scholarly journals DEVELOPMENT OF AN ASSESSMENT METHOD FOR CHRONIC DISEASE MOBILE HEALTH APPLICATIONS

2017 ◽  
Vol 2 (1) ◽  
pp. 148-148
Author(s):  
Kiana Farhadyar ◽  
Farhad Fatehi
Author(s):  
Petre Iltchev ◽  
Andrzej Śliwczyński ◽  
Potr Szynkiewicz ◽  
Michał Marczak

This chapter analyzes the role of m-health applications supporting patients with chronic diseases (based on examples from asthma care). The purpose of the chapter is to describe the mobile health application development cycle. The chapter begins with a presentation of asthma as a chronic disease and its prevalence and costs for society, as a determinant of the role and place of m-health applications in chronic disease management. Subsequent sections analyze trends in the development of health care, information systems, and health care payment systems as components of the environment for the implementation of m-health applications. The chapter focuses on prerequisites for the introduction of this type of solutions, presents existing applications, and discusses how to define the key functionalities and benefits for patients, payers, and doctors. The financing cycle, barriers to implementation, and future trends are also addressed.


Author(s):  
Petre Iltchev ◽  
Andrzej Śliwczyński ◽  
Potr Szynkiewicz ◽  
Michał Marczak

This chapter analyzes the role of m-health applications supporting patients with chronic diseases (based on examples from asthma care). The purpose of the chapter is to describe the mobile health application development cycle. The chapter begins with a presentation of asthma as a chronic disease and its prevalence and costs for society, as a determinant of the role and place of m-health applications in chronic disease management. Subsequent sections analyze trends in the development of health care, information systems, and health care payment systems as components of the environment for the implementation of m-health applications. The chapter focuses on prerequisites for the introduction of this type of solutions, presents existing applications, and discusses how to define the key functionalities and benefits for patients, payers, and doctors. The financing cycle, barriers to implementation, and future trends are also addressed.


2019 ◽  
pp. 1076-1103
Author(s):  
Petre Iltchev ◽  
Andrzej Śliwczyński ◽  
Potr Szynkiewicz ◽  
Michał Marczak

This chapter analyzes the role of m-health applications supporting patients with chronic diseases (based on examples from asthma care). The purpose of the chapter is to describe the mobile health application development cycle. The chapter begins with a presentation of asthma as a chronic disease and its prevalence and costs for society, as a determinant of the role and place of m-health applications in chronic disease management. Subsequent sections analyze trends in the development of health care, information systems, and health care payment systems as components of the environment for the implementation of m-health applications. The chapter focuses on prerequisites for the introduction of this type of solutions, presents existing applications, and discusses how to define the key functionalities and benefits for patients, payers, and doctors. The financing cycle, barriers to implementation, and future trends are also addressed.


2015 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi

2020 ◽  
Author(s):  
Claudia Eberle ◽  
Maxine Löhnert

BACKGROUND Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), Metabolic Syndrome (MetS) as well as cardiovascular disease (CD). Against this background mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM clearly. OBJECTIVE Since there is – to our knowledge – no systematic literature review published, which focusses on the effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes of mother and child, we conducted these much-needed analyses. METHODS Data sources: A systematic literature search in Medline (Pubmed), Cochrane Library, Embase, CINAHL and Web of Science was performed including full text publications since 2008 up to date. An additional manual search in references and Google Scholar was conducted subsequently. Study Eligibility Criteria: Women diagnosed with GDM using specific mHealth-Apps during pregnancy compared to control groups, which met main clinical parameters and outcomes in GDM management as well as maternity and offspring care. Study appraisal and synthesis methods: Study quality was assessed and rated “strong”, “moderate” or “weak” by using the Effective Public Health Practice Project (EPHPP) tool. Study results were strongly categorized by outcomes; an additional qualitative summary was assessed. Study selection: Overall, n= 114 studies were analyzed, n= 46 duplicates were removed, n=5 studies met the eligible criteria and n=1 study was assessed by manual search subsequently. In total, n=6 publications, analyzing n=408 GDM patients in the interventional and n=405 women diagnosed with GDM in the control groups, were included. These studies were divided into n=5 two-arm randomized controlled trials (RCT) and n=1 controlled clinical trial (CCT). RESULTS Distinct improvements in clinical parameters and outcomes, such as fasting blood glucoses (FBG), 2-hour postprandial blood glucoses (PBG), off target blood glucose measurements (OTBG), delivery modes and patient compliance were analyzed in GDM patients using specific mHealth-Apps compared to matched control groups. CONCLUSIONS mHealth-Apps clearly improve clinical outcomes in management of GDM effectively. More studies need to be done more in detail.


Author(s):  
Sahar Khenarinezhad ◽  
Ehsan Ghazanfari Savadkoohi ◽  
Leila Shahmoradi

Aim: During the epidemic and with an increase in coronavirus (COVID-19) disease prevalence, emergency care is essential to help people stay informed and undertake self-management measures to protect their health. One of these self-management procedures is the use of mobile apps in health. Mobile health (mHealth) applications include mobile devices in collecting clinical health data, sharing healthcare information for practitioners and patients, real-time monitoring of patient vital signs, and the direct provision of care (via mobile telemedicine). Mobile apps are increasing to improve health, but before healthcare providers can recommend these applications to patients, they need to be sure the apps will help change patients' lifestyles. Method: A search was conducted systematically using the keywords "Covid-19," "Coronavirus," "Covid-19, and Self-management" at the "Apple App Store". Then we evaluated the apps according to MARS criteria in May 2020. Results: A total of 145 apps for COVID-19 self-management were identified, but only 32 apps met our inclusion criteria after being assessed. The overall mean MARS score was 2.9 out of 5, and more than half of the apps had a minimum acceptability score (range 2.5-3.9). The "who academy" app received the highest functionality score. Who Academy, Corona-Care and First Responder COVID-19 Guide had the highest scores for behavior change. Conclusion: Our findings showed that few apps meet the quality, content, and functionality criteria for Covid-19 self-management. Therefore, developers should use evidence-based medical guidelines in creating mobile health applications so that, they can provide comprehensive and complete information to both patients and healthcare provider.


2017 ◽  
Vol 33 (9) ◽  
pp. 1-6
Author(s):  
Adam Rosenfeld ◽  
Sachin Pendse ◽  
Nicole R. Nugent

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