UNASSIGNED: Abstract Objectives: To develop an economic model that estimates the cost burden of @entity146 relapse and recidivism among @entity1 with @entity161 recently released from incarceration from a US state government perspective. Methods: A Markov state-transition model was developed to estimate the numbers of @entity161 @entity1 recently-released from incarceration who would experience @entity146 and re-incarceration over a period of 3 years, along with corresponding costs. The model includes three health states: (1) in community, on therapy, (2) in community, off therapy, and (3) incarcerated. It is assumed that a @entity1 's probability of @entity146 hospitalization increases with treatment discontinuation, and the probability of arrest increases with the occurrence of a prior @entity146 hospitalization. Data from the US Census and Bureau of Justice Statistics were used to estimate the model population. Published literature was used to estimate the risks of @entity146 relapse, arrest, and all cost inputs. State-specific incarceration rates and sentence length data (from the state of Florida) were applied. The impact on outcomes and costs was evaluated by varying the rates of anti- @entity716 treatment following release from incarceration and the annual risk of medication discontinuation. Results: Among 34,500 @entity1 released from incarceration in the state of Florida annually, 5307 were estimated to have @entity161 . The cumulative 3-year costs to the state government were  21,146,000 and  25,616,000 for criminal justice and @entity146 hospitalization costs, respectively ( 3984 per @entity1 criminal justice;  4827 per @entity1 hospitalization costs). A relative 20% increase in the proportion of patients receiving antipsychotic treatment following release from incarceration decreased total cumulative costs over 3 years by  1,871,100 ( 353 per @entity1 ). Conclusions: The economic impact of @entity146 relapse and recidivism among @entity1 with @entity161 is substantial from the state government perspective. This general model can be made state-specific by utilizing local criminal justice data sources.

Economic impact of @entity146 relapse and recidivism among adults with XXXX recently released from incarceration: a Markov model analysis.

@entity1 :: ('9606', 'Species') :: ['patients', 'patient', 'persons'] @entity161 :: ('MESH:D012559', 'Disease') :: ['schizophrenia'] @entity716 :: ('MESH:D011605', 'Disease') :: ['psychotic'] @entity146 :: ('MESH:D001523', 'Disease') :: ['psychiatric', 'psychiatric relapse and/or arrest']
@entity161 :: (MESH:D012559,Disease) :: ['schizophrenia']
