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Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity

Published online by Cambridge University Press:  26 January 2019

Jonathan H Soslow ,
Matthew Hall ,
W Bryan Burnette ,
Kan Hor ,
Joanne Chisolm ,
Christopher Spurney ,
Justin Godown ,
Meng Xu ,
James C Slaughter  and
Larry W Markham
Jonathan H Soslow*
Affiliation:
Thomas P Graham Division of Pediatric Cardiology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
Matthew Hall
Affiliation:
Children’s Hospital Association, Lenexa, KS, USA
W Bryan Burnette
Affiliation:
Division of Pediatric Neurology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
Kan Hor
Affiliation:
Division of Pediatric Cardiology, Nationwide Children’s Hospital and The Ohio State University, Columbus, OH, USA
Joanne Chisolm
Affiliation:
Division of Pediatric Cardiology, Nationwide Children’s Hospital and The Ohio State University, Columbus, OH, USA
Christopher Spurney
Affiliation:
Division of Cardiology, Children’s National Heart Institute, Children’s National Health System, Washington, DC, USA
Justin Godown
Affiliation:
Thomas P Graham Division of Pediatric Cardiology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
Meng Xu
Affiliation:
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
James C Slaughter
Affiliation:
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
Larry W Markham
Affiliation:
Thomas P Graham Division of Pediatric Cardiology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA Division of Cardiology, Department of Pediatrics, Riley Hospital for Children at Indiana University Health, Indianapolis, IN, USA
*
Author for correspondence: J. H. Soslow, MD, MSCI, Assistant Professor, Pediatrics, Thomas P. Graham, Jr. Division of Pediatric Cardiology, Monroe Carell Jr. Children’s Hospital at Vanderbilt, 2200 Children’s Way, Suite 5230, Doctors’ Office Tower, Nashville, TN 37232-9119, USA. Tel: +1-615-322-7447; Fax: +1-615-322-2210; E-mail: jonathan.h.soslow@vanderbilt.edu
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Abstract

Background

Outcome analyses in large administrative databases are ideal for rare diseases such as Becker and Duchenne muscular dystrophy. Unfortunately, Becker and Duchenne do not yet have specific International Classification of Disease-9/-10 codes. We hypothesised that an algorithm could accurately identify these patients within administrative data and improve assessment of cardiovascular morbidity.

Methods

Hospital discharges (n=13,189) for patients with muscular dystrophy classified by International Classification of Disease-9 code: 359.1 were identified from the Pediatric Health Information System database. An identification algorithm was created and then validated at three institutions. Multi-variable generalised linear mixed-effects models were used to estimate the associations of length of stay, hospitalisation cost, and 14-day readmission with age, encounter severity, and respiratory disease accounting for clustering within the hospital.

Results

The identification algorithm improved identification of patients with Becker and Duchenne from 55% (code 359.1 alone) to 77%. On bi-variate analysis, left ventricular dysfunction and arrhythmia were associated with increased cost of hospitalisation, length of stay, and mortality (p<0.001). After adjustment, Becker and Duchenne patients with left ventricular dysfunction and arrhythmia had increased length of stay with rate ratio 1.4 and 1.2 (p<0.001 and p=0.004) and increased cost of hospitalization with rate ratio 1.4 and 1.4 (both p<0.001).

Conclusions

Our algorithm accurately identifies patients with Becker and Duchenne and can be used for future analysis of administrative data. Our analysis demonstrates the significant effects of cardiovascular disease on length of stay and hospitalisation cost in patients with Becker and Duchenne. Better recognition of the contribution of cardiovascular disease during hospitalisation with earlier more intensive evaluation and therapy may help improve outcomes in this patient population.

Keywords

Duchenne muscular dystrophyBecker muscular dystrophyPediatric Health Information Systemleft ventricular dysfunctionarrhythmiacardiomyopathy
Type
Original Article
Information
Cardiology in the Young , Volume 29 , Issue 3 , March 2019 , pp. 290 - 296
Copyright
© Cambridge University Press 2019 

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Footnotes

Cite this article: Soslow JH, Hall M, Burnette WB, Hor K, Chisolm J, Spurney C, Godown J, Xu M, Slaughter JC, Markham LW. (2019) Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity. Cardiology in the Young29: 290–296. doi: 10.1017/S1047951118002226

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Supplementary material: File

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Table S1

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Table S3

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Table S4

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