%0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e62935 %T Assessment of Digital Capabilities by 9 Countries in the Alliance for Healthy Cities Using AI: Cross-Sectional Analysis %A Lee, Hocheol %K digital capabilities %K digital health cities %K digital transformation %K Asian Forum of Healthy Cities %K assessment %K digital health %K artificial intelligence %K AI %K World Health Organization %K WHO %K healthy city %K data %K health management %K digital era %K qualitative analysis %K cross-sectional survey %K database %K digital health database %K effectiveness %K digital literacy %D 2025 %7 7.2.2025 %9 %J JMIR Form Res %G English %X Background: The Alma-Ata Declaration of 1978 initiated a global focus on universal health, supported by the World Health Organization (WHO) through healthy cities policies. The concept emerged at the 1984 Toronto “Beyond Health Care” conference, leading to WHO’s first pilot project in Lisbon in 1986. The WHO continues to support regional healthy city networks, emphasizing digital transformation and data-driven health management in the digital era. Objective: This study explored the capabilities of digital healthy cities within the framework of digital transformation, focusing on member countries of the Asian Forum of Healthy Cities. It examined the cities’ preparedness and policy needs for transitioning to digital health. Methods: A cross-sectional survey was conducted of 9 countries—Australia, Cambodia, China, Japan, South Korea, Malaysia, Mongolia, the Philippines, and Vietnam—from August 1 to September 21, 2023. The 6-section SPIRIT (setting approach and sustainability; political commitment, policy, and community participation; information and innovation; resources and research; infrastructure and intersectoral; and training) checklist was modified to assess healthy cities’ digital capabilities. With input from 3 healthy city experts, the checklist was revised for digital capabilities, renaming “healthy city” to “digital healthy city.” The revised tool comprises 8 sections with 33 items. The survey leveraged ChatGPT (version 4.0; OpenAI, Microsoft), accessed via Python (Python Software Foundation) application programming interface. The openai library was installed, and an application programming interface key was entered to use ChatGPT (version 4.0). The “GPT-4 Turbo” model command was applied. A qualitative analysis of the collected data was conducted by 5 healthy city experts through group deep-discussions. Results: The results indicate that these countries should establish networks and committees for sustainable digital healthy cities. Cambodia showed the lowest access to electricity (70%) and significant digital infrastructure disparities. Efforts to sustain digital health initiatives varied, with countries such as Korea focusing on telemedicine, while China aimed to build a comprehensive digital health database, highlighting the need for tailored strategies in promoting digital healthy cities. Life expectancy was the highest in the Republic of Korea and Japan (both 84 y). Access to electricity was the lowest in Cambodia (70%) with the remaining countries having had 95% or higher access. The internet use rate was the highest in Malaysia (97.4%), followed by the Republic of Korea (97.2%), Australia (96.2%), and Japan (82.9%). Conclusions: This study highlights the importance of big data-driven policies and personal information protection systems. Collaborative efforts across sectors for effective implementation of digital healthy cities. The findings suggest that the effectiveness of digital healthy cities is diminished without adequate digital literacy among managers and users, suggesting the need for policies to improve digital literacy. %R 10.2196/62935 %U https://formative.jmir.org/2025/1/e62935 %U https://doi.org/10.2196/62935 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 13 %N %P e46047 %T Smartphone-Based Care Platform Versus Traditional Care in Primary Knee Arthroplasty in the United States: Cost Analysis %A Lonner,Jess H %A Naidu-Helm,Ashwini %A Van Andel,David %A Anderson,Mike B %A Ditto,Richard %A Redfern,Roberta E %A Foran,Jared %K telerehabilitation %K telehealth %K telemedicine %K rehabilitation %K physiotherapy %K mobile health %K knee arthroplasty %D 2025 %7 3.2.2025 %9 %J JMIR Mhealth Uhealth %G English %X Cost savings were achieved with the use of a smartphone-based care management platform, considering several health care resources following knee arthroplasty procedures without negatively impacting clinical outcomes.Trial registration: ClinicalTrials.gov NCT03737149; https://clinicaltrials.gov/study/NCT03737149 %R 10.2196/46047 %U https://mhealth.jmir.org/2025/1/e46047 %U https://doi.org/10.2196/46047 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e57385 %T Digital Health Innovations to Catalyze the Transition to Value-Based Health Care %A Zhang,Lan %A Bullen,Christopher %A Chen,Jinsong %K digital health %K value-based health care %K VBHC %K patient-reported outcome measures %K PROM %K digital transformation %K health care innovation %K patient-centric care %K health technology %K patient-reported outcome %K PRO %K outcome measure %K telehealth %K telemedicine %K eHealth %K personalized %K customized %K engagement %K patient-centered care %K standardization %K implementation %D 2025 %7 20.1.2025 %9 %J JMIR Med Inform %G English %X The health care industry is currently going through a transformation due to the integration of technologies and the shift toward value-based health care (VBHC). This article explores how digital health solutions play a role in advancing VBHC, highlighting both the challenges and opportunities associated with adopting these technologies. Digital health, which includes mobile health, wearable devices, telehealth, and personalized medicine, shows promise in improving diagnostic accuracy, treatment options, and overall health outcomes. The article delves into the concept of transformation in health care by emphasizing its potential to reform care delivery through data communication, patient engagement, and operational efficiency. Moreover, it examines the principles of VBHC, with a focus on patient outcomes, and emphasizes how digital platforms play a role in treatment among tertiary hospitals by using patient-reported outcome measures. The article discusses challenges that come with implementing VBHC, such as stakeholder engagement and standardization of patient-reported outcome measures. It also highlights the role played by health innovators in facilitating the transition toward VBHC models. Through real-life case examples, this article illustrates how digital platforms have had an impact on efficiencies, patient outcomes, and empowerment. In conclusion, it envisions directions for solutions in VBHC by emphasizing the need for interoperability, standardization, and collaborative efforts among stakeholders to fully realize the potential of digital transformation in health care. This research highlights the impact of digital health in creating a health care system that focuses on providing high-quality, efficient, and patient-centered care. %R 10.2196/57385 %U https://medinform.jmir.org/2025/1/e57385 %U https://doi.org/10.2196/57385 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e65281 %T Digital Solutions for Health Services and Systems Management: Narrative Review of Certified Software Features in the Brazilian Market %A Bellei,Ericles Andrei %A Domenighi,Pedro Rafael %A Freitas,Carla Maria Dal Sasso %A De Marchi,Ana Carolina Bertoletti %K health services administration %K health information management %K decision support systems %K digital health %K Brazil %K certified software %K features %K systems management %K health services %K interoperability %K digital solutions %D 2024 %7 29.11.2024 %9 %J JMIR Med Inform %G English %X The paper reviews digital solutions for health services management in Brazil, focusing on certified software features. It reveals the integration of various functionalities in operational, financial, and clinical needs simultaneously, which are critical for enhancing operational efficiency and patient care. This study highlights the integration of critical features like interoperability, compliance management, and data-driven decision support, although advancing innovation and integration remains essential for broader impact. %R 10.2196/65281 %U https://medinform.jmir.org/2024/1/e65281 %U https://doi.org/10.2196/65281 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e50378 %T Efficacy of a Multimodal Digital Behavior Change Intervention on Lifestyle Behavior, Cardiometabolic Biomarkers, and Medical Expenditure: Protocol for a Randomized Controlled Trial %A Howard-Wilson,Sakeina %A Ching,Jack %A Gentile,Sherri %A Ho,Martin %A Garcia,Alex %A Ayturk,Didem %A Lazar,Peter %A Hammerquist,Nova %A McManus,David %A Barton,Bruce %A Bird,Steven %A Moore,John %A Soni,Apurv %+ Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Avenue North, Worcester, MA, 01655, United States, 1 (774) 455 6571, sakeina.howard-wilson2@umassmed.edu %K health behavior %K fitness %K digital devices %K lifestyle change %K cardiovascular disease %K chronic disease %K physical activity %K nutrition %K sleep %K mindfulness %D 2024 %7 30.10.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: The US Preventive Services Task Force recommends providers offer individualized healthy behavior interventions for all adults, independent of their risk of cardiovascular disease. While strong evidence exists to support disease-specific programs designed to improve multiple lifestyle behaviors, approaches to adapting these interventions for a broader population are not well established. Digital behavior change interventions (DBCIs) hold promise as a more generalizable and scalable approach to overcome the resource and time limitations that traditional behavioral intervention programs face, especially within an occupational setting. Objective: We aimed to evaluate the efficacy of a multimodal DBCI on (1) self-reported behaviors of physical activity, nutrition, sleep, and mindfulness; (2) cardiometabolic biomarkers; and (3) chronic disease–related medical expenditure. Methods: We conducted a 2-arm randomized controlled trial for 12 months among employees of an academic health care facility in the United States. The intervention arm received a scale, a smartphone app, an activity tracker, a video library for healthy behavior recommendations, and an on-demand health coach. The control arm received standard employer-provided health and wellness benefits. The primary outcomes of the study included changes in self-reported lifestyle behaviors, cardiometabolic biomarkers, and chronic disease–related medical expenditure. We collected health behavior data via baseline and quarterly web-based surveys, biometric measures via clinic visits at baseline and 12 months, and identified relevant costs through claims datasets. Results: A total of 603 participants were enrolled and randomized to the intervention (n=300, 49.8%) and control arms (n=303, 50.2%). The average age was 46.7 (SD 11.2) years, and the majority of participants were female (80.3%, n=484), White (85.4%, n=504), and non-Hispanic (90.7%, n=547), with no systematic differences in baseline characteristics observed between the study arms. We observed retention rates of 86.1% (n=519) for completing the final survey and 77.9% (n=490) for attending the exit visit. Conclusions: This study represents the largest and most comprehensive evaluation of DBCIs among participants who were not selected based on their underlying condition to assess its impact on behavior, cardiometabolic biomarkers, and medical expenditure. Trial Registration: ClinicalTrials.gov NCT04712383; https://clinicaltrials.gov/study/NCT04712383 International Registered Report Identifier (IRRID): RR1-10.2196/50378 %M 39475852 %R 10.2196/50378 %U https://www.researchprotocols.org/2024/1/e50378 %U https://doi.org/10.2196/50378 %U http://www.ncbi.nlm.nih.gov/pubmed/39475852 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e55544 %T Cost-Effectiveness of Digital Mental Health Versus Usual Care During Humanitarian Crises in Lebanon: Pragmatic Randomized Trial %A Abi Hana,Racha %A Abi Ramia,Jinane %A Burchert,Sebastian %A Carswell,Kenneth %A Cuijpers,Pim %A Heim,Eva %A Knaevelsrud,Christine %A Noun,Philip %A Sijbrandij,Marit %A van Ommeren,Mark %A van’t Hof,Edith %A Wijnen,Ben %A Zoghbi,Edwina %A El Chammay,Rabih %A Smit,Filip %+ Clinical, Neuro- and Developmental Psychology Department, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam, 1105 1081 HV, Netherlands, 31 3978968, rasha_abihana@hotmail.com %K depression %K internet-based intervention %K economic evaluation %K Lebanese %K Syrian %K digital mental health %K digital health %K mental health %K usual care %K Lebanon %K anxiety %K stress-related disorders %K treatment %K symptoms %K large randomized controlled trial %K effectiveness %D 2024 %7 29.5.2024 %9 Original Paper %J JMIR Ment Health %G English %X Background: There is evidence from meta-analyses and systematic reviews that digital mental health interventions for depression, anxiety, and stress-related disorders tend to be cost-effective. However, no such evidence exists for guided digital mental health care in low and middle-income countries (LMICs) facing humanitarian crises, where the needs are highest. Step-by-Step (SbS), a digital mental health intervention for depression, anxiety, and stress-related disorders, proved to be effective for Lebanese citizens and war-affected Syrians residing in Lebanon. Assessing the cost-effectiveness of SbS is crucial because Lebanon’s overstretched health care system must prioritize cost-effective treatment options in the face of continuing humanitarian and economic crises. Objective: This study aims to assess the cost-effectiveness of SbS in a randomized comparison with enhanced usual care (EUC). Methods: The cost-effectiveness analysis was conducted alongside a pragmatic randomized controlled trial in 2 parallel groups comparing SbS (n=614) with EUC (n=635). The primary outcome was cost (in US $ for the reference year 2019) per treatment response of depressive symptoms, defined as >50% reduction of depressive symptoms measured using the Patient Health Questionnaire (PHQ). The secondary outcome was cost per remission of depressive symptoms, defined as a PHQ score <5 at last follow-up (5 months post baseline). The evaluation was conducted first from the health care perspective then from the societal perspective. Results: Taking the health care perspective, SbS had an 80% probability to be regarded as cost-effective compared with EUC when there is a willingness to pay US $220 per additional treatment response or US $840 per additional remission. Taking the wider societal perspective, SbS had a >75% probability to be cost-saving while gaining response or remission. Conclusions: To our knowledge, this study is the first cost-effectiveness analysis based on a large randomized controlled trial (n=1249) of a guided digital mental health intervention in an LMIC. From the principal findings, 2 implications flowed, from the (1) health care perspective and (2) wider societal perspective. First, our findings suggest that SbS is associated with greater health benefits, albeit for higher costs than EUC. It is up to decision makers in health care to decide if they find the balance between additional health gains and additional health care costs acceptable. Second, as seen from the wider societal perspective, there is a substantial likelihood that SbS is not costing more than EUC but is associated with cost-savings as SBS participants become more productive, thus offsetting their health care costs. This finding may suggest to policy makers that it is in the interest of both population health and the wider Lebanese economy to implement SbS on a wide scale. In brief, SbS may offer a scalable, potentially cost-saving response to humanitarian emergencies in an LMIC. Trial Registration: ClinicalTrials.gov NCT03720769; https://clinicaltrials.gov/ct2/show/NCT03720769 International Registered Report Identifier (IRRID): RR2-10.2196/21585 %M 38810255 %R 10.2196/55544 %U https://mental.jmir.org/2024/1/e55544 %U https://doi.org/10.2196/55544 %U http://www.ncbi.nlm.nih.gov/pubmed/38810255 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e55483 %T Economic Evaluation of a Web Application Implemented in Primary Care for the Treatment of Depression in Patients With Type 2 Diabetes Mellitus: Multicenter Randomized Controlled Trial %A Varela-Moreno,Esperanza %A Anarte-Ortiz,Maria Teresa %A Jodar-Sanchez,Francisco %A Garcia-Palacios,Azucena %A Monreal-Bartolomé,Alicia %A Gili,Margalida %A García-Campayo,Javier %A Mayoral-Cleries,Fermin %+ Department of Applied Economics, Faculty of Economics and Business Administration, University of Malaga, C. El Ejido, 6, Malaga, 29071, Spain, 34 951976620, fjodar@uma.es %K depression %K depressive %K type 2 %K diabetes %K diabetic %K type 2 diabetes mellitus %K eHealth %K web-based intervention %K efficacy %K economic evaluation %K cost-effectiveness %K cost-utility %K randomized controlled trial %K RCT %K randomized %K controlled trial %K controlled trials %K cost %K costs %K economic %K economics %K web based %K internet based %K CBT %K psychotherapy %K cognitive behavioral therapy %K cognitive behavioral therapy %K mental health %D 2024 %7 16.5.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Depressive disorder and type 2 diabetes mellitus (T2DM) are prevalent in primary care (PC). Pharmacological treatment, despite controversy, is commonly chosen due to resource limitations and difficulties in accessing face-to-face interventions. Depression significantly impacts various aspects of a person’s life, affecting adherence to medical prescriptions and glycemic control and leading to future complications and increased health care costs. To address these challenges, information and communication technologies (eg, eHealth) have been introduced, showing promise in improving treatment continuity and accessibility. However, while eHealth programs have demonstrated effectiveness in alleviating depressive symptoms, evidence regarding glycemic control remains inconclusive. This randomized controlled trial aimed to test the efficacy of a low-intensity psychological intervention via a web app for mild-moderate depressive symptoms in individuals with T2DM compared with treatment as usual (TAU) in PC. Objective: This study aimed to analyze the cost-effectiveness and cost-utility of a web-based psychological intervention to treat depressive symptomatology in people with T2DM compared with TAU in a PC setting. Methods: A multicenter randomized controlled trial was conducted with 49 patients with T2DM, depressive symptoms of moderate severity, and glycosylated hemoglobin (HbA1c) of 7.47% in PC settings. Patients were randomized to TAU (n=27) or a web-based psychological treatment group (n=22). This web-based treatment consisted of cognitive behavioral therapy, improvement of diabetes self-care behaviors, and mindfulness. Cost-effectiveness analysis for the improvement of depressive symptomatology was conducted based on reductions in 3, 5, or 50 points on the Patient Health Questionnaire–9 (PHQ-9). The efficacy of diabetes control was estimated based on a 0.5% reduction in HbA1c levels. Follow-up was performed at 3 and 6 months. The cost-utility analysis was performed based on quality-adjusted life years. Results: Efficacy analysis showed that the web-based treatment program was more effective in improving depressive symptoms than TAU but showed only a slight improvement in HbA1c. Incremental cost-effectiveness ratios of 186.76 for a 3-point reduction in PHQ-9 and 206.31 for reductions of 5 and 50 percentage points were obtained. In contrast, the incremental cost-effectiveness ratio for improving HbA1c levels amounted to €1510.90 (€1=US $1.18 in 2018) per participant. The incremental cost-utility ratio resulted in €4119.33 per quality-adjusted life year gained. Conclusions: The intervention, using web-based modules incorporating cognitive behavioral therapy tools, diabetes self-care promotion, and mindfulness, effectively reduced depressive symptoms and enhanced glycemic control in patients with T2DM. Notably, it demonstrated clinical efficacy and economic efficiency. This supports the idea that eHealth interventions not only benefit patients clinically but also offer cost-effectiveness for health care systems. The study emphasizes the importance of including specific modules to enhance diabetes self-care behaviors in future web-based psychological interventions, emphasizing personalization and adaptation for this population. Trial Registration: ClinicalTrials.gov NCT03426709; https://clinicaltrials.gov/study/NCT03426709 International Registered Report Identifier (IRRID): RR2-10.1186/S12888-019-2037-3 %M 38754101 %R 10.2196/55483 %U https://mhealth.jmir.org/2024/1/e55483 %U https://doi.org/10.2196/55483 %U http://www.ncbi.nlm.nih.gov/pubmed/38754101 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53500 %T Economic Evaluations of Digital Health Interventions for Patients With Heart Failure: Systematic Review %A Zakiyah,Neily %A Marulin,Dita %A Alfaqeeh,Mohammed %A Puspitasari,Irma Melyani %A Lestari,Keri %A Lim,Ka Keat %A Fox-Rushby,Julia %+ Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Jl. Raya Bandung Sumedang KM 21, Bandung, 45363, Indonesia, 62 22 7796200, neily.zakiyah@unpad.ac.id %K digital health %K telemonitoring %K telehealth %K heart failure %K cost-effectiveness %K systematic review %K mobile phone %D 2024 %7 30.4.2024 %9 Review %J J Med Internet Res %G English %X 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 %M 38687991 %R 10.2196/53500 %U https://www.jmir.org/2024/1/e53500 %U https://doi.org/10.2196/53500 %U http://www.ncbi.nlm.nih.gov/pubmed/38687991 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e44574 %T Digital Alcohol Interventions Could Be Part of the Societal Response to Harmful Consumption, but We Know Little About Their Long-Term Costs and Health Outcomes %A Ulfsdotter Gunnarsson,Katarina %A Henriksson,Martin %A Bendtsen,Marcus %+ Department of Health, Medicine, and Caring Sciences, Linköping University, Campus US, Linköping, 58183, Sweden, 46 13281000, katarina.ulfsdotter.gunnarsson@liu.se %K alcohol %K health economics %K telemedicine %K psychological harm %K eHealth %K digital intervention %K decision-making %D 2024 %7 27.3.2024 %9 Viewpoint %J J Med Internet Res %G English %X Alcohol consumption causes both physical and psychological harm and is a leading risk factor for noncommunicable diseases. Digital alcohol interventions have been found to support those looking for help by giving them tools for change. However, whether digital interventions can help tackle the long-term societal consequences of harmful alcohol consumption in a cost-effective manner has not been adequately evaluated. In this Viewpoint, we propose that studies of digital alcohol interventions rarely evaluate the consequences of wider dissemination of the intervention under study, and that when they do, they do not take advantage of modeling techniques that allow for appropriately studying consequences over a longer time horizon than the study period when the intervention is tested. We argue that to help decision-makers to prioritize resources for research and dissemination, it is important to model long-term costs and health outcomes. Further, this type of modeling gives important insights into the context in which interventions are studied and highlights where more research is required and where sufficient evidence is available. The viewpoint therefore invites the researcher not only to reflect on which interventions to study but also how to evaluate their long-term consequences. %M 38536228 %R 10.2196/44574 %U https://www.jmir.org/2024/1/e44574 %U https://doi.org/10.2196/44574 %U http://www.ncbi.nlm.nih.gov/pubmed/38536228 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e51841 %T Effectiveness of Telemonitoring in Reducing Hospitalization and Associated Costs for Patients With Heart Failure in Finland: Nonrandomized Pre-Post Telemonitoring Study %A Kokkonen,Jorma %A Mustonen,Pirjo %A Heikkilä,Eija %A Leskelä,Riikka-Leena %A Pennanen,Paula %A Krühn,Kati %A Jalkanen,Arto %A Laakso,Jussi-Pekka %A Kempers,Jari %A Väisänen,Sami %A Torkki,Paulus %+ Tampere Heart Hospital, Elämänaukio 1, Tampere, 33520, Finland, 358 50 5981078, sydanjopi@gmail.com %K cost %K Finland %K heart failure %K hospital %K resource use %K telemonitoring %D 2024 %7 7.2.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Many patients with chronic heart failure (HF) experience a reduced health status, leading to readmission after hospitalization despite receiving conventional care. Telemonitoring approaches aim to improve the early detection of HF decompensations and prevent readmissions. However, knowledge about the impact of telemonitoring on preventing readmissions and related costs remains scarce. Objective: This study assessed the effectiveness of adding a telemonitoring solution to the standard of care (SOC) for the prevention of hospitalization and related costs in patients with HF in Finland. Methods: We performed a nonrandomized pre-post telemonitoring study to estimate health care costs and resource use during 6 months on SOC followed by 6 months on SOC with a novel telemonitoring solution. The telemonitoring solution consisted of a digital platform for patient-reported symptoms and daily weight and blood pressure measurements, automatically generated alerts triggering phone calls with secondary care nurses, and rapid response to alerts by treating physicians. Telemonitoring solution data were linked to patient register data on primary care, secondary care, and hospitalization. The patient register of the Southern Savonia Social and Health Care Authority (Essote) was used. Eligible patients had at least 1 hospital admission within the last 12 months and self-reported New York Heart Association class II-IV from the central hospital in the Southern Savonia region. Results: Out of 50 recruited patients with HF, 43 completed the study and were included in the analysis. The hospitalization-related cost decreased (49%; P=.03) from €2189 (95% CI €1384-€2994; a currency exchange rate of EUR €1=US $1.10589 is applicable) during SOC to €1114 (95% CI €425-€1803) during telemonitoring. The number of patients with at least 1 hospitalization due to HF was reduced by 70% (P=.002) from 20 (47%) out of 43patients during SOC to 6 (14%) out of 43 patients in telemonitoring. The estimated mean total health care cost per patient was €3124 (95% CI €2212-€4036) during SOC and €2104 (95% CI €1313-€2895) during telemonitoring, resulting in a 33% reduction (P=.07) in costs with telemonitoring. Conclusions: The results suggest that the telemonitoring solution can reduce hospital-related costs for patients with HF with a recent hospital admission. %M 38324366 %R 10.2196/51841 %U https://mhealth.jmir.org/2024/1/e51841 %U https://doi.org/10.2196/51841 %U http://www.ncbi.nlm.nih.gov/pubmed/38324366 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e48229 %T Testing the Effect of a Smartphone App on Hospital Admissions and Sedentary Behavior in Cardiac Rehabilitation Participants: ToDo-CR Randomized Controlled Trial %A Patterson,Kacie %A Davey,Rachel %A Keegan,Richard %A Niyonsenga,Theo %A Mohanty,Itismita %A Bowen,Sarah %A Regan,Elizabeth %A Lander,Michelle %A van Berlo,Sander %A Freene,Nicole %+ Health Research Institute, Faculty of Health, University of Canberra, University Drive, Bruce, ACT, 2617, Australia, 61 2 6201 5550, Kacie.Patterson@canberra.edu.au %K mobile health %K secondary prevention %K cardiovascular disease %K sedentary behavior %K hospital admissions %K cost-effectiveness %K mobile phone %D 2023 %7 3.10.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X 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 %M 37788043 %R 10.2196/48229 %U https://mhealth.jmir.org/2023/1/e48229 %U https://doi.org/10.2196/48229 %U http://www.ncbi.nlm.nih.gov/pubmed/37788043 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e49003 %T Digital Health Reimbursement Strategies of 8 European Countries and Israel: Scoping Review and Policy Mapping %A van Kessel,Robin %A Srivastava,Divya %A Kyriopoulos,Ilias %A Monti,Giovanni %A Novillo-Ortiz,David %A Milman,Ran %A Zhang-Czabanowski,Wojciech Wilhelm %A Nasi,Greta %A Stern,Ariel Dora %A Wharton,George %A Mossialos,Elias %+ LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, United Kingdom, 44 7772 707841, e.a.mossialos@lse.ac.uk %K digital health %K telehealth %K telemedicine %K reimbursement %K policy %K Europe %K policy mapping %K mapping %K pricing %K digital health app %K application %K health care ecosystem %K framework %K integration %D 2023 %7 29.9.2023 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: The adoption of digital health care within health systems is determined by various factors, including pricing and reimbursement. The reimbursement landscape for digital health in Europe remains underresearched. Although various emergency reimbursement decisions were made during the COVID-19 pandemic to enable health care delivery through videoconferencing and asynchronous care (eg, digital apps), research so far has primarily focused on the policy innovations that facilitated this outside of Europe. Objective: This study examines the digital health reimbursement strategies in 8 European countries (Belgium, France, Germany, Italy, the Netherlands, Poland, Sweden, and the United Kingdom) and Israel. Methods: We mapped available digital health reimbursement strategies using a scoping review and policy mapping framework. We reviewed the literature on the MEDLINE, Embase, Global Health, and Web of Science databases. Supplementary records were identified through Google Scholar and country experts. Results: Our search strategy yielded a total of 1559 records, of which 40 (2.57%) were ultimately included in this study. As of August 2023, digital health solutions are reimbursable to some extent in all studied countries except Poland, although the mechanism of reimbursement differs significantly across countries. At the time of writing, the pricing of digital health solutions was mostly determined through discussions between national or regional committees and the manufacturers of digital health solutions in the absence of value-based assessment mechanisms. Financing digital health solutions outside traditional reimbursement schemes was possible in all studied countries except Poland and typically occurs via health innovation or digital health–specific funding schemes. European countries have value-based pricing frameworks that range from nonexistent to embryonic. Conclusions: Studied countries show divergent approaches to the reimbursement of digital health solutions. These differences may complicate the ability of patients to seek cross-country health care in another country, even if a digital health app is available in both countries. Furthermore, the fragmented environment will present challenges for developers of such solutions, as they look to expand their impact across countries and health systems. An increased emphasis on developing a clear conceptualization of digital health, as well as value-based pricing and reimbursement mechanisms, is needed for the sustainable integration of digital health. This study can therein serve as a basis for further, more detailed research as the field of digital health reimbursement evolves. %M 37773610 %R 10.2196/49003 %U https://mhealth.jmir.org/2023/1/e49003 %U https://doi.org/10.2196/49003 %U http://www.ncbi.nlm.nih.gov/pubmed/37773610 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 10 %N %P e47172 %T Economic Evaluation of Telerehabilitation: Systematic Literature Review of Cost-Utility Studies %A Baffert,Sandrine %A Hadouiri,Nawale %A Fabron,Cécile %A Burgy,Floriane %A Cassany,Aurelia %A Kemoun,Gilles %+ Department of Clinical Research, ELSAN, 58 Bis rue de la Boétie, Paris, 75008, France, 33 6 38 22 94 11, recherche-clinique@elsan.care %K telerehabilitation %K cost-effectiveness %K quality-adjusted life year %K economic evaluation %K cost %K rehabilitation %K systematic review %D 2023 %7 5.9.2023 %9 Review %J JMIR Rehabil Assist Technol %G English %X Background: Telerehabilitation could benefit a large population by increasing adherence to rehabilitation protocols. Objective: Our objective was to review and discuss the use of cost-utility approaches in economic evaluations of telerehabilitation interventions. Methods: A review of the literature on PubMed, Scopus, Centres for Review and Dissemination databases (including the HTA database, the Database of Abstracts of Reviews of Effects, and the NHS Economic Evaluation Database), Cochrane Library, and ClinicalTrials.gov (last search on February 8, 2021) was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The inclusion criteria were defined in accordance with the PICOS (population, intervention, comparison, outcomes, and study design) system: the included studies had to evaluate patients in rehabilitation therapy for all diseases and disorders (population) through exercise-based telerehabilitation (intervention) and had to have a control group that received face-to-face rehabilitation (comparison), and these studies had to evaluate effectiveness through gain in quality of life (outcome) and used the design of randomized and controlled clinical studies (study). Results: We included 11 economic evaluations, of which 6 concerned cardiovascular diseases. Several types of interventions were assessed as telerehabilitation, consisting in monitoring of rehabilitation at home (monitored by physicians) or a rehabilitation program with exercise and an educational intervention at home alone. All studies were based on randomized clinical trials and used a validated health-related quality of life instrument to describe patients’ health states. Four evaluations used the EQ-5D, 1 used the EQ-5D-5L, 2 used the EQ-5D-3L, 3 used the Short-Form Six-Dimension questionnaire, and 1 used the 36-item Short Form survey. The mean quality-adjusted life years gained using telerehabilitation services varied from –0.09 to 0.89. These results were reported in terms of the probability that the intervention was cost-effective at different thresholds for willingness-to-pay values. Most studies showed results about telerehabilitation as dominant (ie, more effective and less costly) together with superiority or noninferiority in outcomes. Conclusions: There is evidence to support telerehabilitation as a cost-effective intervention for a large population among different disease areas. There is a need for conducting cost-effectiveness studies in countries because the available evidence has limited generalizability in such countries. Trial Registration: PROSPERO CRD42021248785; https://tinyurl.com/4xurdvwf %M 37669089 %R 10.2196/47172 %U https://rehab.jmir.org/2023/1/e47172 %U https://doi.org/10.2196/47172 %U http://www.ncbi.nlm.nih.gov/pubmed/37669089 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e47473 %T The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study %A Mitchell,Ellen Siobhan %A Fabry,Alexander %A Ho,Annabell Suh %A May,Christine N %A Baldwin,Matthew %A Blanco,Paige %A Smith,Kyle %A Michaelides,Andreas %A Shokoohi,Mostafa %A West,Michael %A Gotera,Kim %A El Massad,Omnya %A Zhou,Anna %+ Academic Research, Noom, Inc, 450 W 33rd St, New York City, NY, 10001, United States, 1 8882665071, christinem@noom.com %K mobile health %K mHealth %K obesity %K overweight %K Noom Weight %K digital weight loss intervention %K health care resource utilization %K costs %K electronic health record %K EHR %K insurance claims %K inverse probability of treatment weighting %K IPTW %K mobile phone %D 2023 %7 24.8.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The Noom Weight program is a smartphone-based weight management program that uses cognitive behavioral therapy techniques to motivate users to achieve weight loss through a comprehensive lifestyle intervention. Objective: This retrospective database analysis aimed to evaluate the impact of Noom Weight use on health care resource utilization (HRU) and health care costs among individuals with overweight and obesity. Methods: Electronic health record data, insurance claims data, and Noom Weight program data were used to conduct the analysis. The study included 43,047 Noom Weight users and 14,555 non–Noom Weight users aged between 18 and 80 years with a BMI of ≥25 kg/m² and residing in the United States. The index date was defined as the first day of a 3-month treatment window during which Noom Weight was used at least once per week on average. Inverse probability treatment weighting was used to balance sociodemographic covariates between the 2 cohorts. HRU and costs for inpatient visits, outpatient visits, telehealth visits, surgeries, and prescriptions were analyzed. Results: Within 12 months after the index date, Noom Weight users had less inpatient costs (mean difference [MD] −US $20.10, 95% CI −US $30.08 to −US $10.12), less outpatient costs (MD −US $124.33, 95% CI −US $159.76 to −US $88.89), less overall prescription costs (MD −US $313.82, 95% CI −US $565.42 to −US $62.21), and less overall health care costs (MD −US $450.39, 95% CI −US $706.28 to −US $194.50) per user than non–Noom Weight users. In terms of HRU, Noom Weight users had fewer inpatient visits (MD −0.03, 95% CI −0.04 to −0.03), fewer outpatient visits (MD −0.78, 95% CI −0.93 to −0.62), fewer surgeries (MD −0.01, 95% CI −0.01 to 0.00), and fewer prescriptions (MD −1.39, 95% CI −1.76 to −1.03) per user than non–Noom Weight users. Among a subset of individuals with 24-month follow-up data, Noom Weight users incurred lower overall prescription costs (MD −US $1139.52, 95% CI −US $1972.21 to −US $306.83) and lower overall health care costs (MD −US $1219.06, 95% CI −US $2061.56 to −US $376.55) per user than non–Noom Weight users. The key differences were associated with reduced prescription use. Conclusions: Noom Weight use is associated with lower HRU and costs than non–Noom Weight use, with potential cost savings of up to US $1219.06 per user at 24 months after the index date. These findings suggest that Noom Weight could be a cost-effective weight management program for individuals with overweight and obesity. This study provides valuable evidence for health care providers and payers in evaluating the potential benefits of digital weight loss interventions such as Noom Weight. %M 37616049 %R 10.2196/47473 %U https://mhealth.jmir.org/2023/1/e47473 %U https://doi.org/10.2196/47473 %U http://www.ncbi.nlm.nih.gov/pubmed/37616049 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e44585 %T Economic Evaluation of Digital Therapeutic Care Apps for Unsupervised Treatment of Low Back Pain: Monte Carlo Simulation %A Lewkowicz,Daniel %A Bottinger,Erwin %A Siegel,Martin %+ Digital Health Center, Hasso Plattner Insitute, University of Potsdam, Prof.-Dr.-Helmert-Straße 2-3, Potsdam, 14482, Germany, 49 331 55094, daniel.lewkowicz@hpi.de %K cost-utility analysis %K cost %K probabilistic sensitivity analysis %K Monte Carlo simulation %K low back pain %K pain %K economic %K cost-effectiveness %K Markov model %K digital therapy %K digital health app %K mHealth, mobile health %K health app %K mobile app %K orthopedic %K QUALY %K DALY %K quality-adjusted life years %K disability-adjusted life years %K time horizon %K veteran %K statistics %D 2023 %7 29.6.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany. Objective: The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results. Methods: The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany. Results: The Monte Carlo simulation yielded on average a €135.97 (a currency exchange rate of EUR €1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional €34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently €239.96 to €164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%. Conclusions: Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps. %M 37384379 %R 10.2196/44585 %U https://mhealth.jmir.org/2023/1/e44585 %U https://doi.org/10.2196/44585 %U http://www.ncbi.nlm.nih.gov/pubmed/37384379 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43980 %T Effectiveness and Medicoeconomic Evaluation of Home Monitoring of Patients With Mild COVID-19: Covidom Cohort Study %A Jaulmes,Luc %A Yordanov,Youri %A Descamps,Alexandre %A Durand-Zaleski,Isabelle %A Dinh,Aurélien %A Jourdain,Patrick %A Dechartres,Agnès %+ Centre de pharmaco-épidémiologie de l’APHP, Dépt. de Santé Publique, Hôpital Pitié Salpêtrière, Sorbonne Université, AP-HP, 47-83 boulevard de l'Hôpital, Paris, 75013, France, 33 1 42 16 03 25, lucjaulmes+jmir@pm.me %K COVID-19 %K Covidom %K home monitoring %K telehealth %K tele-surveillance %K primary outcome %K remote monitoring %K digital health intervention %K emergency medical service %K patient care %K digital care %K mobile phone %D 2023 %7 23.6.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Covidom was a telemonitoring solution for home monitoring of patients with mild to moderate COVID-19, deployed in March 2020 in the Greater Paris area in France to alleviate the burden on the health care system. The Covidom solution included a free mobile application with daily monitoring questionnaires and a regional control center to quickly handle patient alerts, including dispatching emergency medical services when necessary. Objective: This study aimed to provide an overall evaluation of the Covidom solution 18 months after its inception in terms of effectiveness, safety, and cost. Methods: Our primary outcome was to measure effectiveness using the number of handled alerts, response escalation, and patient-reported medical contacts outside of Covidom. Then, we analyzed the safety of Covidom by assessing its ability to detect clinical worsening, defined as hospitalization or death, and the number of patients with clinical worsening without any preceding alert. We evaluated the cost of Covidom and compared the cost of hospitalization for Covidom and non-Covidom patients with mild COVID-19 cases seen in the emergency departments of the largest network of hospitals in the Greater Paris area (Assistance Publique-Hôpitaux de Paris). Finally, we reported on user satisfaction. Results: Of the 60,073 patients monitored by Covidom, the regional control center handled 285,496 alerts and dispatched emergency medical services 518 times. Of the 13,204 respondents who responded to either of the follow-up questionnaires, 65.8% (n=8690) reported having sought medical care outside the Covidom solution during their monitoring period. Of the 947 patients who experienced clinical worsening while adhering to daily monitoring, only 35 (3.7%) did not previously trigger alerts (35 were hospitalized, including 1 who died). The average cost of Covidom was €54 (US $1=€0.8614) per patient, and the cost of hospitalization for COVID-19 worsening was significantly lower in Covidom than in non-Covidom patients with mild COVID-19 cases seen in the emergency departments of Assistance Publique-Hôpitaux de Paris. The patients who responded to the satisfaction questionnaire had a median rating of 9 (out of 10) for the likelihood of recommending Covidom. Conclusions: Covidom may have contributed to alleviating the pressure on the health care system in the initial months of the pandemic, although its impact was lower than anticipated, with a substantial number of patients having consulted outside of Covidom. Covidom seems to be safe for home monitoring of patients with mild to moderate COVID-19. %M 37134021 %R 10.2196/43980 %U https://www.jmir.org/2023/1/e43980 %U https://doi.org/10.2196/43980 %U http://www.ncbi.nlm.nih.gov/pubmed/37134021 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 7 %N %P e45611 %T Smartphone-Based Remote Monitoring in Heart Failure With Reduced Ejection Fraction: Retrospective Cohort Study of Secondary Care Use and Costs %A Zaman,Sameer %A Padayachee,Yorissa %A Shah,Moulesh %A Samways,Jack %A Auton,Alice %A Quaife,Nicholas M %A Sweeney,Mark %A Howard,James P %A Tenorio,Indira %A Bachtiger,Patrik %A Kamalati,Tahereh %A Pabari,Punam A %A Linton,Nick W F %A Mayet,Jamil %A Peters,Nicholas S %A Barton,Carys %A Cole,Graham D %A Plymen,Carla M %+ Imperial College London, Du Cane Road, London, W12 0HS, United Kingdom, 44 2033131000, graham.cole3@nhs.net %K heart failure %K remote monitoring %K smartphone care %K telemonitoring %K self-management %K admission prevention %K cohort study %K hospitalization %K noninvasive %K smartphone %K vital signs %K diagnosis %D 2023 %7 23.6.2023 %9 Original Paper %J JMIR Cardio %G English %X Background: Despite effective therapies, the economic burden of heart failure with reduced ejection fraction (HFrEF) is driven by frequent hospitalizations. Treatment optimization and admission avoidance rely on frequent symptom reviews and monitoring of vital signs. Remote monitoring (RM) aims to prevent admissions by facilitating early intervention, but the impact of noninvasive, smartphone-based RM of vital signs on secondary health care use and costs in the months after a new diagnosis of HFrEF is unknown. Objective: The purpose of this study is to conduct a secondary care health use and health-economic evaluation for patients with HFrEF using smartphone-based noninvasive RM and compare it with matched controls receiving usual care without RM. Methods: We conducted a retrospective study of 2 cohorts of newly diagnosed HFrEF patients, matched 1:1 for demographics, socioeconomic status, comorbidities, and HFrEF severity. They are (1) the RM group, with patients using the RM platform for >3 months and (2) the control group, with patients referred before RM was available who received usual heart failure care without RM. Emergency department (ED) attendance, hospital admissions, outpatient use, and the associated costs of this secondary care activity were extracted from the Discover data set for a 3-month period after diagnosis. Platform costs were added for the RM group. Secondary health care use and costs were analyzed using Kaplan-Meier event analysis and Cox proportional hazards modeling. Results: A total of 146 patients (mean age 63 years; 42/146, 29% female) were included (73 in each group). The groups were well-matched for all baseline characteristics except hypertension (P=.03). RM was associated with a lower hazard of ED attendance (hazard ratio [HR] 0.43; P=.02) and unplanned admissions (HR 0.26; P=.02). There were no differences in elective admissions (HR 1.03, P=.96) or outpatient use (HR 1.40; P=.18) between the 2 groups. These differences were sustained by a univariate model controlling for hypertension. Over a 3-month period, secondary health care costs were approximately 4-fold lower in the RM group than the control group, despite the additional cost of RM itself (mean cost per patient GBP £465, US $581 vs GBP £1850, US $2313, respectively; P=.04). Conclusions: This retrospective cohort study shows that smartphone-based RM of vital signs is feasible for HFrEF. This type of RM was associated with an approximately 2-fold reduction in ED attendance and a 4-fold reduction in emergency admissions over just 3 months after a new diagnosis with HFrEF. Costs were significantly lower in the RM group without increasing outpatient demand. This type of RM could be adjunctive to standard care to reduce admissions, enabling other resources to help patients unable to use RM. %M 37351921 %R 10.2196/45611 %U https://cardio.jmir.org/2023/1/e45611 %U https://doi.org/10.2196/45611 %U http://www.ncbi.nlm.nih.gov/pubmed/37351921 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e40834 %T Willingness to Use and Pay for Digital Health Care Services According to 4 Scenarios: Results from a National Survey %A Lee,Junbok %A Oh,Yumi %A Kim,Meelim %A Cho,Belong %A Shin,Jaeyong %+ Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-Ro, Seodaemun-Gu, Seoul, 03722, Republic of Korea, 82 2 2228 1881, DRSHIN@yuhs.ac %K digital health intervention %K service experience %K willingness to pay %K willingness to use %K digital health %K health technology %D 2023 %7 29.3.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Smartphones and their associated technology have evolved to an extent where these devices can be used to provide digital health interventions. However, few studies have been conducted on the willingness to use (WTU) and willingness to pay (WTP) for digital health interventions. Objective: The purpose of this study was to investigate how previous service experience, the content of the services, and individuals’ health status affect WTU and WTP. Methods: We conducted a nationwide web-based survey in 3 groups: nonusers (n=506), public service users (n=368), and private service users (n=266). Participants read scenarios about an imagined health status (such as having a chronic illness) and the use of digital health intervention models (self-management, expert management, and medical management). They were then asked to respond to questions on WTU and WTP. Results: Public service users had a greater intention to use digital health intervention services than nonusers and private service users: scenario A (health-risk situation and self-management), nonusers=odd ratio [OR] .239 (SE .076; P<.001) and private service users=OR .138 (SE .044; P<.001); scenario B (health-risk situation and expert management), nonusers=OR .175 (SE .040; P<.001) and private service users=OR .219 (SE .053; P<.001); scenario C (chronic disease situation and expert management), nonusers=OR .413 (SE .094; P<.001) and private service users=OR .401 (SE .098; P<.001); and scenario D (chronic disease situation and medical management), nonusers=OR .480 (SE .120; P=.003) and private service users=OR .345 (SE .089; P<.001). In terms of WTP, in scenarios A and B, those who used the public and private services had a higher WTP than those who did not (scenario A: β=–.397, SE .091; P<.001; scenario B: β=–.486, SE .098; P<.001). In scenario C, private service users had greater WTP than public service users (β=.264, SE .114; P=.02), whereas public service users had greater WTP than nonusers (β=–.336, SE .096; P<.001). In scenario D, private service users were more WTP for the service than nonusers (β=–.286, SE .092; P=.002). Conclusions: We confirmed that the WTU and WTP for digital health interventions differed based on individuals’ prior experience with health care services, health status, and demographics. Recently, many discussions have been made to expand digital health care beyond the early adapters and fully into people’s daily lives. Thus, more understanding of people’s awareness and acceptance of digital health care is needed. %M 36989025 %R 10.2196/40834 %U https://mhealth.jmir.org/2023/1/e40834 %U https://doi.org/10.2196/40834 %U http://www.ncbi.nlm.nih.gov/pubmed/36989025 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e45064 %T The Influence of a Wearable-Based Reward Program on Health Care Costs: Retrospective, Propensity Score–Matched Cohort Study %A Zaleski,Amanda %A Sigler,Brittany %A Leggitt,Alan %A Choudhary,Shruti %A Berns,Ryan %A Rhee,Kyu %A Schwarzwald,Heidi %+ Clinical Evidence Development, Aetna Medical Affairs, CVS Health, 151 Farmington Avenue, Hartford, CT, 06156, United States, 1 8024898816, zaleskia@aetna.com %K digital health intervention %K mobile app %K wellness %K physical activity %K wearable %K cost-effectiveness %K mobile health app %K health plan %K medical cost %K health care cost %D 2023 %7 14.3.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Mobile health (mHealth) technology holds great promise as an easily accessible and effective solution to improve population health at scale. Despite the abundance of mHealth offerings, only a minority are grounded in evidence-based practice, whereas even fewer have line of sight into population-level health care spending, limiting the clinical utility of such tools. Objective: This study aimed to explore the influence of a health plan–sponsored, wearable-based, and reward-driven digital health intervention (DHI) on health care spending over 1 year. The DHI was delivered through a smartphone-based mHealth app available only to members of a large commercial health plan and leveraged a combination of behavioral economics, user-generated sensor data from the connected wearable device, and claims history to create personalized, evidence-based recommendations for each user. Methods: This study deployed a propensity score–matched, 2-group, and pre-post observational design. Adults (≥18 years of age) enrolled in a large, national commercial health plan and self-enlisted in the DHI for ≥7 months were allocated to the intervention group (n=56,816). Members who were eligible for the DHI but did not enlist were propensity score–matched to the comparison group (n=56,816). Average (and relative change from baseline) medical and pharmacy spending per user per month was computed for each member of the intervention and comparison groups during the pre- (ie, 12 months) and postenlistment (ie, 7-12 months) periods using claims data. Results: Baseline characteristics and medical spending were similar between groups (P=.89). On average, the total included sample population (N=113,632) consisted of young to middle-age (mean age 38.81 years), mostly White (n=55,562, 48.90%), male (n=46,731, 41.12%) and female (n=66,482, 58.51%) participants. Compared to a propensity score–matched cohort, DHI users demonstrated approximately US $10 per user per month lower average medical spending (P=.02) with a concomitant increase in preventive care activities and decrease in nonemergent emergency department admissions. These savings translated to approximately US $6.8 million in avoidable health care costs over the course of 1 year. Conclusions: This employer-sponsored, digital health engagement program has a high likelihood for return on investment within 1 year owing to clinically meaningful changes in health-seeking behaviors and downstream medical cost savings. Future research should aim to elucidate health behavior–related mechanisms in support of these findings and continue to explore novel strategies to ensure equitable access of DHIs to underserved populations that stand to benefit the most. %M 36917152 %R 10.2196/45064 %U https://www.jmir.org/2023/1/e45064 %U https://doi.org/10.2196/45064 %U http://www.ncbi.nlm.nih.gov/pubmed/36917152 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 9 %P e38903 %T Testing the Pragmatic Effectiveness of a Consumer-Based Mindfulness Mobile App in the Workplace: Randomized Controlled Trial %A Huberty,Jennifer L %A Espel-Huynh,Hallie M %A Neher,Taylor L %A Puzia,Megan E %+ Calm.com, Inc., 77 Geary St. Fl. 3, San Francisco, CA, 94108, United States, 1 402 301 1304, jenhubertyphd@gmail.com %K mindfulness %K mobile apps %K workforce %K workplace %K presenteeism %K mental health %D 2022 %7 28.9.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mental health and sleep problems are prevalent in the workforce, corresponding to costly impairment in productivity and increased health care use. Digital mindfulness interventions are efficacious in improving sleep and mental health in the workplace; however, evidence supporting their pragmatic utility, potential for improving productivity, and ability to reduce employer costs is limited. Objective: This pragmatic, cluster randomized controlled trial aimed to evaluate the experimental effects of implementing a commercially available mindfulness app—Calm—in employees of a large, multisite employer in the United States. Outcomes included mental health (depression, anxiety, and stress), sleep (insomnia and daytime sleepiness), resilience, productivity impairment (absenteeism, presenteeism, overall work impairment, and non–work activity impairment), and health care use (medical visit frequency). Methods: Employees were randomized at the work site to receive either the Calm app intervention or waitlist control. Participants in the Calm intervention group were instructed to use the Calm app for 10 minutes per day for 8 weeks; individuals with elevated baseline insomnia symptoms could opt-in to 6 weeks of sleep coaching. All outcomes were assessed every 2 weeks, with the exception of medical visits (weeks 4 and 8 only). Effects of the Calm intervention on outcomes were evaluated via mixed effects modeling, controlling for relevant baseline characteristics, with fixed effects of the intervention on outcomes assessed at weeks 2, 4, 6, and 8. Models were analyzed via complete-case and intent-to-treat analyses. Results: A total of 1029 employees enrolled (n=585 in the Calm intervention group, including 101 who opted-in to sleep coaching, and n=444 in waitlist control). Of them, 192 (n=88 for the Calm intervention group and n=104 for waitlist) completed all 5 assessments. In the complete-case analysis at week 8, employees at sites randomized to the Calm intervention group experienced significant improvements in depression (P=.02), anxiety (P=.01), stress (P<.001), insomnia (P<.001), sleepiness (P<.001), resilience (P=.02), presenteeism (P=.01), overall work impairment (P=.004), and nonwork impairment (P<.001), and reduced medical care visit frequency (P<.001) and productivity impairment costs (P=.01), relative to the waitlist control. In the intent-to-treat analysis at week 8, significant benefits of the intervention were observed for depression (P=.046), anxiety (P=.01), insomnia (P<.001), sleepiness (P<.001), nonwork impairment (P=.04), and medical visit frequency (P<.001). Conclusions: The results suggest that the Calm app is an effective workplace intervention for improving mental health, sleep, resilience, and productivity and for reducing medical visits and costs owing to work impairment. Future studies should identify optimal implementation strategies that maximize employee uptake and large-scale implementation success across diverse, geographically dispersed employers. Trial Registration: ClinicalTrials.gov NCT05120310; https://clinicaltrials.gov/ct2/show/NCT05120310 %M 36169991 %R 10.2196/38903 %U https://mhealth.jmir.org/2022/9/e38903 %U https://doi.org/10.2196/38903 %U http://www.ncbi.nlm.nih.gov/pubmed/36169991 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 6 %N 2 %P e31302 %T Home Telemonitoring and a Diagnostic Algorithm in the Management of Heart Failure in the Netherlands: Cost-effectiveness Analysis %A Albuquerque de Almeida,Fernando %A Corro Ramos,Isaac %A Al,Maiwenn %A Rutten-van Mölken,Maureen %+ Erasmus School of Health Policy and Management, Erasmus University Rotterdam, P.O. Box 1738, Rotterdam, 3000 DR, Netherlands, 351 918795283, albuquerquedealmeida@eshpm.eur.nl %K discrete event simulation %K cost-effectiveness %K early warning systems %K home telemonitoring %K diagnostic algorithm %K heart failure %D 2022 %7 4.8.2022 %9 Original Paper %J JMIR Cardio %G English %X Background: Heart failure is a major health concern associated with significant morbidity, mortality, and reduced quality of life in patients. Home telemonitoring (HTM) facilitates frequent or continuous assessment of disease signs and symptoms, and it has shown to improve compliance by involving patients in their own care and prevent emergency admissions by facilitating early detection of clinically significant changes. Diagnostic algorithms (DAs) are predictive mathematical relationships that make use of a wide range of collected data for calculating the likelihood of a particular event and use this output for prioritizing patients with regard to their treatment. Objective: This study aims to assess the cost-effectiveness of HTM and a DA in the management of heart failure in the Netherlands. Three interventions were analyzed: usual care, HTM, and HTM plus a DA. Methods: A previously published discrete event simulation model was used. The base-case analysis was performed according to the Dutch guidelines for economic evaluation. Sensitivity, scenario, and value of information analyses were performed. Particular attention was given to the cost-effectiveness of the DA at various levels of diagnostic accuracy of event prediction and to different patient subgroups. Results: HTM plus the DA extendedly dominates HTM alone, and it has a deterministic incremental cost-effectiveness ratio compared with usual care of €27,712 (currency conversion rate in purchasing power parity at the time of study: €1=US $1.29; further conversions are not applicable in cost-effectiveness terms) per quality-adjusted life year. The model showed robustness in the sensitivity and scenario analyses. HTM plus the DA had a 96.0% probability of being cost-effective at the appropriate €80,000 per quality-adjusted life year threshold. An optimal point for the threshold value for the alarm of the DA in terms of its cost-effectiveness was estimated. New York Heart Association class IV patients were the subgroup with the worst cost-effectiveness results versus usual care, while HTM plus the DA was found to be the most cost-effective for patients aged <65 years and for patients in New York Heart Association class I. Conclusions: Although the increased costs of adopting HTM plus the DA in the management of heart failure may seemingly be an additional strain on scarce health care resources, the results of this study demonstrate that, by increasing patient life expectancy by 1.28 years and reducing their hospitalization rate by 23% when compared with usual care, the use of this technology may be seen as an investment, as HTM plus the DA in its current form extendedly dominates HTM alone and is cost-effective compared with usual care at normally accepted thresholds in the Netherlands. %M 35925670 %R 10.2196/31302 %U https://cardio.jmir.org/2022/2/e31302 %U https://doi.org/10.2196/31302 %U http://www.ncbi.nlm.nih.gov/pubmed/35925670 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 4 %P e29408 %T Cost-Effectiveness of Mobile Health–Based Integrated Care for Atrial Fibrillation: Model Development and Data Analysis %A Luo,Xueyan %A Xu,Wei %A Ming,Wai-Kit %A Jiang,Xinchan %A Yuan,Quan %A Lai,Han %A Huang,Chunji %A Zhong,Xiaoni %+ School of Public Health and Management, Chongqing Medical University, 1 Yi Xue Lu, Yu Zhong District, Chongqing, 400016, China, 86 (023)68485008, zhongxiaoni@cqmu.edu.cn %K mobile health %K integrated care %K ABC pathway %K atrial fibrillation %K model-based %K cost-effectiveness %K health economic evaluation %D 2022 %7 19.4.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Mobile health (mHealth) technology is increasingly used in disease management. Using mHealth tools to integrate and streamline care has improved clinical outcomes of patients with atrial fibrillation (AF). Objective: The aim of this study was to investigate the potential clinical and health economic outcomes of mHealth-based integrated care for AF from the perspective of a public health care provider in China. Methods: A Markov model was designed to compare outcomes of mHealth-based care and usual care in a hypothetical cohort of patients with AF in China. The time horizon was 30 years with monthly cycles. Model outcomes measured were direct medical cost, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). Sensitivity analyses were performed to examine the robustness of the base-case results. Results: In the base-case analysis, mHealth-based care gained higher QALYs of 0.0730 with an incurred cost of US $1090. Using US $33,438 per QALY (three times the gross domestic product) as the willingness-to-pay threshold, mHealth-based care was cost-effective, with an ICER of US $14,936 per QALY. In one-way sensitivity analysis, no influential factor with a threshold value was identified. In probabilistic sensitivity analysis, mHealth-based care was accepted as cost-effective in 92.33% of 10,000 iterations. Conclusions: This study assessed the expected cost-effectiveness of applying mHealth-based integrated care for AF according to a model-based health economic evaluation. The exploration suggested the potential cost-effective use of mHealth apps in streamlining and integrating care via the Atrial fibrillation Better Care (ABC) pathway for AF in China. Future economic evaluation alongside randomized clinical trials is highly warranted to verify the suggestion and investigate affecting factors such as geographical variations in patient characteristics, identification of subgroups, and constraints on local implementation. %M 35438646 %R 10.2196/29408 %U https://www.jmir.org/2022/4/e29408 %U https://doi.org/10.2196/29408 %U http://www.ncbi.nlm.nih.gov/pubmed/35438646 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 2 %P e32554 %T A Smartphone-Based Model of Care to Support Patients With Cardiac Disease Transitioning From Hospital to the Community (TeleClinical Care): Pilot Randomized Controlled Trial %A Indraratna,Praveen %A Biswas,Uzzal %A McVeigh,James %A Mamo,Andrew %A Magdy,Joseph %A Vickers,Dominic %A Watkins,Elaine %A Ziegl,Andreas %A Liu,Hueiming %A Cholerton,Nicholas %A Li,Joan %A Holgate,Katie %A Fildes,Jennifer %A Gallagher,Robyn %A Ferry,Cate %A Jan,Stephen %A Briggs,Nancy %A Schreier,Guenter %A Redmond,Stephen J %A Loh,Eugene %A Yu,Jennifer %A Lovell,Nigel H %A Ooi,Sze-Yuan %+ Department of Cardiology, Prince of Wales Hospital, Barker Street, Randwick, 2031, Australia, 61 2 9382 2222, praveen@unsw.edu.au %K digital health %K telemedicine %K mHealth %K heart failure %K ischemic heart disease %K mobile phone %D 2022 %7 28.2.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Patients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission. Objective: This study aims to investigate the feasibility, efficacy, and cost-effectiveness of a smartphone app–based model of care (TeleClinical Care [TCC]) in patients discharged after ACS or HF admission. Methods: In this pilot, 2-center randomized controlled trial, TCC was applied at discharge along with usual care to intervention arm participants. Control arm participants received usual care alone. Inclusion criteria were current admission with ACS or HF, ownership of a compatible smartphone, age ≥18 years, and provision of informed consent. The primary end point was the incidence of unplanned 30-day readmissions. Secondary end points included all-cause readmissions, cardiac readmissions, cardiac rehabilitation completion, medication adherence, cost-effectiveness, and user satisfaction. Intervention arm participants received the app and Bluetooth-enabled devices for measuring weight, blood pressure, and physical activity daily plus usual care. The devices automatically transmitted recordings to the patients’ smartphones and a central server. Thresholds for blood pressure, heart rate, and weight were determined by the treating cardiologists. Readings outside these thresholds were flagged to a monitoring team, who discussed salient abnormalities with the patients’ usual care providers (cardiologists, general practitioners, or HF outreach nurses), who were responsible for further management. The app also provided educational push notifications. Participants were followed up after 6 months. Results: Overall, 164 inpatients were randomized (TCC: 81/164, 49.4%; control: 83/164, 50.6%; mean age 61.5, SD 12.3 years; 130/164, 79.3% men; 128/164, 78% admitted with ACS). There were 11 unplanned 30-day readmissions in both groups (P=.97). Over a mean follow-up of 193 days, the intervention was associated with a significant reduction in unplanned hospital readmissions (21 in TCC vs 41 in the control arm; P=.02), including cardiac readmissions (11 in TCC vs 25 in the control arm; P=.03), and higher rates of cardiac rehabilitation completion (20/51, 39% vs 9/49, 18%; P=.03) and medication adherence (57/76, 75% vs 37/74, 50%; P=.002). The average usability rating for the app was 4.5/5. The intervention cost Aus $6028 (US $4342.26) per cardiac readmission saved. When modeled in a mainstream clinical setting, enrollment of 237 patients was projected to have the same expenditure compared with usual care, and enrollment of 500 patients was projected to save approximately Aus $100,000 (approximately US $70,000) annually. Conclusions: TCC was feasible and safe for inpatients with either ACS or HF. The incidence of 30-day readmissions was similar; however, long-term benefits were demonstrated, including fewer readmissions over 6 months, improved medication adherence, and improved cardiac rehabilitation completion. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12618001547235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375945 %M 35225819 %R 10.2196/32554 %U https://mhealth.jmir.org/2022/2/e32554 %U https://doi.org/10.2196/32554 %U http://www.ncbi.nlm.nih.gov/pubmed/35225819 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 2 %P e35042 %T Digital Therapeutic Care Apps With Decision-Support Interventions for People With Low Back Pain in Germany: Cost-Effectiveness Analysis %A Lewkowicz,Daniel %A Wohlbrandt,Attila M %A Bottinger,Erwin %+ Digital Health Center, Hasso Plattner Institute, University of Potsdam, Prof Dr Helmert Str 2-3, Potsdam, 14482, Germany, 49 (0)331 55094843, daniel.lewkowicz@hpi.de %K cost-utility analysis %K low back pain %K back pain %K cost-effectiveness %K Markov model %K digital therapy %K digital health app %K mHealth %K orthopedic %K eHealth %K mobile health %K digital health %K pain management %K health apps %D 2022 %7 7.2.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Digital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care apps are also driven by personalized decision-support interventions that support the user in self-managing LBP, and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored. Objective: The aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing. Methods: We developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models, and evaluated the cost utility of a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model’s robustness and conditions for changing the reimbursement rate. All costs are reported in Euro (€1=US $1.12). Results: Our base case results indicated that the digital therapeutic care strategy led to an incremental cost of €121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of €5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to €99 per 3 months or decreasing the app’s attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU. Conclusions: The current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app’s attrition rate and effect on the patient’s prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app’s long-term effect on quality of life. %M 35129454 %R 10.2196/35042 %U https://mhealth.jmir.org/2022/2/e35042 %U https://doi.org/10.2196/35042 %U http://www.ncbi.nlm.nih.gov/pubmed/35129454 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 1 %P e23236 %T The Interplay Between Technology Performativity and Health Care Professionals in Hospital Settings: Service Design Approach %A Ogundaini,Oluwamayowa %A de la Harpe,Retha %+ Department of Information Technology, Cape Peninsula University of Technology, Engineering Building, 2nd Floor, Hanover Street, Zonnebloem, Cape Town, 8000, South Africa, 27 0735989341, ogundainio@cput.ac.za %K agency %K health care professionals %K technology performativity %K sub-Saharan Africa %K service design %K work activities %K mobile phone %D 2022 %7 4.1.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The unexpected outbreak of the COVID-19 pandemic and the preventive measures of physical distancing have further necessitated the application of information and communication technologies (ICTs) to enhance the efficiency of work activities in health care. Although the interplay between human agency and technology performativity is critical to the success or failure of ICTs use in routine practice, it is rarely explored when designing health ICTs for hospital settings within the sub-Saharan Africa context. Objective: The objective of this study is to explore how the service delivery quality is being influenced by the technology-enabled activities of health care professionals at points of care using a service design strategy. Methods: An interpretivist stance was assumed to understand the socially constructed realities of health care professionals at points of care in a hospital setting. A service design strategy was identified as suitable for engaging health care professionals in co-design sessions to collect data. A purposive sampling technique was used to identify the participants. Open-ended questions were administered to gain insights into the work activities of physicians and nurses at points of care. Qualitative (textual) data were analyzed using thematic analysis. Ethical concerns about the safety and privacy of participants’ data were addressed as per the university ethics review committee and provincial department of health. Results: The findings show that the attributes of human agency and technology features that drive technology performativity result in an interplay between social concepts and technical features that influence the transformation of human-machine interactions. In addition, the interplay of the double dance of agency model can be divided into 2 successive phases: intermediate and advanced. Intermediate interplay results in the perceived suitability or discomfort of health ICTs as experienced by health care professionals at initial interactions during the execution of work activities. Subsequently, the advanced interplay determines the usefulness and effectiveness of health ICTs in aiding task performance, which ultimately leads to either the satisfaction or dissatisfaction of health care professionals in the completion of their work activities at points of care. Conclusions: The adopted service design strategy revealed that the interaction moments of the tasks performed by health care professionals during the execution of their work activities at point of care determine the features of health ICTs relevant to work activities. Consequently, the ensuing experience of health care professionals at the completion of their work activities influences the use or discontinuation of health ICTs. Health care professionals consider the value-added benefits from the automation of their work activities to ultimately influence the quality of service delivery. The major knowledge contribution of this study is the awareness drawn to both the intermediate and advanced interplay of human-machine interaction when designing health ICTs. %M 34982713 %R 10.2196/23236 %U https://formative.jmir.org/2022/1/e23236 %U https://doi.org/10.2196/23236 %U http://www.ncbi.nlm.nih.gov/pubmed/34982713 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e31702 %T Prescribing Smartphone Apps for Physical Activity Promotion in Primary Care: Modeling Study of Health Gain and Cost Savings %A Grout,Leah %A Telfer,Kendra %A Wilson,Nick %A Cleghorn,Christine %A Mizdrak,Anja %+ Burden of Disease Epidemiology, Equity and Cost-Effectiveness Program, University of Otago Wellington, 23A Mein Street, Newtown, Wellington, 6242, New Zealand, 64 49186192, anja.mizdrak@otago.ac.nz %K physical activity %K smartphone apps %K mobile health %K mHealth %K modeling %K primary care %K mobile phone %D 2021 %7 20.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Inadequate physical activity is a substantial cause of health loss worldwide, and this loss is attributable to diseases such as coronary heart disease, diabetes, stroke, and certain forms of cancer. Objective: This study aims to assess the potential impact of the prescription of smartphone apps in primary care settings on physical activity levels, health gains (in quality-adjusted life years [QALYs]), and health system costs in New Zealand (NZ). Methods: A proportional multistate lifetable model was used to estimate the change in physical activity levels and predict the resultant health gains in QALYs and health system costs over the remaining life span of the NZ population alive in 2011 at a 3% discount rate. Results: The modeled intervention resulted in an estimated 430 QALYs gained (95% uncertainty interval 320-550), with net cost savings of 2011 NZ $2.2 million (2011 US $1.5 million) over the remaining life span of the 2011 NZ population. On a per capita basis, QALY gains were generally larger in women than in men and larger in Māori than in non-Māori. The health impact and cost-effectiveness of the intervention were highly sensitive to assumptions on intervention uptake and decay. For example, the scenario analysis with the largest benefits, which assumed a 5-year maintenance of additional physical activity levels, delivered 1750 QALYs and 2011 NZ $22.5 million (2011 US $15.1 million) in cost savings. Conclusions: The prescription of smartphone apps for promoting physical activity in primary care settings is likely to generate modest health gains and cost savings at the population level in this high-income country. Such gains may increase with ongoing improvements in app design and increased health worker promotion of the apps to patients. %M 34931993 %R 10.2196/31702 %U https://www.jmir.org/2021/12/e31702 %U https://doi.org/10.2196/31702 %U http://www.ncbi.nlm.nih.gov/pubmed/34931993 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 10 %P e30940 %T Accelerating the Appropriate Adoption of Artificial Intelligence in Health Care: Protocol for a Multistepped Approach %A Wiljer,David %A Salhia,Mohammad %A Dolatabadi,Elham %A Dhalla,Azra %A Gillan,Caitlin %A Al-Mouaswas,Dalia %A Jackson,Ethan %A Waldorf,Jacqueline %A Mattson,Jane %A Clare,Megan %A Lalani,Nadim %A Charow,Rebecca %A Balakumar,Sarmini %A Younus,Sarah %A Jeyakumar,Tharshini %A Peteanu,Wanda %A Tavares,Walter %+ University Health Network, 190 Elizabeth Street, R Fraser Elliot Building RFE 3S-441, Toronto, ON, M5G 2C4, Canada, 1 416 340 4800 ext 6322, David.wiljer@uhn.ca %K artificial intelligence %K health care providers %K education %K learning %K patient care %K adoption %K mHealth %D 2021 %7 6.10.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Significant investments and advances in health care technologies and practices have created a need for digital and data-literate health care providers. Artificial intelligence (AI) algorithms transform the analysis, diagnosis, and treatment of medical conditions. Complex and massive data sets are informing significant health care decisions and clinical practices. The ability to read, manage, and interpret large data sets to provide data-driven care and to protect patient privacy are increasingly critical skills for today’s health care providers. Objective: The aim of this study is to accelerate the appropriate adoption of data-driven and AI-enhanced care by focusing on the mindsets, skillsets, and toolsets of point-of-care health providers and their leaders in the health system. Methods: To accelerate the adoption of AI and the need for organizational change at a national level, our multistepped approach includes creating awareness and capacity building, learning through innovation and adoption, developing appropriate and strategic partnerships, and building effective knowledge exchange initiatives. Education interventions designed to adapt knowledge to the local context and address any challenges to knowledge use include engagement activities to increase awareness, educational curricula for health care providers and leaders, and the development of a coaching and practice-based innovation hub. Framed by the Knowledge-to-Action framework, we are currently in the knowledge creation stage to inform the curricula for each deliverable. An environmental scan and scoping review were conducted to understand the current state of AI education programs as reported in the academic literature. Results: The environmental scan identified 24 AI-accredited programs specific to health providers, of which 11 were from the United States, 6 from Canada, 4 from the United Kingdom, and 3 from Asian countries. The most common curriculum topics across the environmental scan and scoping review included AI fundamentals, applications of AI, applied machine learning in health care, ethics, data science, and challenges to and opportunities for using AI. Conclusions: Technologies are advancing more rapidly than organizations, and professionals can adopt and adapt to them. To help shape AI practices, health care providers must have the skills and abilities to initiate change and shape the future of their discipline and practices for advancing high-quality care within the digital ecosystem. International Registered Report Identifier (IRRID): PRR1-10.2196/30940 %M 34612839 %R 10.2196/30940 %U https://www.researchprotocols.org/2021/10/e30940 %U https://doi.org/10.2196/30940 %U http://www.ncbi.nlm.nih.gov/pubmed/34612839 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 8 %P e24890 %T Alignment of Key Stakeholders’ Priorities for Patient-Facing Tools in Digital Health: Mixed Methods Study %A Lyles,Courtney Rees %A Adler-Milstein,Julia %A Thao,Crishyashi %A Lisker,Sarah %A Nouri,Sarah %A Sarkar,Urmimala %+ Division of General Internal Medicine, Department of Medicine, University of California San Francisco, 1001 Potrero Avenue, Box 1364, San Francisco, CA, 94143, United States, 1 628 206 6483, courtney.lyles@ucsf.edu %K medical informatics %K medical informatics apps %K information technology %K implementation science %K mixed methods %D 2021 %7 26.8.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: There is widespread agreement on the promise of patient-facing digital health tools to transform health care. Yet, few tools are in widespread use or have documented clinical effectiveness. Objective: The aim of this study was to gain insight into the gap between the potential of patient-facing digital health tools and real-world uptake. Methods: We interviewed and surveyed experts (in total, n=24) across key digital health stakeholder groups—venture capitalists, digital health companies, payers, and health care system providers or leaders—guided by the Consolidated Framework for Implementation Research. Results: Our findings revealed that external policy, regulatory demands, internal organizational workflow, and integration needs often take priority over patient needs and patient preferences for digital health tools, which lowers patient acceptance rates. We discovered alignment, across all 4 stakeholder groups, in the desire to engage both patients and frontline health care providers in broader dissemination and evaluation of digital health tools. However, major areas of misalignment between stakeholder groups have stymied the progress of digital health tool uptake—venture capitalists and companies focused on external policy and regulatory demands, while payers and providers focused on internal organizational workflow and integration needs. Conclusions: Misalignment of the priorities of digital health companies and their funders with those of providers and payers requires direct attention to improve uptake of patient-facing digital health tools and platforms. %M 34435966 %R 10.2196/24890 %U https://www.jmir.org/2021/8/e24890 %U https://doi.org/10.2196/24890 %U http://www.ncbi.nlm.nih.gov/pubmed/34435966 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 4 %P e19511 %T Mobile Phone Intervention Based on an HIV Risk Prediction Tool for HIV Prevention Among Men Who Have Sex With Men in China: Randomized Controlled Trial %A Yun,Ke %A Chu,Zhenxing %A Zhang,Jing %A Geng,Wenqing %A Jiang,Yongjun %A Dong,Willa %A Shang,Hong %A Xu,Junjie %+ NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, No 155, Nanjing North Street, Heping District, Shenyang, China, 86 8328 2634, hongshang100@hotmail.com %K eHealth intervention %K high-risk behavior intervention %K HIV risk prediction %K men who have sex with men %D 2021 %7 13.4.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: eHealth interventions based on risk stratification have not been extensively applied for HIV behavioral interventions among HIV-negative men who have sex with men (MSM). Objective: This study aimed to evaluate the efficacy of a mobile phone intervention based on an HIV risk prediction tool in promoting HIV testing and reducing high-risk behavior among HIV-negative MSM in China. Methods: We performed a mobile phone–based randomized controlled clinical trial for 12 weeks. A comprehensive intervention package deployed on Jinshuju—an online survey platform—was developed and consisted of 4 components: (1) a validated HIV risk prediction tool that provides information on personalized risk reduction interventions; (2) a map of individualized HIV testing facilities based on their geographic location; (3) a QR code for free resources on HIV prevention, including condoms and HIV self-testing kits; and (4) general resources for HIV health education. MSM participants recruited from WeChat/QQ groups were randomly assigned to the intervention or control group at a 1:1 ratio. The staff sent the QR code for the comprehensive intervention package to MSM in the intervention group over WeChat and sent the QR code only for the resources on HIV health education to those in the control group. At baseline and 12-week follow-up, data on HIV-related risk behavior and HIV testing behavior were collected through the Jinshuju online survey platform. Results: In total, 192 MSM were recruited and assigned to the intervention or control group (n=96 each). At week 12, the total clinical trial retention rate was 87.5%. The number of male sexual partners of the MSM in the past 3 months was significantly lower in the intervention group than in the control group (3.51, SD 4.1 vs 6.01, SD 11.4, respectively; mean difference −2.5; 95% CI −5.12 to 0.12; P=.05); the rate of condom use with casual sexual partners was higher in the intervention group than in the control group (87%, n=66/76 vs 70%, n=54/77 respectively; odds ratio 2.81, 95% CI 1.23-6.39; P=.01). The proportion of individuals intending to undergo HIV testing after in the following 30 days was marginally higher in the intervention group than in the control group (90%, n=77/86 vs 79%, n=65/82 respectively; odds ratio 2.20, 95% CI 0.90-5.35; P=.07). The incremental cost-effectiveness ratio of eHealth intervention was US $131.60 on reducing 1 sexual partner and US $19.70 for a 1% increment in condom usage with casual partners. Conclusions: A comprehensive intervention based on an HIV risk prediction tool can reduce the number of male sexual partners among MSM and increase the rate of condom use with casual partners. Hence, this intervention is a very promising preventive strategy for HIV among MSM, especially in areas with a prominent HIV epidemic. Trial Registration: Chinese Clinical Trial Registry ChiCTR1800017268; http://www.chictr.org.cn/showprojen.aspx?proj=29271 %M 33847597 %R 10.2196/19511 %U https://mhealth.jmir.org/2021/4/e19511 %U https://doi.org/10.2196/19511 %U http://www.ncbi.nlm.nih.gov/pubmed/33847597 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 3 %P e24726 %T eHealth Program to Reduce Hospitalizations Due to Acute Exacerbation of Chronic Obstructive Pulmonary Disease: Retrospective Study %A van Buul,Amanda R %A Derksen,Caroline %A Hoedemaker,Ouke %A van Dijk,Oscar %A Chavannes,Niels H %A Kasteleyn,Marise J %+ Department of Pulmonology, Leiden University Medical Center, Leiden, Netherlands, 31 715297550, a.r.van_buul@lumc.nl %K COPD %K eHealth %K exacerbations %K hospitalizations %K mHealth %D 2021 %7 18.3.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Hospitalization for acute exacerbation of chronic obstructive pulmonary disease (COPD) is associated with poor prognosis. eHealth interventions might improve outcomes and decrease costs. Objective: This study aimed to evaluate the effect of an eHealth program on COPD hospitalizations and exacerbations. Methods: This was a real-world study conducted from April 2018 to December 2019 in the Bravis Hospital, the Netherlands. An eHealth program (EmmaCOPD) was offered to COPD patients at risk of exacerbations. EmmaCOPD consisted of an app that used questionnaires (to monitor symptoms) and a step counter (to monitor the number of steps) to detect exacerbations. Patients and their buddies received feedback when their symptoms worsened or the number of steps declined. Generalized estimating equations were used to compare the number of days admitted to the hospital and the total number of exacerbations 12 months before and (max) 18 months after the start of EmmaCOPD. We additionally adjusted for the potential confounders of age, sex, COPD severity, and inhaled corticosteroid use. Results: The 29 included patients had a mean forced expiratory volume in 1 second of 45.5 (SD 17.7) %predicted. In the year before the intervention, the median total number of exacerbations was 2.0 (IQR 2.0-3.0). The median number of hospitalized days was 8.0 days (IQR 6.0-16.5 days). Afterwards, there was a median 1.0 (IQR 0.0-2.0) exacerbation and 2.0 days (IQR 0.0-4.0 days) of hospitalization. After initiation of EmmaCOPD, both the number of hospitalized days and total number of exacerbations decreased significantly (incidence rate ratio 0.209, 95% CI 0.116-0.382; incidence rate ratio 0.310, 95% CI 0.219-0.438). Adjustment for confounders did not affect the results. Conclusions: The eHealth program seems to reduce the number of total exacerbations and number of days of hospitalization due to exacerbations of COPD. %M 33734091 %R 10.2196/24726 %U https://formative.jmir.org/2021/3/e24726 %U https://doi.org/10.2196/24726 %U http://www.ncbi.nlm.nih.gov/pubmed/33734091 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 3 %P e26516 %T Cost-effectiveness of a Telemonitoring Program for Patients With Heart Failure During the COVID-19 Pandemic in Hong Kong: Model Development and Data Analysis %A Jiang,Xinchan %A Yao,Jiaqi %A You,Joyce Hoi-Sze %+ School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, 8th Floor, Lo Kwee-Seong Integrated Biomedical Sciences Building, Shatin, NT, Hong Kong, China (Hong Kong), 852 39436830, joyceyou@cuhk.edu.hk %K telemonitoring %K mobile health %K smartphone %K heart failure %K COVID-19 %K health care avoidance %K cost-effectiveness %D 2021 %7 3.3.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The COVID-19 pandemic has caused patients to avoid seeking medical care. Provision of telemonitoring programs in addition to usual care has demonstrated improved effectiveness in managing patients with heart failure (HF). Objective: We aimed to examine the potential clinical and health economic outcomes of a telemonitoring program for management of patients with HF during the COVID-19 pandemic from the perspective of health care providers in Hong Kong. Methods: A Markov model was designed to compare the outcomes of a care under COVID-19 (CUC) group and a telemonitoring plus CUC group (telemonitoring group) in a hypothetical cohort of older patients with HF in Hong Kong. The model outcome measures were direct medical cost, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio. Sensitivity analyses were performed to examine the model assumptions and the robustness of the base-case results. Results: In the base-case analysis, the telemonitoring group showed a higher QALY gain (1.9007) at a higher cost (US $15,888) compared to the CUC group (1.8345 QALYs at US $15,603). Adopting US $48,937/QALY (1 × the gross domestic product per capita of Hong Kong) as the willingness-to-pay threshold, telemonitoring was accepted as a highly cost-effective strategy, with an incremental cost-effective ratio of US $4292/QALY. No threshold value was identified in the deterministic sensitivity analysis. In the probabilistic sensitivity analysis, telemonitoring was accepted as cost-effective in 99.22% of 10,000 Monte Carlo simulations. Conclusions: Compared to the current outpatient care alone under the COVID-19 pandemic, the addition of telemonitoring-mediated management to the current care for patients with HF appears to be a highly cost-effective strategy from the perspective of health care providers in Hong Kong. %M 33656440 %R 10.2196/26516 %U https://www.jmir.org/2021/3/e26516 %U https://doi.org/10.2196/26516 %U http://www.ncbi.nlm.nih.gov/pubmed/33656440 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 1 %P e23190 %T Mobile App–Based Remote Patient Monitoring in Acute Medical Conditions: Prospective Feasibility Study Exploring Digital Health Solutions on Clinical Workload During the COVID Crisis %A Shah,Sachin Shailendra %A Gvozdanovic,Andrew %A Knight,Matthew %A Gagnon,Julien %+ Huma Therapeutics, 13th Floor Millbank Tower, 21-24 Millbank, London, SW1P 4QP, United Kingdom, 44 7875210783, sachsshah@gmail.com %K mHealth %K remote patient monitoring %K digital health %K COVID-19 %K service improvement %K cost-effectiveness %K monitoring %D 2021 %7 15.1.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Digital remote patient monitoring can add value to virtual wards; this has become more apparent in the context of the COVID-19 pandemic. Health care providers are overwhelmed, resulting in clinical teams spread more thinly. We aimed to assess the impact of introducing an app-based remote patient monitoring system (Huma Therapeutics) on a clinician’s workload in the context of a COVID-19–specific virtual ward. Objective: This prospective feasibility study aimed to evaluate the health economic effects (in terms of clinical workload) of a mobile app on a telephone-based virtual ward used in the monitoring of patients with COVID-19 who are clinically ready for discharge from the hospital. Methods: A prospective feasibility study was carried out over 1 month where clinician workload was monitored, and full-time equivalents savings were determined. An NHS hospital repurposed a telephone-based respiratory virtual ward for COVID-19. Patients with COVID-19 in the amber zone (according to the National Health Service definition) were monitored for 14 days postdischarge to help identify deteriorating patients earlier. A smartphone-based app was introduced to monitor data points submitted by the patients via communication over telephone calls. We then comparatively evaluated the clinical workload between patients monitored by telephone only (cohort 1) with those monitored via mobile app and telephone (cohort 2). Results: In all, 56 patients were enrolled in the app-based virtual ward (cohort 2). Digital remote patient monitoring resulted in a reduction in the number of phone calls from a mean total of 9 calls to 4 calls over the monitoring period. There was no change in the mean duration of phone calls (8.5 minutes) and no reports of readmission or mortality. These results equate to a mean saving of 47.60 working hours. Moreover, it translates to 3.30 fewer full-time equivalents (raw phone call data), resulting in 1.1 fewer full-time equivalents required to monitor 100 patients when adjusted for time spent reviewing app data. Individual clinicians spent an average of 10.9 minutes per day reviewing data. Conclusions: Smartphone-based remote patient monitoring technologies may offer tangible reductions in clinician workload at a time when service is severely strained. In this small-scale pilot study, we demonstrated the economic and operational impact that digital remote patient monitoring technology can have in improving working efficiency and reducing operational costs. Although this particular RPM solution was deployed for the COVID-19 pandemic, it may set a precedent for wider utilization of digital, remote patient monitoring solutions in other clinical scenarios where increased care delivery efficiency is sought. %M 33400675 %R 10.2196/23190 %U http://formative.jmir.org/2021/1/e23190/ %U https://doi.org/10.2196/23190 %U http://www.ncbi.nlm.nih.gov/pubmed/33400675 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 7 %N 10 %P e18812 %T A Patient-Centered Framework for Measuring the Economic Value of the Clinical Benefits of Digital Health Apps: Theoretical Modeling %A Powell,Adam %A Torous,John %+ Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA, United States, 1 617 667 6700, jtorous@bidmc.harvard.edu %K value %K digital health %K apps %K payment models %D 2020 %7 30.10.2020 %9 Original Paper %J JMIR Ment Health %G English %X Background: As digital health tools such as smartphone apps evolve and enter clinical use, questions regarding their value must be addressed. Although there are scarce generalizable data on the value of health apps given their nascency and diverse use cases, it is possible to estimate the economic value of the clinical improvement they bring to patients using a quality-adjusted life-year (QALY)-based approach and generalized values from existing literature. Objective: This paper aims to provide a patient-centered framework for assessing the economic value of the clinical benefits delivered by digital health apps. Methods: We proposed a model based upon 5 levers: country-specific monetary value of a QALY, QALYs lost due to the condition, engagement rate of app users, average effect size of the app’s health impact, and duration of the app’s impact before remission. Results: Using 2 digital health apps from the United States and United Kingdom as examples, we explored how this model could generate country-specific estimates of the economic value of the clinical benefits of health apps. Conclusions: This new framework can help drive research priorities for digital health by elucidating the factors that influence the economic value. %M 33124995 %R 10.2196/18812 %U https://mental.jmir.org/2020/10/e18812 %U https://doi.org/10.2196/18812 %U http://www.ncbi.nlm.nih.gov/pubmed/33124995 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e20496 %T Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis %A Giebel,Godwin D %+ E-Government/E-Health, Department of Business Information Systems, Baden-Wuerttemberg Cooperative State University Mannheim, Coblitzallee 1-9, Mannheim, 68163, Germany, 49 157 57953048, godwin.giebel@dhbw-mannheim.de %K mHealth %K atrial fibrillation %K screening devices %K strokes %K cost-effectiveness %K photoplethysmography %D 2020 %7 6.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: With an estimated prevalence of around 3% and an about 2.5-fold increased risk of stroke, atrial fibrillation (AF) is a serious threat for patients and a high economic burden for health care systems all over the world. Patients with AF could benefit from screening through mobile health (mHealth) devices. Thus, an early diagnosis is possible with mHealth devices, and the risk for stroke can be markedly reduced by using anticoagulation therapy. Objective: The aim of this work was to assess the cost-effectiveness of algorithm-based screening for AF with the aid of photoplethysmography wrist-worn mHealth devices. Even if prevented strokes and prevented deaths from stroke are the most relevant patient outcomes, direct costs were defined as the primary outcome. Methods: A Monte Carlo simulation was conducted based on a developed state-transition model; 30,000 patients for each CHA2DS2-VASc (Congestive heart failure, Hypertension, Age≥75 years, Diabetes mellitus, Stroke, Vascular disease, Age 65-74 years, Sex category [female]) score from 1 to 9 were simulated. The first simulation served to estimate the economic burden of AF without the use of mHealth devices. The second simulation served to simulate the economic burden of AF with the use of mHealth devices. Afterwards, the groups were compared in terms of costs, prevented strokes, and deaths from strokes. Results: The CHA2DS2-VASc score as well as the electrocardiography (ECG) confirmation rate had the biggest impact on costs as well as number of strokes. The higher the risk score, the lower were the costs per prevented stroke. Higher ECG confirmation rates intensified this effect. The effect was not seen in groups with lower risk scores. Over 10 years, the use of mHealth (assuming a 75% ECG confirmation rate) resulted in additional costs (€1=US $1.12) of €441, €567, €536, €520, €606, €625, €623, €692, and €847 per patient for a CHA2DS2-VASc score of 1 to 9, respectively. The number of prevented strokes tended to be higher in groups with high risk for stroke. Higher ECG confirmation rates led to higher numbers of prevented strokes. The use of mHealth (assuming a 75% ECG confirmation rate) resulted in 25 (7), –68 (–54), 98 (–5), 266 (182), 346 (271), 642 (440), 722 (599), 1111 (815), and 1116 (928) prevented strokes (fatal) for CHA2DS2-VASc score of 1 to 9, respectively. Higher device accuracy in terms of sensitivity led to even more prevented fatal strokes. Conclusions: The use of mHealth devices to screen for AF leads to increased costs but also a reduction in the incidence of stroke. In particular, in patients with high CHA2DS2-VASc scores, the risk for stroke and death from stroke can be markedly reduced. %M 33021489 %R 10.2196/20496 %U http://mhealth.jmir.org/2020/10/e20496/ %U https://doi.org/10.2196/20496 %U http://www.ncbi.nlm.nih.gov/pubmed/33021489 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 7 %P e17846 %T Telemonitoring Versus Usual Care for Elderly Patients With Heart Failure Discharged From the Hospital in the United States: Cost-Effectiveness Analysis %A Jiang,Xinchan %A Yao,Jiaqi %A You,Joyce HS %+ School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, 8/F, Lo Kwee-Seong Integrated Biomedical Sciences Building, CUHK, Shatin, NT, , China (Hong Kong), 852 39436830, joyceyou@cuhk.edu.hk %K telemedicine %K heart failure %K hospitalization %K cost %K quality-adjusted life year %K cost-effectiveness analysis %D 2020 %7 6.7.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Telemonitoring-guided interventional management reduces the need for hospitalization and mortality of patients with chronic heart failure (CHF). Objective: This study aimed to analyze the cost-effectiveness of usual care with and without telemonitoring-guided management in patients with CHF discharged from the hospital, from the perspective of US health care providers. Methods: A lifelong Markov model was designed to estimate outcomes of (1) usual care alone for all postdischarge patients with CHF (New York Heart Association [NYHA] class I-IV), (2) usual care and telemonitoring for all postdischarge patients with CHF, (3) usual care for all postdischarge patients with CHF and telemonitoring for patients with NYHA class III to IV, and (4) usual care for all postdischarge patients with CHF plus telemonitoring for patients with NYHA class II to IV. Model inputs were derived from the literature and public data. Sensitivity analyses were conducted to assess the robustness of model. The primary outcomes were total direct medical cost, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). Results: In the base case analysis, universal telemonitoring group gained the highest QALYs (6.2967 QALYs), followed by the telemonitoring for NYHA class II to IV group (6.2960 QALYs), the telemonitoring for NYHA class III to IV group (6.2450 QALYs), and the universal usual care group (6.1530 QALYs). ICERs of the telemonitoring for NYHA class III to IV group (US $35,393 per QALY) and the telemonitoring for NYHA class II to IV group (US $38,261 per QALY) were lower than the ICER of the universal telemonitoring group (US $100,458 per QALY). One-way sensitivity analysis identified five critical parameters: odds ratio of hospitalization for telemonitoring versus usual care, hazard ratio of all-cause mortality for telemonitoring versus usual care, CHF hospitalization cost and monthly outpatient costs for NYHA class I, and CHF hospitalization cost for NYHA class II. In probabilistic sensitivity analysis, probabilities of the universal telemonitoring, telemonitoring for NYHA class II to IV, telemonitoring for NYHA class III to IV, and universal usual care groups to be accepted as cost-effective at US $50,000 per QALY were 2.76%, 76.31%, 18.6%, and 2.33%, respectively. Conclusions: Usual care for all discharged patients with CHF plus telemonitoring-guided management for NYHA class II to IV patients appears to be the preferred cost-effective strategy. %M 32407288 %R 10.2196/17846 %U https://mhealth.jmir.org/2020/7/e17846 %U https://doi.org/10.2196/17846 %U http://www.ncbi.nlm.nih.gov/pubmed/32407288 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 2 %P e16276 %T A Mobile Phone–Based Support Intervention to Increase Use of Postabortion Family Planning in Cambodia: Cost-Effectiveness Evaluation %A Hill,Jeremy %A McGinn,Jourdan %A Cairns,John %A Free,Caroline %A Smith,Chris %+ Graduate School of Tropical Medicine and Global Health, Nagasaki University, 1-12-4, Sakamoto, Nagasaki-shi, 852-8523, Japan, 81 8087105309, christopher.smith@lshtm.ac.uk %K mHealth %K digital health %K cost-effectiveness %K contraception %K postabortion contraception %K postabortion family planning %K Cambodia %D 2020 %7 25.2.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Despite progress over the last decade, there is a continuing unmet need for contraception in Cambodia. Interventions delivered by mobile phone could help increase uptake and continuation of contraception, particularly among hard-to-reach populations, by providing interactive personalized support inexpensively wherever the person is located and whenever needed. Objective: The objective of this study was to evaluate the cost-effectiveness of mobile phone–based support added to standard postabortion family planning care in Cambodia, according to the results of the MOTIF (MObile Technology for Improved Family planning) trial. Methods: A model was created to estimate the costs and effects of the intervention versus standard care. We adopted a societal perspective when estimating costs, including direct and indirect costs for users. The incremental cost-effectiveness ratio was calculated for the base case, as well as a deterministic and probabilistic sensitivity analysis, which we compared against a range of likely cost-effectiveness thresholds. Results: The incremental cost of mobile phone–based support was estimated to be an additional US $8160.49 per 1000 clients, leading to an estimated 518 couple-years of protection (CYPs) gained per 1000 clients and 99 disability-adjusted life-years (DALYs) averted. The incremental cost-effectiveness ratio was US $15.75 per additional CYP and US $82.57 per DALY averted. The model was most sensitive to personnel and mobile service costs. Assuming a range of cost-effectiveness thresholds from US $58 to US $176 for Cambodia, the probability of the intervention being cost-effective ranged from 11% to 95%. Conclusions: This study demonstrates that the cost-effectiveness of the intervention delivered by mobile phone assessed in the MOTIF trial lies within the estimated range of the cost-effectiveness threshold for Cambodia. When assessing value in interventions to improve the uptake and adherence of family planning services, the use of interactive mobile phone messaging and counselling for women who have had an abortion should be considered as an option by policy makers. Trial Registration: ClinicalTrials.gov NCT01823861; https://clinicaltrials.gov/ct2/show/NCT01823861 %M 32130166 %R 10.2196/16276 %U http://mhealth.jmir.org/2020/2/e16276/ %U https://doi.org/10.2196/16276 %U http://www.ncbi.nlm.nih.gov/pubmed/32130166 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e3 %T Valuing Mobile Health: An Open-Ended Contingent Valuation Survey of a National Digital Health Program %A Somers,Camilla %A Grieve,Eleanor %A Lennon,Marilyn %A Bouamrane,Matt-Mouley %A Mair,Frances S %A McIntosh,Emma %+ General Practice and Primary Care, University of Glasgow, 1 Horselethill Road, Glasgow, G12 9LX, United Kingdom, 44 1413308317, Frances.Mair@glasgow.ac.uk %K mHealth %K public health %K delivery of health care %K public health systems research %D 2019 %7 17.01.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Changing population demographics and technology developments have resulted in growing interest in the potential of consumer-facing digital health. In the United Kingdom, a £37 million (US $49 million) national digital health program delivering assisted living lifestyles at scale (dallas) aimed to deploy such technologies at scale. However, little is known about how consumers value such digital health opportunities. Objective: This study explored consumers’ perspectives on the potential value of digital health technologies, particularly mobile health (mHealth), to promote well-being by examining their willingness-to-pay (WTP) for such health solutions. Methods: A contingent valuation study involving a UK-wide survey that asked participants to report open-ended absolute and marginal WTP or willingness-to-accept for the gain or loss of a hypothetical mHealth app, Healthy Connections. Results: A UK-representative cohort (n=1697) and a dallas-like (representative of dallas intervention communities) cohort (n=305) were surveyed. Positive absolute and marginal WTP valuations of the app were identified across both cohorts (absolute WTP: UK-representative cohort £196 or US $258 and dallas-like cohort £162 or US $214; marginal WTP: UK-representative cohort £160 or US $211 and dallas-like cohort £151 or US $199). Among both cohorts, there was a high prevalence of zeros for both the absolute WTP (UK-representative cohort: 467/1697, 27.52% and dallas-like cohort: 95/305, 31.15%) and marginal WTP (UK-representative cohort: 487/1697, 28.70% and dallas-like cohort: 99/305, 32.5%). In both cohorts, better general health, previous amount spent on health apps (UK-representative cohort 0.64, 95% CI 0.27 to 1.01; dallas-like cohort: 1.27, 95% CI 0.32 to 2.23), and age had a significant (P>.00) association with WTP (UK-representative cohort: −0.1, 95% CI −0.02 to −0.01; dallas-like cohort: −0.02, 95% CI −0.03 to −0.01), with younger participants willing to pay more for the app. In the UK-representative cohort, as expected, higher WTP was positively associated with income up to £30,000 or US $39,642 (0.21, 95% CI 0.14 to 0.4) and increased spending on existing phone and internet services (0.52, 95% CI 0.30 to 0.74). The amount spent on existing health apps was shown to be a positive indicator of WTP across cohorts, although the effect was marginal (UK-representative cohort 0.01, 95% CI 0.01 to 0.01; dallas-like cohort 0.01, 95% CI 0.01 to 0.02). Conclusions: This study demonstrates that consumers value mHealth solutions that promote well-being, social connectivity, and health care control, but it is not universally embraced. For mHealth to achieve its potential, apps need to be tailored to user accessibility and health needs, and more understanding of what hinders frequent users of digital technologies and those with long-term conditions is required. This novel application of WTP in a digital health context demonstrates an economic argument for investing in upskilling the population to promote access and expedite uptake and utilization of such digital health and well-being apps. %M 30664488 %R 10.2196/mhealth.9990 %U http://mhealth.jmir.org/2019/1/e3/ %U https://doi.org/10.2196/mhealth.9990 %U http://www.ncbi.nlm.nih.gov/pubmed/30664488