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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
BACKGROUND: A 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 adher...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074467/ https://www.ncbi.nlm.nih.gov/pubmed/33902570 http://dx.doi.org/10.1186/s12911-021-01491-0 |
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author | Boman, Nea Fernandez-Luque, Luis Koledova, Ekaterina Kause, Marketta Lapatto, Risto |
author_facet | Boman, Nea Fernandez-Luque, Luis Koledova, Ekaterina Kause, Marketta Lapatto, Risto |
author_sort | Boman, Nea |
collection | PubMed |
description | BACKGROUND: A 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. METHODS: Adherence 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. RESULTS: Analyses 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. CONCLUSIONS: 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. |
format | Online Article Text |
id | pubmed-8074467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80744672021-04-26 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 Boman, Nea Fernandez-Luque, Luis Koledova, Ekaterina Kause, Marketta Lapatto, Risto BMC Med Inform Decis Mak Research Article BACKGROUND: A 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. METHODS: Adherence 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. RESULTS: Analyses 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. CONCLUSIONS: 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. BioMed Central 2021-04-26 /pmc/articles/PMC8074467/ /pubmed/33902570 http://dx.doi.org/10.1186/s12911-021-01491-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Boman, Nea Fernandez-Luque, Luis Koledova, Ekaterina Kause, Marketta Lapatto, Risto 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074467/ https://www.ncbi.nlm.nih.gov/pubmed/33902570 http://dx.doi.org/10.1186/s12911-021-01491-0 |
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