Evidence map›Paper›PMID 34674728›Full record

ArticleOrphanet journal of rare diseases2021

The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems.

Ainslie Tisdale, Christine M Cutillo, Ramaa Nathan, Pierantonio Russo, Bryan Laraway, Melissa Haendel, Douglas Nowak, Cindy Hasche, Chun-Hung Chan, Emily Griese and 5 more

Open access · goldAbstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
13.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.

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  9. Characterization of Treatment Utilization in a Metabolic Genetics Clinic.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 8 institutions in 2 countries.

Ainslie TisdaleOffice of Rare Diseases Research (ORDR), National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Bethesda, MD, 20817, USA.
Christine M CutilloNCATS NIH, Bethesda, MD, 20817, USA.
Ramaa NathanEversana Life Science Services, LLC, Chicago, IL, USA.
Pierantonio RussoEversana Life Science Services, LLC, Chicago, IL, USA.
Bryan LarawayOregon Health and Science University (OHSU), Portland, OR, 97239, USA.
Melissa HaendelUniversity of Colorado, Anschutz Medical Campus, Aurora, CO, 80045, USA.
Douglas NowakSanford Health, Sioux Falls, SD, 57117, USA.
Cindy HascheSanford Health, Sioux Falls, SD, 57117, USA.
Chun-Hung ChanSanford Research, Sioux Falls, SD, 57104, USA.
Emily GrieseSanford Research, Sioux Falls, SD, 57104, USA.
Hugh DawkinsSchool of Medicine, The University of Notre Dame Australia, Sydney, Australia.
Oodaye ShuklaEversana Life Science Services, LLC, Chicago, IL, USA.
David A PearceSanford Health, Sioux Falls, SD, 57117, USA.
Joni L RutterNCATS NIH, Bethesda, MD, 20817, USA.
Anne R PariserOffice of Rare Diseases Research (ORDR), National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Bethesda, MD, 20817, USA. anne.pariser@nih.gov.ORCID 0000-0002-9421-0126
Sanford Health · USNational Center for Advancing Translational Sciences · USNational Institutes of Health · USManagement Sciences (United States) · USOregon Health & Science University · USSanford Research · USThe University of Notre Dame Australia · AUUniversity of Colorado Anschutz Medical Campus · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRare 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.

resultsThe 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

conclusionsThe 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.

Indexed as

Machine LearningRare DiseasesCosts and Cost AnalysisDelivery of Health CareHumansPilot ProjectsDiagnosisHealth care costsRare diseasesUtilization

Identifiers

PMID34674728
PMCPMC8532301
OpenAlexW3205669862

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.