Systematic Reviews
Copyright ©The Author(s) 2020.
World J Clin Cases. Jun 6, 2020; 8(11): 2266-2279
Published online Jun 6, 2020. doi: 10.12998/wjcc.v8.i11.2266
Table 1 Summary of included articles
Ref.Country/Study sizeProject titleStudy designAge (mean ± SD)Male (%)SBP (mean ± SD, mm Hg)
Ajay et al[23], 2016India, n = 6061mPower HeartMixed methodsNRNR146.1
Bloss et al[39], 2016United States, n = 160NRPre-post56 ± 9.050.0138.9
Bosworth et al[27], 2011United States, n = 591HINTSRCT64 ± 10.092.0129.0 ± 19.6
Crowley et al[42], 2016United States, n = 591HINTSRCT64 ± 10.092.0129.0 ± 19.6
Crowley et al[31], 2011United States, n = 591HINTSRCT64 ± 10.092.0129.0 ± 19.6
Frias et al[43], 2017United States, n = 118DMOCluster RCT5950.5149.3 ± 1.5
Guthrie et al[25], 2019United States, n = 172DTxsCohort5513.9138.9
Jung et al[24], 2017South Korea, n = 64eHSMQuasi-experimental81 ± 8.622.6133.9 ± 15.1
Jackson et al[44], 2012United States, n = 591HINTSRCT64 ± 10.092.0129.0 ± 19.6
Kim et al[45], 2016United States, n = 160NRPre-Post56 ± 9.050.0138.9
Lewinski et al[46], 2019United States, n = 18mHealthPre-post5738.1139.5 ± 19.8
Litke et al[28], 2018United States, n = 122CPSRetrospectiveNRNR159.0
Liu et al[40], 2018Canada, n = 128NRRCT57 ± 0.852.3140.0 ± 1.1
Maciejewski et al[47], 2014United States, n = 591HINTSRCT64 ± 10.092.0129.0 ± 19.6
McGillicuddy et al[22], 2015United States, n = 18SMASKRCT42 ± 12.055.6139.1 ± 4.4
Milani et al[48], 2016United States, n = 556OchsnerPre-post68 ± 10.046.0147.0 ± 5
Moorhead et al[49], 2017United States, n = 57DMORCT5950.5149.3 ± 1.5
Noble et al[29], 2016United Kingdom, n = 39DHFSPre-post61NR154.3 ± 18.9
Nolan et al[50], 2018Canada, n = 264REACHRCT5842.0141.5
Nordyke et al[26], 2019United States, n = 172DTxsCohort5513.9138.9
Patel et al[51], 2013United States, n = 50Pill PhoneRCT53 ± 8.731.0144.0
Rehman et al[52], 2019Pakistan, n = 120NRRCTNRNR149.3 ± 5.6
Saleh et al[53], 2018Lebanon, n = 3481NRCross-sectionalNR38.6≥ 140.0
Saleh et al[32], 2018Lebanon, n = 2359eSahhaRCTNR43.7133.7 ± 16.1
Saleh et al[54], 2018Lebanon, n = 2359eSahhaRCTNR43.7133.7 ± 16.1
Prabhakaran et al[41], 2019India, n = 3695mWellcareCluster RCT55 ± 11.055.2152.5 ± 14.7
Tobe et al[30], 2019Canada, n = 243DREAM‐GLOBALRCT49 ± 12.850.7143.0 ± 12.0
Williams et al[55], 2012Australia, n = 80MESMIRCT68.0 ± 8.356.4> 140.0, < 160.0
Table 2 Comparison of main elements between digital health interventions for hypertensive care
ProjectStudy base/areaInterventionFocus areaFollow up (mo)Drop off (%)
mPower Heart[23]Primary care; ruralMobile phoneClinical decision-support18NR
NR (Mobile) [39,45]Home; NRMobile phoneHealth care resource utilization; health self-management613.0
HINTS[27,31,42,44,47]Home; urbanTelemedicineImproving BP control1815.0
DMO[43,49]Clinic; urbanDigital medicineEffect of the DMO on BP; patient engagement; provider decision making311.0
DTxs[25,26]NRMobile phoneEffectiveness of Dtxs on reducing BP; using machine learning to predict intervention completion317.4
eHSM[24]Community; urbanTelehealthMonitoring self-management; control of blood pressure66.1
mHealth[46]Community; ruralTelehealth and SMSPatient-centred care and self-management616.3
CPS[28]Primary care; ruralTelehealthMedication management; healthcare access and quality in rural areas29NA
NR (Internet)[40]Home; urbanInternetExpert-driven e-counselling in motivating lifestyle change to control blood pressure411.0
SMASK[22]Primary careMobile phoneSelf-management to improve BP and medication adherence after kidney transplant120.0
Ochsner[48]HomeDigital medicineMedication management and lifestyle change3NR
DHFS[29]Pharmacy; urbanmHealth systemMedication management; self-management to improve BP20.0
REACH[50]UrbanInternete-counselling and motivation in self-care1217.0
Pill Phone[51]UrbanMobile phoneMedication reminder64.0
NR (SMS)[52]Hospital;NRSMSEnhancement of adherence to non-pharmacological treatment; self-management3NR
eSahha[32,53,54]Primary care; ruralSMSEffect of eHealth tools on accessibility to health services; detection and referrals rates in rural settings12NR
mWellcare[41]Primary care; ruralmHealth systemManagement of the chronic conditions; long-term monitoring and follow-up1210.1
DREAM‐GLOBAL[30]Primary care; ruralSMSHealth services delivery, mobile health technologies and patient engagement214.1
MESMI[55]Primary care; urbanMultifactorial interventionSelf-monitoring and medicine review76.3
Table 3 Comparison of findings between digital health interventions
DHIKey findings (impact of DHI)
Perception about devise useClinical assessment and carePractice and self-management
mPower Heart[23]73% of physician agreed with the mDSS suggestionSBP of the intervention group was reduced by 14.6 mmHg from the baseline. Detected newly hypertension 3152 cases (52%)Empowered nurse for management of hypertension, promoted evidence-based practices and overcoming the clinical inertia
NR (Mobile)[39,45]The application was used 10305 times and encouraged participants to change health behavioursReduction in BP for the intervention group was 2.7 mmHg from the baseline but was not significance. No significant differences in health care resource utilizationSignificant differences in health self- management and health behaviour change but no difference in medication adherence between groups
HINTS[27,31,42,44,47]Most of the participants reported that the HINTS was usefulSBP of the intervention group was reduced by 6.5 mmHg from the baseline. Significant reduction in SBP for combined intervention group at 12 mo but not significant difference at 18 moPatients receiving medication management achieved a clinically significant reduction in SBP relative to those not receiving medication management
DMO[43,49]Participants with lower adherence benefited more from seeing the reminder messagesSBP of the intervention group was reduced significantly by 9.0 mmHg from the baseline. The intervention group had a greater proportion of meeting goal compared with usual care groupMedication dose reminders were associated with the improving medication adherence, especially in lower adherence group. Mean medication adherence was 86% and mean on-time adherence was 69.7%
Perception of DHIClinical assessment and carePractice and self-management
DTxs[25,26]Cost effectiveness at total 3-year programSignificant reduction of SBP was 11.5 mmHg and 17.6 mmHg for stage 2 hypertensive participantsSubstantial cost savings by reducing the use of conventional medications
eHSM[24]NRSBP of the intervention group was reduced by 11.4 mmHg from the baseline which was greater than the control groupThe intervention group showed significantly greater improvement in self-efficacy and self-care behaviour than the control group at 24 wk post-intervention
mHealth[46]NRParticipants who completed 4 or more phone calls did not had a statistically significant decrease in SBP compared to those who completed fewer calls
CPS[28]NRA mean SBP reduction was 26.00 mm Hg84% of hypertensive participants were discharged after achieving their goal and tobacco cessation was achieved in 42% of targeted patients
NR (Internet)[40]NRSBP of the intervention group was reduced by 7.5 mmHg from the baseline but was not significantThe expert-driven group was more effective than the control group
SMASK[22]NRSBP of the intervention group was reduced by 9.6 mmHg from the baselineEstablishing and sustaining control of SBP was greater in the intervention group than the control group (11%)
Perception of DHIClinical assessment and carePractice and self-management
Ochsner[48]NRReduction in BP for the intervention group was 14.0 mmHg from the baseline and 71% of intervention group met target blood pressure controlMean patient activation was increased by 2.2%. The proportion of patients with low patient activation decreased by 9% and excess sodium consumption was decreased by 24% in the intervention group
DHFS[29]Participants had positive experience and found the DHFS was helpfulSBP of the intervention group was reduced by 7.9 mmHg from the baselineParticipated pharmacists found the program helped in targeting specific recommendations and creating a collaborative experience with their patients
REACH[50]NRSBP of the intervention group was reduced by 10.1 mmHg from the baselineNR
Pill Phone[51]Majority of participants (96%) reported a high level of satisfactionSBP of the intervention group was reduced significantly by 9.0 mmHg from the baseline92% of participants were engaged in the pre- and post-Morisky medication adherence intervention
NR (SMS)[52]The intervention group had a positive response toward the SMS serviceSBP of the intervention group was reduced by 8.0 mmHg from the baselineThe regular reminders were found very useful in enhancing medication adherence, and educational SMS improved adherence to use of medicines on time
Perception of DHIClinical assessment and carePractice and self-management
eSahha[32,54]94% of participants perceived the SMSs as useful and easy to read and understandSBP of the intervention group was reduced significantly by 1.9 mmHg from the baseline. The refugee camps group had a significantly higher response rate than those in rural areas group76.9% of participants using SMS through behavioural modifications to improve medication adherence. The appointment showup was associated with knowledge of referral reasons and the employment status
mWellcare[41]68% of doctors accepted decision support recommendation for hypertensionSBP of the intervention group was reduced by 15.9 mmHg from the baseline but was not significantThe intervention group reported significantly greater adherence to medication more than the control group, but no significant difference in changes for tobacco and alcohol use
DREAM‐GLOBAL[30]NRSBP of the intervention group was reduced by 5.3 mmHg from the baseline but was not significant. The success in BP control was 37.5% in active group and 32.8% in the passive groupWithin the first 2 mo of follow-up, 9 of the participants were able to consistently control the blood pressure
MESMI[55]All participants reported satisfaction with the interventionSBP of the intervention group was reduced by 6.9 mmHg from the baseline but was not significantNo difference in medication adherence between groups. Participants enjoyed being more actively engaged in their self-management
Table 4 Challenges in implementing digital health intervention for hypertensive patients
Challenges
Limited resources[23]
Technological issues[39]
Collaboration between stakeholders[39]
Discrepancy between BP values obtained from different setting[48] i.e., research setting, home and clinic and socioeconomic status, i.e., income status, education, socioeconomic, access to technology, tech-savvy and motivational biases
Self-limited rash at the wearable sensor site[43,49]
Imprecise message for reminder[51]
Interpatient variation in medication timeline and frequency[42]
Different email addresses, for example, participants who used Yahoo email were more likely to complete the intervention than users of other email domains[50]
Overlap in content of a DTx and conventional interventions[25,26]
Patients’ variable clinic visits and the lack of standardization of the blood pressure measurement[28]
Lack of expert-driven e-counselling protocol[40]
Sustainability of intervention, for example, SMASK patients returned the Bluetooth blood pressure devices and smartphones after the end of clinical trial[22]
Lack of clinical measurement[41]
SMSs sent were reached family members rather than the patients themselves[32,53,54]