MINDSET: Quality Improvement to Enhance Patient Assessment and Tailored Feedback in a Level 4 Neurology Clinic Using Digital Decision Support
Abstract number :
3.156
Submission category :
17. Public Health
Year :
2024
Submission ID :
310
Source :
www.aesnet.org
Presentation date :
12/9/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Ross Shegog, PhD – UT Health Houston
Author: Sharada Wali, MD, MPH – UT Health Houston
Katarzyna W Czerniak, MLA,MPH – University of Texas Health Science Center
Patty Gonzales, RN – Barrows Neurological Institute
Robert Addy, PhD – UT Health Houston
Alison Kukla, MPH – Epilepsy Foundation
Cate Broker, NP – Epilepsy Foundation
Refugio Sepulveda, PhD – University of Arizona
David Labiner, MD – University of Arizona
Susan Herman, MD – Barrows Neurological Institute
Rationale: Effective management of PWE in neurology clinics is predicated on an accurate holistic assessment of clinical parameters (e.g., seizures frequency, side effects), epilepsy self-management (ESM) behaviors (e.g., AED adherence, lifestyle management), epilepsy related co-morbidities (e.g., depression, cognitive impairment & memory), quality of life, and social determinants of health. Accurate systematic assessment can inform collaborative treatment decisions tailored to the needs of the PWE. The purpose of this quality improvement (QI) project is to assess the feasibility of using digital decision-support with embedded validated scales to provide a holistic patient management profile and tailored recommendations to optimizing clinical decision-making and patient education during neurology consultations.
Methods: Participants were adult patients with epilepsy (PWE) attending the Barrow Neurology Clinic in Phoenix, AZ. During their regular neurology visit, they used the digital Management Information Decision Support Epilepsy Tool (MINDSET) to input self-reported data on seizure, medication, and lifestyle ESM behaviors (ESM scale), depression (NDDI-E), quality of life (QoLIE-10), memory (QoLIE-31 cognitive subscale), social determinants of health (Health Leads Survey), and behavioral goals. After their neurologist consultation they received a tailored goal-based Action Plan and seizure calendar.
Results: The sample included 17 PWE (9 females, 8 males), 45.9 ± 18.9 years of age (range: 17- 74; mode 51-70 years). Participants were primarily White (n=11), with Black/African American (n=2) and multi-racial individuals (n=2). Most had focal seizures (n=10) and reported a seizure frequency of 0 to 13 (mean = 6.5 ± 4.03) over 3 months. Common medication side effects included tiredness and difficulty concentrating. Within the sample, 11.8% missed AED doses in the last two weeks. 52.9% reported depression (NIDDI-E scores ≥15) with 22.2% indicating suicidal ideation. Social determinant challenges affected 47.06%, including financial constraints, utility shut-off threats, housing stability concerns, cost barriers to doctor visits, and lack of transportation. Social isolation affected 35.3%, and health literacy limitations affected 23.5%. Barriers to implementation included clinic capacity (leadership support, staff commitment, device access), clinic integration (patient recruitment, workflow), and software integrity (firewall connectivity, onboarding, reporting).
Conclusions: Digital decision support offers a feasible enhancement to neurology visits by facilitating a comprehensive identification of clinical, behavioral, and social determinants of epilepsy self-management (ESM) for people with epilepsy (PWE). This approach can offer precision and customization of treatment plans if implementation barriers of clinical capacity, workflow, and connectivity are mitigated.
Funding: Acknowledgements: This research was funded by Epilepsy Foundation Nationals
Public Health