PLoS ONE (Jan 2022)

Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model

  • Walter S. Mathis,
  • Maria Ferrara,
  • Shadie Burke,
  • Emily Hyun,
  • Fangyong Li,
  • Bin Zhou,
  • John Cahill,
  • Emily R. Kline,
  • Matcheri S. Keshavan,
  • Vinod H. Srihari

Journal volume & issue
Vol. 17, no. 12

Abstract

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Objective An extensive international literature demonstrates that understanding pathways to care (PTC) is essential for efforts to reduce community Duration of Untreated Psychosis (DUP). However, knowledge from these studies is difficult to translate to new settings. We present a novel approach to characterize and analyze PTC and demonstrate its value for the design and implementation of early detection efforts. Methods Type and date of every encounter, or node, along the PTC were encoded for 156 participants enrolled in the clinic for Specialized Treatment Early in Psychosis (STEP), within the context of an early detection campaign. Marginal-delay, or the portion of overall delay attributable to a specific node, was computed as the number of days between the start dates of contiguous nodes on the PTC. Sources of delay within the network of care were quantified and patient characteristic (sex, age, race, income, insurance, living, education, employment, and function) influences on such delays were analyzed via bivariate and mixed model testing. Results The period from psychosis onset to antipsychotic prescription was significantly longer (52 vs. 20.5 days, [p = 0.004]), involved more interactions (3 vs. 1 nodes, [pConclusions The conceptual model and analytic approach outlined in this study give first episode services tools to measure, analyze, and inform strategies to reduce untreated psychosis.