Literature DB >> 22006696

Validity of hospital discharge data for identifying cases of amyotrophic lateral sclerosis.

David E Stickler1, Julie A Royer, James W Hardin.   

Abstract

Inpatient hospital encounters and emergency department visits were examined to identify cases of amyotrophic lateral sclerosis (ALS).The ninth edition of the International Classification of Disease, clinical modification (ICD-9-CM) for ALS was confirmed for ALS was confirmed in 93% of inpatient discharges and in 91% of emergency department visits by the diagnostic standard (chart review). Yearly prevalence rates ranged from 2.94 to 3.28 per 100,000 residents. The low calculated prevalence rates suggest that this method of case identification is inadequate and must be combined with other data sets to maximize confirmation of the clinical diagnosis.
Copyright © 2011 Wiley Periodicals, Inc.

Entities:  

Mesh:

Year:  2011        PMID: 22006696     DOI: 10.1002/mus.22195

Source DB:  PubMed          Journal:  Muscle Nerve        ISSN: 0148-639X            Impact factor:   3.217


  6 in total

1.  Use of state administrative data sources to study adolescents and young adults with rare conditions.

Authors:  J A Royer; J W Hardin; S McDermott; L Ouyang; J R Mann; O D Ozturk; J Bolen
Journal:  J Gen Intern Med       Date:  2014-08       Impact factor: 5.128

Review 2.  Global epidemiology of amyotrophic lateral sclerosis: a systematic review of the published literature.

Authors:  A Chiò; G Logroscino; B J Traynor; J Collins; J C Simeone; L A Goldstein; L A White
Journal:  Neuroepidemiology       Date:  2013-07-11       Impact factor: 3.282

3.  Feasibility of creating a National ALS Registry using administrative data in the United States.

Authors:  Wendy E Kaye; Marchelle Sanchez; Jennifer Wu
Journal:  Amyotroph Lateral Scler Frontotemporal Degener       Date:  2014-03-06       Impact factor: 4.092

4.  Using Administrative Data to Ascertain True Cases of Muscular Dystrophy: Rare Disease Surveillance.

Authors:  Michael G Smith; Julie Royer; Joshua R Mann; Suzanne McDermott
Journal:  JMIR Public Health Surveill       Date:  2017-01-12

Review 5.  Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: A systematic review.

Authors:  Sophie Horrocks; Tim Wilkinson; Christian Schnier; Amanda Ly; Rebecca Woodfield; Kristiina Rannikmäe; Terence J Quinn; Cathie L M Sudlow
Journal:  PLoS One       Date:  2017-02-28       Impact factor: 3.240

6.  Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data: A systematic review.

Authors:  Zoe Harding; Tim Wilkinson; Anna Stevenson; Sophie Horrocks; Amanda Ly; Christian Schnier; David P Breen; Kristiina Rannikmäe; Cathie L M Sudlow
Journal:  PLoS One       Date:  2019-01-31       Impact factor: 3.240

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.