The quantified patient of the future: Opportunities and challenges

Majmudar, Maulik D.; Colucci, Lina A.; Landman, Adam B.

doi:10.1016/j.hjdsi.2015.02.001

Cited by 38 publications

(21 citation statements)

References 10 publications

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“…In the past, these basic measures have been difficult to capture in a passive and unobtrusive way outside of self‐report. If these previously uncollected streams of continuous data can be translated into actionable information and presented at meaningful decision points, patients and their providers may be better able to achieve health goals and manage chronic conditions …”

Section: Landscape Evolution and Growthmentioning

confidence: 99%

“…If these previously uncollected streams of continuous data can be translated into actionable information and presented at meaningful decision points, patients and their providers may be better able to achieve health goals and manage chronic conditions. 10 These advances have led to a large flow of financial support into the mobile and digital health space. In 2014, venture capital funding of digital health companies was a staggering $4.3 billion, which was nearly equal to that of the prior 3 years combined.…”

Section: Landscape Evolution and Growthmentioning

confidence: 99%

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Defining a Mobile Health Roadmap for Cardiovascular Health and Disease

Eapen

Turakhia

McConnell

et al. 2016

JAHA

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Section: Landscape Evolution and Growthmentioning

confidence: 99%

Section: Landscape Evolution and Growthmentioning

confidence: 99%

Defining a Mobile Health Roadmap for Cardiovascular Health and Disease

Eapen

Turakhia

McConnell

et al. 2016

JAHA

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“…For instance, one might have eaten mixed salad, but the system needs to know how many grams of spinach versus carrots and which salad dressing in order to calculate accurate calories and nutritional content. Sophisticated, detailed, quantified tracking practices are not popular for all user groups (13). Tracking detailed health information is a user burden, affecting sustained tracking behavior (7).…”

Section: Introductionmentioning

confidence: 99%

Improving Heart disease risk through quality-focused diet logging: pre-post study of a diet quality tracking app

VanDam

Kwon

Chiuve

et al. 2020

Preprint

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18 Diet-tracking mobile apps have been effective in behavior change. At the same time, 19 quantity-focused diet tracking (e.g., calorie counting) can be time-consuming and 20 tedious, leading to unsustained adoption. Diet Quality-focusing on high-quality 21 dietary patterns rather than quantifying diet into calories-has shown effectiveness 22 in improving heart disease risk. Healthy Heart Score (HHS) predicts 20-year 23 cardiovascular risks based on quality-focused food category consumptions, rather 24 than detailed serving sizes. No studies have examined how mobile health apps 25 focusing on diet quality can bring promising results on health outcomes and ease of 26 adoption. We designed a mobile app to support the HHS informed quality-focused 27 dietary approach by enabling users to log simplified diet quality and view its real-28 time impact on future heart disease risks. Users were asked to log food categories 29 that are the main predictors of HHS. We measured the app's feasibility and efficacy 30 on improving individuals' clinical and behavioral factors affecting future heart 31 disease risks and app use. We recruited 38 overweight or obese participants at high 32 heart disease risk, who used the app for 5 weeks and measured weight, blood sugar, 33 and blood pressure, HHS, and Diet Score (DS) measuring diet quality at baseline and 34 the fifth week of the intervention. The majority used the application every week 35 (84%) and significantly improved DS and HHS at the fifth week (p<0.05), although 36 only 10 participants (31%) checked their risk scores more than once. Other 37 outcomes did not show significant changes. Our study showed logging simplified 38 diet quality significantly improved dietary behavior. The participants were not 3 39 interested in seeing HHS, and the participants perceived logging diet categories 40 irrelevant to improving HHS as important. We discuss the complexities of 41 addressing health risks, quantity vs. quality-based health monitoring, and 42 incorporating secondary behavior change goals that matter to users when designing 43 mobile health. Introduction45 An increasing number of mobile apps have explored ways to efficiently and 46 effectively monitor and improve health behavior (1-3). Among these mobile health 47 apps, diet monitoring is one of the most popular domains. Reasons attribute to 48 diabetes and obesity leading as the top two fields producing revenue in the mobile 49 health market (4) and their significance in impacting public health. A systematic 50 review of mobile applications showed that mobile health apps increased adherence 51 to diet monitoring and reduced efforts to maintain diet without using the apps (5). 52 However, focusing on the quantification of diet can bring a number of challenges.53 Food journaling can be "too much effort," "time-consuming," or "tedious" (6,7). 54 Detailed food journaling entry can be challenging because users often might not 55 remember or know what and how much they have eaten (8). Users also feel the 56 dietary information in the ...

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“…Traditional healthcare innovation has focused on the development of new diagnostics, drugs, and devices for use in hospitals and clinics, with more recent expansion to include quality‐improvement and cost‐containment efforts. The explosion of digital health technologies, centered around smartphones and connected devices, and enabled by advanced low‐cost, miniaturized electronics, presents significant opportunities for clinicians, researchers, and healthcare administrators 1. This is coinciding with the rapid growth of personal and population “big data”—from genome to physiome—that can help us diagnose and treat illness more effectively and efficiently, including in heart disease and stroke care.…”

mentioning

confidence: 99%

“…The explosion of digital health technologies, centered around smartphones and connected devices, and enabled by advanced low-cost, miniaturized electronics, presents significant opportunities for clinicians, researchers, and healthcare administrators. 1 This is coinciding with the rapid growth of personal and population "big data"-from genome to physiome-that can help us diagnose and treat illness more effectively and efficiently, including in heart disease and stroke care. As these advances in healthcare accelerate, academic medical centers should play an active role in collaborating with industry in championing innovation, including implementation of technology-enabled healthcare solutions.…”

mentioning

confidence: 99%