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Study Overview
Objective. To evaluate whether a digital intervention comprising self-monitoring of blood pressure (BP) with reminders and predetermined drug changes combined with lifestyle change support resulted in lower systolic BP in people receiving treatment for hypertension that was poorly controlled, and whether this approach was cost effective.
Design. Unmasked randomized controlled trial.
Settings and participants. Eligible participants were identified from clinical codes recorded in the electronic health records of 76 collaborating general practices from the National Institute for Health Research Clinical Research Network, a United Kingdom government agency. The practices sent invitation letters to eligible participants to come to the clinic to establish eligibility, take consent, and collect baseline data via online questionnaires.
Eligible participants were aged 18 years or older with treated hypertension, a mean baseline BP reading of more than 140/90 mm Hg and were taking no more than 3 antihypertensive drugs. Participants also needed to be willing to self-monitor and have access to the internet (with support from a family member if needed). Exclusions included BP greater than 180/110 mm Hg, atrial fibrillation, hypertension not managed by their general practitioner, chronic kidney disease stage 4-5, postural hypotension (> 20 mm Hg systolic drop), an acute cardiovascular event in the previous 3 months, terminal disease, or another condition which in the opinion of their general practitioner made participation inappropriate.
Of the 11 399 invitation letters sent out, 1389 (12%) potential participants responded positively and were screened for eligibility. Those who declined to take part could optionally give their reasons, and responses were gained from 2426 of 10 010 (24%). The mean age of those who gave a reason for declining was 73 years. The most commonly selected reasons for declining were not having access to the internet (982, 41%), not wanting to participate in a research trial (617, 25%) or an internet study (543, 22%), and not wanting to change drugs (535, 22%). Of the 1389 screened, 734 were ineligible, and 33 did not complete baseline measures and randomization. The remaining 622 people who were randomized in a 1:1 ratio to receive the HOME BP intervention (n = 305) or usual care (n = 317).
Intervention vs usual care. The HOME BP intervention for the self-management of high BP consisted of an integrated patient and health care practitioner online digital intervention, BP self-monitoring (using an Omron M3 monitor), health care practitioner directed and supervised titration of antihypertensive drugs, and user-selected lifestyle modifications. Participants were advised via automated email reminders to take 2 morning BP readings for 7 days each month and to enter online each second reading. Mean home BP was calculated, accompanied by feedback of BP results to both patients and professionals with optional evidence-based lifestyle advice (for healthy eating, physical activity, losing weight if appropriate, and salt and alcohol reduction) and motivational support through practice nurses or health care assistances (using the CARE approach – congratulate, ask, reassure, encourage).
Participants allocated to usual care were not provided with self-monitoring equipment or the HOME BP intervention but had online access to the information provided in a patient leaflet for hypertension. This information comprised definitions of hypertension, causes, and brief guidance on treatment, including lifestyle changes and drugs. These participants received routine hypertension care that typically consisted of clinic BP monitoring to titrate drugs, with appointments and drug changes made at the discretion of the general practitioner. Participants were not prevented from self-monitoring, but data on self-monitoring practices were collected at the end of the trial from patients and practitioners.
Measures and analysis. The primary outcome measure was the difference in systolic BP at 12-month follow-up between the intervention and usual care groups (adjusting for baseline BP, practice, BP target levels, and sex). Secondary outcomes included systolic and diastolic BP at 6 and 12 months, weight, modified patient enablement instrument, drug adherence, health-related quality of life, and side effects from the symptoms section of an adjusted illness perceptions questionnaire. At trial, registration participants and general practitioners were asked about their use of self-monitoring in the usual care group.
The primary analysis used general linear modelling to compare systolic BP in the intervention and usual care groups at follow-up, adjusting for baseline BP, practice (as a random effect to take into account clustering), BP target levels, and sex. Analyses were on an intention-to-treat basis and used multiple imputation for missing data. Sensitivity analyses used complete cases and a repeated measures technique. Secondary analyses used similar techniques to assess differences between groups. A within-trial economic analysis estimated cost per unit reduction in systolic BP by using similar adjustments and multiple imputation for missing values. Repeated bootstrapping was used to estimate the probability of the intervention being cost-effective at different levels of willingness to pay per unit reduction in BP.
Main results. The intervention and usual care groups did not differ significantly – participants had a mean age of 66 years and mean baseline clinical BP of 151.6/85.3 mm Hg and 151.7/86.4 mm Hg (usual care and intervention, respectively). Most participants were White British (94%), just more than half were men, and the time since diagnosis averaged around 11 years. The most deprived group (based on the English Index of Multiple Deprivation) accounted for 63/622 (10%), with the least deprived group accounting for 326/622 (52%).
After 1 year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean BP dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic BP of −3.4 mm Hg (95% CI −6.1 to −0.8 mm Hg) and a mean difference in diastolic BP of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Exploratory subgroup analyses suggested that participants aged 67 years or older had a smaller effect size than those younger than 67. Similarly, while the effect sizes in the standard and diabetes target groups were similar, those older than 80 years with a higher target of 145/85 mm Hg showed little evidence of benefit. Results for other subgroups, including sex, baseline BP, deprivation, and history of self-monitoring, were similar between groups.
Engagement with the digital intervention was high, with 281/305 (92%) participants completing the 2 core training sessions, 268/305 (88%) completing a week of practice BP readings, and 243/305 (80%) completing at least 3 weeks of BP entries. Furthermore, 214/305 (70%) were still monitoring in the last 3 months of participation. However, less than 1/3 of participants chose to register on 1 of the optional lifestyle change modules. In the usual care group, a post-hoc analysis after 12 months showed that 112/234 (47%) patients reported monitoring their own BP at home at least once per month during the trial.
The difference in mean cost per patient was £38 (US $51.30, €41.9; 95% CI £27 to £47), which along with the decrease in systolic BP, gave an incremental cost per mm Hg BP reduction of £11 (£6 to £29). Bootstrapping analysis showed the intervention had high (90%) probability of being cost-effective at willingness to pay above £20 per unit reduction. The probabilities of being cost-effective for the intervention against usual care were 87%, 93%, and 97% at thresholds of £20, £30, and £50, respectively.
Conclusion. The HOME BP digital intervention for the management of hypertension by using self-monitored BP led to better control of systolic BP after 1 year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded.
Commentary
Elevated BP, also known as hypertension, is the most important, modifiable risk factor for cardiovascular disease and mortality.1 Clinically significant effects and improvements in mortality can be achieved with relatively small reductions in BP levels. Long-established lifestyle modifications that effectively lower BP include weight loss, reduced sodium intake, increased physical activity, and limited alcohol intake. However, motivating patients to achieve lifestyle modifications is among the most difficult aspects of managing hypertension. Importantly, for individuals taking antihypertensive medication, lifestyle modification is recommended as adjunctive therapy to reduce BP. Given that target blood pressure levels are reached for less than half of adults, novel interventions are needed to improve BP control – in particular, individualized cognitive behavioral interventions are more likely to be effective than standardized, single-component interventions.
Guided self-management for hypertension as part of systematic, planned care offers the potential for improvements in adherence and in turn improved long-term patient outcomes.2 Self-management can encompass a wide range of behaviors in addition to medication titration and monitoring of symptoms, such as individuals’ ability to manage physical, psychosocial and lifestyle behaviors related to their condition.3 Digital interventions leveraging apps, software, and/or technologies in particular have the potential to support people in self-management, allow for remote monitoring, and enable personalized and adaptive strategies for chronic disease management.4-5 An example of a digital intervention in the context of guided self-management for hypertension can be a web-based program delivered by computer or phone that combines health information with decision support to help inform behavior change in patients and remote monitoring of patient status by health professionals. Well-designed digital interventions can effectively change patient health-related behaviors, improve patient knowledge and confidence for self-management of health, and lead to better health outcomes.6-7
This study adds to the literature as a large, randomized controlled trial evaluating the effectiveness of a digital intervention in the field of hypertension and with follow-up for a year. The authors highlight that relatively few studies have been performed that combine self-monitoring with a digitally delivered cointervention, and none has shown a major effect in an adequately powered trial over a year. Results from this study showed that HOME BP, a digital intervention enabling self-management of hypertension, including self-monitoring, titration based on self-monitored BP, lifestyle advice, and behavioral support for patients and health care professionals, resulted in a worthwhile reduction of systolic BP. In addition, this reduction was achieved at modest cost based on the within trial cost effectiveness analysis.
There are many important strengths of this study, especially related to the design and analysis strategy, and some limitations. This study was designed as a randomized controlled trial with a 1 year follow-up period, although participants were unmasked to the group they were randomized to, which may have impacted their behaviors while in the study. As the authors state, the study was not only adequately powered to detect a difference in blood pressure, but also over-recruitment ensured such an effect was not missed. Recruiting from a large number of general practices ensured generalizability in terms of health care professionals. Importantly, while study participants mostly identified as predominantly White and tended to be of higher socioeconomic status, this is representative of the aged population in England and Wales. Nevertheless, generalizability of findings from this study is still limited to the demographic characteristics of the study population. Other strengths included inclusion of intention-to-treat analysis, multiple imputation for missing data, sensitivity analysis, as well as economic analysis and cost effectiveness analysis.
Of note, results from the study are only attributable to the digital interventions used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital interventions for managing hypertension. Also, as the authors highlight, the relative importance of the different parts of the digital intervention were unable to be distinguished, although this type of analysis is important in multicomponent interventions to better understand the most effective mechanism impacting change in the primary outcome.
Applications for Clinical Practice
Results of this study demonstrated that among participants being treated with hypertension, those engaged with the HOME BP digital intervention (combining self-monitoring of blood pressure with guided self-management) had better control of systolic BP after 1 year compared to participants receiving usual care. While these findings have important implications in the management of hypertension in health care systems, its integration into clinical workflow, sustainability, long-term clinical effectiveness, and effectiveness among diverse populations is unclear. However, clinicians can still encourage and support the use of evidence-based digital tools for patient self-monitoring of BP and guided-management of lifestyle modifications to lower BP. Additionally, clinicians can proactively propose incorporating evidence-based digital interventions like HOME BP into routine clinical practice guidelines.
Financial disclosures: None.
1. Samadian F, Dalili N, Jamalian A. Lifestyle Modifications to Prevent and Control Hypertension. Iran J Kidney Dis. 2016;10(5):237-263.
2. McLean G, Band R, Saunderson K, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34(4):600-612. doi:10.1097/HJH.0000000000000859
3. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002 Nov 20;288(19):2469-2475. doi:10.1001/jama.288.19.2469
4. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Educ Couns. 2017;100(4):616-635. doi:10.1016/j.ped.2016.10.019
5. Kario K. Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring. Hypertension. 2020;76(3):640-650. doi:10.1161/HYPERTENSIONAHA.120.14742
6. Murray E, Burns J, See TS, et al. Interactive Health Communication Applications for people with chronic disease. Cochrane Database Syst Rev. 2005;(4):CD004274. doi:10.1002/14651858.CD004274.pub4
7. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res. 2010;12(1):e4. doi:10.2196/jmir.1376
Study Overview
Objective. To evaluate whether a digital intervention comprising self-monitoring of blood pressure (BP) with reminders and predetermined drug changes combined with lifestyle change support resulted in lower systolic BP in people receiving treatment for hypertension that was poorly controlled, and whether this approach was cost effective.
Design. Unmasked randomized controlled trial.
Settings and participants. Eligible participants were identified from clinical codes recorded in the electronic health records of 76 collaborating general practices from the National Institute for Health Research Clinical Research Network, a United Kingdom government agency. The practices sent invitation letters to eligible participants to come to the clinic to establish eligibility, take consent, and collect baseline data via online questionnaires.
Eligible participants were aged 18 years or older with treated hypertension, a mean baseline BP reading of more than 140/90 mm Hg and were taking no more than 3 antihypertensive drugs. Participants also needed to be willing to self-monitor and have access to the internet (with support from a family member if needed). Exclusions included BP greater than 180/110 mm Hg, atrial fibrillation, hypertension not managed by their general practitioner, chronic kidney disease stage 4-5, postural hypotension (> 20 mm Hg systolic drop), an acute cardiovascular event in the previous 3 months, terminal disease, or another condition which in the opinion of their general practitioner made participation inappropriate.
Of the 11 399 invitation letters sent out, 1389 (12%) potential participants responded positively and were screened for eligibility. Those who declined to take part could optionally give their reasons, and responses were gained from 2426 of 10 010 (24%). The mean age of those who gave a reason for declining was 73 years. The most commonly selected reasons for declining were not having access to the internet (982, 41%), not wanting to participate in a research trial (617, 25%) or an internet study (543, 22%), and not wanting to change drugs (535, 22%). Of the 1389 screened, 734 were ineligible, and 33 did not complete baseline measures and randomization. The remaining 622 people who were randomized in a 1:1 ratio to receive the HOME BP intervention (n = 305) or usual care (n = 317).
Intervention vs usual care. The HOME BP intervention for the self-management of high BP consisted of an integrated patient and health care practitioner online digital intervention, BP self-monitoring (using an Omron M3 monitor), health care practitioner directed and supervised titration of antihypertensive drugs, and user-selected lifestyle modifications. Participants were advised via automated email reminders to take 2 morning BP readings for 7 days each month and to enter online each second reading. Mean home BP was calculated, accompanied by feedback of BP results to both patients and professionals with optional evidence-based lifestyle advice (for healthy eating, physical activity, losing weight if appropriate, and salt and alcohol reduction) and motivational support through practice nurses or health care assistances (using the CARE approach – congratulate, ask, reassure, encourage).
Participants allocated to usual care were not provided with self-monitoring equipment or the HOME BP intervention but had online access to the information provided in a patient leaflet for hypertension. This information comprised definitions of hypertension, causes, and brief guidance on treatment, including lifestyle changes and drugs. These participants received routine hypertension care that typically consisted of clinic BP monitoring to titrate drugs, with appointments and drug changes made at the discretion of the general practitioner. Participants were not prevented from self-monitoring, but data on self-monitoring practices were collected at the end of the trial from patients and practitioners.
Measures and analysis. The primary outcome measure was the difference in systolic BP at 12-month follow-up between the intervention and usual care groups (adjusting for baseline BP, practice, BP target levels, and sex). Secondary outcomes included systolic and diastolic BP at 6 and 12 months, weight, modified patient enablement instrument, drug adherence, health-related quality of life, and side effects from the symptoms section of an adjusted illness perceptions questionnaire. At trial, registration participants and general practitioners were asked about their use of self-monitoring in the usual care group.
The primary analysis used general linear modelling to compare systolic BP in the intervention and usual care groups at follow-up, adjusting for baseline BP, practice (as a random effect to take into account clustering), BP target levels, and sex. Analyses were on an intention-to-treat basis and used multiple imputation for missing data. Sensitivity analyses used complete cases and a repeated measures technique. Secondary analyses used similar techniques to assess differences between groups. A within-trial economic analysis estimated cost per unit reduction in systolic BP by using similar adjustments and multiple imputation for missing values. Repeated bootstrapping was used to estimate the probability of the intervention being cost-effective at different levels of willingness to pay per unit reduction in BP.
Main results. The intervention and usual care groups did not differ significantly – participants had a mean age of 66 years and mean baseline clinical BP of 151.6/85.3 mm Hg and 151.7/86.4 mm Hg (usual care and intervention, respectively). Most participants were White British (94%), just more than half were men, and the time since diagnosis averaged around 11 years. The most deprived group (based on the English Index of Multiple Deprivation) accounted for 63/622 (10%), with the least deprived group accounting for 326/622 (52%).
After 1 year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean BP dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic BP of −3.4 mm Hg (95% CI −6.1 to −0.8 mm Hg) and a mean difference in diastolic BP of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Exploratory subgroup analyses suggested that participants aged 67 years or older had a smaller effect size than those younger than 67. Similarly, while the effect sizes in the standard and diabetes target groups were similar, those older than 80 years with a higher target of 145/85 mm Hg showed little evidence of benefit. Results for other subgroups, including sex, baseline BP, deprivation, and history of self-monitoring, were similar between groups.
Engagement with the digital intervention was high, with 281/305 (92%) participants completing the 2 core training sessions, 268/305 (88%) completing a week of practice BP readings, and 243/305 (80%) completing at least 3 weeks of BP entries. Furthermore, 214/305 (70%) were still monitoring in the last 3 months of participation. However, less than 1/3 of participants chose to register on 1 of the optional lifestyle change modules. In the usual care group, a post-hoc analysis after 12 months showed that 112/234 (47%) patients reported monitoring their own BP at home at least once per month during the trial.
The difference in mean cost per patient was £38 (US $51.30, €41.9; 95% CI £27 to £47), which along with the decrease in systolic BP, gave an incremental cost per mm Hg BP reduction of £11 (£6 to £29). Bootstrapping analysis showed the intervention had high (90%) probability of being cost-effective at willingness to pay above £20 per unit reduction. The probabilities of being cost-effective for the intervention against usual care were 87%, 93%, and 97% at thresholds of £20, £30, and £50, respectively.
Conclusion. The HOME BP digital intervention for the management of hypertension by using self-monitored BP led to better control of systolic BP after 1 year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded.
Commentary
Elevated BP, also known as hypertension, is the most important, modifiable risk factor for cardiovascular disease and mortality.1 Clinically significant effects and improvements in mortality can be achieved with relatively small reductions in BP levels. Long-established lifestyle modifications that effectively lower BP include weight loss, reduced sodium intake, increased physical activity, and limited alcohol intake. However, motivating patients to achieve lifestyle modifications is among the most difficult aspects of managing hypertension. Importantly, for individuals taking antihypertensive medication, lifestyle modification is recommended as adjunctive therapy to reduce BP. Given that target blood pressure levels are reached for less than half of adults, novel interventions are needed to improve BP control – in particular, individualized cognitive behavioral interventions are more likely to be effective than standardized, single-component interventions.
Guided self-management for hypertension as part of systematic, planned care offers the potential for improvements in adherence and in turn improved long-term patient outcomes.2 Self-management can encompass a wide range of behaviors in addition to medication titration and monitoring of symptoms, such as individuals’ ability to manage physical, psychosocial and lifestyle behaviors related to their condition.3 Digital interventions leveraging apps, software, and/or technologies in particular have the potential to support people in self-management, allow for remote monitoring, and enable personalized and adaptive strategies for chronic disease management.4-5 An example of a digital intervention in the context of guided self-management for hypertension can be a web-based program delivered by computer or phone that combines health information with decision support to help inform behavior change in patients and remote monitoring of patient status by health professionals. Well-designed digital interventions can effectively change patient health-related behaviors, improve patient knowledge and confidence for self-management of health, and lead to better health outcomes.6-7
This study adds to the literature as a large, randomized controlled trial evaluating the effectiveness of a digital intervention in the field of hypertension and with follow-up for a year. The authors highlight that relatively few studies have been performed that combine self-monitoring with a digitally delivered cointervention, and none has shown a major effect in an adequately powered trial over a year. Results from this study showed that HOME BP, a digital intervention enabling self-management of hypertension, including self-monitoring, titration based on self-monitored BP, lifestyle advice, and behavioral support for patients and health care professionals, resulted in a worthwhile reduction of systolic BP. In addition, this reduction was achieved at modest cost based on the within trial cost effectiveness analysis.
There are many important strengths of this study, especially related to the design and analysis strategy, and some limitations. This study was designed as a randomized controlled trial with a 1 year follow-up period, although participants were unmasked to the group they were randomized to, which may have impacted their behaviors while in the study. As the authors state, the study was not only adequately powered to detect a difference in blood pressure, but also over-recruitment ensured such an effect was not missed. Recruiting from a large number of general practices ensured generalizability in terms of health care professionals. Importantly, while study participants mostly identified as predominantly White and tended to be of higher socioeconomic status, this is representative of the aged population in England and Wales. Nevertheless, generalizability of findings from this study is still limited to the demographic characteristics of the study population. Other strengths included inclusion of intention-to-treat analysis, multiple imputation for missing data, sensitivity analysis, as well as economic analysis and cost effectiveness analysis.
Of note, results from the study are only attributable to the digital interventions used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital interventions for managing hypertension. Also, as the authors highlight, the relative importance of the different parts of the digital intervention were unable to be distinguished, although this type of analysis is important in multicomponent interventions to better understand the most effective mechanism impacting change in the primary outcome.
Applications for Clinical Practice
Results of this study demonstrated that among participants being treated with hypertension, those engaged with the HOME BP digital intervention (combining self-monitoring of blood pressure with guided self-management) had better control of systolic BP after 1 year compared to participants receiving usual care. While these findings have important implications in the management of hypertension in health care systems, its integration into clinical workflow, sustainability, long-term clinical effectiveness, and effectiveness among diverse populations is unclear. However, clinicians can still encourage and support the use of evidence-based digital tools for patient self-monitoring of BP and guided-management of lifestyle modifications to lower BP. Additionally, clinicians can proactively propose incorporating evidence-based digital interventions like HOME BP into routine clinical practice guidelines.
Financial disclosures: None.
Study Overview
Objective. To evaluate whether a digital intervention comprising self-monitoring of blood pressure (BP) with reminders and predetermined drug changes combined with lifestyle change support resulted in lower systolic BP in people receiving treatment for hypertension that was poorly controlled, and whether this approach was cost effective.
Design. Unmasked randomized controlled trial.
Settings and participants. Eligible participants were identified from clinical codes recorded in the electronic health records of 76 collaborating general practices from the National Institute for Health Research Clinical Research Network, a United Kingdom government agency. The practices sent invitation letters to eligible participants to come to the clinic to establish eligibility, take consent, and collect baseline data via online questionnaires.
Eligible participants were aged 18 years or older with treated hypertension, a mean baseline BP reading of more than 140/90 mm Hg and were taking no more than 3 antihypertensive drugs. Participants also needed to be willing to self-monitor and have access to the internet (with support from a family member if needed). Exclusions included BP greater than 180/110 mm Hg, atrial fibrillation, hypertension not managed by their general practitioner, chronic kidney disease stage 4-5, postural hypotension (> 20 mm Hg systolic drop), an acute cardiovascular event in the previous 3 months, terminal disease, or another condition which in the opinion of their general practitioner made participation inappropriate.
Of the 11 399 invitation letters sent out, 1389 (12%) potential participants responded positively and were screened for eligibility. Those who declined to take part could optionally give their reasons, and responses were gained from 2426 of 10 010 (24%). The mean age of those who gave a reason for declining was 73 years. The most commonly selected reasons for declining were not having access to the internet (982, 41%), not wanting to participate in a research trial (617, 25%) or an internet study (543, 22%), and not wanting to change drugs (535, 22%). Of the 1389 screened, 734 were ineligible, and 33 did not complete baseline measures and randomization. The remaining 622 people who were randomized in a 1:1 ratio to receive the HOME BP intervention (n = 305) or usual care (n = 317).
Intervention vs usual care. The HOME BP intervention for the self-management of high BP consisted of an integrated patient and health care practitioner online digital intervention, BP self-monitoring (using an Omron M3 monitor), health care practitioner directed and supervised titration of antihypertensive drugs, and user-selected lifestyle modifications. Participants were advised via automated email reminders to take 2 morning BP readings for 7 days each month and to enter online each second reading. Mean home BP was calculated, accompanied by feedback of BP results to both patients and professionals with optional evidence-based lifestyle advice (for healthy eating, physical activity, losing weight if appropriate, and salt and alcohol reduction) and motivational support through practice nurses or health care assistances (using the CARE approach – congratulate, ask, reassure, encourage).
Participants allocated to usual care were not provided with self-monitoring equipment or the HOME BP intervention but had online access to the information provided in a patient leaflet for hypertension. This information comprised definitions of hypertension, causes, and brief guidance on treatment, including lifestyle changes and drugs. These participants received routine hypertension care that typically consisted of clinic BP monitoring to titrate drugs, with appointments and drug changes made at the discretion of the general practitioner. Participants were not prevented from self-monitoring, but data on self-monitoring practices were collected at the end of the trial from patients and practitioners.
Measures and analysis. The primary outcome measure was the difference in systolic BP at 12-month follow-up between the intervention and usual care groups (adjusting for baseline BP, practice, BP target levels, and sex). Secondary outcomes included systolic and diastolic BP at 6 and 12 months, weight, modified patient enablement instrument, drug adherence, health-related quality of life, and side effects from the symptoms section of an adjusted illness perceptions questionnaire. At trial, registration participants and general practitioners were asked about their use of self-monitoring in the usual care group.
The primary analysis used general linear modelling to compare systolic BP in the intervention and usual care groups at follow-up, adjusting for baseline BP, practice (as a random effect to take into account clustering), BP target levels, and sex. Analyses were on an intention-to-treat basis and used multiple imputation for missing data. Sensitivity analyses used complete cases and a repeated measures technique. Secondary analyses used similar techniques to assess differences between groups. A within-trial economic analysis estimated cost per unit reduction in systolic BP by using similar adjustments and multiple imputation for missing values. Repeated bootstrapping was used to estimate the probability of the intervention being cost-effective at different levels of willingness to pay per unit reduction in BP.
Main results. The intervention and usual care groups did not differ significantly – participants had a mean age of 66 years and mean baseline clinical BP of 151.6/85.3 mm Hg and 151.7/86.4 mm Hg (usual care and intervention, respectively). Most participants were White British (94%), just more than half were men, and the time since diagnosis averaged around 11 years. The most deprived group (based on the English Index of Multiple Deprivation) accounted for 63/622 (10%), with the least deprived group accounting for 326/622 (52%).
After 1 year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean BP dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic BP of −3.4 mm Hg (95% CI −6.1 to −0.8 mm Hg) and a mean difference in diastolic BP of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Exploratory subgroup analyses suggested that participants aged 67 years or older had a smaller effect size than those younger than 67. Similarly, while the effect sizes in the standard and diabetes target groups were similar, those older than 80 years with a higher target of 145/85 mm Hg showed little evidence of benefit. Results for other subgroups, including sex, baseline BP, deprivation, and history of self-monitoring, were similar between groups.
Engagement with the digital intervention was high, with 281/305 (92%) participants completing the 2 core training sessions, 268/305 (88%) completing a week of practice BP readings, and 243/305 (80%) completing at least 3 weeks of BP entries. Furthermore, 214/305 (70%) were still monitoring in the last 3 months of participation. However, less than 1/3 of participants chose to register on 1 of the optional lifestyle change modules. In the usual care group, a post-hoc analysis after 12 months showed that 112/234 (47%) patients reported monitoring their own BP at home at least once per month during the trial.
The difference in mean cost per patient was £38 (US $51.30, €41.9; 95% CI £27 to £47), which along with the decrease in systolic BP, gave an incremental cost per mm Hg BP reduction of £11 (£6 to £29). Bootstrapping analysis showed the intervention had high (90%) probability of being cost-effective at willingness to pay above £20 per unit reduction. The probabilities of being cost-effective for the intervention against usual care were 87%, 93%, and 97% at thresholds of £20, £30, and £50, respectively.
Conclusion. The HOME BP digital intervention for the management of hypertension by using self-monitored BP led to better control of systolic BP after 1 year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded.
Commentary
Elevated BP, also known as hypertension, is the most important, modifiable risk factor for cardiovascular disease and mortality.1 Clinically significant effects and improvements in mortality can be achieved with relatively small reductions in BP levels. Long-established lifestyle modifications that effectively lower BP include weight loss, reduced sodium intake, increased physical activity, and limited alcohol intake. However, motivating patients to achieve lifestyle modifications is among the most difficult aspects of managing hypertension. Importantly, for individuals taking antihypertensive medication, lifestyle modification is recommended as adjunctive therapy to reduce BP. Given that target blood pressure levels are reached for less than half of adults, novel interventions are needed to improve BP control – in particular, individualized cognitive behavioral interventions are more likely to be effective than standardized, single-component interventions.
Guided self-management for hypertension as part of systematic, planned care offers the potential for improvements in adherence and in turn improved long-term patient outcomes.2 Self-management can encompass a wide range of behaviors in addition to medication titration and monitoring of symptoms, such as individuals’ ability to manage physical, psychosocial and lifestyle behaviors related to their condition.3 Digital interventions leveraging apps, software, and/or technologies in particular have the potential to support people in self-management, allow for remote monitoring, and enable personalized and adaptive strategies for chronic disease management.4-5 An example of a digital intervention in the context of guided self-management for hypertension can be a web-based program delivered by computer or phone that combines health information with decision support to help inform behavior change in patients and remote monitoring of patient status by health professionals. Well-designed digital interventions can effectively change patient health-related behaviors, improve patient knowledge and confidence for self-management of health, and lead to better health outcomes.6-7
This study adds to the literature as a large, randomized controlled trial evaluating the effectiveness of a digital intervention in the field of hypertension and with follow-up for a year. The authors highlight that relatively few studies have been performed that combine self-monitoring with a digitally delivered cointervention, and none has shown a major effect in an adequately powered trial over a year. Results from this study showed that HOME BP, a digital intervention enabling self-management of hypertension, including self-monitoring, titration based on self-monitored BP, lifestyle advice, and behavioral support for patients and health care professionals, resulted in a worthwhile reduction of systolic BP. In addition, this reduction was achieved at modest cost based on the within trial cost effectiveness analysis.
There are many important strengths of this study, especially related to the design and analysis strategy, and some limitations. This study was designed as a randomized controlled trial with a 1 year follow-up period, although participants were unmasked to the group they were randomized to, which may have impacted their behaviors while in the study. As the authors state, the study was not only adequately powered to detect a difference in blood pressure, but also over-recruitment ensured such an effect was not missed. Recruiting from a large number of general practices ensured generalizability in terms of health care professionals. Importantly, while study participants mostly identified as predominantly White and tended to be of higher socioeconomic status, this is representative of the aged population in England and Wales. Nevertheless, generalizability of findings from this study is still limited to the demographic characteristics of the study population. Other strengths included inclusion of intention-to-treat analysis, multiple imputation for missing data, sensitivity analysis, as well as economic analysis and cost effectiveness analysis.
Of note, results from the study are only attributable to the digital interventions used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital interventions for managing hypertension. Also, as the authors highlight, the relative importance of the different parts of the digital intervention were unable to be distinguished, although this type of analysis is important in multicomponent interventions to better understand the most effective mechanism impacting change in the primary outcome.
Applications for Clinical Practice
Results of this study demonstrated that among participants being treated with hypertension, those engaged with the HOME BP digital intervention (combining self-monitoring of blood pressure with guided self-management) had better control of systolic BP after 1 year compared to participants receiving usual care. While these findings have important implications in the management of hypertension in health care systems, its integration into clinical workflow, sustainability, long-term clinical effectiveness, and effectiveness among diverse populations is unclear. However, clinicians can still encourage and support the use of evidence-based digital tools for patient self-monitoring of BP and guided-management of lifestyle modifications to lower BP. Additionally, clinicians can proactively propose incorporating evidence-based digital interventions like HOME BP into routine clinical practice guidelines.
Financial disclosures: None.
1. Samadian F, Dalili N, Jamalian A. Lifestyle Modifications to Prevent and Control Hypertension. Iran J Kidney Dis. 2016;10(5):237-263.
2. McLean G, Band R, Saunderson K, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34(4):600-612. doi:10.1097/HJH.0000000000000859
3. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002 Nov 20;288(19):2469-2475. doi:10.1001/jama.288.19.2469
4. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Educ Couns. 2017;100(4):616-635. doi:10.1016/j.ped.2016.10.019
5. Kario K. Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring. Hypertension. 2020;76(3):640-650. doi:10.1161/HYPERTENSIONAHA.120.14742
6. Murray E, Burns J, See TS, et al. Interactive Health Communication Applications for people with chronic disease. Cochrane Database Syst Rev. 2005;(4):CD004274. doi:10.1002/14651858.CD004274.pub4
7. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res. 2010;12(1):e4. doi:10.2196/jmir.1376
1. Samadian F, Dalili N, Jamalian A. Lifestyle Modifications to Prevent and Control Hypertension. Iran J Kidney Dis. 2016;10(5):237-263.
2. McLean G, Band R, Saunderson K, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34(4):600-612. doi:10.1097/HJH.0000000000000859
3. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002 Nov 20;288(19):2469-2475. doi:10.1001/jama.288.19.2469
4. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Educ Couns. 2017;100(4):616-635. doi:10.1016/j.ped.2016.10.019
5. Kario K. Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring. Hypertension. 2020;76(3):640-650. doi:10.1161/HYPERTENSIONAHA.120.14742
6. Murray E, Burns J, See TS, et al. Interactive Health Communication Applications for people with chronic disease. Cochrane Database Syst Rev. 2005;(4):CD004274. doi:10.1002/14651858.CD004274.pub4
7. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res. 2010;12(1):e4. doi:10.2196/jmir.1376