Literature DB >> 19681442

The accuracy of hospital discharge coding for hemorrhagic stroke.

Matthew Anthony Kirkman1, Wattana Mahattanakul, Barbara A Gregson, A David Mendelow.   

Abstract

BACKGROUND: Hospital discharge data is used in monitoring stroke epidemiology, and ensuring adequate resource allocation to treatment programs. Previous studies have reported variable accuracy levels for such data. We present the first study assessing the accuracy of International Classification of Diseases 10th Edition (ICD-10) discharge coding for hemorrhagic stroke in England.
METHODS: We identified all patients with a primary diagnosis of intracerebral hemorrhage (ICH; ICD-10 code: I61.x) and subarachnoid hemorrhage (SAH; I60.x) admitted to the Newcastle upon Tyne Hospitals from 2002-2007. Positive predictive values (PPV) were calculated through validation with patient notes.
RESULTS: Hospital discharge coding identified 978 ICH and 1169 SAH admissions over the six years. The number of diagnoses verified by patient notes was excellent for both ICH (n = 938) and SAH (n = 1123), with a PPV of 95.9% for ICH (95% confidence interval, CI = 94.5-97.0%) and 96.1%for SAH (95% CI = 94.8-97.0%). The coding errors observed were largely expected, with different types of stroke miscoded as ICH and SAH.
CONCLUSIONS: The accuracy of ICD-10 hospital discharge coding for hemorrhagic stroke was excellent. However further research is needed to find ways to further improve its accuracy.

Entities:  

Mesh:

Year:  2009        PMID: 19681442

Source DB:  PubMed          Journal:  Acta Neurol Belg        ISSN: 0300-9009            Impact factor:   2.396


  26 in total

Review 1.  Systematic review of discharge coding accuracy.

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Journal:  J Public Health (Oxf)       Date:  2011-07-27       Impact factor: 2.341

2.  Validity of international classification of disease codes to identify ischemic stroke and intracranial hemorrhage among individuals with associated diagnosis of atrial fibrillation.

Authors:  Jonathan L Thigpen; Chrisly Dillon; Kristen B Forster; Lori Henault; Emily K Quinn; Yorghos Tripodis; Peter B Berger; Elaine M Hylek; Nita A Limdi
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4.  Meeting the ambition of measuring the quality of hospitals' stroke care using routinely collected administrative data: a feasibility study.

Authors:  William L Palmer; Alex Bottle; Charlie Davie; Charles A Vincent; Paul Aylin
Journal:  Int J Qual Health Care       Date:  2013-04-12       Impact factor: 2.038

5.  Validity of hospital discharge diagnosis codes for stroke: the Atherosclerosis Risk in Communities Study.

Authors:  Sydney A Jones; Rebecca F Gottesman; Eyal Shahar; Lisa Wruck; Wayne D Rosamond
Journal:  Stroke       Date:  2014-09-04       Impact factor: 7.914

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Authors:  Christopher Ma; Marcelo Crespin; Marie-Claude Proulx; Shanika DeSilva; James Hubbard; Martin Prusinkiewicz; Geoffrey C Nguyen; Remo Panaccione; Subrata Ghosh; Robert P Myers; Hude Quan; Gilaad G Kaplan
Journal:  BMC Gastroenterol       Date:  2012-04-27       Impact factor: 3.067

8.  Incidence estimate and guideline-oriented treatment for post-stroke spasticity: an analysis based on German statutory health insurance data.

Authors:  Veronika Egen-Lappe; Ingrid Köster; Ingrid Schubert
Journal:  Int J Gen Med       Date:  2013-03-13

9.  Vascular disease in women: comparison of diagnoses in hospital episode statistics and general practice records in England.

Authors:  F Lucy Wright; Jane Green; Dexter Canoy; Benjamin J Cairns; Angela Balkwill; Valerie Beral
Journal:  BMC Med Res Methodol       Date:  2012-10-23       Impact factor: 4.615

10.  Intracerebral Hemorrhage and Coronavirus Disease 2019 in a Cohort of 282,718 Hospitalized Patients.

Authors:  Adnan I Qureshi; William I Baskett; Wei Huang; Danny Myers; Iryna Lobanova; Muhammad F Ishfaq; Syed Hasan Naqvi; Brandi R French; Premkumar N Chandrasekaran; Farhan Siddiq; Camilo R Gomez; Chi-Ren Shyu
Journal:  Neurocrit Care       Date:  2021-07-06       Impact factor: 3.210

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