Decision Support for Pediatric Epilepsy Quality Measures
Abstract number :
1.384
Submission category :
13. Health Services (Delivery of Care, Access to Care, Health Care Models)
Year :
2022
Submission ID :
2204061
Source :
www.aesnet.org
Presentation date :
12/3/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:23 AM
Authors :
Stephen Downs, MD, MS – Wake Forest School of Medicine; Katie Hetges, BS – Director, Programs, Child Neurology Foundation; Ann Clark, MA – Clinical Research Specialist, Pediatrics, Indiana University; Anup Patel, MD – Associate Professor, Neurology, Nationwide Children's Hospital
Rationale: The American Academy of Neurology (AAN) in collaboration with representatives from the American Epilepsy Society (AES) and others, has published quality measures related to epilepsy, many applicable to children. Limited data exist showing how well child neurologists perform relative to these child neurology quality metrics. Data that are available show a need for ways to track and improve the quality of care. The Child Neurology Foundation (CNF) in partnership with Digital Health Solutions, LLC (DHS) initiated a national quality improvement initiative aimed at developing a clinical decision support system to implement quality measures and improve care and patient education for epilepsy and child neurology more broadly.
Methods: CNF convened an expert panel comprising child neurologists, quality experts, a clinical informatician, and a patient representative. Beginning with published quality measures and relevant to child neurology, algorithms were developed, using formal algorithmic flow diagrams. A modified Delphi technique and nominal group method, conducted by teleconference and email, were used to modify each algorithm in several rounds until consensus was achieved. For each algorithm, CNF and the expert panel developed a handout that neurologists can use to educate patients.
Results: The panel created 25 algorithms that address quality metrics related to epilepsy, and other areas of child neurology, including depression screening, genetic testing, gastrointestinal issues, neurodevelopmental surveillance, school problems, transition of care, migraine management, muscular dystrophy, tic disorder and Tourette syndrome. For each of these a handout was developed. The clinical content has now been encoded into a software system, embedded into an electronic medical record, that will be pilot tested in neurology clinics in two academic medical centers.
Conclusions: Expert consensus was achieved on a broad set of clinical algorithms based on published quality metrics. The algorithms were associated with patient handouts and encoded in a clinical system that runs in an electronic medical record.
Funding: This work was supported by the Child Neurology Foundation.
Health Services (Delivery of Care, Access to Care, Health Care Models)