Interobserver variability in the classification of neonatal seizures based on medical record data

Mary Jo Lanska; Douglas J. Lanska; Robert J. Baumann; Stacey L. Allen; Keith G. Slone; Richard J. Kryscio

doi:10.1016/0887-8994(96)00155-5

Interobserver variability in the classification of neonatal seizures based on medical record data

Mary Jo Lanska, Douglas J. Lanska, Robert J. Baumann, Stacey L. Allen, Keith G. Slone, Richard J. Kryscio

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

This population-based, retrospective cohort study of neonatal seizures included all 16,428 neonates born to residents of Fayette County, Kentucky, from 1985 to 1989. Eighty potential cases were ascertained by computer search of hospital-based medical record systems, birth certificate data files, and multiple-cause-of-death mortality data files. Medical records for potential cases were abstracted, and relevant portions were reviewed independently by three neurologists using prospectively determined criteria. Both unweighted and weighted κ statistics were used to measure agreement between each pair of observers in the classification of potential cases as seizures, possible seizures, or not seizures, adjusting for the proportion of agreement expected by chance. Agreement in the classification of potential cases was excellent (κ = 0.72-0.79, average = 0.76; weighted κ = 0.85-0.88, average = 0.87). The κ extension statistic of Kraemer was used to assess agreement in the classification of seizure types by a simplification of the classification scheme of Volpe. This documented excellent agreement between raters in the classification of seizure types (κ(e) = 0.72). Experienced raters can reliably classify potential cases of neonatal seizures using seizure descriptions transcribed from medical records.

Original language	English
Pages (from-to)	120-123
Number of pages	4
Journal	Pediatric Neurology
Volume	15
Issue number	2
DOIs	https://doi.org/10.1016/0887-8994(96)00155-5
State	Published - Sep 1996

Bibliographical note

Funding Information:
This work was supported in part by Public Health Service Biomedical Research Support Grant No. RR05374-29 (MJL), National Institutes of Health Clinical Investigator Development Award No. K08-NS-01549 (DJL), Research Advisory Group funding (DJL) from the Office of Research and Development, Department of Veterans Affairs, and the philanthropic support of Jayne Bolotin (DJL). The authors thank the following persons for assistance: Betty Ballinger, Jo Warren, and Donna Yount of the Health Data Branch, and Barbara White, Registrar of the Vital Statistics Branch, Kentucky Center for Health Statistics, Frankfort, Kentucky; Gregory Robinson, Ph.D., of the United States Bureau of the Census, Washington, D.C.; Robin Moore and the medical records staff at Central Baptist Hospital, Lexington, Kentucky; Shawna Sharpe, Connie Rice, Hema Sudaker, and the medical records staff at Good Samaritan Hospital, Lexington, Kentucky; Charlotte Colmbs, John Barnes, Nancy Goldsborough, Nancy Hamilton, Judy Stevens, and the medical records staff at Humana Hospital, Lexington, Kentucky; Cindy Moore, Lisa Coleman and the medical records staff at Saint Joseph Hospital, Lexington, Kentucky; Bernice Bolin, Rose Burke, Sherry Drury, Cindy Bablitz, and the medical records staff of University of Kentucky Medical center, Lexington, Kentucky; and Robert Crovo, Wanda Dixon, and Lorinda Wang of the University of Kentucky Computing Center, Lexington, Kentucky.

Funding

This work was supported in part by Public Health Service Biomedical Research Support Grant No. RR05374-29 (MJL), National Institutes of Health Clinical Investigator Development Award No. K08-NS-01549 (DJL), Research Advisory Group funding (DJL) from the Office of Research and Development, Department of Veterans Affairs, and the philanthropic support of Jayne Bolotin (DJL). The authors thank the following persons for assistance: Betty Ballinger, Jo Warren, and Donna Yount of the Health Data Branch, and Barbara White, Registrar of the Vital Statistics Branch, Kentucky Center for Health Statistics, Frankfort, Kentucky; Gregory Robinson, Ph.D., of the United States Bureau of the Census, Washington, D.C.; Robin Moore and the medical records staff at Central Baptist Hospital, Lexington, Kentucky; Shawna Sharpe, Connie Rice, Hema Sudaker, and the medical records staff at Good Samaritan Hospital, Lexington, Kentucky; Charlotte Colmbs, John Barnes, Nancy Goldsborough, Nancy Hamilton, Judy Stevens, and the medical records staff at Humana Hospital, Lexington, Kentucky; Cindy Moore, Lisa Coleman and the medical records staff at Saint Joseph Hospital, Lexington, Kentucky; Bernice Bolin, Rose Burke, Sherry Drury, Cindy Bablitz, and the medical records staff of University of Kentucky Medical center, Lexington, Kentucky; and Robert Crovo, Wanda Dixon, and Lorinda Wang of the University of Kentucky Computing Center, Lexington, Kentucky.

Funders	Funder number
Public Health Service Biomedical Research Support	K08-NS-01549
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council	K08NS001549
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council
U.S. Department of Veterans Affairs
Biomedical Laboratory Research and Development, VA Office of Research and Development

ASJC Scopus subject areas

Pediatrics, Perinatology, and Child Health
Neurology
Developmental Neuroscience
Clinical Neurology

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10.1016/0887-8994(96)00155-5

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@article{c877411b12ef477d95629ff5fc81e45a,

title = "Interobserver variability in the classification of neonatal seizures based on medical record data",

abstract = "This population-based, retrospective cohort study of neonatal seizures included all 16,428 neonates born to residents of Fayette County, Kentucky, from 1985 to 1989. Eighty potential cases were ascertained by computer search of hospital-based medical record systems, birth certificate data files, and multiple-cause-of-death mortality data files. Medical records for potential cases were abstracted, and relevant portions were reviewed independently by three neurologists using prospectively determined criteria. Both unweighted and weighted κ statistics were used to measure agreement between each pair of observers in the classification of potential cases as seizures, possible seizures, or not seizures, adjusting for the proportion of agreement expected by chance. Agreement in the classification of potential cases was excellent (κ = 0.72-0.79, average = 0.76; weighted κ = 0.85-0.88, average = 0.87). The κ extension statistic of Kraemer was used to assess agreement in the classification of seizure types by a simplification of the classification scheme of Volpe. This documented excellent agreement between raters in the classification of seizure types (κ(e) = 0.72). Experienced raters can reliably classify potential cases of neonatal seizures using seizure descriptions transcribed from medical records.",

author = "Lanska, {Mary Jo} and Lanska, {Douglas J.} and Baumann, {Robert J.} and Allen, {Stacey L.} and Slone, {Keith G.} and Kryscio, {Richard J.}",

note = "Funding Information: This work was supported in part by Public Health Service Biomedical Research Support Grant No. RR05374-29 (MJL), National Institutes of Health Clinical Investigator Development Award No. K08-NS-01549 (DJL), Research Advisory Group funding (DJL) from the Office of Research and Development, Department of Veterans Affairs, and the philanthropic support of Jayne Bolotin (DJL). The authors thank the following persons for assistance: Betty Ballinger, Jo Warren, and Donna Yount of the Health Data Branch, and Barbara White, Registrar of the Vital Statistics Branch, Kentucky Center for Health Statistics, Frankfort, Kentucky; Gregory Robinson, Ph.D., of the United States Bureau of the Census, Washington, D.C.; Robin Moore and the medical records staff at Central Baptist Hospital, Lexington, Kentucky; Shawna Sharpe, Connie Rice, Hema Sudaker, and the medical records staff at Good Samaritan Hospital, Lexington, Kentucky; Charlotte Colmbs, John Barnes, Nancy Goldsborough, Nancy Hamilton, Judy Stevens, and the medical records staff at Humana Hospital, Lexington, Kentucky; Cindy Moore, Lisa Coleman and the medical records staff at Saint Joseph Hospital, Lexington, Kentucky; Bernice Bolin, Rose Burke, Sherry Drury, Cindy Bablitz, and the medical records staff of University of Kentucky Medical center, Lexington, Kentucky; and Robert Crovo, Wanda Dixon, and Lorinda Wang of the University of Kentucky Computing Center, Lexington, Kentucky.",

year = "1996",

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doi = "10.1016/0887-8994(96)00155-5",

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AU - Slone, Keith G.

AU - Kryscio, Richard J.

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N2 - This population-based, retrospective cohort study of neonatal seizures included all 16,428 neonates born to residents of Fayette County, Kentucky, from 1985 to 1989. Eighty potential cases were ascertained by computer search of hospital-based medical record systems, birth certificate data files, and multiple-cause-of-death mortality data files. Medical records for potential cases were abstracted, and relevant portions were reviewed independently by three neurologists using prospectively determined criteria. Both unweighted and weighted κ statistics were used to measure agreement between each pair of observers in the classification of potential cases as seizures, possible seizures, or not seizures, adjusting for the proportion of agreement expected by chance. Agreement in the classification of potential cases was excellent (κ = 0.72-0.79, average = 0.76; weighted κ = 0.85-0.88, average = 0.87). The κ extension statistic of Kraemer was used to assess agreement in the classification of seizure types by a simplification of the classification scheme of Volpe. This documented excellent agreement between raters in the classification of seizure types (κ(e) = 0.72). Experienced raters can reliably classify potential cases of neonatal seizures using seizure descriptions transcribed from medical records.

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Interobserver variability in the classification of neonatal seizures based on medical record data

Abstract

Bibliographical note

Funding

ASJC Scopus subject areas

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