Economic impact assessment from the use of a mobile app for the self-management of heart diseases by patients with heart failure in a Spanish region

Economic Evaluations of Digital Health Interventions for Patients With Heart Failure: Systematic Review

BACKGROUND

Digital health interventions (DHIs) have shown promising results in enhancing the management of heart failure (HF). Although health care interventions are increasingly being delivered digitally, with growing evidence on the potential cost-effectiveness of adopting them, there has been little effort to collate and synthesize the findings.

OBJECTIVE

This study's objective was to systematically review the economic evaluations that assess the adoption of DHIs in the management and treatment of HF.

METHODS

A systematic review was conducted using 3 electronic databases: PubMed, EBSCOhost, and Scopus. Articles reporting full economic evaluations of DHIs for patients with HF published up to July 2023 were eligible for inclusion. Study characteristics, design (both trial based and model based), input parameters, and main results were extracted from full-text articles. Data synthesis was conducted based on the technologies used for delivering DHIs in the management of patients with HF, and the findings were analyzed narratively. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed for this systematic review. The reporting quality of the included studies was evaluated using the CHEERS (Consolidated Health Economic Evaluation Reporting Standards) guidelines.

RESULTS

Overall, 27 economic evaluations were included in the review. The economic evaluations were based on models (13/27, 48%), trials (13/27, 48%), or a combination approach (1/27, 4%). The devices evaluated included noninvasive remote monitoring devices (eg, home telemonitoring using digital tablets or specific medical devices that enable transmission of physiological data), telephone support, mobile apps and wearables, remote monitoring follow-up in patients with implantable medical devices, and videoconferencing systems. Most of the studies (24/27, 89%) used cost-utility analysis. The majority of the studies (25/27, 93%) were conducted in high-income countries, particularly European countries (16/27, 59%) such as the United Kingdom and the Netherlands. Mobile apps and wearables, remote monitoring follow-up in patients with implantable medical devices, and videoconferencing systems yielded cost-effective results or even emerged as dominant strategies. However, conflicting results were observed, particularly in noninvasive remote monitoring devices and telephone support. In 15% (4/27) of the studies, these DHIs were found to be less costly and more effective than the comparators (ie, dominant), while 33% (9/27) reported them to be more costly but more effective with incremental cost-effectiveness ratios below the respective willingness-to-pay thresholds (ie, cost-effective). Furthermore, in 11% (3/27) of the studies, noninvasive remote monitoring devices and telephone support were either above the willingness-to-pay thresholds or more costly than, yet as effective as, the comparators (ie, not cost-effective). In terms of reporting quality, the studies were classified as good (20/27, 74%), moderate (6/27, 22%), or excellent (1/27, 4%).

CONCLUSIONS

Despite the conflicting results, the main findings indicated that, overall, DHIs were more cost-effective than non-DHI alternatives.

TRIAL REGISTRATION

PROSPERO CRD42023388241; https://tinyurl.com/2p9axpmc.

Testing the Effect of a Smartphone App on Hospital Admissions and Sedentary Behavior in Cardiac Rehabilitation Participants: ToDo-CR Randomized Controlled Trial

BACKGROUND

People with coronary heart disease are at an increased risk of morbidity and mortality even if they attend cardiac rehabilitation. High sedentary behavior levels potentially contribute to this morbidity. Smartphone apps may be feasible to facilitate sedentary behavior reductions and lead to reduced health care use.

OBJECTIVE

We aimed to test the effect of a sedentary behavior change smartphone app (Vire app and ToDo-CR program) as an adjunct to cardiac rehabilitation on hospital admissions and emergency department (ED) presentations over 12 months.

METHODS

A multicenter, randomized controlled trial was conducted with 120 participants recruited from 3 cardiac rehabilitation programs. Participants were randomized 1:1 to cardiac rehabilitation plus the fully automated 6-month Vire app and ToDo-CR program (intervention) or usual care (control). The primary outcome was nonelective hospital admissions and ED presentations over 12 months. Secondary outcomes including accelerometer-measured sedentary behavior, BMI, waist circumference, and quality of life were recorded at baseline and 6 and 12 months. Logistic regression models were used to analyze the primary outcome, and linear mixed-effects models were used to analyze secondary outcomes. Data on intervention and hospital admission costs were collected, and the incremental cost-effectiveness ratios (ICERs) were calculated.

RESULTS

Participants were, on average, aged 62 (SD 10) years, and the majority were male (93/120, 77.5%). The intervention group were more likely to experience all-cause (odds ratio [OR] 1.54, 95% CI 0.58-4.10; P=.39) and cardiac-related (OR 3.26, 95% CI 0.84-12.55; P=.09) hospital admissions and ED presentations (OR 2.07, 95% CI 0.89-4.77; P=.09) than the control group. Despite this, cardiac-related hospital admission costs were lower in the intervention group over 12 months (Aus $252.40 vs Aus $859.38; P=.24; a currency exchange rate of Aus $1=US $0.69 is applicable). There were no significant between-group differences in sedentary behavior minutes per day over 12 months, although the intervention group completed 22 minutes less than the control group (95% CI -22.80 to 66.69; P=.33; Cohen d=0.21). The intervention group had a lower BMI (β=1.62; P=.05), waist circumference (β=5.81; P=.01), waist-to-hip ratio (β=.03, P=.03), and quality of life (β=3.30; P=.05) than the control group. The intervention was more effective but more costly in reducing sedentary behavior (ICER Aus $351.77) and anxiety (ICER Aus $10,987.71) at 12 months. The intervention was also more effective yet costly in increasing quality of life (ICER Aus $93,395.50) at 12 months.

CONCLUSIONS

The Vire app and ToDo-CR program was not an outcome-effective or cost-effective solution to reduce all-cause hospital admissions or ED presentations in cardiac rehabilitation compared with usual care. Smartphone apps that target sedentary behavior alone may not be an effective solution for cardiac rehabilitation participants to reduce hospital admissions and sedentary behavior.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12619001223123; https://australianclinicaltrials.gov.au/anzctr/trial/ACTRN12619001223123.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2020-040479.

Examining standardized tools used for the evaluation of mobile health applications for cardiovascular disease

Cardiovascular disease is one of the leading causes of death worldwide. Scarce resources and rising costs are pushing healthcare systems to their limits. There is an urgency to develop, optimize and evaluate technologies that provide more effective care for patients. Modern technologies, such as mobile health (mHealth) applications, can provide relief as a key strategy. To integrate digital interventions into care structures, a detailed impact assessment of all professional mHealth applications is needed. The aim of this study is to analyze the standardized tools used in the field of cardiovascular disease. The results show that questionnaires, usage logs, and key indicators are predominantly used. Although the identified mHealth interventions are specific to cardiovascular disease and thus require particular questions to evaluate apps, the user readiness, usability, or quality of life criteria are non-specific. Therefore, the results contribute to understanding how different mHealth interventions can be assessed, categorized, evaluated, and accepted.

Effect of a mobile-based educational app on blood pressure of patients with hypertension

BACKGROUND

Hypertension is known as one of the most important non-communicable pervasive diseases.

OBJECTIVE

The purpose of the present study was to determine the effect of a mobile-based educational app on the blood pressure (BP) of patients with hypertension.

METHODS

This clinical trial was conducted on 66 military personnel who were definitively diagnosed with hypertension by a physician, and then assigned randomly into two groups as intervention (receiving mobile-based educational app) and control (receiving standard medical management but no app). Before the intervention, BP levels of both groups were measured with a calibrated sphygmomanometer. After 6 weeks, the BPs of both groups were remeasured using the same sphygmomanometer. Thereafter, descriptive and inferential statistics, including paired t-test, Mann-Whitney, Chi-square and Wilcoxon tests, were used. The data obtained were analysed using SPSS-21 software at a significance level of p<0.05.

RESULTS

Comparison of the intervention and control groups showed no statistically significant difference between the groups in systolic BP (p=0.479) and diastolic BP (p=0.851) in the pre-intervention phase, but after the intervention, systolic and diastolic BP levels were significantly lower in the intervention group than in the control group (p=0.0001).

CONCLUSION

The results suggested that the mobile-based educational app had a significant effect on reducing BP in patients with hypertension. Therefore, using this app is recommended for those military personnel with hypertension.

Repostioning of Telemedicine in Cardiovascular World Post-COVID-19 Pandemic

Background

During the COVID-19 pandemic, telemedicine is a quickest expanding service solution to provide improved access to sophisticated healthcare that is efficient, cost-effective, and time-consuming.

Methods

This analysis is evaluated on the basis of several studies that look at the history, benefits, various techniques, challenges, uses, and impact of telemedicine in the treatment of heart failure and cardiac rehabilitation as during COVID-19 outbreak.

Results

Patients avoided or refused medical treatment during COVID-19 pandemic despite the risk of illness and the threat of infections spreading. Telemedicine has become a non-traditional form of care delivery due to better access and high-end technologies such as virtual consultations, face-to-face video, smartphone visits, two-way text communication, distant patient history, and distal characteristic assessment. Remote monitoring can help manage cardiovascular disease risk factors and increase patient participation in blood pressure, heart failure data, and workout or other activity progress.

Conclusion

Based on the findings of past studies, we can infer that telemedicine is still an emerging subject in the treatment and management of cardiovascular disease. Telemedicine and similar technologies will also revolutionize healthcare services by expanding their reach and providing a big pool of database for better research and analysis.

Methods Used to Evaluate mHealth Applications for Cardiovascular Disease: A Quasi-Systematic Scoping Review

In the face of demographic change and constantly increasing health care costs, health care system decision-makers face ever greater challenges. Mobile health applications (mHealth apps) have the potential to combat this trend. However, in order to integrate mHealth apps into care structures, an evaluation of such apps is needed. In this paper, we focus on the criteria and methods of evaluating mHealth apps for cardiovascular disease and the implications for developing a widely applicable evaluation framework for mHealth interventions. Our aim is to derive substantiated patterns and starting points for future research by conducting a quasi-systematic scoping review of relevant peer-reviewed literature published in English or German between 2000 and 2021. We screened 4066 articles and identified n = 38 studies that met our inclusion criteria. The results of the data derived from these studies show that usability, motivation, and user experience were evaluated primarily using standardized questionnaires. Usage protocols and clinical outcomes were assessed primarily via laboratory diagnostics and quality-of-life questionnaires, and cost effectiveness was tested primarily based on economic measures. Based on these findings, we propose important considerations and elements for the development of a common evaluation framework for professional mHealth apps, including study designs, data collection tools, and perspectives.

Design and Evaluation of a Smartphone Medical Guidance App for Outpatients of Large-Scale Medical Institutions: A Retrospective Observational Study

BACKGROUND

The greatest stressor for outpatients is the waiting time before an examination. If the patient is able to use their smartphone to check in with the reception, the patient can wait for their examination at any location, and the burden of waiting can be reduced.

OBJECTIVE

This study aimed to report the system design and post-introductory outcomes of the Tori RinRin (TR2) system that was developed to reduce outpatient burden imposed by wait times before examination.

METHODS

The TR2 system was introduced at Tottori University Hospital, a large medical facility that accepts a daily average of 1,500 outpatients. The system, which links the hospital's electronic medical record database with patients' mobile devices, has the following two functions: 1) GPS-based examination check-in processing and 2) sending appointment notification messages via a cloud notification service. In order to evaluate the usefulness of the TR2 system, we surveyed the utilization rate of the TR2 system among outpatient, implemented a user questionnaire and polling the average time required for patients to respond to call notifications about their turn.

RESULTS

The 3 months average of TR2 users 9 months after the TR 2 system introduction was 17.9% (81,066 of 14,536 patients). In an investigation of 363 subjects, the mean examination call message response time using the TR2 system was 31 seconds (median 14 seconds). Among 166 subjects who responded to a user survey, 86.7% (144 of 166 patients) said that the system help reduce the burden of waiting time.

CONCLUSIONS

The app allowed 17.9% of outpatients at a large medical facility to check in remotely and wait for examinations anywhere. Hence, it is effective in preventing the spread of infection, especially during pandemics such as the coronavirus disease. The app reported in this study is beneficial for large medical facilities striving to reduce outpatient burden imposed by wait times.

CLINICALTRIAL

'Routine' versus 'Smart Phone Application Based - Intense' follow up of patients with acute coronary syndrome undergoing percutaneous coronary intervention: Impact on clinical outcomes and patient satisfaction

Background

Acute coronary syndrome (ACS) refers to the spectrum of clinical presentation of coronary artery disease (CAD). As a routine practice at our institute, following PCI, ACS patients are called for the first follow up after two weeks. This period of two weeks can be full of anxieties, concerns and medical issues. In this study, we planned to assess the feasibility/acceptability of smart phone application (app) based system for patient follow-up and its comparison to routine practice among patients with ACS who have undergone a PCI.

Methods

A randomized controlled trial (RCT) was conducted over a period of one year from January to December 2017. After the PCI was deemed successful, patients were recruited and enrolled based on the understanding of basic English language and operation of a smart phone. Those who consented to be part of study were then randomly allocated either the conventional follow up group or the intense follow up (routine + smart phone app based follow up) group. First co- primary outcome was composite of clinical outcomes (mortality, myocardial infarction, stroke, target vessel revascularisation, heart failure admission and emergency visit). Second co- primary outcome was patient satisfaction. The overall patient satisfaction was assessed by the patients using a five-point patient satisfaction survey instrument containing five questions with 5 marks each, in which higher scores meant more satisfaction. Secondary outcome was controlled hypertension in hypertensive patients. It was defined as systolic BP less than 130 and diastolic BP less than 80 mmHg.

Results

A cohort of 228 patients (109 in intense app-based arm; 119 in routine follow up arm) were analyzed. The result showed significant improvement in blood pressure control in hypertensive population in intense app based follow up group (76.2%) when compared to routine follow up group (45%) with p value 0.0062. The satisfaction score was significantly higher in the intense app based follow up (20.7 ± 1.29) as compared to routine follow up (16.5 ± 2.68); p value 0.0001. In the intense app based follow up 72.5% patient felt it was excellent tool (score 21-25) while 27.5% categorized it as good (score 16-20). While the routine follows up was perceived as good by most (91.6%) of the patients. Only 4.2% graded it as excellent and an equal number (4.2%) graded it as a poor way of follow up.

Conclusions

App based system shows higher satisfaction rate and comparable clinical outcome when compared to traditional hospital based follow up protocol alone. It has a high acceptance rate and thus this system should be explored further to optimize long term patient care.

[Artificial intelligence in cardiology : Relevance, current applications, and future developments]

Big data and applications of artificial intelligence (AI), such as machine learning or deep learning, will enrich healthcare in the future and become increasingly important. Among other things, they have the potential to avoid unnecessary examinations as well as diagnostic and therapeutic errors. They could enable improved, early and accelerated decision-making. In the article, the authors provide an overview of current AI-based applications in cardiology. The examples describe innovative solutions for risk assessment, diagnosis and therapy support up to patient self-management. Big data and AI serve as a basis for efficient, predictive, preventive and personalised medicine. However, the examples also show that research is needed to further develop the solutions for the benefit of the patient and the medical profession, to demonstrate the effectiveness and benefits in health care and to establish legal and ethical standards.

Systematic review of cost-effectiveness analysis of behavior change communication apps: Assessment of key methods

OBJECTIVE

Evidence backing the effectiveness of mobile health technology is growing, and behavior change communication applications (apps) are fast becoming a useful platform for behavioral health programs. However, data to support the cost-effectiveness of these interventions are limited. Suggestions for overcoming the low output of economic data include addressing the methodological challenges for conducting cost-effectiveness analysis of behavior change app programs. This study is a systematic review of cost-effectiveness analyses of behavior change communication apps and a documentation of the reported challenges for investigating their cost-effectiveness.

MATERIALS AND METHODS

Four academic databases: Medline (Ovid), CINAHL, EMBASE and Google Scholar, were searched. Eligibility criteria included original articles that use a cost-effectiveness evaluation method, published between 2008 and 2018, and in the English language.

RESULTS

Out of the 60 potentially eligible studies, 6 used cost-effectiveness analysis method and met the inclusion criteria.

CONCLUSION

The evidence to support the cost-effectiveness of behavior change communication apps is insufficient, with all studies reporting significant study challenges for estimating program costs and outcomes. The main challenges included limited or lack of cost data, inappropriate cost measures, difficulty with identifying and quantifying app effectiveness, representing app effects as Quality-adjusted Life Years, and aggregating cost and effects into a single quantitative measure like Incremental Cost Effectiveness Ratio. These challenges highlight the need for comprehensive economic evaluation methods that balance app data quality issues with practical concerns. This would likely improve the usefulness of cost-effectiveness data for decisions on adoption, implementation, scalability, sustainability, and the benefits of broader healthcare investments.

Effectiveness of continuous monitoring by activity tracker of patients undergoing chemotherapy for urothelial carcinoma

BACKGROUND

It is difficult to objectively evaluate chemotherapy-related adverse events early in elderly patients with urothelial carcinoma. A delayed response causes a reduction in quality of life (QoL). Wearable activity systems that objectively record life logs have recently been used.

OBJECTIVES

This study was undertaken to verify the reliability and effectiveness of a wearable activity system (Fitbit) to monitor subjective symptoms in an objective manner during chemotherapy for elderly patients with urothelial cancer (UC).

MATERIALS AND METHODS

This was a cohort prospective study. Elderly patients with UC were enrolled who received short hydration gemcitabine and cisplatin (shGC) combination therapy at Nagoya City University Hospital from January 2018 to March 2020. A Fitbit was used to monitor heart rate, distance moved, and cardio zone time. Heart rate was also monitored by an oscillometric method. The relationship between Fitbit recordings and perceived adverse events, such as fatigue, constipation and nausea, observed during chemotherapy was investigated using a general linear mixed effects model.

RESULTS

Twenty-one of 28 inpatients were enrolled and observed for a total of 824 days. A significant, moderately strong correlation was found between two measurements of heart rate (Pearson's r = 0.65, p < 0.05). The measurement of fatigue using Fitbit was effective (p = 0.03).

CONCLUSION

Fitbit monitoring can measure the QoL of a patient and was useful for monitoring elderly patients with UC undergoing shGC therapy in an outpatient setting. Fitbit may be useful for monitoring outpatients and their QoL during chemotherapy.

Cost-utility analysis of home-based cardiac rehabilitation as compared to usual post-discharge care: systematic review and meta-analysis of randomized controlled trials

INTRODUCTION

Determining cost-utility differences between home-based cardiac rehabilitation (HBCR) on the one hand, and usual post-discharge care (UC) on the other, can improve resource-allocation in healthcare settings.

AREAS COVERED

In June 2019, PubMed, Web of Science, Scopus, and Cochrane library were searched for randomized controlled HBCR trials. Standardized mean differences (SMDs) of cost and quality-adjusted life years (QALYs) between HBCRs and UCs were calculated using random effect models. Heterogeneity was assessed by inconsistency index (I2) and publication bias by funnel plot and Egger's regression test. Thirteen articles, representing 2,992 participants, were deemed representative for final analysis. In the meta-analysis, a significant difference with respect to QALYs favored HBCR, while no significant cost difference was observed between HBCR and UC. However, subgroup-analysis of trials with different follow-up durations revealed somewhat different results, and HBCR was found to be significantly better with regard to both cost and QALYs for patients with heart failure. Cost-utility analysis categorizing interventions as 'dominant', 'effective', 'doubtful', and 'dominated', found HBCRs dominant.

EXPERT OPINION

Although HBCR tended to be superior compared to UC in this review, larger and more robust trials addressing specific patients groups are needed for definitive results.

Estimating the Impact of Novel Digital Therapeutics in Type 2 Diabetes and Hypertension: Health Economic Analysis

BACKGROUND

Behavioral interventions can meaningfully improve cardiometabolic conditions. Digital therapeutics (DTxs) delivering these interventions may provide benefits comparable to pharmacologic therapies, displacing medications for some patients.

OBJECTIVE

Our objective was to estimate the economic impact of a digital behavioral intervention in type 2 diabetes mellitus (T2DM) and hypertension (HTN) and estimate the impact of clinical inertia on deprescribing medications.

METHODS

Decision analytic models estimated health resource savings and cost effectiveness from a US commercial payer perspective. A 3-year time horizon was most relevant to the intervention and payer. Effectiveness of the DTx in improving clinical outcomes was based on cohort studies and published literature. Health resource utilization (HRU), health state utilities, and costs were drawn from the literature with costs adjusted to 2018 dollars. Future costs and quality-adjusted life years (QALYs) were discounted at 3%. Sensitivity analyses assessed uncertainty.

RESULTS

Average HRU savings ranged from $97 to $145 per patient per month, with higher potential benefits in T2DM. Cost-effectiveness acceptability analyses using a willingness-to-pay of $50,000/QALY indicated that the intervention would be cost effective at total 3-year program costs of $6468 and $6620 for T2DM and HTN, respectively. Sensitivity analyses showed that reduced medication costs are a primary driver of potential HRU savings, and the results were robust within values tested. A resistance to deprescribe medications when a patient's clinical outcomes improve can substantially reduce the estimated economic benefits. Our models rely on estimates of clinical effectiveness drawn from limited cohort studies with DTxs and cannot account for other disease management programs that may be implemented. Performance of DTxs in real-world settings is required to further validate their economic benefits.

CONCLUSIONS

The DTxs studied may provide substantial cost savings, in part by reducing the use of conventional medications. Clinical inertia may limit the full cost savings of DTxs.

The Cost-Effectiveness of Digital Health Interventions on the Management of Cardiovascular Diseases: Systematic Review

BACKGROUND

With the advancement in information technology and mobile internet, digital health interventions (DHIs) are improving the care of cardiovascular diseases (CVDs). The impact of DHIs on cost-effective management of CVDs has been examined using the decision analytic model-based health technology assessment approach.

OBJECTIVE

The aim of this study was to perform a systematic review of the decision analytic model-based studies evaluating the cost-effectiveness of DHIs on the management of CVDs.

METHODS

A literature review was conducted in Medline, Embase, Cumulative Index to Nursing and Allied Health Literature Complete, PsycINFO, Scopus, Web of Science, Center for Review and Dissemination, and Institute for IEEE Xplore between 2001 and 2018. Studies were included if the following criteria were met: (1) English articles, (2) DHIs that promoted or delivered clinical interventions and had an impact on patients' cardiovascular conditions, (3) studies that were modeling works with health economic outcomes of DHIs for CVDs, (4) studies that had a comparative group for assessment, and (5) full economic evaluations including a cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, and cost-consequence analysis. The primary outcome collected was the cost-effectiveness of the DHIs, presented by incremental cost per additional quality-adjusted life year (QALY). The quality of each included study was evaluated using the Consolidated Health Economic Evaluation Reporting Standards.

RESULTS

A total of 14 studies met the defined criteria and were included in the review. Among the included studies, heart failure (7/14, 50%) and stroke (4/14, 29%) were two of the most frequent CVDs that were managed by DHIs. A total of 9 (64%) studies were published between 2015 and 2018 and 5 (36%) published between 2011 and 2014. The time horizon was ≤1 year in 3 studies (21%), >1 year in 10 studies (71%), and 1 study (7%) did not declare the time frame. The types of devices or technologies used to deliver the health interventions were short message service (1/14, 7%), telephone support (1/14, 7%), mobile app (1/14, 7%), video conferencing system (5/14, 36%), digital transmission of physiologic data (telemonitoring; 5/14, 36%), and wearable medical device (1/14, 7%). The DHIs gained higher QALYs with cost saving in 43% (6/14) of studies and gained QALYs at a higher cost at acceptable incremental cost-effectiveness ratio (ICER) in 57% (8/14) of studies. The studies were classified as excellent (0/14, 0%), good (9/14, 64%), moderate (4/14, 29%), and low (1/14, 7%) quality.

CONCLUSIONS

This study is the first systematic review of decision analytic model-based cost-effectiveness analyses of DHIs in the management of CVDs. Most of the identified studies were published recently, and the majority of the studies were good quality cost-effectiveness analyses with an adequate duration of time frame. All the included studies found the DHIs to be cost-effective.

A qualitative study on the design and development of an mHealth app to facilitate communication with the Deaf community: perspective of community pharmacists

PURPOSE

This study prepares the groundwork on the potential design and development of a mobile health (mHealth) app that will be able to bridge the communication gap between pharmacists and patients who are Deaf and Hard of Hearing (DHoH).

PATIENTS AND METHODS

A focus group discussion was conducted with 12 community pharmacists. Participants were recruited using snowball sampling. Audio-recordings were transcribed verbatim, and analyzed using a thematic approach.

RESULTS

Three themes were apparent: 1) suggestions for app design and content, 2) perceived benefits of the app, and 3) potential challenges related to the app. Participants believed the app would be able to facilitate and improve communication, and hence relationship, between pharmacists and the DHoH. Potential challenges of the app were highlighted, such as the need for manpower to manage the app, and its cost to this group of economically disadvantaged people. There were also concerns about privacy and security.

CONCLUSIONS

This study allowed community pharmacists, one of the end-users of the app, to provide feedback on the contents and design of the app, which would allow them to provide pharmaceutical care services to patients who are DHoH, and better serve them. Potential benefits and challenges of the app were also identified. Undoubtedly, through the mHealth app, community pharmacists will be better equipped to serve and communicate with the DHoH, and this will hopefully translate to improved health outcomes in these patients.

Mobile Applications for Patient-centered Care Coordination: A Review of Human Factors Methods Applied to their Design, Development, and Evaluation

OBJECTIVES

To examine if human factors methods were applied in the design, development, and evaluation of mobile applications developed to facilitate aspects of patient-centered care coordination.

METHODS

We searched MEDLINE and EMBASE (2013-2014) for studies describing the design or the evaluation of a mobile health application that aimed to support patients' active involvement in the coordination of their care.

RESULTS

34 papers met the inclusion criteria. Applications ranged from tools that supported self-management of specific conditions (e.g. asthma) to tools that provided coaching or education. Twelve of the 15 papers describing the design or development of an app reported the use of a human factors approach. The most frequently used methods were interviews and surveys, which often included an exploration of participants' current use of information technology. Sixteen papers described the evaluation of a patient application in practice. All of them adopted a human factors approach, typically an examination of the use of app features and/or surveys or interviews which enquired about patients' views of the effects of using the app on their behaviors (e.g. medication adherence), knowledge, and relationships with healthcare providers. No study in our review assessed the impact of mobile applications on health outcomes.

CONCLUSION

The potential of mobile health applications to assist patients to more actively engage in the management of their care has resulted in a large number of applications being developed. Our review showed that human factors approaches are nearly always adopted to some extent in the design, development, and evaluation of mobile applications.

"What Goes Around Comes Around": Lessons Learned from Economic Evaluations of Personalized Medicine Applied to Digital Medicine

BACKGROUND

The growth of "big data" and the emphasis on patient-centered health care have led to the increasing use of two key technologies: personalized medicine and digital medicine. For these technologies to move into mainstream health care and be reimbursed by insurers, it will be essential to have evidence that their benefits provide reasonable value relative to their costs. These technologies, however, have complex characteristics that present challenges to the assessment of their economic value. Previous studies have identified the challenges for personalized medicine and thus this work informs the more nascent topic of digital medicine.

OBJECTIVES

To examine the methodological challenges and future opportunities for assessing the economic value of digital medicine, using personalized medicine as a comparison.

METHODS

We focused specifically on digital biomarker technologies and multigene tests. We identified similarities in these technologies that can present challenges to economic evaluation: multiple results, results with different types of utilities, secondary findings, downstream impact (including on family members), and interactive effects.

RESULTS

Using a structured review, we found that there are few economic evaluations of digital biomarker technologies, with limited results.

CONCLUSIONS

We conclude that more evidence on the effectiveness of digital medicine will be needed but that the experiences with personalized medicine can inform what data will be needed and how such analyses can be conducted. Our study points out the critical need for typologies and terminology for digital medicine technologies that would enable them to be classified in ways that will facilitate research on their effectiveness and value.

REPRODUCIBILITY AND COMPARISON OF VISUAL ACUITY OBTAINED WITH SIGHTBOOK MOBILE APPLICATION TO NEAR CARD AND SNELLEN CHART

PURPOSE

To investigate test-retest reproducibility of visual acuities obtained with a popular mobile application (app) and to explore the agreement with the standard clinic charts.

METHODS

Records of patients who had visual acuity measured during the same routine clinic visit with Snellen chart, Rosenbaum near vision card, and SightBook mobile app were reviewed. Acuities were converted to approximate ETDRS letters for statistical purposes.

RESULTS

One hundred and twenty-six patients were identified. SightBook, Snellen, and near card acuities had excellent test-retest reproducibility. SightBook acuities were significantly different from the near card acuities (mean absolute difference of 5.4 and 6.1 letters in the right and left eyes) and the Snellen acuities (mean absolute difference of 7.7 and 7.9 letters in the right and left eyes). The agreement was also poor between the near card and the Snellen acuities (mean absolute difference of 6.4 and 7.6 letters in the right and left eyes).

CONCLUSION

The discrepancy between SightBook mobile app and the clinic charts acuities may be large; however, the results are highly reproducible. Obtaining baseline SightBook acuity allows future vision comparisons. SightBook mobile app offers a new portable vision assessment tool for the office and remote patient monitoring.

Utility of a mHealth App for Self-Management and Education of Cardiac Diseases in Spanish Urban and Rural Areas

Analyze the utility of a mobile health app named HeartKeeper in several groups of population and obtain conclusions to be applied to other similar apps. A questionnaire has been designed to evaluate the usage and utility of the HeartKeeper app. The questionnaire information was collected by collaborating cardiologists from 32 patients before and after they used the app. Patients were randomly selected with established quotas within interest groups, so that men and women, patients older or younger than 60 years old and patients living in urban or rural areas were equally represented. Using the appropriate statistical techniques we see that the HeartKeeper app was useful for patients as they qualify with 70 points (out of 100) the overall opinion of the app, it helps them remember more easily taking their pills with a mean improvement of 20.94 points (p < 0.001) and they perceive a global improvement of their health (8.28 points, p < 0.001). We also observe that these improvements do not depend, in general, on the area (urban or rural) where the patient comes from or on their sex. Although older patients needed more help to use the app and used it slightly less frequently, the improvements on several measures considered, such as remembering taking pills, breathing problems or trouble developing activities, depend significantly (p < 0.05) on age with older patients reporting higher improvements than younger ones. The results obtained with the sample of patients considered in this research prove the utility of the HeartKeeper app. This utility is similar in urban and rural areas and for patients of both sexes and, to some extent, depends on the age of the patient with older patients reporting slightly lower frequency of use but higher health improvements than younger ones.

An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases

This paper presents a robust device for automated screening of pediatric heart diseases based on our unique processing method in murmur characterization; the Arash-Band method. The present study modifies the Arash-Band method and employs output of the modified method in conjunction with the two other original techniques to extract indicative feature vectors for the screening. The extracted feature vectors are classified by using the support vector machine method. Results show that the proposed modifications significantly enhances performance of the Arash-Band in terms of the both accuracy and sensitivity as the corresponding effect sizes are sufficiently large. The proposed algorithm has been incorporated into an Android-based tablet to constitute an intelligent phonocardiogram with the automatic screening capability. In order to obtain confidence interval of the accuracy and sensitivity, an inferable statistical test is applied on our database containing the phonocardiogram signals recorded from 263 of the referrals to a hospital. The expected value of the accuracy/sensitivity is estimated to be 87.45 % / 87.29 % with a 95 % confidence interval of (80.19 % - 92.47 %) / (76.01 % - 95.78 %) exhibiting superior performance than a pediatric cardiologist who relies on conventional or even computer-assisted auscultation.