Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
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
_version_ 1784587039422808064
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
work_keys_str_mv AT tisdaleainslie theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT cutillochristinem theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT nathanramaa theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT russopierantonio theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT larawaybryan theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT haendelmelissa theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT nowakdouglas theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT haschecindy theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT chanchunhung theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT grieseemily theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT dawkinshugh theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT shuklaoodaye theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT pearcedavida theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT rutterjonil theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT pariseranner theideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT tisdaleainslie ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT cutillochristinem ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT nathanramaa ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT russopierantonio ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT larawaybryan ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT haendelmelissa ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT nowakdouglas ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT haschecindy ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT chanchunhung ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT grieseemily ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT dawkinshugh ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT shuklaoodaye ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT pearcedavida ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT rutterjonil ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems
AT pariseranner ideasinitiativepilotstudytoassesstheimpactofrarediseasesonpatientsandhealthcaresystems