Using Smart Technology to Improve Outcomes in Myocardial Infarction Patients: Rationale and Design of a Protocol for a Randomized Controlled Trial, The Box

Learning healthcare systems in cardiology: A qualitative interview study on ethical dilemmas of a learning healthcare system

Background

Implementation of an LHS in cardiology departments presents itself with ethical challenges, including ethical review and informed consent. In this qualitative study, we investigated stakeholders' attitudes toward ethical issues regarding the implementation of an LHS in the cardiology department.

Methods

We conducted a qualitative study using 35 semi-structured interviews and 5 focus group interviews with 34 individuals. We interviewed cardiologists, research nurses, cardiovascular patients, ethicists, health lawyers, epidemiologists/statisticians and insurance spokespersons.

Results

Respondents identified different ethical obstacles for the implementation of an LHS within the cardiology department. These obstacles were mainly on ethical oversight in LHSs; in particular, informed con sent and data ownership were discussed. In addition, respondents reported on the role of patients in LHS. Respondents described the LHS as a possibility for patients to engage in both research and care. While the LHS can promote patient engagement, patients might also be reduced to their data and are therefore at risk, according to respondents.

Conclusions

Views on the ethical dilemmas of a LHSs within cardiology are diverse. Similar to the literary debate on oversight, there are different views on how ethical oversight should be regulated. This study adds to the literary debate on oversight by highlighting that patients wish to be informed about the learning activities within the LHS they participate in, and that they wish to actively contribute by sharing their data and identifying learning goals, provided that informed consent is obtained.

The Box—eHealth in the Outpatient Clinic Follow-up of Patients With Acute Myocardial Infarction: Cost-Utility Analysis

Background

Smartphone compatible wearables have been released on the consumers market, enabling remote monitoring. Remote monitoring is often named as a tool to reduce the cost of care.

Objective

The primary purpose of this paper is to describe a cost-utility analysis of an eHealth intervention compared to regular follow-up in patients with acute myocardial infarction (AMI).

Methods

In this trial, of which clinical results have been published previously, patients with an AMI were randomized in a 1:1 fashion between an eHealth intervention and regular follow-up. The remote monitoring intervention consisted of a blood pressure monitor, weight scale, electrocardiogram device, and step counter. Furthermore, two in-office outpatient clinic visits were replaced by e-visits. The control group received regular care. The differences in mean costs and quality of life per patient between both groups during one-year follow-up were calculated.

Results

Mean costs per patient were €2417±2043 (US $2657±2246) for the intervention and €2888±2961 (US $3175±3255) for the control group. This yielded a cost reduction of €471 (US $518) per patient. This difference was not statistically significant (95% CI –€275 to €1217; P=.22, US $–302 to $1338). The average quality-adjusted life years in the first year of follow-up was 0.74 for the intervention group and 0.69 for the control (difference –0.05, 95% CI –0.09 to –0.01; P=.01).

Conclusions

eHealth in the outpatient clinic setting for patients who suffered from AMI is likely to be cost-effective compared to regular follow-up. Further research should be done to corroborate these findings in other patient populations and different care settings.

Trial Registration

ClinicalTrials.gov NCT02976376; https://clinicaltrials.gov/ct2/show/NCT02976376

International Registered Report Identifier (IRRID)

RR2-10.2196/resprot.8038

Impacts on Context Aware Systems in Evidence-Based Health Informatics: A Review

Background: The application of Context Aware Computing (CAC) can be an effective, useful, feasible, and acceptable way to advance medical research and provide health services. Methods: This review was conducted in accordance with the principles of the development of a mixed methods review and existing knowledge in the field via the Synthesis Framework for the Assessment of Health Information Technology to evaluate CAC implemented by Evidence-Based Health Informatics (EBHI). A systematic search of the literature was performed during 18 November 2021–22 January 2022 in Cochrane Library, IEEE Xplore, PUBMED, Scopus and in the clinical registry platform Clinicaltrials.gov. The author included the articles in the review if they were implemented by EBHI and concerned with CAC technologies. Results: 29 articles met the inclusion criteria and refer to 26 trials published between 2011 and 2022. The author noticed improvements in healthcare provision using EBHI in the findings of CAC application. She also confirmed that CAC systems are a valuable and reliable method in health care provision. Conclusions: The use of CAC systems in healthcare is a promising new area of research and development. The author presented that the evaluation of CAC systems in EBHI presents positive effects on the state of health and the management of long-term diseases. These implications are presented in this article in a detailed, clear, and reliable manner.

Smartphone-based counseling and support platform and the effect on postpartum lactation: a randomized controlled trial

BACKGROUND

Human milk lactation provides health benefits for both the mother and infant. Patients commonly report stopping breastfeeding sooner than they planned. Interventions with proper accessible counseling and support to the mother can potentially increase lactation rates and duration.

OBJECTIVE

This study aimed to investigate the impact of introducing a smartphone-based daily feedback and counseling platform between women after delivery and a multidisciplinary lactation support team on lactation rates and various maternal and neonatal outcomes. Counseling was provided via a specifically developed application from a multidisciplinary team (obstetricians, nurses, lactation counselors, and psychologist) in an attempt to assist and counsel to maintain lactation.

STUDY DESIGN

This was a prospective, single-center, randomized controlled trial. Women planning to lactate were recruited at postpartum day 1 and were randomized to (1) routine lactation counseling and support (control group) or (2) additional daily detailed counseling and feedback on lactation from the team via the application (App group). The primary outcome was partial or full lactation at 3 months after delivery. The secondary outcomes included lactation at additional time points up to 6 months after delivery. The study was adequately powered to detect a 15% difference in the primary outcome.

RESULTS

A total of 197 patients were recruited, 97 in the App group and 100 in the control group. The 2 groups did not differ in any background or delivery characteristics. The App group showed higher rates of lactation 6 weeks after delivery (96.9% vs 82.0%; P<.001) and 3 months after delivery (81.4% vs 69.0%; P=.049) than the control group. Patients in the App group reported excellent satisfaction from the use of the application and their overall postnatal care.

CONCLUSION

Our study has provided further information on the growing efficacy of technology platforms in obstetrical care. The introduction of a smartphone-based daily feedback and counseling platform between postpartum patients and a multidisciplinary lactation support team increased the lactation rates after delivery with excellent patient satisfaction.

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.

E-health bij poliklinische follow-up van myocardinfarctpatiënten

E-health maakt het mogelijk om goede poliklinische zorg aan hartinfarctpatiënten te leveren, zelfs gedurende de huidige COVID-19-pandemie. We deden een haalbaarheidsonderzoek om te kijken of e-health kan worden ingezet als een bruikbaar alternatief voor fysieke polikliniekbezoeken bij het leveren van poliklinische zorg. We verdeelden 200 hartinfarctpatiënten at random over een e-health-interventie of standaard follow-up. De primaire uitkomst was bloeddrukregulatie, secundaire uitkomsten waren patiënttevredenheid en klinische opnamen. Tussen beide groepen waren er geen significante verschillen in uitkomsten. E-health produceert daarmee gelijke uitkomsten.

Assessment of a standalone photoplethysmography (PPG) algorithm for detection of atrial fibrillation on wristband-derived data

INTRODUCTION

Atrial fibrillation (AF) is the most common cardiac arrhythmia in the developed world. Using photoplethysmography (PPG) and software algorithms, AF can be detected with high accuracy using smartphone camera-derived data. However, reports of diagnostic accuracy of standalone algorithms using wristband-derived PPG data are sparse, while this provides a means to perform long-term AF screening and monitoring. This study evaluated the diagnostic accuracy of a well-known standalone algorithm using wristband-derived PPG data.

MATERIALS AND METHODS

Subjects recruited from a community senior care organization were instructed to wear the Wavelet PPG wristband on one arm and the Alivecor KardiaBand one-lead-ECG wristband on the other. Three consecutive measurements (duration per measurement: 60 s for PPG and 30 s for one-lead ECG) were performed with both devices, simultaneously. The PPG data were analyzed by the Fibricheck standalone algorithm and the ECG data by the Kardia algorithm. The results were compared to a reference standard (interpretation of the one-lead ECG by two independent cardiologists).

RESULTS

A total of 180 PPGs and one-lead ECGs were recorded in 60 subjects, with a mean age of 70±17. AF was identified in 6 (10%) of the users, two users (3%) were not classifiable by the PPG algorithm and 1 user (2%) was not classifiable by the one-lead ECG algorithm. The diagnostic performance (sensitivity/specificity/positive predictive value/negative predictive value/accuracy) on user level was 100/96/75/100/97% for the PPG wristband and 100/98/86/100/98% for the one-lead ECG wristband.

CONCLUSIONS

In a small real-world cohort of elderly people, the standalone Fibricheck AF algorithm can accurately detect AF using Wavelet wristband-derived PPG data. Results are comparable to the Alivecor Kardia one-lead ECG device, with an acceptable unclassifiable/bad quality rate. This opens the door for long-term AF screening and monitoring.

Use of Smart Technology for the Early Diagnosis of Complications After Cardiac Surgery: The Box 2.0 Study Protocol

BACKGROUND

Atrial fibrillation (AF), sternal wound infection, and cardiac decompensation are complications that can occur after cardiac surgery. Early detection of these complications is clinically relevant, as early treatment is associated with better clinical outcomes. Remote monitoring with the use of a smartphone (mobile health [mHealth]) might improve the early detection of complications after cardiac surgery.

OBJECTIVE

The primary aim of this study is to compare the detection rate of AF diagnosed with an mHealth solution to the detection rate of AF diagnosed with standard care. Secondary objectives include detection of sternal wound infection and cardiac decompensation, as well as assessment of quality of life, patient satisfaction, and cost-effectiveness.

METHODS

The Box 2.0 is a study with a prospective intervention group and a historical control group for comparison. Patients undergoing cardiac surgery at Leiden University Medical Center are eligible for enrollment. In this study, 365 historical patients will be used as controls and 365 other participants will be asked to receive either The Box 2.0 intervention consisting of seven home measurement devices along with a video consultation 2 weeks after discharge or standard cardiac care for 3 months. Patient information will be analyzed according to the intention-to-treat principle. The Box 2.0 devices include a blood pressure monitor, thermometer, weight scale, step count watch, single-lead electrocardiogram (ECG) device, 12-lead ECG device, and pulse oximeter.

RESULTS

The study started in November 2018. The primary outcome of this study is the detection rate of AF in both groups. Quality of life is measured with the five-level EuroQol five-dimension (EQ-5D-5L) questionnaire. Cost-effectiveness is calculated from a society perspective using prices from Dutch costing guidelines and quality of life data from the study. In the historical cohort, 93.9% (336/358) completed the EQ-5D-5L and patient satisfaction questionnaires 3 months after cardiac surgery.

CONCLUSIONS

The rationale and design of a study to investigate mHealth devices in postoperative cardiac surgery patients are presented. The first results are expected in September 2020.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03690492; http://clinicaltrials.gov/show/NCT03690492.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/16326.

Effect of Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among Patients After Myocardial Infarction: A Randomized Clinical Trial

IMPORTANCE

Smart technology via smartphone-compatible devices might improve blood pressure (BP) regulation in patients after myocardial infarction.

OBJECTIVES

To investigate whether smart technology in clinical practice can improve BP regulation and to evaluate the feasibility of such an intervention.

DESIGN, SETTING, AND PARTICIPANTS

This study was an investigator-initiated, single-center, nonblinded, feasibility, randomized clinical trial conducted at the Department of Cardiology of the Leiden University Medical Center between May 2016 and December 2018. Two hundred patients, who were admitted with either ST-segment elevation myocardial infarction or non-ST-segment acute coronary syndrome, were randomized in a 1:1 fashion between follow-up groups using smart technology and regular care. Statistical analysis was performed from January 2019 to March 2019.

INTERVENTIONS

For patients randomized to regular care, 4 physical outpatient clinic visits were scheduled in the year following the initial event. In the intervention group, patients were given 4 smartphone-compatible devices (weight scale, BP monitor, rhythm monitor, and step counter). In addition, 2 in-person outpatient clinic visits were replaced by electronic visits.

MAIN OUTCOMES AND MEASURES

The primary outcome was BP control. Secondary outcomes, as a parameter of feasibility, included patient satisfaction (general questionnaire and smart technology-specific questionnaire), measurement adherence, all-cause mortality, and hospitalizations for nonfatal adverse cardiac events.

RESULTS

In total, 200 patients (median age, 59.7 years [interquartile range, 52.9-65.6 years]; 156 men [78%]) were included, of whom 100 were randomized to the intervention group and 100 to the control group. After 1 year, 79% of patients in the intervention group had controlled BP vs 76% of patients in the control group (P = .64). General satisfaction with care was the same between groups (mean [SD] scores, 82.6 [14.1] vs 82.0 [15.1]; P = .88). The all-cause mortality rate was 2% in both groups (P > .99). A total of 20 hospitalizations for nonfatal adverse cardiac events occurred (8 in the intervention group and 12 in the control group). Of all patients, 32% sent in measurements each week, with 63% sending data for more than 80% of the weeks they participated in the trial. In the intervention group only, 90.3% of patients were satisfied with the smart technology intervention.

CONCLUSIONS AND RELEVANCE

These findings suggest that smart technology yields similar percentages of patients with regulated BP compared with the standard of care. Such an intervention is feasible in clinical practice and is accepted by patients. More research is mandatory to improve patient selection of such an intervention.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02976376.

Mobile health application platform 'Corrie' personalises and empowers the heart attack recovery patient experience in the hospital and at home for an underserved heart attack survivor

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide with an estimated 17.5 million deaths annually, according to the World Health Organization (WHO). CVD prevention efforts have the potential to prevent the majority of these deaths by supporting guideline-directed medical therapy (GDMT) and lifestyle modification. Mobile health (mHealth) has the potential to address this gap, but has limited evaluation in clinical studies to date. We present the case of a middle-aged patient of low socioeconomic status, with multiple comorbidities, and no prior smartphone experience, who suffered an acute myocardial infarction (MI) and was given the Corrie intervention while hospitalised. The patient demonstrated improvement in lifestyle modification, adherence to GDMT and post-MI recovery through 2.4 years follow-up. This case supports (1) the potential of mHealth interventions to enhance patient experience and outcomes, (2) intuitive design for adoption and improvement in end user experience and (3) the capability of mHealth to reach and empower underserved patients.

eHealth to improve patient outcome in rehabilitating myocardial infarction patients

INTRODUCTION

Cardiac rehabilitation is aimed at risk factor modification and improving quality of life. eHealth has a couple of potential benefits to improve this aim. The primary purpose of this review is to summarize available literature for eHealth strategies that have been investigated in randomized controlled trials in post-myocardial infarction (MI) patients. The second purpose of this review is to investigate the clinical effectiveness in post-MI patients. Areas covered: The literature was searched using PubMed. Randomized controlled trials (RCTs) describing interventions in patients that had experienced an ST-elevation myocardial infarction or non-ST acute coronary syndrome were eligible for inclusion. Fifteen full-texts were included and their results are described in this review. These RCTs described interventions that used remote coaching or remote monitoring in post-MI patients. Most interventions resulted in an improved cardiovascular risk profile. Remote coaching had a positive effect on activity and dietary intake. Expert opinion: eHealth might be clinically beneficial in post-MI patients, particularly for risk estimation. Moreover, eHealth as a tool for remote coaching on activity is a good addition to traditional cardiac rehabilitation programs. Further research needs to corroborate these findings.

Expectations and perceived barriers to widespread implementation of e‑Health in cardiology practice: Results from a national survey in the Netherlands

INTRODUCTION

Expectations of physicians concerning e‑Health and perceived barriers to implementation in clinical practice are scarcely reported in the literature. The purpose of this study was to assess these aspects of cardiovascular e‑Health.

METHODS

A survey was sent to members of the Netherlands Society of Cardiology. In total, the questionnaire contained 30 questions about five topics: personal use of smartphones, digital communication between respondents and patients, current e‑Health implementation in clinical practice, expectations about e‑Health and perceived barriers for e‑Health implementation. Age, personal use of smartphones and professional environment were noted as baseline characteristics.

RESULTS

In total, 255 respondents filled out the questionnaire (response rate 25%); 89.4% of respondents indicated that they considered e‑Health to be clinically beneficial, improving patient satisfaction (90.2%), but also that it will increase the workload (83.9%). Age was a negative predictor and personal use of smartphones was a positive predictor of having high expectations. Lack of reimbursement was identified by 66.7% of respondents as a barrier to e‑Health implementation, as well as a lack of reliable devices (52.9%) and a lack of data integration with electronic medical records (EMRs) (69.4%).

CONCLUSION

Cardiologists are in general positive about the possibilities of e‑Health implementation in routine clinical care; however, they identify deficient data integration into the EMR, reimbursement issues and lack of reliable devices as major barriers. Age and personal use of smartphones are predictors of expectations of e‑Health, but the professional working environment is not.