Insight : An ontology-based integrated database and analysis platform for epilepsy self-management research

Sahoo, Satya S.; Ramesh, Priya; Welter, Elisabeth; Bukach, Ashley; Valdez, Joshua; Tatsuoka, Curtis; Bamps, Yvan; Stoll, Shelley; Jobst, Barbara C.; Sajatovic, Martha

doi:10.1016/j.ijmedinf.2016.06.009

Cited by 10 publications

(5 citation statements)

References 35 publications

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“…Details on the MEW Network and the research community providing data has been described elsewhere [9, 12, 13]. For this analysis, the data used originated from 6 epilepsy self-management studies conducted across 4 research sites and comprised 459 PWE.…”

Section: Methodsmentioning

confidence: 99%

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Correlates of quality of life among individuals with epilepsy enrolled in self-management research

Sajatovic

Tatsuoka

Welter

et al. 2017

Epilepsy & Behavior

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Rationale: Epilepsy is a chronic neurological condition that causes substantial burden on patients and families. Quality of life may be reduced due to the stress of coping with epilepsy. For nearly a decade, the Centers for Disease Control (CDC) Prevention Research Center’s Managing Epilepsy Well (MEW) Network has been conducting research on epilepsy self-management to address research and practice gaps. Studies have been conducted by independent centers across the U.S. Recently, the MEW Network sites, collaboratively, began compiling an integrated database to facilitate aggregate secondary analysis of completed and ongoing studies. In this preliminary analysis, correlates of quality of life in people with epilepsy (PWE) were analyzed from pooled baseline data from the MEW Network. Methods: For this analysis, data originated from 6 epilepsy studies conducted across 4 research sites and comprised 459 PWE. Descriptive comparisons assessed common data elements that included gender, age, ethnicity, race, education, employment, income, seizure frequency, quality of life, and depression. Standardized rating scales were used for quality of life (QOLIE-10) and for depression (Patient Health Questionnaire, PHQ-9). Results: While not all datasets included all common data elements, baseline descriptive analysis found a mean age of 42 (SD 13.22), 289 women (63.0%), 59 African Americans (13.7%), 58 Hispanics (18.5%). Most, 422 (92.8%), completed at least high school, while 169 (61.7%) were unmarried, divorced/separated, or widowed. Median 30-day seizure frequency was 0.71 (range 0-308). Depression at baseline was common, with a mean PHQ-9 score of 8.32 (SD 6.04); 69 (29.0%) had depression in the mild range (PHQ-9 score 5-9) and 92 (38.7%) had depression in the moderate to severe range (PHQ-9 score > 9). Lower baseline quality of life was associated with greater depressive severity (p <.001), more frequent seizures (p<.04) and lower income (p<.05). Conclusions: The MEW Network integrated database offers a unique opportunity for secondary analysis of data from multiple community-based epilepsy research studies. While findings must be tempered by potential sample bias, i.e. a relative under-representation of men and relatively small sample of some racial/ethnic subgroups, results of analyses derived from this first integrated epilepsy self-management database have potential to be useful to the field. Associations between depression severity and lower QOL in PWE are consistent with previous studies derived from clinical samples. Self-management efforts that focus on mental health comorbidity and seizure control may be one way to address modifiable factors that affect quality of life in PWE.

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Section: Methodsmentioning

confidence: 99%

“…To address this issue, mappings were defined to map value “1” in WebEase to value “3” in the integrated database. [12]…”

Section: Methodsmentioning

confidence: 99%

Correlates of quality of life among individuals with epilepsy enrolled in self-management research

Sajatovic

Tatsuoka

Welter

et al. 2017

Epilepsy & Behavior

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“…Our development team envisions that as WWECA is promoted and adopted globally, experts and scholars can adapt and enhance its domain knowledge to better serve women with epilepsy of child-bearing age based on their cultural and technological contexts. Epilepsy self-management platform [31] Natural language processing based text data extraction [32] Multicenter data integration system for sudden death in epilepsy [33] Electrophysiological data visualization and analysis platform [34] Information capture system for epilepsy medical record data [35] Multicenter data integration system for sudden death in epilepsy [36] Extraction of epileptic phenotypes and their associated anatomical locations from discharge medical records [37] Satya…”

Section: Discussionmentioning

confidence: 99%

Whole-cycle management of women with epilepsy of child-bearing age: ontology construction and application

Xia,

Duan,

Sha

et al. 2024

BMC Med Inform Decis Mak

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Background The effective management of epilepsy in women of child-bearing age necessitates a concerted effort from multidisciplinary teams. Nevertheless, there exists an inadequacy in the seamless exchange of knowledge among healthcare providers within this context. Consequently, it is imperative to enhance the availability of informatics resources and the development of decision support tools to address this issue comprehensively. Materials and methods The development of the Women with Epilepsy of Child-Bearing Age Ontology (WWECA) adhered to established ontology construction principles. The ontology’s scope and universal terminology were initially established by the development team and subsequently subjected to external evaluation through a rapid Delphi consensus exercise involving domain experts. Additional entities and attribute annotation data were sourced from authoritative guideline documents and specialized terminology databases within the respective field. Furthermore, the ontology has played a pivotal role in steering the creation of an online question-and-answer system, which is actively employed and assessed by a diverse group of multidisciplinary healthcare providers. Results WWECA successfully integrated a total of 609 entities encompassing various facets related to the diagnosis and medication for women of child-bearing age afflicted with epilepsy. The ontology exhibited a maximum depth of 8 within its hierarchical structure. Each of these entities featured three fundamental attributes, namely Chinese labels, definitions, and synonyms. The evaluation of WWECA involved 35 experts from 10 different hospitals across China, resulting in a favorable consensus among the experts. Furthermore, the ontology-driven online question and answer system underwent evaluation by a panel of 10 experts, including neurologists, obstetricians, and gynecologists. This evaluation yielded an average rating of 4.2, signifying a positive reception and endorsement of the system’s utility and effectiveness. Conclusions Our ontology and the associated online question and answer system hold the potential to serve as a scalable assistant for healthcare providers engaged in the management of women with epilepsy (WWE). In the future, this developmental framework has the potential for broader application in the context of long-term management of more intricate chronic health conditions.

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“…This analysis used baseline data from 9 studies of the MEW Network integrated research database (MEW DB), details of which are described elsewhere 10. All studies that were analyzed were approved by local Institutional Review Boards (IRBs) and the integrated dataset infrastructure and analysis was approved by a local IRB.…”

Section: Methodsmentioning

confidence: 99%

<p>Depressive Symptoms in Older versus Younger People with Epilepsy: Findings from an Integrated Epilepsy Self-Management Clinical Research Dataset</p>

Khalid¹,

Momotaz²,

Briggs³

et al. 2019

JMDH

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Insight : An ontology-based integrated database and analysis platform for epilepsy self-management research

Cited by 10 publications

References 35 publications

Correlates of quality of life among individuals with epilepsy enrolled in self-management research

Correlates of quality of life among individuals with epilepsy enrolled in self-management research

Whole-cycle management of women with epilepsy of child-bearing age: ontology construction and application

<p>Depressive Symptoms in Older versus Younger People with Epilepsy: Findings from an Integrated Epilepsy Self-Management Clinical Research Dataset</p>

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