Improved readability and functions needed for mHealth apps targeting patients with heart failure: An app store review.
Karen Dunn LopezSena ChaeGirgis MicheleDan FraczkowskiPantea HabibiDebaleena ChattopadhyaySara B DonevantPublished in: Research in nursing & health (2020)
To maintain their quality of life and avoid hospitalization and early mortality, patients with heart failure must recognize and respond to symptoms of exacerbation. A promising method for engaging patients in their self-care is through mobile health applications (mHealth apps). However, for mHealth to have its greatest chance for improving patient outcomes, the app content must be readable, provide useful functions and be based in evidence. The study aimed to determine: (1) readability, (2) types of functions, and (3) linkage to authoritative sources of evidence for self-care focused mHealth apps targeting heart failure patients that are available in the Apple and Google Play Stores. We systematically searched for mHealth apps targeting patients with heart failure in the Apple and Google Play Stores and applied selection criteria. Readability of randomly selected informational paragraphs were determined using Flesch-Kincaid grade level test tool in Microsoft Word. Ten mHealth apps met our criteria. Only one had a reading grade level at or below the recommended 6th grade reading level (average 9.35). The most common functions were tracking, clinical data feedback, and non-data-based reminders and alerts. Only three had statements that clearly linked the mHealth app content to trustworthy, evidence-based sources. Only two had interoperability with the electronic health record and only one had a communication feature with clinicians. Future mHealth designs that are tailored to patients' literacy level and have advanced functions may hold greater potential for improving patient outcomes.
Keyphrases
- electronic health record
- end stage renal disease
- ejection fraction
- health information
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- healthcare
- cancer therapy
- working memory
- big data
- chronic obstructive pulmonary disease
- tyrosine kinase
- intensive care unit
- genome wide
- smoking cessation
- hiv infected
- social media
- artificial intelligence
- dna methylation
- hepatitis c virus
- current status
- antiretroviral therapy