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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.
Afiliación
  • Tisdale A; Office of Rare Diseases Research (ORDR), National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Bethesda, MD, 20817, USA.
  • Cutillo CM; NCATS NIH, Bethesda, MD, 20817, USA.
  • Nathan R; Eversana Life Science Services, LLC, Chicago, IL, USA.
  • Russo P; Eversana Life Science Services, LLC, Chicago, IL, USA.
  • Laraway B; Population Health Management Spring Hills MSO, Edison, NJ, 08817, USA.
  • Haendel M; Oregon Health and Science University (OHSU), Portland, OR, 97239, USA.
  • Nowak D; University of Colorado, Anschutz Medical Campus, Aurora, CO, 80045, USA.
  • Hasche C; Sanford Health, Sioux Falls, SD, 57117, USA.
  • Chan CH; Sanford Health, Sioux Falls, SD, 57117, USA.
  • Griese E; Sanford Research, Sioux Falls, SD, 57104, USA.
  • Dawkins H; Sanford Research, Sioux Falls, SD, 57104, USA.
  • Shukla O; Sanford Health Plan, Sioux Falls, SD, 57103, USA.
  • Pearce DA; School of Medicine, The University of Notre Dame Australia, Sydney, Australia.
  • Rutter JL; Eversana Life Science Services, LLC, Chicago, IL, USA.
  • Pariser AR; Sanford Health, Sioux Falls, SD, 57117, USA.
Orphanet J Rare Dis ; 16(1): 429, 2021 10 22.
Article en En | MEDLINE | ID: mdl-34674728
ABSTRACT

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.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedades Raras / Aprendizaje Automático Tipo de estudio: Health_economic_evaluation Idioma: En Revista: Orphanet J Rare Dis Asunto de la revista: MEDICINA Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedades Raras / Aprendizaje Automático Tipo de estudio: Health_economic_evaluation Idioma: En Revista: Orphanet J Rare Dis Asunto de la revista: MEDICINA Año: 2021 Tipo del documento: Article