Patient characteristics and antiseizure medication pathways in newly diagnosed epilepsy: Feasibility and pilot results using the common data model in a single-center electronic medical record database

被引:3
|
作者
Spotnitz, Matthew [1 ]
Ostropolets, Anna [1 ]
Castano, Victor G. [2 ]
Natarajan, Karthik [1 ]
Waldman, Genna J. [3 ]
Argenziano, Michael [2 ]
Ottman, Ruth [3 ,4 ,5 ,6 ]
Hripcsak, George [1 ]
Choi, Hyunmi [3 ]
Youngerman, Brett E. [2 ]
机构
[1] Columbia Univ, Dept Biomed Informat, Irving Med Ctr, New York, NY 10032 USA
[2] Columbia Univ, Dept Neurol Surg, Irving Med Ctr, New York, NY 10032 USA
[3] Columbia Univ, Dept Neurol, Irving Med Ctr, New York, NY 10032 USA
[4] Columbia Univ, Gertrude H Sergievsky Ctr, Vagelos Coll Phys & Surg, New York, NY 10032 USA
[5] Columbia Univ, Mailman Sch Publ Hlth, Dept Epidemiol, Irving Med Ctr, New York, NY 10032 USA
[6] New York State Psychiat Inst & Hosp, Div Translat Epidemiol, New York, NY 10032 USA
关键词
Antiseizure medication; Epilepsy; Practice patterns; Observational Medical Outcomes  Partnership (OMOP); Observational Health Data Science and  Informatics (OHDSI); DRUG-RESISTANT EPILEPSY; ANTIEPILEPTIC DRUGS; AMERICAN-ACADEMY; TREATMENT CHOICE; EFFICACY; TOLERABILITY; ADULTS; IMPLEMENTATION; SUBCOMMITTEE; LAMOTRIGINE;
D O I
10.1016/j.yebeh.2022.108630
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Introduction: Efforts to characterize variability in epilepsy treatment pathways are limited by the large number of possible antiseizure medication (ASM) regimens and sequences, heterogeneity of patients, and challenges of measuring confounding variables and outcomes across institutions. The Observational Health Data Science and Informatics (OHDSI) collaborative is an international data network representing over 1 billion patient records using common data standards. However, few studies have applied OHDSI's Common Data Model (CDM) to the population with epilepsy and none have validated relevant concepts. The goals of this study were to demonstrate the feasibility of characterizing adult patients with epilepsy and ASM treatment pathways using the CDM in an electronic health record (EHR)-derived database.Methods: We validated a phenotype algorithm for epilepsy in adults using the CDM in an EHR-derived database (2001-2020) against source records and a prospectively maintained database of patients with confirmed epilepsy. We obtained the frequency of all antecedent conditions and procedures for patients meeting the epilepsy phenotype criteria and characterized ASM exposure sequences over time and by age and sex.Results: The phenotype algorithm identified epilepsy with 73.0-85.0% positive predictive value and 86.3% sensitivity. Many patients had neurologic conditions and diagnoses antecedent to meeting epilepsy criteria. Levetiracetam incrementally replaced phenytoin as the most common first-line agent, but significant heterogeneity remained, particularly in second-line and subsequent agents. Drug sequences included up to 8 unique ingredients and a total of 1,235 unique pathways were observed.Conclusions: Despite the availability of additional ASMs in the last 2 decades and accumulated guidelines and evidence, ASM use varies significantly in practice, particularly for second-line and subsequent agents. Multi-center OHDSI studies have the potential to better characterize the full extent of variability and support observational comparative effectiveness research, but additional work is needed to validate covariates and outcomes.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页数:8
相关论文
共 6 条
  • [1] Characterization of Anti-seizure Medication Treatment Pathways in Pediatric Epilepsy Using the Electronic Health Record-Based Common Data Model
    Kim, Hunmin
    Yoo, Sooyoung
    Jeon, Yonghoon
    Yi, Soyoung
    Kim, Seok
    Choi, Sun Ah
    Hwang, Hee
    Kim, Ki Joong
    FRONTIERS IN NEUROLOGY, 2020, 11
  • [2] Transforming electronic health record polysomnographic data into the Observational Medical Outcome Partnership's Common Data Model: a pilot feasibility study
    Kim, Jeong-Whun
    Kim, Seok
    Ryu, Borim
    Song, Wongeun
    Lee, Ho-Young
    Yoo, Sooyoung
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [3] Transforming electronic health record polysomnographic data into the Observational Medical Outcome Partnership's Common Data Model: a pilot feasibility study
    Jeong-Whun Kim
    Seok Kim
    Borim Ryu
    Wongeun Song
    Ho-Young Lee
    Sooyoung Yoo
    Scientific Reports, 11
  • [4] Identification of patients with drug-resistant epilepsy in electronic medical record data using the Observational Medical Outcomes Partnership Common Data Model
    Castano, Victor G.
    Spotnitz, Matthew
    Waldman, Genna J.
    Joiner, Evan F.
    Choi, Hyunmi
    Ostropolets, Anna
    Natarajan, Karthik
    McKhann, Guy M.
    Ottman, Ruth
    Neugut, Alfred, I
    Hripcsak, George
    Youngerman, Brett E.
    EPILEPSIA, 2022, 63 (11) : 2981 - 2993
  • [5] Patient-Level Fall Risk Prediction Using the Observational Medical Outcomes Partnership's Common Data Model: Pilot Feasibility Study
    Jung, Hyesil
    Yoo, Sooyoung
    Kim, Seok
    Heo, Eunjeong
    Kim, Borham
    Lee, Ho-Young
    Hwang, Hee
    JMIR MEDICAL INFORMATICS, 2022, 10 (03)
  • [6] Using longitudinal progress test data to determine the effect size of learning in undergraduate medical education - a retrospective, single-center, mixed model analysis of progress testing results
    Goerlich, Dennis
    Friederichs, Hendrik
    MEDICAL EDUCATION ONLINE, 2021, 26 (01):