Literature DB >> 34075580

Assessing seizure burden in pediatric epilepsy using an electronic medical record-based tool through a common data element approach.

Mark P Fitzgerald1,2,3, Michael C Kaufman1,2,4, Shavonne L Massey1,2,3, Sara Fridinger1,3, Marisa Prelack1,3, Colin Ellis1,2,3, Xilma Ortiz-Gonzalez1,2,3, Lawrence E Fried1,3, Marissa P DiGiovine1,3, Susan Melamed1, Marissa Malcolm1, Brenda Banwell1,3, Donna Stephenson1,3, Stephanie M Witzman1, Alexander Gonzalez4, Dennis Dlugos1,3, Sudha Kilaru Kessler1,3, Ethan M Goldberg1,2,3, Nicholas S Abend1,3, Ingo Helbig1,2,3,4.   

Abstract

OBJECTIVE: Improvement in epilepsy care requires standardized methods to assess disease severity. We report the results of implementing common data elements (CDEs) to document epilepsy history data in the electronic medical record (EMR) after 12 months of clinical use in outpatient encounters.
METHODS: Data regarding seizure frequency were collected during routine clinical encounters using a CDE-based form within our EMR. We extracted CDE data from the EMR and developed measurements for seizure severity and seizure improvement scores. Seizure burden and improvement was evaluated by patient demographic and encounter variables for in-person and telemedicine encounters.
RESULTS: We assessed a total of 1696 encounters in 1038 individuals with childhood epilepsies between September 6, 2019 and September 11, 2020 contributed by 32 distinct providers. Childhood absence epilepsy (n = 121), Lennox-Gastaut syndrome (n = 86), and Dravet syndrome (n = 42) were the most common epilepsy syndromes. Overall, 43% (737/1696) of individuals had at least monthly seizures, 17% (296/1696) had a least daily seizures, and 18% (311/1696) were seizure-free for >12 months. Quantification of absolute seizure burden and changes in seizure burden over time differed between epilepsy syndromes, including high and persistent seizure burden in patients with Lennox-Gastaut syndrome. Individuals seen via telemedicine or in-person encounters had comparable seizure frequencies. Individuals identifying as Hispanic/Latino, particularly from postal codes with lower median household incomes, were more likely to have ongoing seizures that worsened over time. SIGNIFICANCE: Standardized documentation of clinical data in childhood epilepsies through CDE can be implemented in routine clinical care at scale and enables assessment of disease burden, including characterization of seizure burden over time. Our data provide insights into heterogeneous patterns of seizure control in common pediatric epilepsy syndromes and will inform future initiatives focusing on patient-centered outcomes in childhood epilepsies, including the impact of telemedicine and health care disparities.
© 2021 International League Against Epilepsy.

Entities:  

Keywords:  common data elements; epilepsy outcomes; health care disparities; seizure frequency; telemedicine

Mesh:

Substances:

Year:  2021        PMID: 34075580      PMCID: PMC8637497          DOI: 10.1111/epi.16934

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  18 in total

1.  Design and implementation of electronic health record common data elements for pediatric epilepsy: Foundations for a learning health care system.

Authors:  Zachary M Grinspan; Anup D Patel; Renée A Shellhaas; Anne T Berg; Erika T Axeen; Jeffrey Bolton; David F Clarke; Jason Coryell; William D Gaillard; Howard P Goodkin; Sookyong Koh; Alison Kukla; Juma S Mbwana; Lindsey A Morgan; Nilika S Singhal; Margaret M Storey; Elissa G Yozawitz; Nicholas S Abend; Mark P Fitzgerald; Sara E Fridinger; Ingo Helbig; Shavonne L Massey; Marisa S Prelack; Jeffrey Buchhalter
Journal:  Epilepsia       Date:  2020-12-24       Impact factor: 5.864

2.  Good intentions are not enough: how informatics interventions can worsen inequality.

Authors:  Tiffany C Veinot; Hannah Mitchell; Jessica S Ancker
Journal:  J Am Med Inform Assoc       Date:  2018-08-01       Impact factor: 4.497

3.  Child Neurology Telemedicine: Understanding the Data We Have and Finding the Patients We Do Not See.

Authors:  Madeline Chadehumbe; Sansanee Craig; Donna Stephenson; Ingo Helbig
Journal:  Pediatr Neurol       Date:  2020-12-13       Impact factor: 3.372

Review 4.  Social determinants of health in epilepsy.

Authors:  Magdalena Szaflarski
Journal:  Epilepsy Behav       Date:  2014-07-04       Impact factor: 2.937

Review 5.  Disparities in epilepsy: report of a systematic review by the North American Commission of the International League Against Epilepsy.

Authors:  Jorge G Burneo; Nathalie Jette; William Theodore; Charles Begley; Karen Parko; David J Thurman; Samuel Wiebe
Journal:  Epilepsia       Date:  2009-09-03       Impact factor: 5.864

6.  The digital divide: How COVID-19's telemedicine expansion could exacerbate disparities.

Authors:  Mina Bakhtiar; Nada Elbuluk; Jules B Lipoff
Journal:  J Am Acad Dermatol       Date:  2020-07-16       Impact factor: 11.527

7.  Analysis of the aetiology of epilepsy in 3,216 adult patients attending a tertiary referral center enabled by an electronic patient record.

Authors:  S Delaney; M Fitzsimons; M White; K Power; S O' Donoghue; R Kilbride; P Widdess-Walsh; H El Naggar; N Delanty
Journal:  Seizure       Date:  2020-08-22       Impact factor: 3.184

8.  Forecasting the Maturation of Electronic Health Record Functions Among US Hospitals: Retrospective Analysis and Predictive Model.

Authors:  Hadi Kharrazi; Claudia P Gonzalez; Kevin B Lowe; Timothy R Huerta; Eric W Ford
Journal:  J Med Internet Res       Date:  2018-08-07       Impact factor: 5.428

9.  Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19.

Authors:  Rumi Chunara; Yuan Zhao; Ji Chen; Katharine Lawrence; Paul A Testa; Oded Nov; Devin M Mann
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

10.  Analyzing 2,589 child neurology telehealth encounters necessitated by the COVID-19 pandemic.

Authors:  Salvatore C Rametta; Sara E Fridinger; Alexander K Gonzalez; Julie Xian; Peter D Galer; Michael Kaufman; Marisa S Prelack; Uzma Sharif; Mark P Fitzgerald; Susan E Melamed; Marissa P Malcolm; Sudha Kilaru Kessler; Donna J Stephenson; Brenda L Banwell; Nicholas S Abend; Ingo Helbig
Journal:  Neurology       Date:  2020-06-09       Impact factor: 9.910

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  1 in total

Review 1.  Computational analysis of neurodevelopmental phenotypes: Harmonization empowers clinical discovery.

Authors:  David Lewis-Smith; Shridhar Parthasarathy; Julie Xian; Michael C Kaufman; Shiva Ganesan; Peter D Galer; Rhys H Thomas; Ingo Helbig
Journal:  Hum Mutat       Date:  2022-05-22       Impact factor: 4.700

  1 in total

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