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The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems
BACKGROUND: Rare diseases (RD) are a diverse collection of more than 7–10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorders, the medical needs of RD patients are not well r...
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/PMC8532301/ https://www.ncbi.nlm.nih.gov/pubmed/34674728 http://dx.doi.org/10.1186/s13023-021-02061-3 |
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author | Tisdale, Ainslie Cutillo, Christine M. Nathan, Ramaa Russo, Pierantonio Laraway, Bryan Haendel, Melissa Nowak, Douglas Hasche, Cindy Chan, Chun-Hung Griese, Emily Dawkins, Hugh Shukla, Oodaye Pearce, David A. Rutter, Joni L. Pariser, Anne R. |
author_facet | Tisdale, Ainslie Cutillo, Christine M. Nathan, Ramaa Russo, Pierantonio Laraway, Bryan Haendel, Melissa Nowak, Douglas Hasche, Cindy Chan, Chun-Hung Griese, Emily Dawkins, Hugh Shukla, Oodaye Pearce, David A. Rutter, Joni L. Pariser, Anne R. |
author_sort | Tisdale, Ainslie |
collection | PubMed |
description | BACKGROUND: Rare diseases (RD) are a diverse collection of more than 7–10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorders, the medical needs of RD patients are not well recognized or quantified in healthcare systems (HCS). METHODOLOGY: We performed a pilot IDeaS study, where we attempted to quantify the number of RD patients and the direct medical costs of 14 representative RD within 4 different HCS databases and performed a preliminary analysis of the diagnostic journey for selected RD patients. RESULTS: The overall findings were notable for: (1) RD patients are difficult to quantify in HCS using ICD coding search criteria, which likely results in under-counting and under-estimation of their true impact to HCS; (2) per patient direct medical costs of RD are high, estimated to be around three–fivefold higher than age-matched controls; and (3) preliminary evidence shows that diagnostic journeys are likely prolonged in many patients, and may result in progressive, irreversible, and costly complications of their disease CONCLUSIONS: The results of this small pilot suggest that RD have high medical burdens to patients and HCS, and collectively represent a major impact to the public health. Machine-learning strategies applied to HCS databases and medical records using sentinel disease and patient characteristics may hold promise for faster and more accurate diagnosis for many RD patients and should be explored to help address the high unmet medical needs of RD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-02061-3. |
format | Online Article Text |
id | pubmed-8532301 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85323012021-10-25 The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems Tisdale, Ainslie Cutillo, Christine M. Nathan, Ramaa Russo, Pierantonio Laraway, Bryan Haendel, Melissa Nowak, Douglas Hasche, Cindy Chan, Chun-Hung Griese, Emily Dawkins, Hugh Shukla, Oodaye Pearce, David A. Rutter, Joni L. Pariser, Anne R. Orphanet J Rare Dis Research BACKGROUND: Rare diseases (RD) are a diverse collection of more than 7–10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorders, the medical needs of RD patients are not well recognized or quantified in healthcare systems (HCS). METHODOLOGY: We performed a pilot IDeaS study, where we attempted to quantify the number of RD patients and the direct medical costs of 14 representative RD within 4 different HCS databases and performed a preliminary analysis of the diagnostic journey for selected RD patients. RESULTS: The overall findings were notable for: (1) RD patients are difficult to quantify in HCS using ICD coding search criteria, which likely results in under-counting and under-estimation of their true impact to HCS; (2) per patient direct medical costs of RD are high, estimated to be around three–fivefold higher than age-matched controls; and (3) preliminary evidence shows that diagnostic journeys are likely prolonged in many patients, and may result in progressive, irreversible, and costly complications of their disease CONCLUSIONS: The results of this small pilot suggest that RD have high medical burdens to patients and HCS, and collectively represent a major impact to the public health. Machine-learning strategies applied to HCS databases and medical records using sentinel disease and patient characteristics may hold promise for faster and more accurate diagnosis for many RD patients and should be explored to help address the high unmet medical needs of RD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-02061-3. BioMed Central 2021-10-22 /pmc/articles/PMC8532301/ /pubmed/34674728 http://dx.doi.org/10.1186/s13023-021-02061-3 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 Tisdale, Ainslie Cutillo, Christine M. Nathan, Ramaa Russo, Pierantonio Laraway, Bryan Haendel, Melissa Nowak, Douglas Hasche, Cindy Chan, Chun-Hung Griese, Emily Dawkins, Hugh Shukla, Oodaye Pearce, David A. Rutter, Joni L. Pariser, Anne R. The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
title | The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
title_full | The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
title_fullStr | The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
title_full_unstemmed | The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
title_short | The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
title_sort | ideas initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8532301/ https://www.ncbi.nlm.nih.gov/pubmed/34674728 http://dx.doi.org/10.1186/s13023-021-02061-3 |
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