Connected health for growth hormone treatment research and clinical practice: learnings from different sources of real-world evidence (RWE)-large electronically collected datasets, surveillance studies and individual patients' cases.
Nea BomanLuis Fernandez-LuqueEkaterina KoledovaMarketta KauseRisto LapattoPublished in: BMC medical informatics and decision making (2021)
The data and case studies presented herein illustrate the importance of adherence to GH therapy and how good growth outcomes can be achieved by following treatment as described. They also show how the device, software, and database ecosystem can complement normal clinical follow-up by providing HCPs with reliable information about patient adherence between visits and also providing researchers with real-world evidence of adherence and growth outcomes across a large population of patients with growth disorders treated with GH via the easypod™ device.
Keyphrases
- growth hormone
- clinical practice
- public health
- end stage renal disease
- healthcare
- ejection fraction
- newly diagnosed
- chronic kidney disease
- glycemic control
- emergency department
- type diabetes
- prognostic factors
- machine learning
- electronic health record
- adipose tissue
- combination therapy
- metabolic syndrome
- peritoneal dialysis
- human health
- single cell
- skeletal muscle
- deep learning
- rna seq
- artificial intelligence
- risk assessment
- health promotion
- patient reported outcomes