e33261



In 2018, nearly half a million deaths in the United States included hypertension as a primary or contributing cause [1]. Current data support the use of out-of-office blood pressure (BP) monitoring for hypertension management because it provides clinical information beyond in-office BP monitoring and enhances titration of the medication dose [2-4]. This evidence has led to the proliferation of consumer patient-generated health data (PGHD) devices for hypertension management.

The Office of the National Coordinator for Health Information Technology defines PGHD as “health-related data created, recorded, or gathered by or from patients (or family members or other caregivers) to help address a health concern” [5]. These health-related data are captured by the patient, who may also need to share this information with a health care provider or others (if data transmission is not automatic). The adoption curve of consumer PGHD devices for hypertension management is maturing due to the rising numbers of wearables and BP monitors on the market. The global market size of automated home BP monitors is expected to gain market growth between 2020 and 2025, with a compound annual growth rate of 2.3%, forecasting US $1068.3 million by 2025, from US $975.6 million in 2019 [6].

Consumer PGHD devices can improve the health outcomes of patients and play an important role in managing hypertension. This review summarizes findings on hypertension from a larger report that addressed PGHD for 11 chronic conditions. The full report can be downloaded from the website of the Effective Healthcare Program at the Agency for Healthcare Research and Quality (AHRQ) [7]. In this paper, we summarize the clinical effectiveness of consumer BP monitors in collecting PGHD on health and surrogate outcomes. We also summarize the process outcomes (eg, medication titration) and consumer experience outcomes (eg, device adherence, ease of use, and technical problems).

Search Strategy

A professional information specialist searched MEDLINE and Embase, in-process MEDLINE and PubMed unique content, and the Cochrane Database of Systematic Reviews for systematic reviews or controlled trials published from inception until May 12, 2020. We also searched for active studies until June 19, 2020. The review protocol is posted on the PROSPERO website [7].

Selection Criteria

Textbox 1 shows study eligibility criteria for studies evaluating the effects of BP monitors on hypertension. Device engineers examined the devices from the screened studies (manufacturer and model names) and determined whether each device was available for direct purchase by consumers. Studies that included nonconsumer devices (eg, devices requiring a prescription) were excluded. The technology had to collect and store consumer data without requiring manual input and potentially could be sent to a health care professional, although data transmission was not required for study inclusion. We included both US-marketed and non–US-marketed technologies that met the criteria. However, any technology subject to Food and Drug Administration (FDA) clearance must have received FDA clearance to be included.

We carefully examined the interventions provided to each treatment group and determined whether the study design isolated the effect of the BP monitor. This occurred when the intervention group received the BP monitor whereas other comparison groups did not, and any additional treatments were the same between groups. In cases where clinicians made changes to treatment plans (eg, medication or dose adjustments) based on feedback from the BP monitor, we considered it as part of the BP monitor’s effect because such adjustments were only possible due to the device. The comparison groups commonly received usual care, which would not preclude the clinician’s decisions to modify hypertension treatment plans based on BP measurements in other contexts and settings.

Using DistillerSR (Evidence Partners), 3 reviewers (JRT, BR, and JR) screened the titles, and all 6 screened abstracts and full-text articles. For titles, only 1 reviewer assessed the general relevance to the topic. For abstract screening, 2 reviewers were necessary to exclude an article from further consideration; however, only 1 reviewer was necessary to order the full text. Regarding full texts, 2 reviewers assessed the study against the inclusion criteria, and disagreements were resolved by a (senior-level) third reviewer (JRT or JR). Full-text screening also involved determining which articles were associated with other included articles of the same trial.

Eligibility criteria.

Category and criteria

  • Populations
    • Include individuals who have (or may potentially develop) hypertension
    • Exclude individuals with other conditions and pregnant and postpartum women
  • Interventions
    • Include consumer blood pressure (BP) monitors for the prevention or treatment of hypertension. The monitor must collect and store the patient data without manual input, which could be used by the patient or sent to a health care professional (data transmission was not required but could be via the same or a different technology)
  • Comparators
    • Include non–patient-generated health data (PGHD) interventions, other PGHD interventions, or no intervention
    • Exclude comparators that used the same PGHD intervention
  • Outcomes
    • Include health outcomes: direct measures of health (eg, mortality, emergency room visits, hospitalizations, disease progression, and quality of life)
    • Include blood pressure: systolic or diastolic BP change and change in BP control
    • Include potential harms: serious adverse events (eg, hospitalization or delay in care) and other potential harms such as underuse or overuse of medications secondary to inaccurate BP data
    • Include process outcomes (if 1 of the first 3 outcome categories were reported): medication changes
    • Include consumer outcomes (if 1 of the first 3 outcome categories were reported): BP measurement adherence, interoperability, functions, acceptability/usability, sustainability, feasibility, fidelity, and integration into electronic health records
    • Include costs (if 1 of the first 3 outcome categories were reported): total cost and cost-effectiveness
    • Exclude surrogates such as prescription filling behavior, biomarkers that do not define the condition, adherence, disease knowledge, beliefs, opinions, dietary behavior, activity level, and steps per day
  • Timing/setting
    • Include no limitations on timing. The setting must be at home or otherwise outside of a hospital or health care center.
  • Study designs
    • Include any study design with a separate comparison group of patients who received a different intervention strategy or single-arm registry studies. Systematic reviews were only used to screen their included studies to ensure none were missed by the database searches.
    • Exclude reviews, case reports, editorials, comments, letters, meeting abstracts, and studies with <10 patients per arm at follow-up.
  • Language
    • Include studies published in English.
Textbox 1. Eligibility criteria.

Data Extraction

For each included trial, 1 reviewer (BR or NM) extracted the general trial information, patient characteristics (eg, baseline BP), treatment details (including specific PGHD devices), risk-of-bias items, and outcome data. We examined data on the following reported health outcomes: mortality, emergency room visits, hospitalization, quality of life (QoL), and adverse events (AEs). Surrogate outcomes for hypertension consisted of systolic BP (SBP) and diastolic BP (DBP). Process outcomes included medication changes, dose adjustments, physician consultations, and office visits. We also extracted data on consumer experience, including device adherence, the number of BP readings taken or transmitted, device alerts, ease of use, patient satisfaction, and technical problems.

Risk-of-Bias Assessment

We assessed the overall risk of bias based on 9 items, including randomization, allocation concealment, baseline similarity between groups, and masking of outcome assessors. The items were adapted from the AHRQ report titled “Mobile Applications for Self-Management of Diabetes” [8]. In addition, we included an item about whether the device’s effects could be isolated (ie, consumer BP monitor alone vs usual care). After considering all 9 items, we categorized each trial as at low, moderate, or high risk of bias.

Device Similarity

Given that the included studies were published as early as 1997, for each BP monitor used within the included studies, device engineers assessed the similarity to devices currently on the market from that manufacturer. They used the following scale: (1) this model is similar to a device available from this manufacturer; (2) this model is somewhat different than any device available from this manufacturer; (3) this model is very different from any device available from this manufacturer; and (4) we could not reliably determine the similarity of this model with the ones currently available from this manufacturer.

Results Classification

For isolated effects on health outcomes, we narratively synthesized the summary effect into one of four categories: (1) likely no effect, (2) unclear, (3) possible positive effect, or (4) likely positive effect. If the results consistently demonstrated the lack of an effect (via narrow CIs around a null effect), we coded it as likely no effect. If the results were inconsistent in the direction of effect or study authors could not reach a conclusion, the findings were coded as unclear for that outcome. If ≥1 outcomes had minor inconsistency in findings, but at least 1 study with moderate or low risk of bias showed a positive effect, the findings were coded as possible positive effect. If the results had a consistent positive effect, we coded it as likely positive effect.

When we categorized health outcome data as unclear, we then examined surrogate outcomes, which for hypertension were SBP and DBP. To help interpret the SBP/DBP outcomes, we used a minimally important difference of 2 mm Hg [9,10].

For studies of multicomponent interventions, we did not attempt to classify the data in the manner described earlier because the effect of BP monitoring in those studies could not be determined.

Literature Search

For the full report (ie, 11 clinical conditions), our searches identified 8667 potentially relevant articles, of which we excluded 5755 (66.40%) at the title level (not relevant) and 2196 (25.33%) at the abstract level (Figure 1). We dual-screened the full texts of the remaining 716 articles (8.26%). The review team included 126 (17.6%) of these studies, but upon further review of the devices by device engineers, 12 studies (1.7%) had used only nonconsumer devices and were therefore excluded from the full report (none of the 12 addressed hypertension). A total of 114 unique studies were described in 166 articles. For the subset of screened studies enrolling patients with hypertension, we included 51 studies reported in 80 articles. This review focuses on 49 (96%; 79 articles) of those 51 studies that used BP monitors to generate PGHD for managing hypertension; 2 studies did not use BP monitors to manage hypertension, 1 evaluated a pedometer [11], and the other compared 2 mobile apps [12]. Of the 49 studies, 18 (36.7%) used designs that isolated the effect of BP monitors (eg, BP monitor alone vs usual care or BP monitor+scale vs scale alone), whereas the other 31 (63.3%) used multicomponent designs that did not permit conclusions about the impact on outcomes specific to BP monitors (eg, BP monitor+scale vs usual care).

Figure 1. Study flow diagram. BP: blood pressure; DBP: diastolic blood pressure; PGHD: patient-generated health data; SBP: systolic blood pressure.
View this figure

Study Characteristics

Key characteristics of the studies using BP monitors for hypertension are shown in Table 1 (18 isolated-effect studies) and Multimedia Appendix 1 (Table S1; 31 multicomponent studies). Of the 49 studies, 47 (96%) were randomized trials, and 2 (4%) were nonrandomized; 21 (43%) studies were conducted in the United States, and other notable countries included the United Kingdom (n=6 studies, 12%), Canada (n=3 studies, 6%), Denmark (n=2 studies. 4%), Finland (n=2 studies, 4%), and South Korea (n=2 studies, 4%). The median number of patients per study at baseline was 222 (IQR 80-433). Patient enrollment dates were reported in 29 (59%) studies and ranged from May 1999 to June 2017. The median length of follow-up was 6 months (IQR 4-12).

Study group comparisons are shown in Table 2 and Multimedia Appendix 1 (Table S1). Of the 49 studies, 42 (86%) had 2 study groups, 4 (8%) studies had 3 groups, and 3 (6%) studies had 4 groups. A usual care control group was used in 43 (88%) studies, whereas 3 (6%) studies used a consumer device in the control group, and 4 (8%) other studies used active comparators without a consumer device (eg, counseling alone). Statistical power analyses were conducted a priori in 39 of the 49 (80%) studies, and 29 of these 39 (74%) studies were based on SBP, DBP, or BP control. Note that 31 of the 49 (62%) studies used only multicomponent interventions, making it impossible to discern the impact specific to the BP monitor. Among these 31 studies, 25 (81%) used a BP monitor along with nondevice interventions, 3 (10%) studies used a BP monitor along with another device, and the other 4 (12%) studies used a BP monitor along with ≥2 other devices.

Table 1. General characteristics of studies isolating the effect of blood pressure monitors.
StudyDesignCountryN at baselineStudy durationStudy groups (BPa monitor manufacturer and model)Outcomes
Aekplakorn et al (2016) [13]RCTbThailand22412 months
  • PGHDc (Omron HEM 7117)
  • Usual care
  • Surrogate (SBPd, DBPe, or BP control)
  • Process
  • Consumer experience
Bosworth et al (2009) [14]RCTUnited States6362 years
  • PGHD (Omron 773AC or 637)
  • Behavioral intervention
  • Combination (PGHD+behavioral)
  • Usual care
  • Health (hospitalizations)
  • Surrogate (SBP, DBP, or BP control)
  • Process
  • Adverse events
  • Consumer experience
Bosworth et al (2011) [15-17]RCTUnited States63624 months
  • PGHD (Omron 773AC or 637)
  • Behavioral intervention
  • Combination (PGHD+behavioral)
  • Usual care
  • Surrogate (SBP or DBP)
Broege 2001 [18]RCTUnited States403 months
  • PGHD (Omron HEM-702)
  • Usual care
  • Health (QoLf)
  • Surrogate (SBP or DBP)
  • Consumer experience
Fuchs et al (2012) [19]RCTBrazil12160 days
  • PGHD (Omron HEM-705 CP)
  • Usual care
  • Surrogate (SBP or DBP)
  • Consumer experience
Green et al (2008) [20,21]RCTUnited States7781 year
  • PGHD (Omron HEM-705 CP)
  • Combination (PGHD+pharmacist care)
  • Usual care
  • Health (QoL)
  • Surrogate (SBP, DBP, or BP control)
  • Adverse events
Hebert et al (2012) [22]RCTUnited States41618 months
  • PGHD (Omron HEM-712C)
  • Combination (PGHD+nurse management)
  • Usual care
  • Health (mortality)
  • Surrogate (SBP, DBP, or BP control)
  • Process
Hoffmann-Petersen et al (2017) [23]RCTDenmark3563 months
  • PGHD (A&D 767PlusBT or Omron 705IT)
  • Usual care
  • Surrogate (SBP, DBP, or BP control)
  • Process
Hosseininasab et al (2014) [24]RCTIran19424 weeks
  • PGHD (Samsung SHB-200w)
  • Usual care
  • Surrogate (SBP or DBP)
Kaihara et al (2014) [25]RCTJapan572 weeks
  • PGHD (Omron HEM-7251G)
  • Conventional BP monitor
  • Surrogate (SBP or DBP)
  • Consumer experience
Kauric-Klein et al (2007) [26]RCTUnited States3412 weeks
  • PGHD (Omron IC)
  • Usual care
  • Surrogate (SBP or DBP)
Kim et al (2016) [27,28]RCTUnited States1606 months
  • PGHD (Withings)
  • Usual care
  • Surrogate (SBP, DBP, or BP control)
  • Consumer experience
Lakshminarayan et al (2018) [29]RCTUnited States5013 weeks
  • PGHD (upper arm Withings [Nikia] wireless BP monitor)
  • Conventional BP monitor
  • Surrogate (SBP)
  • Consumer experience
Márquez-Contreras et al (2006) [30]RCTSpain2506 months
  • PGHD (Omron M4 automatic monitor)
  • Usual care
  • Surrogate (SBP, DBP, or BP control)
McManus et al (2018) [4,31-33]RCTUnited Kingdom117312 months
  • PGHD (Omron M10-IT)
  • Combination (PGHD+telemonitoring)
  • Usual care
  • Health (QoL)
  • Surrogate (SBP or DBP); process
  • Adverse events
Qi et al (2017) [34]RCTChina10325 years
  • PGHD (Omron HEM-7121)
  • Control group
  • Surrogate (SBP, DBP, or BP control)
Zaleski et al (2019) [35]RCTUnited States244 months
  • PGHD (BP Omron 705 CPN)
  • Usual care
  • Surrogate (SBP or DBP)
  • Adverse events
  • Consumer experience
Zha et al (2019) [36]RCTUnited States256 months
  • PGHD (iHealth BP 7 wireless BP wrist monitor)
  • Usual care
  • Health (QoL)
  • Surrogate (SBP, DBP, or BP control)
  • Consumer experience

aBP: blood pressure.

bRCT: randomized controlled trial.

cPGHD: patient-generated health data.

dSBP: systolic blood pressure.

eDBP: diastolic blood pressure.

fQoL: quality of life.

Table 2. Patient characteristics in studies isolating the effect of blood pressure monitors.
StudyAge (years),
(female), n
n (%)
Baseline disease severity
Aekplakorn et al (2016) [13]59224148 (66)
  • Mean SBPa PGHDb: 149.4 mm Hg
  • Mean DBPc PGHD: 83.4 mm Hg
  • Mean SBP UCd: 147.2 mm Hg
  • Mean DBP UC: 82.2 mm Hg
Bosworth et al (2009) [14]61636420 (66)
  • BP controlled at baseline 73%
  • Mean SBP: 125 mm Hg
  • Mean DBP: 71 mm Hg
Bosworth et al (2011) [15]; Bosworth et al (2007) [16]; Bosworth et al (2008) [17]61636407 (64)
  • Mean SBP: 125 mm Hg
  • Mean DBP: 71 mm Hg
Broege et al (2001) [18]734028 (70)
  • Mean ambulatory awake SBP: 147 mm Hg
  • Mean ambulatory awake DBP: 82 mm Hg
Fuchs et al (2012) [19]59.012173 (60)
  • Mean office SBP: 158.6 mm Hg
  • Mean office DBP: 89.5 mm Hg
  • Mean 24-hour systolic ABPMe: 148.8 mm Hg
  • Mean 24-hour diastolic ABPM: 87.5 mm Hg
Green et al (2008) [20,21]59.1778405 (52)
  • Mean SBP: 151.9 mm Hg
  • Mean DBP: 89.1 mm Hg
Hebert et al (2012) [22]60.8416295 (71)
  • Mean SBP: 153 mm Hg
  • Mean DBP: 86.0 mm Hg
Hoffmann-Petersen et al (2017) [23]60.5356164 (46)
  • Mean office SBP: 154.6 mm Hg
  • Mean office DBP: 93.2 mm Hg
Hosseininasab et al (2014) [24]58.7194118 (61)
  • Mean SBP: 145.2 mm Hg
  • Mean DBP: 85.3 mm Hg
Kaihara et al (2014) [25]64.45737 (65)
  • Mean SBP: 144 mm Hg
  • Mean DBP: 83 mm Hg
Kauric-Kleinet et al (2007) [26]48.73423 (68)
  • Mean SBP PGHD: 161 mm Hg and 162 mm Hg in the UC group
  • Mean DBP PGHD: 94 mm Hg
  • Mean DBP UC: 100 mm Hg
  • Patients were chronic hemodialysis patients
Kim et al (2016) [27]; Bloss (2016) [28]57.6160104 (65)
  • Mean SBP: 140.6 mm Hg
  • Mean DBP: 89.4 mm Hg
  • Mean number of antihypertensive medications: 2
Lakshminarayan et al (2018) [29]665014 (28)
  • Mean SBP: 140 mm Hg
  • Mean DBP: not reported
Márquez-Contreras et al (2006) [30]59.1250123 (49)
  • Mean SBP: 157.4 mm Hg
  • Mean DBP: 91.7 mm Hg
McManus et al (2018) [4,31-33]66.91173540 (46)
  • Mean SBP: 153.1 mm Hg
  • Mean DBP: 85.5 mm Hg
Qi et al (2017) [34]64.01032464 (45)
  • Mean SBP: 140.0 mm Hg
  • Mean DBP: 92.5 mm Hg
Zaleski et al (2019) [35]52.32413 (54)
  • Mean SBP: 136.2 mm Hg
  • Mean DBP: 85.2 mm Hg
  • Mean duration of hypertension: 6.2 years
Zha et al (2019) [36]52.22522 (88)
  • Mean SBP: 145.72 mm Hg
  • Mean DBP: 90.57 mm Hg

aSBP: systolic blood pressure.

bPGHD: patient-generated health data.

cDBP: diastolic blood pressure.

dUC: usual care.

eABPM: ambulatory blood pressure monitoring.

Table 2 (isolated-effect studies) and Multimedia Appendix 1 (Table S2; multicomponent studies) show the patient characteristics from the 49 studies. The mean age ranged from 49 to 73 years, and the percentage of females ranged from 5% to 88%. The mean baseline SBP was reported in 44 (90%) studies and ranged from 125 to 161 mm Hg. The mean baseline DBP was reported in 42 (86%) studies and ranged from 71 to 97 mm Hg. Only 3 (6%) studies were conducted in rural populations [25,37,38], whereas 24 (49%) were not of rural populations [22,23,26,29,30,35,36,39-62] and the other 22 (44%) did not specify.

Only 21 of the 49 (43%) studies reported health outcomes, which included mortality (n=3 studies, 6%), hospitalizations or emergency room visits (n=2 studies, 4%), QoL (n=13 studies, 26%), and AEs (n=13 studies, 26%). No studies reported other health outcomes related to hypertension, such as major adverse cardiovascular events. All studies reported SBP, DBP, or BP control.

Device Characteristics

The included studies used 41 different BP monitoring devices (see specifics in Table 1). Of these, 34 (83%) were arm devices and 2 (5%) were wrist devices, and the wrist or arm was unclear in the other 5 (12%) studies. A total of 38 (93%) BP monitors were judged as similar to devices currently on the market from the corresponding manufacturer, 1 (2%) was judged as somewhat different, and 2 (5%) were of unknown similarity.

Regarding the transmission of data (eg, to a website, to study staff, or to health care providers), 19 of 49 (39%) studies used automatic transmission, 6 (12%) used manual data entry for transmission, 20 (41%) had no electronic data transmission, and the other 4 (8%) did not report whether or how data were transmitted.

Isolated Effects on Health Outcomes

The isolated effects of a consumer BP monitor device on health outcomes were evaluated in 6 of the 49 (12%) studies. The consumer BP monitors examined included the iHealth BP 7 Wireless Wrist Monitor, Omron 637, Omron 773AC, Omron HEM-705 CP, Omron HEM-712C, and Omron M10-IT. Only 1 of the 6 (17%) studies reported mortality [22], 1 (17%) reported hospitalization [14], and the other 4 (67%) reported QoL [4,18,20,21,31-33,36].

  • For mortality, Hebert et al [22] followed patients for 18 months and found that 8 deaths occurred in the 3 study groups (Omron HEM-712C BP monitor, Omron HEM-712C BP monitor plus nurse management, and usual care). Mortality rates did not differ significantly across the groups (group-specific rates were not reported).
  • For hospitalizations, Bosworth et al [14] reported no statistically significant differences in hospitalization rates among the 4 study groups. The rates ranged from 19% to 23% (group-specific rates were not reported). The groups received Omron 773AC or 637 (depending on patient arm circumference) compared with usual care, behavioral management alone, or a combination of BP monitoring and behavioral management.
  • For QoL, 3 of the 4 (75%) studies found no statistically significant differences between groups at follow-ups ranging from 3 to 12 months. To measure QoL, the studies used the Short Form Health Survey 36 (SF-36) [18], the Short Form Health Survey-12 [20,21], or the EQ-5D [4,31-33]. The fourth study [36] found that at both baseline and the 6-month follow-up, there was a statistically significant difference in SF-36 scores favoring the usual care group over the BP monitor group (suggesting a problem with randomization rather than an effect of the BP monitor).

Isolated Effects on Surrogate Outcomes

Of the 49 studies, 18 (37%) [4,13-26,28-36] examined the isolated effects of consumer BP monitors on blood pressure. All evaluated the effects compared with usual care (ie, no BP monitor), except for 2 (11%) studies [25,29], each of which compared BP monitors with automatic data transmission with BP monitors without automatic transmission.

All 16 studies on comparisons with usual care reported the effects of PGHD interventions on SBP (Figure 2). The top 4 points were from studies using automatic transmission of BP data, and the remaining 28 points were from studies that did not use automatic transmission. Six studies [4,15-17,19-21,26,31-34] found a statistically significant reduction in SBP favoring the BP monitoring group compared with the control group. However, the results were somewhat inconsistent. For example, Bosworth et al [15-17] found significant improvement only in non-White patients at 12 months; differences were not statistically significant for White patients at any time point or 24 months for any subgroup. The point estimates for SBP are shown in Figure 2, corresponding to 32 reported outcomes from 16 studies. Moreover, 4 of 32 (13%) SBP outcomes identified a reduction of 6 mm Hg or more favoring the consumer BP monitor group compared with usual care; 12 (38%) identified an SBP reduction between 2 mm Hg and 6 mm Hg favoring the consumer BP monitor, 10 (31%) identified SBP differences from −2 mm Hg to +2 mm Hg, and the remaining 3 (9%) found an SBP reduction ≥2 mm Hg favoring the usual care groups. Whether the BP monitor automatically transmitted data (comparing the top 4 points with the other points) did not appear to modify the effect on SBP.

The overall findings for DBP were similar to those for SBP; 5 (31%) [4,15,19,30-34] studies found that consumer BP monitors significantly reduced DBP compared with controls. However, similar to SBP, the results were inconsistent, and statistical significance was found only for particular subgroups or time points in a study. The 32 point estimates for DBP are shown in Figure 3 (restricted to studies with usual care comparison groups). Of these, 1 (3%) identified a DBP reduction of 6 mm Hg or more favoring the consumer BP monitor, 9 (28%) identified a DBP reduction between 2 mm Hg and 6 mm Hg, favoring the consumer BP monitor, and the remaining 19 (59%) identified DBP differences from −2 mm Hg to +2 mm Hg. Whether the BP monitor automatically transmitted data did not appear to modify its effect on DBP.

Regarding the 2 studies examining the effect of data transmission (eg, BP monitor with vs without data transmission), Kaihara et al [25] found that data transmission resulted in an estimated 6 mm Hg lower SBP but no statistically significant effect on DBP. Lakshminarayan et al [29] found a statistically nonsignificant difference of 3.7 mm Hg in favor of data transmission and did not report data on DBP.

BP control was examined in 9 (15%) studies of the isolated effects of consumer BP monitors [13,14,19-23,27,28,30,34]. Most defined BP control as SBP <140 mm Hg and DBP <90 mm Hg, but 1 study [23] used <135/<85 mm Hg; 2 [14,23] studies included a separate definition of <130/80 mm Hg for patients with diabetes. Only 2 of the 9 (22%) studies [19,34] reported statistically significantly higher rates of BP control with BP monitors than with controls.

  • Fuchs et al [19] found that at 60 days, the BP control rates measured in the office were similar for BP-monitored patients and usual care patients (43% and 41%, respectively), but for 24-hour BP, 32% of BP-monitored patients had BP control compared with only 16% of usual care patients;
  • Qi et al [34] found that at 5 years, 85% of BP-monitored patients had BP control compared with 80% of usual care patients.

The remaining 7 (78%) studies found nonsignificant differences in BP control rates between BP-monitored and control patients.

Figure 2. Systolic blood pressure (SBP) differences in studies of isolated effects of blood pressure (BP) monitors. PGHD: patient-generated health data.
View this figure
Figure 3. Diastolic blood pressure (DBP) differences in studies of isolated effects of blood pressure (BP) monitors. PGHD: patient-generated health data.
View this figure

Isolated Effects on Process Outcomes

Of the 18 studies on isolated effects of BP monitors, 5 (28%) reported process outcomes, and the results were mixed. For medication prescribing, McManus et al [4,31-33] found that those in the BP monitor group were prescribed statistically significantly more antihypertensive drugs than those in the usual care group (difference 0.11; 95% CI 0.02-0.19), and 3 other studies found no statistically significant impact of BP monitoring on prescriptions.

  • Hebert et al [22] reported that the percentage of patients who had no change in medications at 9 months was not statistically significantly different among those who had BP monitoring (44%) compared with the control group (38%).
  • Hoffmann-Petersen et al [23] found that at baseline, 59% of the BP-monitored group and 61% of the control group did not receive any antihypertensive medication. At follow-up, these percentages were reduced to 23% in the BP-monitored group and 22% in the control group (not a significant difference).
  • Aekplakorn et al [13] found that prescription of antihypertensive medications increased in both groups, but there were no significant between-group differences in drug items or drug classes (the authors did not report the number of prescriptions at follow-up).

However, these studies were not statistically powered to detect such effects, so they did not rule out the possibility of an impact on prescriptions.

In addition, Bosworth et al (2009) [14] found no between-group differences in the number of outpatient encounters (medians ranged from 13 to 15).

With regard to data transmission, 5 of the 18 (28%) studies used automatic data transmission, 2 (11%) used manual entry, 10 (31%) had no electronic data transmission, and 1 (3%) did not report whether or how data were transmitted. Of those using automatic data transmission, in Hoffmann-Petersen et al [23], data were transmitted using a Tunstall RTX3371 or Numera telehealth monitor to a study database or an electronic health record after BP measurements.

In Kaihara et al [25], the BP monitor wirelessly transmitted data to a study database over the internet.

In Kim et al [27], the BP monitor readings were wirelessly transmitted via the HealthCircles app on a smartphone to a website.

In Lakshminarayan et al [29], a smartphone transmitted daily BP measurements to a study database. Participants in the PGHD group transmitted data on an average of 89% of the study days and rated the ease of use of the system favorably.

In Zha et al [36], the wireless BP wrist monitor would transmit data to a website using the iHealth MyVitals app on a smartphone.

Of the 18 studies, 2 (18%) studies used manual data transmission [4,35]. In these 2 studies, participants sent BP readings via an SMS text message service or web-based form to a website [4] or entered their BP measurements on a BP-tracking website [35].

Adverse Events

Of the 49 studies, 12 (24%) reported on AEs and generally found them to occur infrequently, and 4 [4,14,20,21,31-33,35] of the 18 (22%) studies on isolated effects of BP monitoring reported on AEs; 2 (17%) studies reported that no AEs occurred during the course of the study. A study [20,21] found that serious AEs, including nonfatal cardiovascular events, were rare and not substantially different between the BP monitoring and control groups. Another study [4,31-33] reported on various other AEs, including pain, fatigue, and dry mouth. Only dry mouth occurred significantly more frequently in the BP monitor group than in the usual care group. Of the 49 studies, 11 (22%) [4,14,20,21,31-33,38,44-46,50-56,60,63-74] reported on AEs in studies with multicomponent device groups. Only one of those studies [69-73] reported a significant increase of an AE, swelling of legs, in a multicomponent intervention group that included a BP monitor compared with usual care.

Consumer Experience

Of the 49 studies, 26 (53%) reported the outcomes of consumer experience. Adherence to the use of BP monitors ranged from 38% to 89%, but device adherence had variable definitions. For example, Logan et al [47] defined adherence as a minimum of 8 readings per week. Zaleski et al [35] only determined whether patients said they were still monitoring their BP. Zha et al [36] measured adherence by dividing the number of received readings by expected readings.

Some studies reported that adherence declined throughout the study. For example, Bosworth et al [14] reported that during the first 2 months, 91% of those using a BP monitor were adherent, whereas 64% were adherent during the last 2 months. The studies also measured BP monitor use in various ways, including the total number of transmissions during the study and the average number of transmissions per week.

Studies measuring the ease of use or satisfaction with consumer BP monitors found favorable ratings. For example, Magid et al [49] reported that 68% of patients using the monitor found it very or extremely easy to use. Rifkin et al [75] reported that 96% of patients would continue to use the BP monitor.

Only 2 studies reported problems with BP monitors. Bosworth et al [63-65] found that 35 alerts were triggered by the monitoring system due to BP monitor problems, which represented 5% of the total alerts that occurred during the study. Lakshminarayan et al [29] found that some patients experienced issues with the BP monitor and the smartphone provided to transmit BP data, including an inability to hold a charge and difficulty using the phone app to see BP data.

Multicomponent Effects

Of the 31 multicomponent studies [38-87], 11 (35%) examined the multicomponent effect of BP monitors on health outcomes, and all 31 evaluated multicomponent PGHD for surrogate outcomes including SBP, DBP, and BP control. These study designs did not permit any determination of the effectiveness specific to BP monitors.

Risk of Bias

Of the 18 studies of isolated effects, we rated 6 (33%) as low risk of bias, 9 (50%) as moderate risk of bias, and 3 (17%) as high risk of bias. In contrast, of the 31 studies of multicomponent effects, we rated 6 (19%) as low risk of bias, 13 (42%) as moderate risk of bias, and 12 (39%) as high risk of bias. The full AHRQ report (in its Appendix Table C-26) contains the item-level and overall risk-of-bias ratings for each study [7].

Principal Findings

This systematic review summarizes 49 comparative studies that used consumer BP monitors for hypertension management. However, the effects of these devices on health outcomes remain unclear. Only 18 studies were designed to isolate the BP monitor effect, and only 6 of these 18 (33%) studies reported any health outcome, such as mortality, hospitalization, and QoL. One study [36] found a statistically significant difference in QoL at follow-up favoring usual care over BP monitoring, but QoL also favored usual care at baseline (suggesting a problem in the randomization process). None of the 5 remaining studies found statistically significant effects on health outcomes, possibly because they were powered to detect differences in BP measurements and not necessarily differences in health outcomes. Many studies had only 6 months of follow-up, which may also explain the uncertain effect of BP monitors on health outcomes.

We found consistent benefits of BP monitoring on both surrogate outcomes, SBP and DBP. SBP reductions typical of included studies ranged between 2 and 4 mm Hg, and DBP reductions ranged from 1 to 3 mm Hg. It is unclear whether these modest changes in BP related to consumer BP monitors lead to lower risks of hypertension-related complications or mortality. Many factors may have potentially modified BP reduction in these studies. BP self-monitoring may support behavioral changes or reminder strategies to assist with lifestyle changes or medication adherence [2-4]. In addition, select BP monitors transmit data to health care providers and can improve BP control by facilitating timely recommendations from providers to patients to better manage their BP [87,88]. However, only 5 [23,25,27-29,36] of the 18 (27%) studies on isolated effects of BP monitors used automatic data transmission, and the effects on provider behavior change were rarely described among the included studies. This indicates that many studies did not use the advanced capabilities of modern BP monitors and may explain the unclear impact on health outcomes.

Most studies reported adherence to BP monitor use that ranged from 38% to 89%, but adherence was inconsistently measured. There was also a large gap between self-reported and measured adherence, such as a set number of recordings per week, as self-reported information is not always reliable. In addition, adherence can be affected by a variety of factors, such as daily access to the device, consumer comfort with the device, or self-motivation factors [89]. Spillover to other adherence factors, such as medication adherence or compliance with lifestyle behavior changes to manage hypertension, were not reported but may ultimately be a mechanism by which consumers of BP monitors improve their hypertension. Another consumer experience outcome, overall satisfaction, was reported as highly favorable among the included studies, thus validating the current rising consumer market for these devices.

Many studies evaluated multicomponent interventions, with BP monitors representing only 1 component, and did not separately evaluate the impact of the BP monitor. In our evidence base, only 18 of the 49 (37%) studies permitted such a direct assessment of BP monitor impact. Many PGHD technologies are intended to be used in combination with other interventions for chronic disease management, such as additional devices, exercise sessions, or health education sessions with medical personnel. These interventions may also influence outcomes; therefore, studies should be designed to measure the impact of isolated PGHD technology when added to other components.

Strengths and Limitations

This systematic review has several strengths. To our knowledge, this is the first systematic review to synthesize the patient-centered health effects of consumer BP monitors for hypertension management, in addition to their effects on BP. We closely followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting standards and used robust AHRQ Evidence-based Practice Center systematic review methodology, including duplicate literature screening and data extraction. The findings of our review mirror those from 2 recent meta-analyses of systematic reviews of individual patient data [90,91] and contribute summary-level data on health effects as well as key data on medication management and consumer experience. Furthermore, in this review, we used device engineers to verify the consumer availability of BP monitors used in studies and their similarity to currently available models.

This systematic review has limitations related to both the review methodology and the generalizability of the available literature. We judged the overall risk of bias using an adapted tool designed for mobile apps in managing diabetes [8] and therefore may not have detected some biases. We did not assess the possibility of publication bias, which may be a key problem in studies funded by manufacturers of devices that collect PGHD. The included studies rarely provided sufficient detail to delineate the contributions of cointerventions to outcomes, particularly those related to changes in BP. This limits the generalizability of our findings to patients with limited access to care or underserved patient populations. This may also further limit the confidence in the validity of our findings not otherwise captured in our risk-of-bias assessment. Studies with usual care groups often provided few details about what happened with these patients, which may potentially explain the wide variation in BP results among studies. The inclusion criteria of multiple studies were specific to consumers who had access to and familiarity with technology, which could include using the internet, smartphones or computers, arm or wrist devices, or access to electricity. Less technically adept consumers may not experience the same benefits as those enrolled in these studies. In addition, only 3 [25,37,38] of the 49 (6%) studies focused on rural populations, suggesting that these populations are underrepresented. Only 19 of the 49 (39%) studies used automatic data transmission from PGHD devices to health care providers.

Future studies are needed to examine the effectiveness of BP monitors that transmit data to health care providers (which are then used to inform medical decisions). Additional data from implementation studies may help determine which components are critical for sustained BP improvement, which in turn may improve prescription decisions by clinicians and coverage decisions by policy makers. In addition, challenges related to data accuracy, interoperability, privacy, and security should be explored as this field continues to grow.


The authors greatly appreciate the contributions of the ECRI employees who contributed to the development of this paper: Brad Bonnette, Kitty Donahue, Helen Dunn, Eileen Erinoff, Andrew Furman, Jacki Hostetter, Janice Kaczmarek, Christopher Lavanchy, Jennifer Maslin, Emily McDonell, Kristy McShea, Michael Phillips, Karen Schoelles, Priyanka Shah, Julianne Teitman, and Polly Tremoulet. This study was funded by the Agency for Healthcare Research and Quality (contract 290-2015-00005I).

Conflicts of Interest

None declared.

Multimedia Appendix 1

Tables showing general characteristics and patients characteristics of the 31 multicomponent studies.

DOCX File , 27 KB

  1. Centers FDC. About underlying cause of death, 1999-2018. Centers for Disease Control and Prevention. 2018.   URL: [accessed 2020-11-03]
  2. Ward AM, Takahashi O, Stevens R, Heneghan C. Home measurement of blood pressure and cardiovascular disease: systematic review and meta-analysis of prospective studies. J Hypertens 2012 Mar;30(3):449-456. [CrossRef] [Medline]
  3. Mancia G, Facchetti R, Bombelli M, Grassi G, Sega R. Long-term risk of mortality associated with selective and combined elevation in office, home, and ambulatory blood pressure. Hypertension 2006 May;47(5):846-853. [CrossRef] [Medline]
  4. McManus RJ, Mant J, Franssen M, Nickless A, Schwartz C, Hodgkinson J, TASMINH4 investigators. Efficacy of self-monitored blood pressure, with or without telemonitoring, for titration of antihypertensive medication (TASMINH4): an unmasked randomised controlled trial. Lancet 2018 Mar 10;391(10124):949-959 [FREE Full text] [CrossRef] [Medline]
  5. National Learning Consortium. Patient-generated health data fact sheet. The Office of the National Coordinator for Health Information Technology (ONC). 2014.   URL: [accessed 2020-08-17]
  6. Global automated home blood pressure monitors market 2020 by manufacturers, type and application, forecast to 2025. Markets and Research. 2020.   URL: https:/​/www.​​report/​95547/​global-automated-home-blood-pressure-monitors-market-2020-by-manufacturers-type-and-application-forecast-to-2025 [accessed 2020-11-03]
  7. Treadwell JR, Reston JT, Rouse B, Fontanarosa J, Patel N, Mull NK. Automated-entry patient-generated health data for chronic conditions: the evidence on health outcomes. Technical brief No. 38. Agency for Healthcare Research and Quality. 2021 Mar 1.   URL: [accessed 2020-04-02]
  8. Veazie S, Winchell K, Gilbert J, Paynter R, Ivlev I, Eden K, et al. Mobile Applications for Self-Management of Diabetes. Technical Brief No. 31. Agency for Healthcare Research and Quality. 2018 May.   URL: [accessed 2022-04-02]
  9. Makai P, IntHout J, Deinum J, Jenniskens K, van der Wilt GJ. A network meta-analysis of clinical management strategies for treatment-resistant hypertension: making optimal use of the evidence. J Gen Intern Med 2017 Aug;32(8):921-930 [FREE Full text] [CrossRef] [Medline]
  10. Whelton PK, He J, Appel LJ, Cutler JA, Havas S, Kotchen TA, National High Blood Pressure Education Program Coordinating Committee. Primary prevention of hypertension: clinical and public health advisory from The National High Blood Pressure Education Program. JAMA 2002 Oct 16;288(15):1882-1888. [CrossRef] [Medline]
  11. Bennett GG, Steinberg D, Askew S, Levine E, Foley P, Batch BC, et al. Effectiveness of an app and provider counseling for obesity treatment in primary care. Am J Prev Med 2018 Dec;55(6):777-786 [FREE Full text] [CrossRef] [Medline]
  12. Chandler J, Sox L, Diaz V, Kellam K, Neely A, Nemeth L, et al. Impact of 12-month smartphone breathing meditation program upon systolic blood pressure among non-medicated stage 1 hypertensive adults. Int J Environ Res Public Health 2020 Mar 17;17(6):1955 [FREE Full text] [CrossRef] [Medline]
  13. Aekplakorn W, Suriyawongpaisal P, Tansirisithikul R, Sakulpipat T, Charoensuk P. Effectiveness of self-monitoring blood pressure in primary care: a randomized controlled trial. J Prim Care Community Health 2016 Apr;7(2):58-64 [FREE Full text] [CrossRef] [Medline]
  14. Bosworth HB, Olsen MK, Grubber JM, Neary AM, Orr MM, Powers BJ, et al. Two self-management interventions to improve hypertension control: a randomized trial. Ann Intern Med 2009 Nov 17;151(10):687-695 [FREE Full text] [CrossRef] [Medline]
  15. Bosworth HB, Olsen MK, Grubber JM, Powers BJ, Oddone EZ. Racial differences in two self-management hypertension interventions. Am J Med 2011 May;124(5):468.e1-468.e8 [FREE Full text] [CrossRef] [Medline]
  16. Bosworth HB, Olsen MK, Dudley T, Orr M, Neary A, Harrelson M, et al. The Take Control of Your Blood pressure (TCYB) study: study design and methodology. Contemp Clin Trials 2007 Jan;28(1):33-47. [CrossRef] [Medline]
  17. Bosworth HB, Olsen MK, Neary A, Orr M, Grubber J, Svetkey L, et al. Take Control of Your Blood Pressure (TCYB) study: a multifactorial tailored behavioral and educational intervention for achieving blood pressure control. Patient Educ Couns 2008 Mar;70(3):338-347 [FREE Full text] [CrossRef] [Medline]
  18. Broege PA, James GD, Pickering TG. Management of hypertension in the elderly using home blood pressures. Blood Press Monit 2001 Jun;6(3):139-144. [CrossRef] [Medline]
  19. Fuchs SC, Ferreira-da-Silva AL, Moreira LB, Neyeloff JL, Fuchs FC, Gus M, et al. Efficacy of isolated home blood pressure monitoring for blood pressure control: randomized controlled trial with ambulatory blood pressure monitoring - MONITOR study. J Hypertens 2012 Jan;30(1):75-80. [CrossRef] [Medline]
  20. Green BB, Cook AJ, Ralston JD, Fishman PA, Catz SL, Carlson J, et al. Effectiveness of home blood pressure monitoring, web communication, and pharmacist care on hypertension control: a randomized controlled trial. JAMA 2008 Jun 25;299(24):2857-2867 [FREE Full text] [CrossRef] [Medline]
  21. Ralston JD, Cook AJ, Anderson ML, Catz SL, Fishman PA, Carlson J, et al. Home blood pressure monitoring, secure electronic messaging and medication intensification for improving hypertension control: a mediation analysis. Appl Clin Inform 2014;5(1):232-248 [FREE Full text] [CrossRef] [Medline]
  22. Hebert PL, Sisk JE, Tuzzio L, Casabianca JM, Pogue VA, Wang JJ, et al. Nurse-led disease management for hypertension control in a diverse urban community: a randomized trial. J Gen Intern Med 2012 Jun;27(6):630-639 [FREE Full text] [CrossRef] [Medline]
  23. Hoffmann-Petersen N, Lauritzen T, Bech JN, Pedersen EB. Short-term telemedical home blood pressure monitoring does not improve blood pressure in uncomplicated hypertensive patients. J Hum Hypertens 2017 Feb;31(2):93-98. [CrossRef] [Medline]
  24. Hosseininasab M, Jahangard-Rafsanjani Z, Mohagheghi A, Sarayani A, Rashidian A, Javadi M, et al. Self-monitoring of blood pressure for improving adherence to antihypertensive medicines and blood pressure control: a randomized controlled trial. Am J Hypertens 2014 Nov;27(11):1339-1345 [FREE Full text] [CrossRef] [Medline]
  25. Kaihara T, Eguchi K, Kario K. Home BP monitoring using a telemonitoring system is effective for controlling BP in a remote island in Japan. J Clin Hypertens (Greenwich) 2014 Nov;16(11):814-819 [FREE Full text] [CrossRef] [Medline]
  26. Kauric-Klein Z, Artinian N. Improving blood pressure control in hypertensive hemodialysis patients. CANNT J 2007;17(4):24-38. [Medline]
  27. Kim JY, Wineinger NE, Steinhubl SR. The influence of wireless self-monitoring program on the relationship between patient activation and health behaviors, medication adherence, and blood pressure levels in hypertensive patients: a substudy of a randomized controlled trial. J Med Internet Res 2016 Jun 22;18(6):e116 [FREE Full text] [CrossRef] [Medline]
  28. Bloss CS, Wineinger NE, Peters M, Boeldt DL, Ariniello L, Kim JY, et al. A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors. PeerJ 2016 Jan 14;4:e1554 [FREE Full text] [CrossRef] [Medline]
  29. Lakshminarayan K, Westberg S, Northuis C, Fuller CC, Ikramuddin F, Ezzeddine M, et al. A mHealth-based care model for improving hypertension control in stroke survivors: pilot RCT. Contemp Clin Trials 2018 Jul;70:24-34 [FREE Full text] [CrossRef] [Medline]
  30. Márquez-Contreras E, Martell-Claros N, Gil-Guillén V, de la Figuera-Von Wichmann M, Casado-Martínez JJ, Martin-de Pablos JL, Compliance Group of the Spanish Society of Hypertension (SEE). Efficacy of a home blood pressure monitoring programme on therapeutic compliance in hypertension: the EAPACUM-HTA study. J Hypertens 2006 Jan;24(1):169-175. [CrossRef] [Medline]
  31. Franssen M, Farmer A, Grant S, Greenfield S, Heneghan C, Hobbs R, et al. Telemonitoring and/or self-monitoring of blood pressure in hypertension (TASMINH4): protocol for a randomised controlled trial. BMC Cardiovasc Disord 2017 Feb 13;17(1):58 [FREE Full text] [CrossRef] [Medline]
  32. Grant S, Hodgkinson J, Schwartz C, Bradburn P, Franssen M, Hobbs FR, et al. Using mHealth for the management of hypertension in UK primary care: an embedded qualitative study of the TASMINH4 randomised controlled trial. Br J Gen Pract 2019 Sep;69(686):e612-e620 [FREE Full text] [CrossRef] [Medline]
  33. Monahan M, Jowett S, Nickless A, Franssen M, Grant S, Greenfield S, et al. Cost-effectiveness of telemonitoring and self-monitoring of blood pressure for antihypertensive titration in primary care (TASMINH4). Hypertension 2019 Jun;73(6):1231-1239 [FREE Full text] [CrossRef] [Medline]
  34. Qi L, Qiu Y, Zhang W. Home blood pressure monitoring is a useful measurement for patients with hypertension: a long-term follow-up study. Biomed Res 2017;28(7):2898-2902.
  35. Zaleski AL, Taylor BA, Park CL, Santos LP, Panza G, Kramarz M, et al. Using the immediate blood pressure benefits of exercise to improve exercise adherence among adults with hypertension: a randomized clinical trial. J Hypertens 2019 Sep;37(9):1877-1888. [CrossRef] [Medline]
  36. Zha P, Qureshi R, Porter S, Chao YY, Pacquiao D, Chase S, et al. Utilizing a mobile health intervention to manage hypertension in an underserved community. West J Nurs Res 2020 Mar;42(3):201-209. [CrossRef] [Medline]
  37. Bernocchi P, Scalvini S, Bertacchini F, Rivadossi F, Muiesan ML. Home based telemedicine intervention for patients with uncontrolled hypertension--a real life non-randomized study. BMC Med Inform Decis Mak 2014 Jun 12;14:52 [FREE Full text] [CrossRef] [Medline]
  38. Petrella RJ, Stuckey MI, Shapiro S, Gill DP. Mobile health, exercise and metabolic risk: a randomized controlled trial. BMC Public Health 2014 Oct 18;14:1082 [FREE Full text] [CrossRef] [Medline]
  39. Bove AA, Homko CJ, Santamore WP, Kashem M, Kerper M, Elliott DJ. Managing hypertension in urban underserved subjects using telemedicine--a clinical trial. Am Heart J 2013 Apr;165(4):615-621. [CrossRef] [Medline]
  40. Dorough AE, Winett RA, Anderson ES, Davy BM, Martin EC, Hedrick V. DASH to wellness: emphasizing self-regulation through e-health in adults with prehypertension. Health Psychol 2014 Mar;33(3):249-254. [CrossRef] [Medline]
  41. Earle KA, Istepanian RS, Zitouni K, Sungoor A, Tang B. Mobile telemonitoring for achieving tighter targets of blood pressure control in patients with complicated diabetes: a pilot study. Diabetes Technol Ther 2010 Jul;12(7):575-579. [CrossRef] [Medline]
  42. Green BB, Anderson ML, Cook AJ, Catz S, Fishman PA, McClure JB, et al. e-Care for heart wellness: a feasibility trial to decrease blood pressure and cardiovascular risk. Am J Prev Med 2014 Apr;46(4):368-377 [FREE Full text] [CrossRef] [Medline]
  43. He J, Irazola V, Mills KT, Poggio R, Beratarrechea A, Dolan J, HCPIA Investigators. Effect of a community health worker-led multicomponent intervention on blood pressure control in low-income patients in Argentina: a randomized clinical trial. JAMA 2017 Sep 19;318(11):1016-1025 [FREE Full text] [CrossRef] [Medline]
  44. Kerry SM, Markus HS, Khong TK, Cloud GC, Tulloch J, Coster D, et al. Home blood pressure monitoring with nurse-led telephone support among patients with hypertension and a history of stroke: a community-based randomized controlled trial. CMAJ 2013 Jan 08;185(1):23-31 [FREE Full text] [CrossRef] [Medline]
  45. Kerry S, Markus H, Khong T, Doshi R, Conroy R, Oakeshott P. Community based trial of home blood pressure monitoring with nurse-led telephone support in patients with stroke or transient ischaemic attack recently discharged from hospital. Trials 2008 Mar 19;9:15 [FREE Full text] [CrossRef] [Medline]
  46. Ovaisi S, Oakeshott P, Kerry S, Crabtree AE, Kyei G, Kerry SM. Home blood pressure monitoring in hypertensive stroke patients: a prospective cohort study following a randomized controlled trial. Fam Pract 2013 Aug;30(4):398-403. [CrossRef] [Medline]
  47. Logan AG, Irvine MJ, McIsaac WJ, Tisler A, Rossos PG, Easty A, et al. Effect of home blood pressure telemonitoring with self-care support on uncontrolled systolic hypertension in diabetics. Hypertension 2012 Jul;60(1):51-57. [CrossRef] [Medline]
  48. Magid DJ, Ho PM, Olson KL, Brand DW, Welch LK, Snow KE, et al. A multimodal blood pressure control intervention in 3 healthcare systems. Am J Manag Care 2011 Apr;17(4):e96-103. [Medline]
  49. Magid DJ, Olson KL, Billups SJ, Wagner NM, Lyons EE, Kroner BA. A pharmacist-led, American Heart Association Heart360 web-enabled home blood pressure monitoring program. Circ Cardiovasc Qual Outcomes 2013 Mar 01;6(2):157-163. [CrossRef] [Medline]
  50. Margolis KL, Asche SE, Bergdall AR, Dehmer SP, Groen SE, Kadrmas HM, et al. Effect of home blood pressure telemonitoring and pharmacist management on blood pressure control: a cluster randomized clinical trial. JAMA 2013 Jul 03;310(1):46-56 [FREE Full text] [CrossRef] [Medline]
  51. Margolis KL, Asche SE, Bergdall AR, Dehmer SP, Maciosek MV, Nyboer RA, et al. A successful multifaceted trial to improve hypertension control in primary care: why did it work? J Gen Intern Med 2015 Nov;30(11):1665-1672 [FREE Full text] [CrossRef] [Medline]
  52. Beran M, Asche SE, Bergdall AR, Crabtree B, Green BB, Groen SE, et al. Key components of success in a randomized trial of blood pressure telemonitoring with medication therapy management pharmacists. J Am Pharm Assoc (2003) 2018;58(6):614-621 [FREE Full text] [CrossRef] [Medline]
  53. Dehmer SP, Maciosek MV, Trower NK, Asche SE, Bergdall AR, Nyboer RA, et al. Economic evaluation of the home blood pressure telemonitoring and pharmacist case management to control hypertension (Hyperlink) trial. J Am Coll Clin Pharm 2018 Oct;1(1):21-30 [FREE Full text] [CrossRef] [Medline]
  54. Margolis KL, Kerby TJ, Asche SE, Bergdall AR, Maciosek MV, O'Connor PJ, et al. Design and rationale for home blood pressure telemonitoring and case management to control hypertension (HyperLink): a cluster randomized trial. Contemp Clin Trials 2012 Jul;33(4):794-803 [FREE Full text] [CrossRef] [Medline]
  55. Margolis KL, Asche SE, Dehmer SP, Bergdall AR, Green BB, Sperl-Hillen JM, et al. Long-term outcomes of the effects of home blood pressure telemonitoring and pharmacist management on blood pressure among adults with uncontrolled hypertension: follow-up of a cluster randomized clinical trial. JAMA Netw Open 2018 Sep 07;1(5):e181617 [FREE Full text] [CrossRef] [Medline]
  56. Kerby TJ, Asche SE, Maciosek MV, O'Connor PJ, Sperl-Hillen JM, Margolis KL. Adherence to blood pressure telemonitoring in a cluster-randomized clinical trial. J Clin Hypertens (Greenwich) 2012 Oct;14(10):668-674 [FREE Full text] [CrossRef] [Medline]
  57. Mehos BM, Saseen JJ, MacLaughlin EJ. Effect of pharmacist intervention and initiation of home blood pressure monitoring in patients with uncontrolled hypertension. Pharmacotherapy 2000 Nov;20(11):1384-1389. [CrossRef] [Medline]
  58. Mendelson M, Vivodtzev I, Tamisier R, Laplaud D, Dias-Domingos S, Baguet JP, et al. CPAP treatment supported by telemedicine does not improve blood pressure in high cardiovascular risk OSA patients: a randomized, controlled trial. Sleep 2014 Nov 01;37(11):1863-1870 [FREE Full text] [CrossRef] [Medline]
  59. Niiranen TJ, Leino K, Puukka P, Kantola I, Karanko H, Jula AM. Lack of impact of a comprehensive intervention on hypertension in the primary care setting. Am J Hypertens 2014 Mar;27(3):489-496. [CrossRef] [Medline]
  60. Ogedegbe G, Tobin JN, Fernandez S, Cassells A, Diaz-Gloster M, Khalida C, et al. Counseling African Americans to control hypertension: cluster-randomized clinical trial main effects. Circulation 2014 May 20;129(20):2044-2051 [FREE Full text] [CrossRef] [Medline]
  61. Sarfo FS, Treiber F, Gebregziabher M, Adamu S, Nichols M, Singh A, PINGS Team. Phone-based intervention for blood pressure control among Ghanaian stroke survivors: a pilot randomized controlled trial. Int J Stroke 2019 Aug;14(6):630-638. [CrossRef] [Medline]
  62. Yoo HJ, Park MS, Kim TN, Yang SJ, Cho GJ, Hwang TG, et al. A ubiquitous chronic disease care system using cellular phones and the internet. Diabet Med 2009 Jun;26(6):628-635. [CrossRef] [Medline]
  63. Bosworth HB, Powers BJ, Olsen MK, McCant F, Grubber J, Smith V, et al. Home blood pressure management and improved blood pressure control: results from a randomized controlled trial. Arch Intern Med 2011 Jul 11;171(13):1173-1180. [CrossRef] [Medline]
  64. Maciejewski ML, Bosworth HB, Olsen MK, Smith VA, Edelman D, Powers BJ, et al. Do the benefits of participation in a hypertension self-management trial persist after patients resume usual care? Circ Cardiovasc Qual Outcomes 2014 Mar;7(2):269-275. [CrossRef] [Medline]
  65. McCant F, McKoy G, Grubber J, Olsen MK, Oddone E, Powers B, et al. Feasibility of blood pressure telemonitoring in patients with poor blood pressure control. J Telemed Telecare 2009;15(6):281-285. [CrossRef] [Medline]
  66. McKinstry B, Hanley J, Wild S, Pagliari C, Paterson M, Lewis S, et al. Telemonitoring based service redesign for the management of uncontrolled hypertension: multicentre randomised controlled trial. BMJ 2013 May 24;346:f3030 [FREE Full text] [CrossRef] [Medline]
  67. Hanley J, Ure J, Pagliari C, Sheikh A, McKinstry B. Experiences of patients and professionals participating in the HITS home blood pressure telemonitoring trial: a qualitative study. BMJ Open 2013 May 28;3(5):e002671 [FREE Full text] [CrossRef] [Medline]
  68. Stoddart A, Hanley J, Wild S, Pagliari C, Paterson M, Lewis S, et al. Telemonitoring-based service redesign for the management of uncontrolled hypertension (HITS): cost and cost-effectiveness analysis of a randomised controlled trial. BMJ Open 2013 May 28;3(5):e002681 [FREE Full text] [CrossRef] [Medline]
  69. McManus RJ, Mant J, Bray EP, Holder R, Jones MI, Greenfield S, et al. Telemonitoring and self-management in the control of hypertension (TASMINH2): a randomised controlled trial. Lancet 2010 Jul 17;376(9736):163-172. [CrossRef] [Medline]
  70. Bray EP, Jones MI, Banting M, Greenfield S, Hobbs FD, Little P, et al. Performance and persistence of a blood pressure self-management intervention: telemonitoring and self-management in hypertension (TASMINH2) trial. J Hum Hypertens 2015 Jul;29(7):436-441. [CrossRef] [Medline]
  71. McManus RJ, Bray EP, Mant J, Holder R, Greenfield S, Bryan S, et al. Protocol for a randomised controlled trial of telemonitoring and self-management in the control of hypertension: telemonitoring and self-management in hypertension. [ISRCTN17585681]. BMC Cardiovasc Disord 2009 Feb 16;9:6 [FREE Full text] [CrossRef] [Medline]
  72. Kaambwa B, Bryan S, Jowett S, Mant J, Bray EP, Hobbs FD, et al. Telemonitoring and self-management in the control of hypertension (TASMINH2): a cost-effectiveness analysis. Eur J Prev Cardiol 2014 Dec;21(12):1517-1530. [CrossRef] [Medline]
  73. Jones MI, Greenfield SM, Bray EP, Hobbs FR, Holder R, Little P, et al. Patient self-monitoring of blood pressure and self-titration of medication in primary care: the TASMINH2 trial qualitative study of health professionals' experiences. Br J Gen Pract 2013 Jun;63(611):e378-e385 [FREE Full text] [CrossRef] [Medline]
  74. McManus RJ, Mant J, Haque MS, Bray EP, Bryan S, Greenfield SM, et al. Effect of self-monitoring and medication self-titration on systolic blood pressure in hypertensive patients at high risk of cardiovascular disease: the TASMIN-SR randomized clinical trial. JAMA 2014 Aug 27;312(8):799-808. [CrossRef] [Medline]
  75. Rifkin DE, Abdelmalek JA, Miracle CM, Low C, Barsotti R, Rios P, et al. Linking clinic and home: a randomized, controlled clinical effectiveness trial of real-time, wireless blood pressure monitoring for older patients with kidney disease and hypertension. Blood Press Monit 2013 Feb;18(1):8-15 [FREE Full text] [CrossRef] [Medline]
  76. Kao CW, Chen TY, Cheng SM, Lin WS, Chang YC. A Web-based self-titration program to control blood pressure in patients with primary hypertension: randomized controlled trial. J Med Internet Res 2019 Dec 05;21(12):e15836 [FREE Full text] [CrossRef] [Medline]
  77. Zarnke KB, Feagan BG, Mahon JL, Feldman RD. A randomized study comparing a patient-directed hypertension management strategy with usual office-based care. Am J Hypertens 1997 Jan;10(1):58-67. [CrossRef] [Medline]
  78. Istepanian RS, Zitouni K, Harry D, Moutosammy N, Sungoor A, Tang B, et al. Evaluation of a mobile phone telemonitoring system for glycaemic control in patients with diabetes. J Telemed Telecare 2009;15(3):125-128. [CrossRef] [Medline]
  79. Halme L, Vesalainen R, Kaaja M, Kantola I, HOme MEasuRement of blood pressure study group. Self-monitoring of blood pressure promotes achievement of blood pressure target in primary health care. Am J Hypertens 2005 Nov;18(11):1415-1420. [CrossRef] [Medline]
  80. Kim YN, Shin DG, Park S, Lee CH. Randomized clinical trial to assess the effectiveness of remote patient monitoring and physician care in reducing office blood pressure. Hypertens Res 2015 Jul;38(7):491-497. [CrossRef] [Medline]
  81. Klarskov P, Bang LE, Schultz-Larsen P, Gregers Petersen H, Benee Olsen D, Berg RM, et al. Intensive versus conventional blood pressure monitoring in a general practice population. The Blood Pressure Reduction in Danish General Practice trial: a randomized controlled parallel group trial. Fam Pract 2018 Jul 23;35(4):433-439. [CrossRef] [Medline]
  82. Neumann CL, Menne J, Rieken EM, Fischer N, Weber MH, Haller H, et al. Blood pressure telemonitoring is useful to achieve blood pressure control in inadequately treated patients with arterial hypertension. J Hum Hypertens 2011 Dec;25(12):732-738. [CrossRef] [Medline]
  83. Neumann CL, Menne J, Schettler V, Hagenah GC, Brockes C, Haller H, et al. Long-term effects of 3-month telemetric blood pressure intervention in patients with inadequately treated arterial hypertension. Telemed J E Health 2015 Mar;21(3):145-150. [CrossRef] [Medline]
  84. Rogers MA, Small D, Buchan DA, Butch CA, Stewart CM, Krenzer BE, et al. Home monitoring service improves mean arterial pressure in patients with essential hypertension. A randomized, controlled trial. Ann Intern Med 2001 Jun 05;134(11):1024-1032. [CrossRef] [Medline]
  85. Sarfo F, Treiber F, Gebregziabher M, Adamu S, Patel S, Nichols M, et al. PINGS (Phone-based Intervention under Nurse Guidance after Stroke): interim results of a pilot randomized controlled trial. Stroke 2018 Jan;49(1):236-239 [FREE Full text] [CrossRef] [Medline]
  86. Stewart K, George J, Mc Namara KP, Jackson SL, Peterson GM, Bereznicki LR, et al. A multifaceted pharmacist intervention to improve antihypertensive adherence: a cluster-randomized, controlled trial (HAPPy trial). J Clin Pharm Ther 2014 Oct;39(5):527-534. [CrossRef] [Medline]
  87. Rodriguez S, Hwang K, Wang J. Connecting home-based self-monitoring of blood pressure data into electronic health records for hypertension care: a qualitative inquiry with primary care providers. JMIR Form Res 2019 May 23;3(2):e10388 [FREE Full text] [CrossRef] [Medline]
  88. Asayama K, Ohkubo T, Metoki H, Obara T, Inoue R, Kikuya M, Hypertension Objective Treatment Based on Measurement by Electrical Devices of Blood Pressure (HOMED-BP). Cardiovascular outcomes in the first trial of antihypertensive therapy guided by self-measured home blood pressure. Hypertens Res 2012 Nov;35(11):1102-1110. [CrossRef] [Medline]
  89. Burke LE, Ma J, Azar KM, Bennett GG, Peterson ED, Zheng Y, American Heart Association Publications Committee of the Council on Epidemiology and Prevention, Behavior Change Committee of the Council on Cardiometabolic Health, Council on Cardiovascular and Stroke Nursing, Council on Functional Genomics and Translational Biology, Council on Quality of Care and Outcomes Research, and Stroke Council. Current science on consumer use of mobile health for cardiovascular disease prevention: a scientific statement from the American Heart Association. Circulation 2015 Sep 22;132(12):1157-1213 [FREE Full text] [CrossRef] [Medline]
  90. Sheppard JP, Tucker KL, Davison WJ, Stevens R, Aekplakorn W, Bosworth HB, et al. Self-monitoring of blood pressure in patients with hypertension-related multi-morbidity: systematic review and individual patient data meta-analysis. Am J Hypertens 2020 Mar 13;33(3):243-251 [FREE Full text] [CrossRef] [Medline]
  91. Tucker KL, Sheppard JP, Stevens R, Bosworth HB, Bove A, Bray EP, et al. Self-monitoring of blood pressure in hypertension: a systematic review and individual patient data meta-analysis. PLoS Med 2017 Sep;14(9):e1002389 [FREE Full text] [CrossRef] [Medline]

AE: adverse event
AHRQ: Agency for Healthcare Research and Quality
BP: blood pressure
DBP: diastolic blood pressure
FDA: Food and Drug Administration
PGHD: patient-generated health data
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
QoL: quality of life
SBP: systolic blood pressure
SF-36: Short Form Health Survey 36

Edited by L Buis; submitted 30.08.21; peer-reviewed by B Green, M Santero, S Westberg; comments to author 20.12.21; revised version received 07.02.22; accepted 17.03.22; published 02.05.22


©Jonathan R Treadwell, Benjamin Rouse, James Reston, Joann Fontanarosa, Neha Patel, Nikhil K Mull. Originally published in JMIR mHealth and uHealth (, 02.05.2022.

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