Remote Monitoring of Chronic Diseases: A Landscape Assessment of Policies in Four European Countries

Rojahn, Katherine; Laplante, Suzanne; Sloand, James A.; Main, Claire; Ibrahim, Aftab; Wild, Janet; Sturt, Nicky; Areteou, T; Johnson, Katherine

doi:10.1371/journal.pone.0155738

Cited by 53 publications

(42 citation statements)

References 24 publications

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“…Moreover, Spain in recent years has greatly participated in European programs funding activities on ICT and ageing [37], throughout the "National Plans Research, Development and Innovation", running from 2007 to 2012 [78]. In particular, in Spain, a great part of funding for remote monitoring projects is provided by the European Commission [80]. Moving specifically to health system characteristics of countries, we found on the whole a greater implementation of care programs adopting eHealth tools in decentralized countries, with a NHS model and with a strong/medium PC.…”

Section: Discussionmentioning

confidence: 99%

Integrated Care Programs for People with Multimorbidity in European Countries: eHealth Adoption in Health Systems

Melchiorre

Papa

Quattrini

et al. 2020

BioMed Research International

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Introduction. eHealth applications have the potential to provide new integrated care services to patients with multimorbidity (MM), also supporting multidisciplinary care. The aim of this paper is to explore how widely eHealth tools have been currently adopted in integrated care programs for (older) people with MM in European countries, including benefits and barriers concerning their adoption, according to some basic health system characteristics. Materials and Methods. In 2014, in the framework of the ICARE4EU project, expert organizations in 24 European countries identified 101 integrated care programs. Managers of the selected programs completed an online questionnaire on several dimensions, including the use of eHealth. We analyzed data from this questionnaire, in addition to qualitative information from six innovative programs which were studied in depth through case study methodology, according to characteristics of national health systems: a national health model (financing system), overall strength of primary care (PC) (structure/service delivery process), and level of (de)centralization of health system (executive powers in a country). Results. 85 programs (out of 101) adopted at least one eHealth tool, and 42 of these targeted explicitly older people. In most cases, Electronic Health Records (EHRs) were used and some benefits emerged like improved care management and integration, although inadequate funding mechanisms represented a major barrier. The analysis by health system characteristics showed a greater adoption of eHealth applications in decentralized countries, in countries with a National Health Service (NHS) model, and in countries with a strong/medium level of PC development. Conclusions. Although in the light of some limitations, findings indicate a relation between implementation of care programs using eHealth tools and basic characteristics of health systems, with decentralization of a health system, NHS model, and strong/medium PC having a key role. However adaptations of European health systems seem necessary, in order to provide a more innovative and integrated care.

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Section: Discussionmentioning

confidence: 99%

Integrated Care Programs for People with Multimorbidity in European Countries: eHealth Adoption in Health Systems

Melchiorre

Papa

Quattrini

et al. 2020

BioMed Research International

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“…Yet, while our study showcased the benefit of automated systems, we feel the next frontier in this field needs to address the interpretation of data collected from these devices beyond displaying the data to users in attractive pictures [32]. Many studies have shown the benefit of remote monitoring in improving outcomes with patients not only in chronic condition such as chronic obstructive pulmonary disease, heart failure, diabetes, or hypertension [33,34] but also meaningful interpretation of data at the point of need can be valuable in acute infectious disease such as Ebola outbreak [35]. …”

Section: Discussionmentioning

confidence: 99%

Self-Monitoring Utilization Patterns Among Individuals in an Incentivized Program for Healthy Behaviors

Kim¹,

Taitel²,

Radin³

et al. 2016

J Med Internet Res

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BackgroundThe advent of digital technology has enabled individuals to track meaningful biometric data about themselves. This novel capability has spurred nontraditional health care organizations to develop systems that aid users in managing their health. One of the most prolific systems is Walgreens Balance Rewards for healthy choices (BRhc) program, an incentivized, Web-based self-monitoring program.ObjectiveThis study was performed to evaluate health data self-tracking characteristics of individuals enrolled in the Walgreens’ BRhc program, including the impact of manual versus automatic data entries through a supported device or apps.MethodsWe obtained activity tracking data from a total of 455,341 BRhc users during 2014. Upon identifying users with sufficient follow-up data, we explored temporal trends in user participation.ResultsThirty-four percent of users quit participating after a single entry of an activity. Among users who tracked at least two activities on different dates, the median length of participating was 8 weeks, with an average of 5.8 activities entered per week. Furthermore, users who participated for at least twenty weeks (28.3% of users; 33,078/116,621) consistently entered 8 to 9 activities per week. The majority of users (77%; 243,774/315,744) recorded activities through manual data entry alone. However, individuals who entered activities automatically through supported devices or apps participated roughly four times longer than their manual activity-entering counterparts (average 20 and 5 weeks, respectively; P<.001).ConclusionsThis study provides insights into the utilization patterns of individuals participating in an incentivized, Web-based self-monitoring program. Our results suggest automated health tracking could significantly improve long-term health engagement.

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“…Phone counseling is one of the options to overcome these barriers that have emerged over the last decade, offering promising results. Its potential to increase the efficiency of healthcare for chronic diseases has been studied, as in the case of alcohol abuse (4, 5). Furthermore, some research has indicated that this tool might provide a way for the patient to not suffer the stigma of being identified as an addict (6, 7).…”

Section: Introductionmentioning

confidence: 99%

CBI-20: Psychometric Properties for the Coping Behaviors Inventory for Alcohol Abuse in Brazil

Constant¹,

Moret-Tatay

Benchaya³

et al. 2018

Front. Psychiatry

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For any professional, it is of crucial importance to know not only how coping styles and strategies are present in an individual, but to know about its role to the treatment of alcohol abuse. Moreover, new approaches have emerged in this area in terms of relapse prevention and the counseling by phone can be an alternative. The aim of this study is to examine the factor structure of the Coping Behaviors Inventory (CBI) and to test its invariance across groups face-to-face and phone counseling in Brazil. For this purpose, two studies were carried out: study I, the factor structure was revisited in terms of exploratory factor analysis. Study II, face-to-face and phone counseling were examined through confirmatory factor analysis and multigroup analysis. The results confirmed the 4-factor solution with a revised model for the removal of 16 items. Thus presented, a reduced version with better indexes than the previous versions developed over the last 30 years that was ones reformulated from 60 items. The Internal consistency for study I presented α = 0.90 and homogeneity was between 0.17 and 0.5). In addition the KMO = 0.9 = 0.932, X(df=630)2 = 6091.94, p < 0.0 < 0.001. In study II, cronbach's alpha = 0.91 and homogeneity 0.23–0.61 (telemedicine treatment) and α = 0.90 0.17 to 0.63 (face-to-face treatment). In the CFA, the examination of the current version has better fit than the that the traditional model. Moreover, the new version showed convergent validity with the IDHEA questionnaire. In the multigroup analysis no significant changes between groups to a metric level. Finally, the Brazilian version of inventory showed no differences between the phone counseling and face-to-face participants in a metric level after a multigroup analysis.

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Remote Monitoring of Chronic Diseases: A Landscape Assessment of Policies in Four European Countries

Cited by 53 publications

References 24 publications

Integrated Care Programs for People with Multimorbidity in European Countries: eHealth Adoption in Health Systems

Integrated Care Programs for People with Multimorbidity in European Countries: eHealth Adoption in Health Systems

Self-Monitoring Utilization Patterns Among Individuals in an Incentivized Program for Healthy Behaviors

CBI-20: Psychometric Properties for the Coping Behaviors Inventory for Alcohol Abuse in Brazil

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