Changes in Intrapersonal Factors of Participants in the Pregnancy Remote Monitoring Study Who Are at Risk for Pregnancy-Induced Hypertension: Descriptive Quantitative Study.

BACKGROUND: The peripartum period, defined as the period from the beginning of the gestation until 1 year after the delivery, has long been shown to be potentially associated with increased levels of stress and anxiety with regard to one's transition to the status of parent and the accompanying parental tasks. Yet, no research to date has investigated changes in intrapersonal factors during the peripartum period in women at risk for pregnancy-induced hypertension (PIH). OBJECTIVE: The aim of this study is to explore and describe changes in intrapersonal factors in participants at risk for PIH. METHODS: We used an explorative design in which 3 questionnaires were sent by email to 110 participants the day following enrollment in the Pregnancy Remote Monitoring program for pregnant women at risk for PIH. Women were invited to complete the questionnaires at the beginning of their participation in the Pregnancy Remote Monitoring project (mostly at 14 weeks of gestation) and after approaching 32 weeks of gestational age (GA). The Generalized Anxiety Disorder-7 Scale (GAD-7) and the Patient Health Questionnaire-9 were used to assess anxiety and depression, and adaptation of the Pain Catastrophizing Scale was used to measure trait pain catastrophizing. RESULTS: Scores were significantly higher at 32 weeks of GA than at the moment of enrollment (GAD-7 score=7, range 4-11 vs 5, range 3-8; P=.01; and Patient Health Questionnaire-9 score=6, range 4-10 vs 4, range 2-7; P<.001). The subscale scores of the Pain Catastrophizing Scale were all lower at 32 weeks of GA compared with 14 weeks of GA (rumination: 4, range 1-6 vs 5, range 2-9.5; P=.11; magnification: 3, range 1-5.5 vs 4, range 3-7; P=.04; and helplessness: 5, range 2-9 vs 6, range 3.5-12; P=.06). The proportion of women with a risk for depression (GAD-7 score >10) was 13.3% (10/75) at enrollment and had increased to 35.6% (26/75) at 32 weeks of GA. CONCLUSIONS: This study shows that pregnant women at risk for PIH have higher levels of stress and anxiety at 32 weeks of GA than at the moment of enrollment. Further research is recommended to investigate potential strategies to help pregnant women at risk for PIH manage feelings of stress and anxiety. TRIAL REGISTRATION: ClinicalTrials.gov NCT03246737; https://clinicaltrials.gov/study/NCT03246737.

A Vendor-Independent Mobile Health Monitoring Platform for Digital Health Studies: Development and Usability Study.

BACKGROUND: Medical smartphone apps and mobile health devices are rapidly entering mainstream use because of the rising number of smartphone users. Consequently, a large amount of consumer-generated data is being collected. Technological advances in innovative sensory systems have enabled data connectivity and aggregation to become cornerstones in developing workable solutions for remote monitoring systems in clinical practice. However, few systems are currently available to handle such data, especially for clinical use. OBJECTIVE: The aim of this study was to develop and implement the digital health research platform for mobile health (DHARMA) that combines data saved in different formats from a variety of sources into a single integrated digital platform suitable for mobile remote monitoring studies. METHODS: DHARMA comprises a smartphone app, a Web-based platform, and custom middleware and has been developed to collect, store, process, and visualize data from different vendor-specific sensors. The middleware is a component-based system with independent building blocks for user authentication, study and patient administration, data handling, questionnaire management, patient files, and reporting. RESULTS: A prototype version of the research platform has been tested and deployed in multiple clinical studies. In this study, we used the platform for the follow-up of pregnant women at risk of developing pre-eclampsia. The patients' blood pressure, weight, and activity were semi-automatically captured at home using different devices. DHARMA automatically collected and stored data from each source and enabled data processing for the end users in terms of study-specific parameters, thresholds, and visualization. CONCLUSIONS: The increasing use of mobile health apps and connected medical devices is leading to a large amount of data for collection. There has been limited investment in handling and aggregating data from different sources for use in academic and clinical research focusing on remote monitoring studies. In this study, we created a modular mobile health research platform to collect and integrate data from a variety of third-party devices in several patient populations. The functionality of the platform was demonstrated in a real-life setting among women with high-risk pregnancies.

Relationship Between Adherence to Remote Monitoring and Patient Characteristics: Observational Study in Women With Pregnancy-Induced Hypertension.

BACKGROUND: Pregnancy-induced hypertension (PIH) is associated with high levels of morbidity and mortality in mothers, fetuses, and newborns. New technologies, such as remote monitoring (RM), were introduced in 2015 into the care of patients at risk of PIH in Ziekenhuis Oost-Limburg (Genk, Belgium) to improve both maternal and neonatal outcomes. In developing new strategies for obstetric care in pregnant women, including RM, it is important to understand the psychosocial characteristics associated with adherence to RM to optimize care. OBJECTIVE: The aim of this study was to explore the role of patients' psychosocial characteristics (severity of depression or anxiety, cognitive factors, attachment styles, and personality traits) in their adherence to RM. METHODS: Questionnaires were sent by email to 108 mothers the day after they entered an RM program for pregnant women at risk of PIH. The Generalized Anxiety Disorder Assessment-7 and Patient Health Questionnaire-9 (PHQ-9) were used to assess anxiety and the severity of depression, respectively; an adaptation of the Pain Catastrophizing Scale was used to assess cognitive factors; and attachment and personality were measured with the Experiences in Close Relationships-Revised Scale (ECR-R), the Depressive Experiences Questionnaire, and the Multidimensional Perfectionism Scale, respectively. RESULTS: The moderate adherence group showed significantly higher levels of anxiety and depression, negative cognitions, and insecure attachment styles, especially compared with the over adherence group. The low adherence group scored significantly higher than the other groups on other-oriented perfectionism. There were no significant differences between the good and over adherence groups. Single linear regression showed that the answers on the PHQ-9 and ECR-R questionnaires were significantly related to the adherence rate. CONCLUSIONS: This study demonstrates the relationships between adherence to RM and patient characteristics in women at risk of PIH. Alertness toward the group of women who show less than optimal adherence is essential. These findings call for further research on the management of PIH and the importance of individual tailoring of RM in this patient group. TRIAL REGISTRATION: ClinicalTrials.gov NCT03509272; https://clinicaltrials.gov/ct2/show/NCT03509272.

Midwives', Obstetricians', and Recently Delivered Mothers' Perceptions of Remote Monitoring for Prenatal Care: Retrospective Survey.

BACKGROUND: The Pregnancy Remote Monitoring (PREMOM) study enrolled pregnant women at increased risk of developing hypertensive disorders of pregnancy and investigated the effect of remote monitoring in addition to their prenatal follow-up. OBJECTIVE: The objective of this study was to investigate the perceptions and experiences of remote monitoring among mothers, midwives, and obstetricians who participated in the PREMOM study. METHODS: We developed specific questionnaires for the mothers, midwives, and obstetricians addressing 5 domains: (1) prior knowledge and experience of remote monitoring, (2) reactions to abnormal values, (3) privacy, (4) quality and patient safety, and (5) financial aspects. We also questioned the health care providers about which issues they considered important when implementing remote monitoring. We used a 5-point Likert scale to provide objective scores. It was possible to add free-text feedback at every question. RESULTS: A total of 91 participants completed the questionnaires. The mothers, midwives, and obstetricians reported positive experiences and perceptions of remote monitoring, although most of them had no or little prior experience with this technology. They supported a further rollout of remote monitoring in Belgium. Nearly three-quarters of the mothers (34/47, 72%) did not report any problems with taking the measurements at the required times. Almost half of the mothers (19/47, 40%) wanted to be contacted within 3 to 12 hours after abnormal measurement values, preferably by telephone. CONCLUSIONS: Although most of midwives and obstetricians had no or very little experience with remote monitoring before enrolling in the PREMOM study, they reported, based on their one-year experience, that remote monitoring was an important component in the follow-up of high-risk pregnancies and would recommend it to their colleagues and pregnant patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT03246737; https://clinicaltrials.gov/ct2/show/NCT03246737 (Archived by WebCite at http://www.webcitation.org/76KVnHSYY).

A Prenatal Remote Monitoring Program in Pregnancies Complicated with Gestational Hypertensive Disorders: What Are the Contributors to the Cost Savings?

Background: In 2015, we performed a cost analysis of a prenatal remote monitoring (RM) program compared with conventional care (CC) for women diagnosed with gestational hypertensive disorders (GHD). Introduction: We investigated where the cost savings were distributed by dividing our patient population into three subgroups, according to the gestational age (GA) at the time of delivery: (1) <34 weeks; (2) 34-37 weeks; and (3) >37 weeks of GA. Materials and Methods: Health care costs were calculated from patient-specific hospital bills at Ziekenhuis Oost Limburg (Genk, Belgium) in 2015-2016. Cost comparisons were made from the perspectives of the Belgium national health care system (HCS), the National Institution for Insurance of Disease and Disability (RIZIV), and the costs to individual patients. Results: A total of 256 pregnant women were included, 80 (31.25%) of whom received RM and 176 (68.75%) of whom received CC. The greatest difference in costs between RM and CC was in the group that delivered before 34 weeks of GA, followed by the group who delivered after 37 weeks of GA, and then the group of women who delivered at 34-37 weeks of GA. Most of the cost savings were in neonatal care, for both the three separate study subgroups and the total study group. Discussion and Conclusion: Our data showed that RM is more cost-effective than CC for pregnant women with GHD. Further investigation of the effects of RM on the long-term economic and social costs is recommended, together with an analysis of the price that should be asked for RM services.

Metadata Correction: Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study.

[This corrects the article DOI: 10.2196/mhealth.7254.].

Prenatal Remote Monitoring of Women With Gestational Hypertensive Diseases: Cost Analysis.

BACKGROUND: Remote monitoring in obstetrics is relatively new; some studies have shown its effectiveness for both mother and child. However, few studies have evaluated the economic impact compared to conventional care, and no cost analysis of a remote monitoring prenatal follow-up program for women diagnosed with gestational hypertensive diseases (GHD) has been published. OBJECTIVE: The aim of this study was to assess the costs of remote monitoring versus conventional care relative to reported benefits. METHODS: Patient data from the Pregnancy Remote Monitoring (PREMOM) study were used. Health care costs were calculated from patient-specific hospital bills of Ziekenhuis Oost-Limburg (Genk, Belgium) in 2015. Cost comparison was made from three perspectives: the Belgian national health care system (HCS), the National Institution for Insurance of Disease and Disability (RIZIV), and costs for individual patients. The calculations were made for four major domains: prenatal follow-up, prenatal admission to the hospital, maternal and neonatal care at and after delivery, and total amount of costs. A simulation exercise was made in which it was calculated how much could be demanded of RIZIV for funding the remote monitoring service. RESULTS: A total of 140 pregnancies were included, of which 43 received remote monitoring (30.7%) and 97 received conventional care (69.2%). From the three perspectives, there were no differences in costs for prenatal follow-up. Compared to conventional care, remote monitoring patients had 34.51% less HCS and 41.72% less RIZIV costs for laboratory test results (HCS: mean €0.00 [SD €55.34] vs mean €38.28 [SD € 44.08], P<.001; RIZIV: mean €21.09 [SD €27.94] vs mean €36.19 [SD €41.36], P<.001) and a reduction of 47.16% in HCS and 48.19% in RIZIV costs for neonatal care (HCS: mean €989.66 [SD €3020.22] vs mean €1872.92 [SD €5058.31], P<.001; RIZIV: mean €872.97 [SD €2761.64] vs mean €1684.86 [SD €4702.20], P<.001). HCS costs for medication were 1.92% lower in remote monitoring than conventional care (mean €209.22 [SD €213.32] vs mean €231.32 [SD 67.09], P=.02), but were 0.69% higher for RIZIV (mean €122.60 [SD €92.02] vs mean €121.78 [SD €20.77], P<.001). Overall HCS costs for remote monitoring were mean €4233.31 (SD €3463.31) per person and mean €4973.69 (SD €5219.00) per person for conventional care (P=.82), a reduction of €740.38 (14.89%) per person, with savings mainly for RIZIV of €848.97 per person (23.18%; mean €2797.42 [SD €2905.18] vs mean €3646.39 [SD €4878.47], P=.19). When an additional fee of €525.07 per month per pregnant woman for funding remote monitoring costs is demanded, remote monitoring is acceptable in their costs for HCS, RIZIV, and individual patients. CONCLUSIONS: In the current organization of Belgian health care, a remote monitoring prenatal follow-up of women with GHD is cost saving for the global health care system, mainly via savings for the insurance institution RIZIV.

Protocol-driven remote monitoring of cardiac resynchronization therapy as part of a heart failure disease management strategy.

BACKGROUND: Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure (HF) with reduced ejection fraction. CRT devices are equipped with remote monitoring functions, which are pivotal in the detection of device problems, but may also facilitate disease management. The aim of this study was to provide a comprehensive overview of the clinical interventions taken based on remote monitoring. METHODS: This is a single centre observational study of consecutive CRT patients (n = 192) participating in protocol-driven remote follow-up. Incoming technical- and disease-related alerts were analysed together with subsequently triggered interventions. RESULTS: During 34 ± 13 months of follow-up, 1372 alert-containing notifications were received (2.53 per patient-year of follow-up), comprising 1696 unique alerts (3.12 per patient-year of follow-up). In 60%, notifications resulted in a phone contact. Technical alerts constituted 8% of incoming alerts (0.23 per patient-year of follow-up). Rhythm (1.43 per patient-year of follow-up) and bioimpedance alerts (0.98 per patient-year of follow-up) were the most frequent disease-related alerts. Notifications included a rhythm alert in 39%, which triggered referral to the emergency room (4%), outpatient cardiology clinic (36%) or general practitioner (7%), or resulted in medication changes (13%). Sole bioimpedance notifications resulted in a telephone contact in 91%, which triggered outpatient evaluation in 8% versus medication changes in 10%. Clinical outcome was excellent with 97% 1-year survival. CONCLUSIONS: Remote CRT follow-up resulted in 0.23 technical- versus 2.64 disease-related alerts annually. Rhythm and bioimpedance notifications constituted the majority of incoming notifications which triggered an actual intervention in 22% and 15% of cases, respectively.

Bioimpedance Alerts from Cardiovascular Implantable Electronic Devices: Observational Study of Diagnostic Relevance and Clinical Outcomes.

BACKGROUND: The use of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT) devices is expanding in the treatment of heart failure. Most of the current devices are equipped with remote monitoring functions, including bioimpedance for fluid status monitoring. The question remains whether bioimpedance measurements positively impact clinical outcome. OBJECTIVE: The aim of this study was to provide a comprehensive overview of the clinical interventions taken based on remote bioimpedance monitoring alerts and their impact on clinical outcome. METHODS: This is a single-center observational study of consecutive ICD and CRT patients (n=282) participating in protocol-driven remote follow-up. Bioimpedance alerts were analyzed with subsequently triggered interventions. RESULTS: A total of 55.0% (155/282) of patients had an ICD or CRT device equipped with a remote bioimpedance algorithm. During 34 (SD 12) months of follow-up, 1751 remote monitoring alarm notifications were received (2.2 per patient-year of follow-up), comprising 2096 unique alerts (2.6 per patient-year of follow-up). Since 591 (28.2%) of all incoming alerts were bioimpedance-related, patients with an ICD or CRT including a bioimpedance algorithm had significantly more alerts (3.4 versus 1.8 alerts per patient-year of follow-up, P<.001). Bioimpedance-only alerts resulted in a phone contact in 91.0% (498/547) of cases, which triggered an actual intervention in 15.9% (87/547) of cases, since in 75.1% (411/547) of cases reenforcing heart failure education sufficed. Overall survival was lower in patients with a cardiovascular implantable electronic device with a bioimpedance algorithm; however, this difference was driven by differences in baseline characteristics (adjusted hazard ratio of 2.118, 95% CI 0.845-5.791). No significant differences between both groups were observed in terms of the number of follow-up visits in the outpatient heart failure clinic, the number of hospital admissions with a primary diagnosis of heart failure, or mean length of hospital stay. CONCLUSIONS: Bioimpedance-only alerts constituted a substantial amount of incoming alerts when turned on during remote follow-up and triggered an additional intervention in only 16% of cases since in 75% of cases, providing general heart failure education sufficed. The high frequency of heart failure education that was provided could have contributed to fewer heart failure-related hospitalizations despite significant differences in baseline characteristics.

Effectiveness of Telemonitoring in Obstetrics: Scoping Review.

BACKGROUND: Despite reported positive results of telemonitoring effectiveness in various health care domains, this new technology is rarely used in prenatal care. A few isolated investigations were performed in the past years but with conflicting results. OBJECTIVE: The aim of this review was to (1) assess whether telemonitoring adds any substantial benefit to this patient population and (2) identify research gaps in this area to suggest goals for future research. METHODS: This review includes studies exploring the effectiveness of telemonitoring interventions for pregnant women reported in the English language. Due to the paucity of research in this area, all reports including uncontrolled nonrandomized and randomized controlled studies were selected. RESULTS: Fourteen studies, which performed their data collection from 1988 to 2010, met the inclusion criteria and were published from 1995 to present; four of the 14 published papers were multicenter randomized controlled trials (RCTs), five papers were single-center RCTs, three papers were retrospective studies, one paper was an observational study, and one paper was a qualitative study. Of the 14 papers, nine were available for a risk of bias assessment: three papers were classified as low risk, one as medium risk, and five as high risk. Furthermore, of those 14 papers, 13 focused on telemonitoring for maternal outcomes, and nine of the 14 papers focused on telemonitoring for fetal or neonatal outcomes. The studies reviewed report that telemonitoring can contribute to significant reductions in health care costs, (unscheduled) face-to-face visits, low neonatal birth weight, and admissions to the neonatal intensive care unit (NICU), as well as prolonged gestational age and improved feelings of maternal satisfaction when compared with a control group. When only studies with low risk of bias were taken into account, the added value of telemonitoring became less pronounced: the only added value of telemonitoring is for pregnant women who transmitted their uterine activity by telecommunication. They had significant prolonged pregnancy survivals, and the newborns were less likely to be of low birth weight or to be admitted to the NICU. Following these results, telemonitoring can only be recommended by pregnant women at risk for preterm delivery. It is however important to consider that these studies were published in the mid-90s, which limits their direct applicability given the current technologies and practice. CONCLUSIONS: This review shows that telemonitoring can be tentatively recommended for pregnant women at risk for preterm delivery. More recent RCTs with a blinded protocol are needed to strengthen the level of evidence around this topic and to have an insight in the added value of the technologies that are available nowadays. In addition, studies investigating patient satisfaction and economic effects in relation to telemonitoring are suggested for future research.

Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study.

BACKGROUND: Photoplethysmography (PPG) is a proven way to measure heart rate (HR). This technology is already available in smartphones, which allows measuring HR only by using the smartphone. Given the widespread availability of smartphones, this creates a scalable way to enable mobile HR monitoring. An essential precondition is that these technologies are as reliable and accurate as the current clinical (gold) standards. At this moment, there is no consensus on a gold standard method for the validation of HR apps. This results in different validation processes that do not always reflect the veracious outcome of comparison. OBJECTIVE: The aim of this paper was to investigate and describe the necessary elements in validating and comparing HR apps versus standard technology. METHODS: The FibriCheck (Qompium) app was used in two separate prospective nonrandomized studies. In the first study, the HR of the FibriCheck app was consecutively compared with 2 different Food and Drug Administration (FDA)-cleared HR devices: the Nonin oximeter and the AliveCor Mobile ECG. In the second study, a next step in validation was performed by comparing the beat-to-beat intervals of the FibriCheck app to a synchronized ECG recording. RESULTS: In the first study, the HR (BPM, beats per minute) of 88 random subjects consecutively measured with the 3 devices showed a correlation coefficient of .834 between FibriCheck and Nonin, .88 between FibriCheck and AliveCor, and .897 between Nonin and AliveCor. A single way analysis of variance (ANOVA; P=.61 was executed to test the hypothesis that there were no significant differences between the HRs as measured by the 3 devices. In the second study, 20,298 (ms) R-R intervals (RRI)-peak-to-peak intervals (PPI) from 229 subjects were analyzed. This resulted in a positive correlation (rs=.993, root mean square deviation [RMSE]=23.04 ms, and normalized root mean square error [NRMSE]=0.012) between the PPI from FibriCheck and the RRI from the wearable ECG. There was no significant difference (P=.92) between these intervals. CONCLUSIONS: Our findings suggest that the most suitable method for the validation of an HR app is a simultaneous measurement of the HR by the smartphone app and an ECG system, compared on the basis of beat-to-beat analysis. This approach could lead to more correct assessments of the accuracy of HR apps.

Remote Monitoring of Hypertension Diseases in Pregnancy: A Pilot Study.

BACKGROUND: Although remote monitoring (RM) has proven its added value in various health care domains, little is known about the remote follow-up of pregnant women diagnosed with a gestational hypertensive disorders (GHD). OBJECTIVE: The aim of this study was to evaluate the added value of a remote follow-up program for pregnant women diagnosed with GHD. METHODS: A 1-year retrospective study was performed in the outpatient clinic of a 2nd level prenatal center where pregnant women with GHD received RM or conventional care (CC). Primary study endpoints include number of prenatal visits and admissions to the prenatal observation ward. Secondary outcomes include gestational outcome, mode of delivery, neonatal outcome, and admission to neonatal intensive care (NIC). Differences in continuous and categorical variables in maternal demographics and characteristics were tested using Unpaired Student's two sampled t test or Mann-Whitney U test and the chi-square test. Both a univariate and multivariate analysis were performed for analyzing prenatal follow-up and gestational outcomes. All statistical analyses were done at nominal level, Cronbach alpha=.05. RESULTS: Of the 166 patients diagnosed with GHD, 53 received RM and 113 CC. After excluding 5 patients in the RM group and 15 in the CC group because of the missing data, 48 patients in RM group and 98 in CC group were taken into final analysis. The RM group had more women diagnosed with gestational hypertension, but less with preeclampsia when compared with CC (81.25% vs 42.86% and 14.58% vs 43.87%). Compared with CC, univariate analysis in RM showed less induction, more spontaneous labors, and less maternal and neonatal hospitalizations (48.98% vs 25.00%; 31.63% vs 60.42%; 74.49% vs 56.25%; and 27.55% vs 10.42%). This was also true in multivariate analysis, except for hospitalizations. CONCLUSIONS: An RM follow-up of women with GHD is a promising tool in the prenatal care. It opens the perspectives to reverse the current evolution of antenatal interventions leading to more interventions and as such to ever increasing medicalized antenatal care.

eEduHeart I: A Multicenter, Randomized, Controlled Trial Investigating the Effectiveness of a Cardiac Web-Based eLearning Platform - Rationale and Study Design.

OBJECTIVES: Cardiac telerehabilitation includes, in its most comprehensive format, telemonitoring, telecoaching, social interaction, and eLearning. The specific role of eLearning, however, was seldom assessed. The aim of eEduHeart I is to investigate the medium-term effectiveness of the addition of a cardiac web-based eLearing platform to conventional cardiac care. METHODS: In this prospective, multicenter randomized, controlled trial, 1,000 patients with coronary artery disease will be randomized 1:1 to an intervention group (receiving 1-month unrestricted access to the cardiac eLearning platform in addition to conventional cardiac care) or to conventional cardiac care alone. The primary endpoint is health-related quality of life, assessed by the HeartQoL questionnaire at the 1- and 3-month follow-ups. Secondary endpoints include pathology-specific knowledge and self-reported eLearning platform user experience. Data on the eLearning platform usage will be gathered through web logging during the study period. RESULTS: eEduHeart I will be one of the first studies to report on the added value of eLearning. CONCLUSIONS: If the intervention is proven effective, current cardiac telerehabilitation programs can be augmented by including eLearning, too. The platform can then be used as a model for other chronic diseases in which patient education plays a key role.