Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients.

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.

Racial and Ethnic Disparities in Hospital-Based Care Associated with Postpartum Depression.

OBJECTIVE: To estimate racial and ethnic differences in rates of hospital-based care associated with postpartum depression. METHODS: This is a retrospective cohort study using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes within data from the Office of Statewide Planning and Development in California. We included primiparous women who underwent delivery hospitalization from 2008 to 2012. The primary outcome was the first postpartum hospital encounter with a ICD-9-CM code for depression over a 9-month period after delivery. We examined the cumulative incidence of hospital-based care for postpartum depression by race/ethnicity. Logistic regression was used to estimate relative risk. RESULTS: The study cohort consisted of 984,167 primiparous women: 314,037 (32%) were non-Hispanic White; 59,754 (6%) were non-Hispanic Black; 150,855 (15%) were non-Hispanic Asian; 448,770 (46%) were Hispanic; and 10,399 (1%) were other races. The cumulative incidence of hospital-based care for postpartum depression was highest for Black women (39; 95% CI = 34-44 per 10,000 deliveries) and lowest for Asian women (7; 95% CI = 5-8 per 10,000 deliveries). Compared with White women, hospital-based care for postpartum depression was more likely to be provided to Black women (OR = 2.3; 95% CI = 1.9-2.7), whereas care was less likely for Asians (OR = 0.4; 95% CI = 0.3-0.5) and Hispanics (OR = 0.8; 95% CI = 0.7-1.0). Similar findings were observed after excluding women with antepartum depression, adjusting for sociodemographic and clinical variables, and stratifying according to care settings. CONCLUSION: Compared with White women, hospital-based care for postpartum depression more frequently impacts Black women. Identifying and improving inequities in access to and utilization of mental health care for postpartum women should be a maternal health priority.