The Utility of Predicting Hospitalizations Among Patients With Heart Failure Using mHealth: Observational Study.
Susie CartledgeRalph MaddisonSara VogrinRoman FallsOdgerel TumurIngrid HopperChristopher NeilPublished in: JMIR mHealth and uHealth (2020)
The use of subjective respiratory symptom reporting on a 5-point Likert scale may facilitate a simple and low-cost method of predicting heart failure decompensation and imminent hospitalization. Serial collection of symptom data could be augmented using ecological momentary assessment of self-reported symptoms within a mobile health monitoring strategy for patients at high risk for heart failure decompensation.
Keyphrases
- heart failure
- low cost
- end stage renal disease
- ejection fraction
- newly diagnosed
- patient reported
- peritoneal dialysis
- left ventricular
- chronic kidney disease
- prognostic factors
- climate change
- atrial fibrillation
- cardiac resynchronization therapy
- electronic health record
- acute heart failure
- patient reported outcomes
- deep learning
- human health