The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study

Cartledge, Susie; Maddison, Ralph; Vogrin, Sara; Falls, Roman; Tumur, Odgerel; Hopper, Ingrid; Neil, Christopher

doi:10.2196/18496

Cited by 5 publications

(8 citation statements)

References 17 publications

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“…The Seeing is Believing (SIB) study was a large prospective observational pilot study that evaluated the feasibility and acceptability of using wearable cameras and point-of-care testing for self-care in patients with HF [ 21 , 26 ]. As a pilot study, no formal power calculations were performed to determine the optimum sample size.…”

Section: Methodsmentioning

confidence: 99%

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Daily Activity Lifelogs of People With Heart Failure: Observational Study

Tegegne,

Tran,

Nourse

et al. 2024

JMIR Form Res

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Background Globally, heart failure (HF) affects more than 64 million people, and attempts to reduce its social and economic burden are a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalizations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear. Objective This study aimed to determine the potential utility of wearable cameras to better understand the activities of daily living in people living with HF. Methods The “Seeing is Believing (SIB)” study involved 30 patients with HF who wore wearable cameras for a maximum of 30 days. We used the E-Myscéal web-based lifelog retrieval system to process and analyze the wearable camera image data set. Search terms for 7 daily activities (physical activity, gardening, shopping, screen time, drinking, eating, and medication intake) were developed and used for image retrieval. Sensitivity analysis was conducted to compare the number of images retrieved using different search terms. Temporal patterns in daily activities were examined, and differences before and after hospitalization were assessed. Results E-Myscéal exhibited sensitivity to specific search terms, leading to significant variations in the number of images retrieved for each activity. The highest number of images returned were related to eating and drinking, with fewer images for physical activity, screen time, and taking medication. The majority of captured activities occurred before midday. Notably, temporal differences in daily activity patterns were observed for participants hospitalized during this study. The number of medication images increased after hospital discharge, while screen time images decreased. Conclusions Wearable cameras offer valuable insights into daily activities and self-management in people living with HF. E-Myscéal efficiently retrieves relevant images, but search term sensitivity underscores the need for careful selection.

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Section: Methodsmentioning

confidence: 99%

“…Baseline assessment included medical history, demographics, and physical measurements. A research assistant collected point-of-care test data, hospitalization information, and other variables twice a week during the 30-day study [ 26 ]. At the end of this study, participants underwent a brief interview about their camera usage experience.…”

Section: Methodsmentioning

confidence: 99%

Daily Activity Lifelogs of People With Heart Failure: Observational Study

Tegegne,

Tran,

Nourse

et al. 2024

JMIR Form Res

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“…The acceptability of wearable cameras to all participants (N=30) is also reported. The feasibility of point-of-care testing is reported elsewhere [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

“…The research team visited participants twice weekly during the study period to download images, at which time participants were given the opportunity to delete images. Physical parameters were also monitored at the twice-weekly visits; the results were reported elsewhere [ 28 ]. At the end of the study period, a short interview was conducted with each participant to ask about their experience using a wearable camera.…”

Section: Methodsmentioning

confidence: 99%

Feasibility and Acceptability of Wearable Cameras to Assess Self-care in People With Heart Failure: Pilot Study

Askman¹,

Löf²,

Maddison³

et al. 2023

JMIR Form Res

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Background Heart failure (HF) is a common chronic condition that affects over 26 million people worldwide. It is a progressive and debilitating disease with a broad symptom profile, intermittently marked by periods of acute decompensation. People with HF generally do not self-manage their condition well (eg, monitoring symptoms, taking medications regularly, physical activity, etc). A better understanding of self-care activities and what factors may indicate deterioration is warranted. Objective The aim of this study was to determine the feasibility and acceptability of using wearable cameras to assess self-care activities in people with HF. The study objectives were to (1) explore whether changes in self-care activities could be identified prior to hospitalization and (2) determine the acceptability of wearable cameras to people with HF. Methods A total of 30 people recently diagnosed with HF wore a camera for a maximum of 30 days; the camera took a photo every 30 seconds in the forward-facing direction. At the end of the study, all 30 participants were presented with 8 statements of acceptability, scored on a 5-point Likert scale. To determine whether camera images could identify changes in self-care activities and lifestyle risk factors before hospitalization, we analyzed images from participants (n=8) who were hospitalized during the 30-day study period. Images from the period immediately prior to hospitalization and a comparison were selected for each participant. Images were manually coded according to 9 different event categories relating to self-care and lifestyle risk factors, and events were compared between the 2 periods. Results The participants reported high acceptability for wearing the cameras, as most strongly agreed or agreed that they were comfortable to wear (28/30, 93%) and easy to use (30/30, 100%). The results of the camera image analysis showed that participants undertook fewer activities of daily living (P=.008) and were more sedentary (P=.02) prior to being hospitalized, compared to a period nonadjacent to hospitalization. Conclusions Adults with HF were accepting of using a wearable camera for periods within a 30-day time frame. Wearable cameras were a feasible approach for providing data on selected self-care activities and lifestyle risk factors for HF and offer the potential to be a valuable tool for improving our understanding of self-care.

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“…There's a lot of hype about using sensors embedded in smartphones to detect changes in usage patterns which imply a worsening of disease [60] or for detection of disease [61][62][63]. Even very recent studies are exploratory and need additional validation before being translated into the field [64,65]. Although the research base that makes production use of smartphone sensors is still in its infancy [66], there are some promising developments in creating architectures that are ready for conducting research.…”

Section: Ecological Momentary Assessments and Interventions Are Usefu...mentioning

confidence: 99%

Designing Disease-Specific mHealth Apps for Clinical Value

Keshavjee¹,

Johnston-Jewell²,

Lee³

et al. 2022

Smart and Pervasive Healthcare

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mHealth apps for patient use are promising but continue to face a plateau in usage. Current apps work for a limited segment of the patient population, i.e., those who enjoy tracking for intrinsic rewards. There are many opportunities to support patient care in between health care provider visits that are not currently being met for many diseases and patient types (personas). This is an area of great potential growth for mHealth apps and could contribute greatly to patient health and wellness. In this chapter, we propose a framework for how to think about the between-visit needs of patients that would motivate continued use of mhealth apps. We view the app design process from the following perspectives: 1) disease-specific needs, 2) non-disease specific needs, 3) behavioral theoretical aspects of app usage and 4) app-intrinsic usage motivators. Myasthenia gravis serves as the use case for illustrating these perspectives and how to use them in designing a disease-specific mHealth app.

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The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study

Cited by 5 publications

References 17 publications

Daily Activity Lifelogs of People With Heart Failure: Observational Study

Daily Activity Lifelogs of People With Heart Failure: Observational Study

Feasibility and Acceptability of Wearable Cameras to Assess Self-care in People With Heart Failure: Pilot Study

Designing Disease-Specific mHealth Apps for Clinical Value

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