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Impact of ICD-9 to ICD-10 Coding Transition on Prevalence Trends in Neurology.
Hamedani, Ali G; Blank, Leah; Thibault, Dylan P; Willis, Allison W.
Afiliação
  • Hamedani AG; Department of Neurology and Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research (AGH, DPT), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Departments of Neurology and Population Health Science and Policy (LB), Icahn School of Medicine at
  • Blank L; Department of Neurology and Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research (AGH, DPT), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Departments of Neurology and Population Health Science and Policy (LB), Icahn School of Medicine at
  • Thibault DP; Department of Neurology and Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research (AGH, DPT), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Departments of Neurology and Population Health Science and Policy (LB), Icahn School of Medicine at
  • Willis AW; Department of Neurology and Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research (AGH, DPT), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Departments of Neurology and Population Health Science and Policy (LB), Icahn School of Medicine at
Neurol Clin Pract ; 11(5): e612-e619, 2021 Oct.
Article em En | MEDLINE | ID: mdl-34840874
ABSTRACT

OBJECTIVE:

To determine the effect of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) coding transition on the point prevalence and longitudinal trends of 16 neurologic diagnoses.

METHODS:

We used 2014-2017 data from the National Inpatient Sample to identify hospitalizations with one of 16 common neurologic diagnoses. We used published ICD-9-CM codes to identify hospitalizations from January 1, 2014, to September 30, 2015, and used the Agency for Healthcare Research and Quality's MapIt tool to convert them to equivalent ICD-10-CM codes for October 1, 2015-December 31, 2017. We compared the prevalence of each diagnosis before vs after the ICD coding transition using logistic regression and used interrupted time series regression to model the longitudinal change in disease prevalence across time.

RESULTS:

The average monthly prevalence of subarachnoid hemorrhage was stable before the coding transition (average monthly increase of 4.32 admissions, 99.7% confidence interval [CI] -8.38 to 17.01) but increased after the coding transition (average monthly increase of 24.32 admissions, 99.7% CI 15.71-32.93). Otherwise, there were no significant differences in the longitudinal rate of change in disease prevalence over time between ICD-9-CM and ICD-10-CM. Six of 16 neurologic diagnoses (37.5%) experienced significant changes in cross-sectional prevalence during the coding transition, most notably for status epilepticus (odds ratio 0.30, 99.7% CI 0.26-0.34).

CONCLUSIONS:

The transition from ICD-9-CM to ICD-10-CM coding affects prevalence estimates for status epilepticus and other neurologic disorders, a potential source of bias for future longitudinal neurologic studies. Studies should limit to 1 coding system or use interrupted time series models to adjust for changes in coding patterns until new neurology-specific ICD-9 to ICD-10 conversion maps can be developed.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article