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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

Authors
  • Boman, Nea1
  • Fernandez-Luque, Luis2
  • Koledova, Ekaterina3
  • Kause, Marketta4
  • Lapatto, Risto1
  • 1 University of Helsinki and Helsinki University Central Hospital, Stenbackinkatu 11, Helsinki, 00029, Finland , Helsinki (Finland)
  • 2 Adhera Health Inc., Palo Alto, CA, USA , Palo Alto (United States)
  • 3 Merck KGaA, Darmstadt, Germany , Darmstadt (Germany)
  • 4 Merck Oy Finland (an affiliate of Merck KGaA, Darmstadt, Germany), Espoo, Finland , Espoo (Finland)
Type
Published Article
Journal
BMC Medical Informatics and Decision Making
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Apr 26, 2021
Volume
21
Issue
1
Identifiers
DOI: 10.1186/s12911-021-01491-0
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundA range of factors can reduce the effectiveness of treatment prescribed for the long-term management of chronic health conditions, such as growth disorders. In particular, prescription medications may not achieve the positive outcomes expected because approximately half of patients adhere poorly to the prescribed treatment regimen.MethodsAdherence to treatment has previously been assessed using relatively unreliable subjective methods, such as patient self-reporting during clinical follow-up, or counting prescriptions filled or vials returned by patients. Here, we report on a new approach, the use of electronically recorded objective evidence of date, time, and dose taken which was obtained through a comprehensive eHealth ecosystem, based around the easypod™ electromechanical auto-injection device and web-based connect software. The benefits of this eHealth approach are also illustrated here by two case studies, selected from the Finnish cohort of the easypod™ Connect Observational Study (ECOS), a 5-year, open-label, observational study that enrolled children from 24 countries who were being treated with growth hormone (GH) via the auto-injection device.ResultsAnalyses of data from 9314 records from the easypod™ connect database showed that, at each time point studied, a significantly greater proportion of female patients had high adherence (≥ 85%) than male patients (2849/3867 [74%] vs 3879/5447 [71%]; P < 0.001). Furthermore, more of the younger patients (< 10 years for girls, < 12 years for boys) were in the high adherence range (P < 0.001). However, recursive partitioning of data from ECOS identified subgroups with lower adherence to GH treatment ‒ children who performed the majority of injections themselves at an early age (~ 8 years) and teenagers starting treatment aged ≥ 14 years.ConclusionsThe 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.

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