Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model.
<h4>Objective</h4>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...
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Public Library of Science (PLoS)
2022-01-01
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| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270234&type=printable |
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| author | Walter S Mathis Maria Ferrara Shadie Burke Emily Hyun Fangyong Li Bin Zhou John Cahill Emily R Kline Matcheri S Keshavan Vinod H Srihari |
| author_facet | Walter S Mathis Maria Ferrara Shadie Burke Emily Hyun Fangyong Li Bin Zhou John Cahill Emily R Kline Matcheri S Keshavan Vinod H Srihari |
| author_sort | Walter S Mathis |
| collection | DOAJ |
| description | <h4>Objective</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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, [p<0.001]), and was predominated by encounters with non-clinical nodes while the period from antipsychotic to STEP enrollment was shorter and predominated by clinical nodes. Outpatient programs were the greatest contributor of marginal delays on both before antipsychotic prescription (median [IQR] of 36.5 [1.3-132.8] days) and (median [IQR] of 56 [15-210.5] days). Sharper functional declines in the year before enrollment correlated significantly with longer DUP (p<0.001), while those with higher functioning moved significantly faster through nodes (p<0.001). No other associations were found with patient characteristics and PTCs.<h4>Conclusions</h4>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. |
| format | Article |
| id | doaj-art-720e92e9ee674f999c85e4c7c2a374c8 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-720e92e9ee674f999c85e4c7c2a374c82025-08-20T03:05:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-011712e027023410.1371/journal.pone.0270234Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model.Walter S MathisMaria FerraraShadie BurkeEmily HyunFangyong LiBin ZhouJohn CahillEmily R KlineMatcheri S KeshavanVinod H Srihari<h4>Objective</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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, [p<0.001]), and was predominated by encounters with non-clinical nodes while the period from antipsychotic to STEP enrollment was shorter and predominated by clinical nodes. Outpatient programs were the greatest contributor of marginal delays on both before antipsychotic prescription (median [IQR] of 36.5 [1.3-132.8] days) and (median [IQR] of 56 [15-210.5] days). Sharper functional declines in the year before enrollment correlated significantly with longer DUP (p<0.001), while those with higher functioning moved significantly faster through nodes (p<0.001). No other associations were found with patient characteristics and PTCs.<h4>Conclusions</h4>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.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270234&type=printable |
| spellingShingle | Walter S Mathis Maria Ferrara Shadie Burke Emily Hyun Fangyong Li Bin Zhou John Cahill Emily R Kline Matcheri S Keshavan Vinod H Srihari Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model. PLoS ONE |
| title | Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model. |
| title_full | Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model. |
| title_fullStr | Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model. |
| title_full_unstemmed | Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model. |
| title_short | Granular analysis of pathways to care and durations of untreated psychosis: A marginal delay model. |
| title_sort | granular analysis of pathways to care and durations of untreated psychosis a marginal delay model |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0270234&type=printable |
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