The Impact of eHealth Interventions on the Improvement of Self-Care in Chronic Patients: An Overview of Systematic Reviews

Abstract

Promoting self-care is one of the most promising strategies for managing chronic conditions. This overview aimed to investigate the effectiveness of eHealth interventions at improving self-care in patients with type-2 diabetes mellitus, cardiovascular disease, and chronic obstructive pulmonary disease when compared to standard care. We carried out a review of systematic reviews on PubMed, Scopus, Cochrane, PsychInfo, and CINAHL. AMSTAR-2 was used for quality appraisal. Eight systematic reviews (six with meta-analysis) were included, involving a total of 41,579 participants. eHealth interventions were categorized into three subgroups: (i) reminders via messaging apps, emails, and apps; (ii) telemonitoring and online operator support; (iii) internet and web-based educational programs. Six systematic reviews showed an improvement in self-care measurements through eHealth interventions, which also led to a better quality of life and clinical outcomes (HbA1C, blood pressure, hospitalization, cholesterol, body weight). This overview provided some implications for practice and research: eHealth is effective in increasing self-care in chronic patients; however, it is required to designate the type of eHealth intervention based on the needed outcome (e.g., implementing telemonitoring to increase self-monitoring of blood pressure). In addition, there is a need to standardize self-care measures through increased use of validated assessment tools.

Designing a Future eHealth Service for Posthospitalization Self-management Support in Long-term Illness: Qualitative Interview Study

“…Research on eHealth-based support interventions for people with NCDs recommends that the interventions be theory-based and hold an element of communication in addition to web-based material [ 41 ]. eHealth programs are found to be most efficient when led by multidisciplinary teams where HCPs can encourage the patients to adhere to the program and when the eHealth program is designed based on the outcomes to be achieved [ 42 ]. Critical gaps remain in the design and evaluation of self-management interventions, with a lack of patient and clinician involvement [ 43 ].…”

A Deep Dive into the Nexus between Digital Health and Life Sciences Amidst the COVID-19 Pandemic: An Editorial Expedition

“…All the other studies [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ] have dealt with the use of DH in the life sciences, which, in addition to bioengineering, touched by all, have examined, from time to time, other categories ( Table 1 ), such as Anatomy [ 8 , 11 ], Bioinformatics [ 14 , 16 ], Cell biology [ 8 , 11 ], Neuroscience [ 8 , 12 , 15 , 17 , 20 ], Physiology [ 9 , 10 , 12 , 13 ], Population biology [ 14 , 16 , 18 , 19 ], and others that are shown in Table 1 .…”

“…Two specific reviews addressed and overviewed the impact of DH in remote health care and healthcare interventions [ 18 , 19 ]. The impact of eHealth interventions on the improvement of self-care in chronic patients was overviewed in [ 18 ], while the healthcare professionals’ experience of reforming digital care visits was investigated in [ 19 ].…”

“…The published works on the DH, reported in the collection [ 1 , 2 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ], demonstrate the usefulness of DH in connecting various branches of life sciences, especially during the pandemic. The use of DH in contact tracing has been particularly significant, with several studies reporting on its impact and factors influencing its use [ 2 , 4 , 5 , 6 , 7 ].…”

“…Additionally, DH applications have been used in biomedical diagnostics [ 8 , 11 ], physical activity [ 12 , 13 ], mental health monitoring [ 17 ], and remote healthcare interventions [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ].…”