School of Medicine
Bioinformatics | Health Information Technology | Health Services Administration | Health Services Research | Neurology | Pediatrics | Psychiatry | Psychiatry and Psychology
OBJECTIVE: Pediatric acute-onset neuropsychiatric syndrome (PANS) is a complex neuropsychiatric syndrome characterized by an abrupt onset of obsessive-compulsive symptoms and/or severe eating restrictions, along with at least two concomitant debilitating cognitive, behavioral, or neurological symptoms. A wide range of pharmacological interventions along with behavioral and environmental modifications, and psychotherapies have been adopted to treat symptoms and underlying etiologies. Our goal was to develop a data-driven approach to identify treatment patterns in this cohort.
MATERIALS AND METHODS: In this cohort study, we extracted medical prescription histories from electronic health records. We developed a modified dynamic programming approach to perform global alignment of those medication histories. Our approach is unique since it considers time gaps in prescription patterns as part of the similarity strategy.
RESULTS: This study included 43 consecutive new-onset pre-pubertal patients who had at least 3 clinic visits. Our algorithm identified six clusters with distinct medication usage history which may represent clinician's practice of treating PANS of different severities and etiologies i.e., two most severe groups requiring high dose intravenous steroids; two arthritic or inflammatory groups requiring prolonged nonsteroidal anti-inflammatory drug (NSAID); and two mild relapsing/remitting group treated with a short course of NSAID. The psychometric scores as outcomes in each cluster generally improved within the first two years.
DISCUSSION AND CONCLUSION: Our algorithm shows potential to improve our knowledge of treatment patterns in the PANS cohort, while helping clinicians understand how patients respond to a combination of drugs.
Cluster analysis, Longitudinal studies, Patient similarity, Pediatric acute-onset neuropsychiatric syndrome, Polypharmacy
Rights and Permissions
© 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
DOI of Published Version
Lopez Pineda A, Pourshafeie A, Ioannidis A, Leibold CM, Chan AL, Bustamante CD, Frankovich J, Wojcik GL. Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients. J Biomed Inform. 2021 Jan;113:103664. doi: 10.1016/j.jbi.2020.103664. Epub 2020 Dec 28. PMID: 33359113. Link to article on publisher's site
Journal of biomedical informatics
Lopez Pineda A, Pourshafeie A, Ioannidis A, Leibold CM, Chan AL, Bustamante CD, Frankovich J, Wojcik GL. (202). Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients. Open Access Publications by UMMS Authors. https://doi.org/10.1016/j.jbi.2020.103664. Retrieved from https://escholarship.umassmed.edu/oapubs/4547
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Bioinformatics Commons, Health Information Technology Commons, Health Services Administration Commons, Health Services Research Commons, Neurology Commons, Pediatrics Commons, Psychiatry Commons, Psychiatry and Psychology Commons