Adults with congenital heart disease: ready for mobile health?

A comparison of ECG-based home monitoring devices in adults with CHD

BACKGROUND

Various electrocardiogram (ECG)-based devices are available for home monitoring, but the reliability in adults with CHD is unknown. Therefore, we determined the accuracy of different ECG-based devices compared to the standard 12-lead ECG in adult CHD.

METHODS AND RESULTS

This is a single-centre, prospective, cross-sectional study in 176 consecutive adults with CHD (54% male, age 40 ± 16.6 years, 24% severe CHD, 84% previous surgery, 3% atrial fibrillation (AF), 24% right bundle branch block). Diagnostic accuracy of the Withings Scanwatch (lead I), Eko DUO (precordial lead), and Kardia 6L (six leads) was determined in comparison to the standard 12-lead ECG on several tasks: 1) AF classification (percentage correct), 2) QRS-morphology classification (percentage correct), and 3) ECG intervals calculation (QTc time ≤ 40 ms difference). Both tested AF algorithms had high accuracy (Withings: 100%, Kardia 6L: 97%) in ECGs that were classified. However, the Withings algorithm classified fewer ECGs as inconclusive (5%) compared to 31% of Kardia (p < 0.001). Physician evaluation of Kardia correctly classified QRS morphology more frequently (90% accuracy) compared to Eko DUO (84% accuracy) (p = 0.03). QTc was underestimated on all ECG-based devices (p < 0.01). QTc duration accuracy was acceptable in only 51% of Withings versus 70% Eko and 74% Kardia (p < 0.001 for both comparisons).

CONCLUSIONS

Although all devices demonstrated high accuracy in AF detection, the Withings automatic algorithm had fewest uninterpretable results. Kardia 6L was most accurate in overall evaluation such as QRS morphology and QTc duration. These findings can inform both patients and caregivers for optimal choice of home monitoring.

Impact of mHealth Interventions on Supporting Dietary Adherence in Cardiovascular Disease: A Systematic Review

INTRODUCTION

A systematic review was conducted to determine if mobile health (mHealth) interventions, and which intervention characteristics, effectively support dietary adherence and reduce risk factors in patients with cardiovascular disease (CVD).

METHOD

Using 7 databases, studies involving adult participants with specific CVD diagnoses, mHealth intervention testing, and dietary adherence assessment were identified. Systematic reviews, qualitative studies, or studies testing interventions involving open dialogue between participants and health care providers or researchers were excluded. Two independent reviewers conducted screening and assessed the risk of bias.

RESULTS

Thirteen studies involved participants with prehypertension (n = 1), hypertension (n = 9), coronary artery disease (n = 2), and heart failure (n = 1). mHealth interventions in 8 studies improved dietary adherence, 4 showed mixed results, and 1 showed no improvements. Eight studies found interactive text and/or application-based mHealth intervention features effectively improved dietary adherence. One study had a low risk of bias, 2 had some concerns/moderate risk, and 10 had a high/critical or serious risk.

DISCUSSION

In most included studies, mHealth interventions positively impacted dietary adherence for patients with CVD.

IMPLICATIONS FOR RESEARCH AND PRACTICE

Clinicians may recommend mHealth interventions to support nutrition education and self-management for their patients with CVD.

The Box: Methods and Results of a Real World Experience of mHealth Implementation in Clinical Practice

Background

Mobile health (mHealth) is an emerging field of scientific interest worldwide. Potential benefits include increased patient engagement, improved clinical outcomes, and reduced health care costs. However, mHealth is often studied in projects or trials, and structural implantation in clinical practice is less common.

Objective

The purpose of this paper is to outline the design of the Box and its implementation and use in an outpatient clinic setting. The impact on logistical outcomes and patient and provider satisfaction is discussed.

Methods

In 2016, an mHealth care track including smartphone-compatible devices, named the Box, was implemented in the cardiology department of a tertiary medical center in the Netherlands. Patients with myocardial infarction, rhythm disorders, cardiac surgery, heart failure, and congenital heart disease received devices to measure daily weight, blood pressure, heart rate, temperature, and oxygen saturation. In addition, professional and patient user comments on the experience with the care track were obtained via structured interviews.

Results

From 2016 to April 2020, a total of 1140 patients were connected to the mHealth care track. On average, a Box cost €350 (US $375), not including extra staff costs. The median patient age was 60.8 (IQR 52.9-69.3) years, and 73.59% (839/1140) were male. A median of 260 (IQR 105-641) measurements was taken on a median of 189 (IQR 98-372) days. Patients praised the ease of use of the devices and felt more involved with their illness and care. Professionals reported more productive outpatient consultations as well as improved insight into health parameters such as blood pressure and weight. A feedback loop from the hospital to patient to focus on measurements was commented as an important improvement by both patients and professionals.

Conclusions

In this study, the design and implementation of an mHealth care track for outpatient follow-up of patients with various cardiovascular diseases is described. Data from these 4 years indicate that mHealth is feasible to incorporate in outpatient management and is generally well-accepted by patients and providers. Limitations include the need for manual measurement data checks and the risk of data overload. Moreover, the tertiary care setting in which the Box was introduced may limit the external validity of logistical and financial end points to other medical centers. More evidence is needed to show the effects of mHealth on clinical outcomes and on cost-effectiveness.

Potential of eHealth smart technology in optimization and monitoring of heart failure treatment in adults with systemic right ventricular failure

Aims

Patients with a systemic right ventricle (sRV) in the context of transposition of the great arteries (TGA) after atrial switch or congenitally corrected TGA are prone to heart failure and arrhythmias. This study evaluated feasibility, patient adherence, and satisfaction of a smart technology-based care pathway for heart failure treatment optimization in these patients.

Methods and results

Patients with symptomatic sRV failure eligible for initiation of sacubitril/valsartan were provided with four smartphone compatible devices (blood pressure monitor, weight scale, step counter, and rhythm monitor) and were managed according to a smart technology-based care pathway. Biweekly sacubitril/valsartan titration visits were replaced by electronical visits, patients were advised to continue measurements at least weekly after titration. Data of 24 consecutive sRV patients (median age 47 years, 50% female) who participated in the smart technology-based care pathway were analysed. Median home-hospital distance was 65 km (maximum 227 km). Most patients (20, 83.3%) submitted weekly measurements; 100% submitted prior to electronical visits. Titration conventionally occurs during a hospital visit. By implementing eHealth smart technology, 68 such trips to hospital were replaced by virtual visits facilitated by remote monitoring. An eHealth questionnaire was completed by 22 patients (92%), and 96% expressed satisfaction. After titration, 30 instances of remote adjustment of heart failure medication in addition to scheduled outpatient clinic visits occurred, one (4%) heart failure admission followed, despite ambulant adjustments. Five patients (21%) sent in rhythm registrations (n = 17), of these 77% showed sinus rhythm, whereas supraventricular tachycardia was detected in the remaining four registrations.

Conclusion

These data suggest that implementation of a smart technology-based care pathway for optimization of medical treatment sRV failure is feasible with high measurement adherence and patient satisfaction.

The Mobile Health Readiness of People Receiving In-Center Hemodialysis and Home Dialysis

BACKGROUND AND OBJECTIVES

Mobile health is the health care use of mobile devices, such as smartphones. Mobile health readiness is a prerequisite to successful implementation of mobile health programs. The aim of this study was to examine the status and correlates of mobile health readiness among individuals on dialysis.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A cross-sectional 30-item questionnaire guided by the Khatun mobile health readiness conceptual model was distributed to individuals on dialysis from 21 in-center hemodialysis facilities and 14 home dialysis centers. The survey assessed the availability of devices and the internet, proficiency, and interest in using mobile health.

RESULTS

In total, 949 patients (632 hemodialysis and 317 home dialysis) completed the survey. Of those, 81% owned smartphones or other internet-capable devices, and 72% reported using the internet. The majority (70%) reported intermediate or advanced mobile health proficiency. The main reasons for using mobile health were appointments (56%), communication with health care personnel (56%), and laboratory results (55%). The main reported concerns with mobile health were privacy and security (18%). Mobile health proficiency was lower in older patients: compared with the 45- to 60-years group, respondents in age groups <45, 61-70, and >70 years had adjusted odds ratios of 5.04 (95% confidence interval, 2.23 to 11.38), 0.39 (95% confidence interval, 0.24 to 0.62), and 0.22 (95% confidence interval, 0.14 to 0.35), respectively. Proficiency was lower in participants with Hispanic/Latinx ethnicity (adjusted odds ratio, 0.49; 95% confidence interval, 0.31 to 0.75) and with less than college education (adjusted odds ratio for "below high school," 0.09; 95% confidence interval, 0.05 to 0.16 and adjusted odds ratio for "high school only," 0.26; 95% confidence interval, 0.18 to 0.39). Employment was associated with higher proficiency (adjusted odds ratio, 2.26; 95% confidence interval, 1.18 to 4.32). Although home dialysis was associated with higher proficiency in the unadjusted analyses, we did not observe this association after adjustment for other factors.

CONCLUSIONS

The majority of patients on dialysis surveyed were ready for, and proficient in, mobile health. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER DIALYSIS MHEALTH SURVEY,: NCT04177277.

Advantages of mobile health in the management of adult patients with congenital heart disease

BACKGROUND

Adults with congenital heart disease (ACHD) often suffer from deterioration related to cardiac arrhythmias, hypertension (HT) or heart failure (HF), frequently occurring between planned visits. Mobile health (mHealth) could improve management through remote monitoring by enabling swift therapeutic response and detecting new diagnoses.

METHODS

We performed a prospective study employing mHealth in ACHD patients, weekly monitoring heart rhythm, weight and blood pressure. In case of consecutive threshold exceeding measurements or in case of new diagnosis, patients were contacted and if needed the treating physician was consulted. Inclusion criteria were: palpitations within the last three years (with or without arrhythmia diagnosis) or HF NYHA class ≥ II. We evaluated the detection of recurrences and new diagnosis of arrhythmias, HT and HF, adherence and patient experience (Net Promotor Score (NPS)).

RESULTS

In total, 109 of the 268 invited ACHD patients were enrolled, 80 with palpitations, 13 with HF, 16 experienced both, mean age 45 (±13) years, 33% male. Median follow-up was 12 (Q1-Q3;9-14) months, 91 patients initiated all measurements (heart rhythm, weight and blood pressure). In 25% of the patients with diagnosed arrhythmias (14/56) recurrences of arrhythmias were detected; 13% of the patients with undiagnosed palpitations (4/32) were diagnosed with novel arrhythmias. In 38% of the patients with HT at baseline (6/16), treatment adjustment was necessary, 4% of the patients without HT (4/76) received novel HT diagnosis. Diuretics were adjusted in 7% of the patients with HF (2/29). Adherence was > 70% in 77% of the patients that started weekly measurements (70/91). Patients that were female, older of age and experienced palpitations at inclusion were more likely to acquire an adherence of > 70%. NPS was completed by 68 patients, 57 patients (84%) were promotors or neutral, and 11 patients (16%) were critics.

CONCLUSIONS

mHealth offers advantages in the management of selected ACHD patients; it enabled early detection of recurrences and new diagnosis of arrhythmias, hypertension and heart failure, which lead to swift therapeutic response or remote reassurance. Furthermore, mHealth was well accepted with high adherence and positive patient experience.

First real-world experience with mobile health telemonitoring in adult patients with congenital heart disease

BACKGROUND

Arrhythmias and heart failure are common and invalidating sequelae in adult patients with congenital heart disease (CHD). Mobile health (m-Health) enables daily monitoring and a timely response that might prevent deterioration. We present an observational prospective registry to evaluate feasibility of an m‑Health telemonitoring program for managing arrhythmia, heart failure and blood pressure in symptomatic adults with CHD.

METHODS

Symptomatic adult patients with CHD are enrolled in an m‑Health telemonitoring program, which evaluates single-lead ECG, blood pressure and weight measurements. In case of symptoms extra measurements could be performed. Data are collected by mobile apps, matched with individualised thresholds. Patients are contacted if thresholds were exceeded or if arrhythmias were found, for treatment adjustments or reassurance. Data on emergency care utilisation, hospitalisation and patient-reported outcome measures are used to assess quality of life and self-management.

RESULTS

129 symptomatic CHD patients were invited to participate, 55 participated. Reasons for refusing consent included too time consuming to participate in research (30) and to monitor vital signs (14). At baseline 22 patients were in New York Heart Association class ≥ II heart failure, 43 patients had palpitations or documented arrhythmias, and 8 had hypertension. Mean follow-up was 3.0 months, one patient dropped out, and adherence was 97%.

CONCLUSION

The first results indicate that this program is feasible with high adherence.