Strategies for the Successful Implementation of a Novel iPhone Loaner System (iShare) in mHealth Interventions: Prospective Study

Yang, William; Spaulding, Erin M; Lumelsky, David; Hung, George; Huynh, Pauline P.; Knowles, Kellen; Marvel, Francoise A; Vilarino, Valerie; Wang, Jane; Shah, Lochan M.; Xun, Helen; Shan, Rongzi; Wongvibulsin, Shannon; Martin, Seth S.

doi:10.2196/16391

Cited by 26 publications

(19 citation statements)

References 5 publications

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“…Third, underserved patients were included via our iShare program to improve the generalizability of our findings to vulnerable populations. 15 , 40 Fourth, we employed an interdisciplinary approach to patient-centered technology development and clinical implementation. 10 , 41 …”

Section: Discussionmentioning

confidence: 99%

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Digital Health Intervention in Acute Myocardial Infarction

Marvel

Spaulding

Lee

et al. 2021

Circ: Cardiovascular Quality and Outcomes

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Background: Thirty-day readmissions among patients with acute myocardial infarction (AMI) contribute to the US health care burden of preventable complications and costs. Digital health interventions (DHIs) may improve patient health care self-management and outcomes. We aimed to determine if patients with AMI using a DHI have lower 30-day unplanned all-cause readmissions than a historical control. Methods: This nonrandomized controlled trial with a historical control, conducted at 4 US hospitals from 2015 to 2019, included 1064 patients with AMI (DHI n=200, control n=864). The DHI integrated a smartphone application, smartwatch, and blood pressure monitor to support guideline-directed care during hospitalization and through 30-days post-discharge via (1) medication reminders, (2) vital sign and activity tracking, (3) education, and (4) outpatient care coordination. The Patient Activation Measure assessed patient knowledge, skills, and confidence for health care self-management. All-cause 30-day readmissions were measured through administrative databases. Propensity score–adjusted Cox proportional hazard models estimated hazard ratios of readmission for the DHI group relative to the control group. Results: Following propensity score adjustment, baseline characteristics were well-balanced between the DHI versus control patients (standardized differences <0.07), including a mean age of 59.3 versus 60.1 years, 30% versus 29% Women, 70% versus 70% White, 54% versus 54% with private insurance, 61% versus 60% patients with a non ST-elevation myocardial infarction, and 15% versus 15% with high comorbidity burden. DHI patients were predominantly in the highest levels of patient activation for health care self-management (mean score 71.7±16.6 at 30 days). The DHI group had fewer all-cause 30-day readmissions than the control group (6.5% versus 16.8%, respectively). Adjusting for hospital site and a propensity score inclusive of age, sex, race, AMI type, comorbidities, and 6 additional confounding factors, the DHI group had a 52% lower risk for all-cause 30-day readmissions (hazard ratio, 0.48 [95% CI, 0.26–0.88]). Similar results were obtained in a sensitivity analysis employing propensity matching. Conclusions: Our results suggest that in patients with AMI, the DHI may be associated with high patient activation for health care self-management and lower risk of all-cause unplanned 30-day readmissions. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03760796.

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Section: Discussionmentioning

confidence: 99%

“…If the participant had an Android or older generation iPhone, they were given a loaner smartphone called an “iShare” preloaded with Corrie and a subscriber identity module card for cellular data access. 15 Intervention components were equivalent for those using Corrie on a personal iPhone and for those using Corrie on an iShare.…”

Section: Methodsmentioning

confidence: 99%

Digital Health Intervention in Acute Myocardial Infarction

Marvel

Spaulding

Lee

et al. 2021

Circ: Cardiovascular Quality and Outcomes

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“…To reduce selection bias, participants who did not own an iPhone were given a loaner phone to use for the duration of the study. 11 , 12 Data exclusion criteria for this sub-study analysis were: (1) BP values outside of the manufacturer-specified measurement ranges of 60-260 mmHg systolic BP or 40-199 mmHg diastolic BP, 13 (2) participants who were not given an iHealth BP monitor (due to participation during the pilot phase or lack of cuff availability in appropriate size) to minimize erroneous values, 10 and (3) participants who only recorded BP values on a single day that would preclude assessment of trends over time. Ethical approval was obtained from the Johns Hopkins University School of Medicine Institutional Review Board and other participating sites.…”

Section: Methodsmentioning

confidence: 99%

Early blood pressure assessment after acute myocardial infarction: Insights using digital health technology

Shan

Ding

Weng

et al. 2020

American Journal of Preventive Cardiology

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Objective There is rising interest in digital health in preventive cardiology, particularly for blood pressure (BP) management. In a digital health study of early BP assessment following acute myocardial infarction (AMI), we sought to examine feasibility and the (1) proportion of post-AMI patients with controlled BP and hypotension, and (2) association between prior cardiovascular disease (CVD) and BP post-AMI. Methods In this substudy of the parent Myocardial infarction, COmbined-device, Recovery Enhancement (MiCORE) study, type 1 AMI patients were enrolled between October 2017 and April 2019. Participants self-monitored their BP through 30 days after hospital discharge using an FDA-approved wireless BP monitor connected with a smartphone application. Linear mixed-effects models assessed the association between prior CVD and BP trajectory post-discharge, adjusting for antihypertensive medications and a propensity score inclusive of CVD risk factors. Results Sixty-eight AMI patients (mean age 58±10 years, 75% male, 68% white race, 68% history of hypertension, 24% prior CVD) provided 2,638 measurements over 30 days. The percentage of BP control <130/80 mmHg was 59.6% (95% CI: 54.3 - 64.9%) and <140/90 mmHg was 83.7% (95% CI: 80.3-87.2%). The percentage of systolic BP <90 mmHg was 1.1% (95% CI: 0.17-2.0%) and the percentage of diastolic BP <60 mmHg was 3.9% (95% CI: 2.6-5.2%). Prior CVD was associated with 12.2 mmHg higher mean daily systolic BP during admission (95% CI: 3.5-20.9 mmHg), which persisted over follow-up. There was no association between prior CVD and diastolic BP. Conclusion The digital health program was feasible and ∼40% of post-AMI patients who engaged in it had uncontrolled BP according to recent guideline cutpoints, while hypotension occurred rarely. The gap in BP control was especially large in patients in whom AMI represented recurrent CVD. These data suggest an opportunity for more aggressive secondary prevention early after MI as care models integrate digital health.

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“…While this may incur a cost, the return of value in terms of incentivizing recruitment may be worthwhile. 14 Social Connectedness and Mutual Trust: Use of an online platform can lead to novel opportunities to establish trust and strengthen participant engagement. While in-person experiences may allow participants to feel more fully connected, 8 a 'patient-centered' approach that includes involving the patient or family directly in research functions and obtaining their feedback may enrich engagement and connectedness.…”

Section: Increased Participant Inclusion and Enrollment/retentionmentioning

confidence: 99%

“…Hardware considerations may require budgeting for loaner devices so that those few participants without access to computers or smartphones can still complete the study, thereby improving study participation and generalizability. While this may incur a cost, the return of value in terms of incentivizing recruitment may be worthwhile [14].…”

Section: Digital Equalitymentioning

confidence: 99%