Economic impact of psychiatric relapse and recidivism among adults with schizophrenia recently released from incarceration: a Markov model analysis

Abstract

Objectives:

To develop an economic model that estimates the cost burden of psychiatric relapse and recidivism among patients with schizophrenia recently released from incarceration from a US state government perspective.

Methods:

A Markov state-transition model was developed to estimate the numbers of schizophrenia patients recently-released from incarceration who would experience psychiatric relapse and/or arrest 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 patient’s probability of psychiatric hospitalization increases with treatment discontinuation, and the probability of arrest increases with the occurrence of a prior psychiatric 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 psychiatric 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-psychotic treatment following release from incarceration and the annual risk of medication discontinuation.

Results:

Among 34,500 persons released from incarceration in the state of Florida annually, 5307 were estimated to have schizophrenia. The cumulative 3-year costs to the state government were $21,146,000 and $25,616,000 for criminal justice and psychiatric hospitalization costs, respectively ($3984 per patient criminal justice; $4827 per patient 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 patient).

Conclusions:

The economic impact of psychiatric relapse and recidivism among patients with schizophrenia is substantial from the state government perspective. This general model can be made state-specific by utilizing local criminal justice data sources.

Keywords::

• Recidivism
• Anti-psychotic therapy
• Economics
• Adherence
• Serious mental illness
• Re-incarceration

Introduction

Individuals with severe mental illness, such as schizophrenia, are disproportionately represented in the criminal justice system in the US. A survey of inmates conducted by the US Bureau of Justice Statistics estimated that 56% of State prisoners and 64% of jail inmates reported symptoms of mental health disorders or had a recent history of mental health problems1. Repeated encounters with the criminal justice system are also more common among people with a serious mental illness. Among inmates in prison or jail who had a mental health problem, approximately a quarter had served three or more prior incarcerations, compared to one-fifth among those without mental health problems1. Furthermore, a 2012 analysis of patient records and linked criminal justice data found co-occurring substance abuse disorder, homelessness, and a diagnosis of schizophrenia to be significant predictors of re-incarceration among patients with a serious mental illness2. Those with schizophrenia had higher odds of re-incarceration compared to other psychiatric diagnoses included in the analysis, such as major depression and bipolar disorder.

Given the high rate of recidivism among this population, successful transition of care after release from incarceration to the community is important. Adults with schizophrenia who are recently released from incarceration and entering back into the community are particularly vulnerable, and there are opportunities within this group for expanded and improved mental health treatment. Recent analyses have demonstrated that access to care, particularly the utilization of anti-psychotic treatment, can significantly reduce the probability of recidivism among patients with serious mental illness3. However, to date, there has been limited research into the costs of care–through medical providers and the criminal justice system–for this high-risk group of recently-released persons with severe mental illness.

The criminal justice system bears the responsibility and cost of providing mental health services for persons that are incarcerated. Domino et al.4 found evidence of a trend of institutionalizing individuals with mental illness in jails, rather than mental hospitals or general hospitals. The studies that are currently published on adults with serious mental illness and their engagement with the criminal justice system focus on predictors and rates of incarceration/re-incarceration or arrest2^,5–7. One paper estimated costs associated with encounters with the legal system among adults with co-occurring severe mental illness and substance use disorders8. However, the study did not follow individuals past the arrest stage and no cost information is collected during their time in incarceration or possible recidivism after they are released. The studies that examine cost and resource use associated with schizophrenia tend to focus on inpatient and outpatient care9^,10 for individuals with schizophrenia, but not necessarily people who have been through the criminal justice system. One study that touched upon criminal justice costs estimated that the excess cost of schizophrenia in the US was $62.7 billion, of which $2.6 billion was direct non-healthcare costs for law enforcement11.

The present study uses an economic model to estimate the cost burden of psychiatric relapse and recidivism among individuals with schizophrenia recently released from incarceration over a 3-year time horizon. The model captures both psychiatric hospitalization costs and costs to the criminal justice system, which includes the cost of arrest, trial, and incarceration. Findings presented in this paper add to the current literature by providing insights into the estimated costs related to psychiatric relapse and recidivism. By varying model inputs, the impact of certain parameters on total cost from a state government perspective is examined, potentially highlighting areas of focus for further policy evaluation and implementation research.

Methods

Model overview

This model was developed in Microsoft Excel (version 2010) spreadsheet format using a population-based Markov modeling approach. Markov models are frequently used in the economic evaluation of real-world scenarios and represent random processes that develop over time. Markov modeling involves considering individuals in mutually exclusive states and repeatedly applying the probability of events that transition individuals between states. Given that the modeling of criminal justice costs and outcomes requires us to follow individuals and evaluate their transition between discrete states (e.g., incarceration, in community), a Markov model was chosen for this analysis. Model inputs and transition probabilities were drawn from published scientific literature and publicly-available criminal justice data. The model population was based on adults (age ≥ 18) with a diagnosis of schizophrenia who were recently released from incarceration. The starting population size of the model reflects the estimated number of patients with schizophrenia who were released from incarceration in a given year. Probabilities related to transition of care from incarceration to community setting and treatment compliance are applied upon the starting population entering the model. The population was followed for 3 years (a time horizon that is similar to other published models in schizophrenia)12 and the analysis was conducted from a state government perspective. Psychiatric hospitalizations (and corresponding direct costs), arrest/re-incarceration rates, and direct costs to the criminal justice system were evaluated. Criminal justice costs included the cost of arrests, infractions, trials, and incarceration.

Based on a review of the literature, Florida was selected as the base-case state for the model given the quantity and quality of available state-specific criminal justice data among patients with schizophrenia/mental illness.

Model assumptions

The following assumptions were made in the design of this economic model:

1. The population (defined as all recently released persons with schizophrenia) enter the model at the same time point (i.e., starting population does not enter the model at varying release dates);

2. Only treatment with anti-psychotic therapy is considered in the model and the impact of other forms of non-pharmacological treatments such as mental-health services, assisted outpatient treatment (AOT), crisis intervention team (CIT), mental health courts, outpatient or social services, or combination treatment (e.g., medications and services) are not included;

3. If an individual receives anti-psychotic treatment after release from incarceration, they are assumed to receive at least a 1-month supply. Once an individual discontinues anti-psychotic treatment, he or she remains off treatment for the remainder of the model, unless re-incarcerated, where they receive a probability of having treatment upon release;

4. If an individual experiences both a hospitalization and an arrest during a cycle, the hospitalization event precedes arrest; an individual’s probability of being arrested during a model cycle will increase if the individual experiences a psychiatric hospitalization during the same cycle; and an infraction does not lead to an arrest/incarceration and the risk of an infraction was not assumed to increase with the presence of a psychiatric hospitalization;

5. Healthcare costs while incarcerated are not explicitly identified due to limited data availability, and it is assumed that healthcare costs are included in the incarceration cost estimates used in this model.

Model structure

After initial release from incarceration, all individuals enter the community, some of whom will be treated with anti-psychotic therapy and others will not be started at the time of release (Assumption #1). If on therapy, an individual has the probability of discontinuing their regimen, which has an impact on subsequent transition probabilities. The model uses monthly cycles and discontinuation in the first cycle is assumed to be zero (i.e., if an individual receives anti-psychotic treatment after release from incarceration, they are assumed to receive/use at least 1 month’s supply).

Individuals are assigned a probability of experiencing a psychiatric hospitalization during each cycle based on their anti-psychotic treatment status. Individuals who are not treated upon release from incarceration or who discontinue treatment are assumed to have a greater probability of experiencing a psychiatric hospitalization (annual hospitalization rate 9.6% for individuals on treatment; 23.9% for those off treatment)13. Individuals experiencing a psychiatric hospitalization accrue the direct costs associated with the hospitalization.

Modeled individuals also have a probability of being arrested during a cycle for an infraction, misdemeanor, or felony charge. Individuals who are not treated with an anti-psychotic upon release from incarceration, or who discontinue treatment, have a greater probability of experiencing an arrest (odds ratio for treatment vs no treatment was 0.81 for felony arrests and 0.89 for misdemeanor arrests)3^,7. A 2011 study of Florida Medicaid patients with schizophrenia or bipolar disorder found an increased risk of felony and misdemeanor arrests among individuals experiencing a psychiatric hospitalization prior to the arrest7. Based on the findings published in the study, it was assumed that if an individual experiences both a hospitalization and an arrest during a given cycle, the hospitalization occurs prior to the arrest and increases the risk of experiencing an arrest7. This relationship has not been demonstrated between infractions and psychiatric hospitalizations; therefore, an increased risk of infraction was not applied to hospitalized individuals. While it is possible that the arrest of an individual with schizophrenia may lead to a hospitalization through referral, probabilistic data on this temporal relationship in the population of interest was not available to support assumptions that could be used in this model.

If an individual is arrested for a felony or misdemeanor, they are assigned probabilities of receiving a trial and of being incarcerated. Infractions do not result in a trial or incarceration. Once incarcerated, the appropriate sentence length is applied, depending on the type of crime committed by the individual (e.g., violent felony, drug felony, or misdemeanor; see Criminal Justice Inputs in Table 1 for sentence lengths). If not incarcerated, an individual will re-enter the community and accrue the cost of the arrest (for all) and trial (if applicable). All arrested individuals are assigned the cost of the arrest and, based on the probability of an arrest leading to trial, a proportion of patients in the cohort additionally will be assigned a cost of trial. At the end of a cycle, an individual who is incarcerated can either remain incarcerated (if sentence is not over) or be released into the community. Upon release from incarceration, the probability of entering the community on/off anti-psychotic treatment is applied again. Direct criminal justice system costs are applied during incarceration according to the average sentence length.

Table 1. Model inputs.

Input	Overall/on anti-psychotic treatment	Off anti-psychotic treatment†	Low estimate	High estimate
Population inputs
Total Florida Population23	19,317,568	–	N/A	N/A
Percent of total population incarcerated each year24	0.52%	–	0.468%*	0.572%*
Percent released from incarceration each year24	34.31%	–	30.88%*	37.74%*
Percent of incarcerated population with schizophrenia1	15.40%	–	10.2%	23.9%
Treatment compliance
Proportion of individuals on anti-psychotic treatment  upon release from incarceration25	61%	–	54.9%*	67.1%*
Treatment discontinuation15
Year 1	50.1%	–	39.6%	68.4%
Year 2	11.9%	–	11.8%	20.4%
Year 3	7.7%	–	7.6%	10.7%
Treatment efficacy
Psychiatric hospitalization rate (Annual)13	9.2%	23.9%	0.27 (OR)	0.55 (OR)
Criminal Justice inputs
Felony arrest risk (monthly)3^,7	0.5%	0.6%	0.63 (OR)	1.04 (OR)
Misdemeanor arrest risk (monthly)3^,7	1.0%	1.1%	0.68 (OR)	1.15 (OR)
Infraction risk (monthly)5	1.3%	1.4%	0.68 (OR)**	1.15 (OR)**
Increased risk of arrest if hospitalized7	53%		41%	67%
Probability of trial if arrested26	20.3%	–	18.3%*	22.3%*
Probability of incarceration if trial  (felony/misdemeanor)26^,27	21.6%/17.8%	–	19.4%/16.0%*	23.8%/19.6%*
Average misdemeanor sentence length (months)6	1		0	3
Average felony sentence length (months)28	49		34.8	70.4
Violent
Murder	105	–	69.7	147.8
Sexual Offenses	70	–	54.8	89.4
Violent Personal Crimes	34	–	20.5	73.4
Property
Robbery	63	–	46.8	79.3
Burglary	60	–	41.8	76.0
Theft, Forgery, Fraud	21	–	17.6	31.6
Drug offenses	29	–	17.2	43.9
Weapon offenses	32	–	28.7	34.5
Other	26	–	15.9	57.4
Economic Inputs
Cost of psychiatric hospitalization16	$9181	–	$8474	$9888
Cost per arrest16	$3245	–	$3102	$3387
Average cost per infraction5	$855	–	$48	$1583
Average trial cost16	$7837	–	$2620	$6185
Average incarceration cost per month16	$5100	–	$4023	$6185

†Inputs that are blank in the ‘Off Anti-psychotic Treatment’ column are assumed to be the same, regardless of treatment status.

*Assumptions of ±10% applied if high/low estimate not provided in the literature.

**Assumed to be the same as misdemeanor (misdemeanor estimate based on data in the literature).

OR, Odds ratio (on treatment vs off treatment); OR varied for parameters that have different estimates for on/off anti-psychotic treatment.

This Markov model includes three health states that an individual can transition to once per cycle: (1) In the community and on anti-psychotic therapy; (2) In the community and off anti-psychotic therapy; and (3) Incarcerated (an individual can be incarcerated either for a felony or a misdemeanor, with varying sentence lengths). A schematic diagram of the model health states and transitions is provided in Figure 1.

Figure 1. Model schematic.

Model inputs

Model inputs included in the analysis are presented in Table 1. All model inputs are based on the scientific literature and publicly-available criminal justice data. State-specific data were used when available, specifically for criminal justice inputs where rates of arrests and incarceration can vary widely by state14. Clinical inputs, such as rates of psychiatric hospitalizations and treatment discontinuation, were assumed to not vary by state, and national data were used when available.

Model data sources

This analysis was not treatment-specific; therefore, data on pooled rates of discontinuation data for atypical and typical treatment regimens were used. A 2006 study conducted by Ascher-Svanum et al.15 evaluated the time to discontinuation of atypical and typical anti-psychotics for 1 year following initiation among a national database of schizophrenic patients. Survival curves for treatment discontinuation of typical and atypical anti-psychotics were extrapolated to 3 years, and the mean of the discontinuation rates for the two drug groups was used as an overall rate of anti-psychotic treatment discontinuation. The resulting annual discontinuation rates were applied evenly across 12 months (i.e., average monthly rates were calculated for each year of the model).

Data from a 2012 meta-analysis of 65 clinical trials (typical and atypical) that evaluated psychiatric hospital admission rates for patients randomized to active treatment or placebo were used as the source for treatment efficacy inputs13. The placebo rate of hospitalizations was applied to individuals discontinuing treatment in the model. Annual hospitalization rates were converted to monthly probabilities and applied to each model cycle.

Data from two publications that evaluated the impact of anti-psychotic treatment on arrest rates among Florida Medicaid patients with a diagnosis of schizophrenia or bipolar disorder were used to derive arrest risk inputs3^,7. In order to derive the risk of a repeat arrest among treated individuals with schizophrenia, an arrest rate among schizophrenic patients with continuous treatment (i.e., > 60 days) was used as the base rate3^,7. Using data from the same patient population, this rate was increased by the hazard ratio of experiencing an arrest among individuals with a history of arrests (HR = 7.61 vs no previous arrest)3^,7. Published odds ratios were then used to establish annual arrest rates for felony and misdemeanors among schizophrenic individuals with and without anti-psychotic treatment3. An additional publication among a national population of individuals with schizophrenia was used to establish a base infraction rate5. All derived annual arrest risks were converted to monthly probabilities for modeling purposes (see Table 1 for a complete list of model inputs).

Probabilities for the proportion of arrests that go to trial, proportion of trials that lead to an incarceration, felony type (e.g., violent, property, drug, other), and average sentence length by felony type were determined using publicly-available data from the Florida Department of Corrections. Data for the cost per arrest, average trial cost, and average incarceration cost per month among mentally ill individuals were derived from a previously conducted literature review16. Cost estimates from the literature were adjusted to 2011 dollars using the Bureau of Labor Statistics Consumer Price Index for all items. The cost of psychiatric hospitalization was based on a retrospective analysis of a multi-state Medicaid database16. The analysis included claims with costs greater than $1000 to remove the majority of capitated claims, or claims where other insurance could influence the payment amount, or claims with potential data errors. The sample used for the analysis was patients with at least one diagnosis in 2011 for schizophrenia (ICD-9-CM codes 295.30, 295.10, 295.90, or 295.60). Mental health-related hospitalization costs were identified using the same diagnosis codes. Only direct costs for criminal justice and psychiatric hospitalizations were considered, and all future costs observed in the model were discounted using a rate of 3%.

Model outcomes

Model outcomes were evaluated over a 3-year time horizon, and included the total number of psychiatric hospitalizations, the total number of infractions, total number of arrests (misdemeanor/felony), and the total number of re-incarcerations (misdemeanor/felony). Economic outcomes included the total direct cost of psychiatric hospitalizations and the total direct cost to the criminal justice system (including arrest, infraction, trial, and incarceration costs). Criminal justice costs reflect the cost of sentencing observed during the model time horizon only (i.e., costs incurred for sentences that are beyond the 3-year model time horizon were not included in the total cost estimate). The cost of anti-psychotic drug treatment was not included in the model. Outcomes were reported as overall estimates, as well as per 100 individuals (for clinical/criminal justice outcomes) and per individual (for cost outcomes) with schizophrenia recently released from incarceration.

Sensitivity analyses

In order to estimate the impact of select policy-oriented inputs on economic and clinical outcomes, one-way sensitivity analyses (i.e., variation of a single model input while maintaining the base-case value for all other inputs) were conducted on the proportion of individuals receiving treatment with an anti-psychotic upon release from incarceration and the annual anti-psychotic discontinuation rate. The base-case model inputs were increased/decreased by a relative 20% for each model input.

Probabilistic sensitivity analyses were undertaken using a second order Monte Carlo simulation. Mean, high and low estimates were taken from the publication of each model input, when available. For rates where a confidence interval was not included in the published literature, a ±10% assumption was made for the high and low estimates. All cost inputs (using a gamma distribution), odds ratios of arrest risk (using a log-normal distribution), criminal justice and clinical inputs (using a uniform distribution) were varied within the model. One thousand simulations were conducted and results (i.e., mean, median, 95% CI) were used to determine the impact of varying all input estimates on model outcomes.

Results

Base-case results

Using data from the US Census, the US Bureau of Justice Statistics, and the Florida Department of Corrections, it was estimated that, of the total Florida population (19,317,568; US Census 2012 estimate), there were ∼100,451 persons incarcerated, of which 34,464 (34.3%) would be released in the year prior to the start of the model17. Of these persons recently released from incarceration, it was assumed that 15.4% had a serious mental-illness1 (used as a proxy for schizophrenia), resulting in 5307 individuals with schizophrenia that would be released from incarceration at the beginning of the model (i.e., Year 1).

Over the 3-year time horizon, there were an estimated 2877 psychiatric hospitalizations (54.2 per 100 individuals with schizophrenia) among the study population. The rate of hospitalizations increased each year, with rates of 16.7 per 100 individuals with schizophrenia during the first year of the model, 18.5 per 100 individuals during the second, and 19.0 per 100 during the third (Table 2).

Table 2. Economic and criminal justice outcomes among individuals with schizophrenia 3 years after release from incarceration.

	Year 1		Year 2		Year 3		Total (Cumulative)
	Total	Per 100 individuals†	Total	Per 100 individuals†	Total	Per 100 individuals†	Total	Per 100 individuals†
Clinical outcomes
Total number of psychiatric hospitalizations	887	16.7	984	18.5	1,006	19.0	2,877	54.2
Criminal Justice outcomes
Total number of encounters
Infraction	851	16.0	861	16.2	862	16.2	2,573	48.5
Arrests
Misdemeanor	670	12.6	678	12.8	679	12.8	2,027	38.2
Felony	353	6.6	362	6.8	363	6.8	1,077	20.3
Re-incarcerations
Misdemeanor	24	0.5	25	0.5	25	0.5	73	1.4
Felony	15	0.3	16	0.3	16	0.3	47	0.9
Economic outcomes		Per individual†		Per individual†		Per individual†		Per individual†
Direct cost to the criminal justice system*	$6,305,008	$1,188	$7,144,546	$1,346	$7,696,438	$1,450	$21,145,992	$3,984
Psychiatric hospitalization cost	$8,139,471	$1,534	$8,770,965	$1,653	$8,706,007	$1,640	$25,616,442	$4,827
Total direct cost	$14,444,479	$2,722	$15,915,510	$2,999	$16,402,444	$3,091	$46,762,434	$8,811

*Includes the total cost (i.e., cost that will be incurred by serving a full sentence, even if sentence goes beyond the given year) of all incarcerations that occurred during the year.

†Per 100 individuals/individuals with schizophrenia recently released from custody.

A total of 2573 infractions (48.5 per 100 individuals with schizophrenia), 2027 misdemeanor arrests (38.2 per 100 individuals), and 1077 felony arrests (20.3 per 100 individuals) were made over the 3-year period. Felony and misdemeanor incarcerations during the model time horizon were 47 (0.9 per 100 individuals) and 73 (1.4 per 100 individuals), respectively. Similar to psychiatric hospitalizations, the rates of criminal justice encounters increased slightly each year.

The cumulative 3-year total direct costs (i.e., psychiatric hospitalization plus criminal justice) to the state government were $46,762,000 ($8811 per individual). Three-year direct costs were roughly evenly split between psychiatric hospitalizations ($25,616,000) and criminal justice costs ($21,146,000).

Sensitivity analyses

When the proportion of individuals on anti-psychotic treatment upon release from incarceration increased by a relative 20% (from the base-case value of 61% to 73%), psychiatric hospitalizations decreased by 3.4 per 100 individuals with schizophrenia over the 3 year time horizon (Table 3). When anti-psychotic discontinuation decreased by a relative 20% from the base-case value for each year of the 3-year time horizon (i.e., from 50.1% to 40.1% in year 1, from 11.9% to 9.5% in year 2, and from 7.7% to 6.2% in year 3), psychiatric hospitalizations decreased by 1.6 per 100 individuals with schizophrenia (Table 4).

Table 3. Impact of 20% increase in proportion of individuals with schizophrenia receiving anti-psychotic treatment upon release from incarceration on economic outcomes and psychiatric hospitalizations 3 years after release.

	Base case* (Total cumulative)		New scenario** (Total cumulative)		Difference (New − Base)†
	n	Per 100 individuals	n	Per 100 individuals	n	Per 100 individuals
Clinical outcomes
Total number of psychiatric hospitalizations	2,877	54.2	2,697	50.8	−179	−3.4
Economic outcomes	Total	Per individual	Total	Per individual	Total	Per individual
Direct cost to the criminal justice system	$21,145,992	$3,984	$20,880,251	$3,934	−$265,740	−$50
Psychiatric hospitalization cost	$25,616,442	$4,827	$24,011,072	$4,524	−$1,605,370	−$302
Total direct cost	$46,762,434	$8,811	$44,891,324	$8,458	−$1,871,110	−$353

*Proportion of individuals receiving anti-psychotic treatment upon release = 61%.

**Proportion of individuals receiving anti-psychotic treatment upon release = 73%.

†May not exactly reflect the difference in reported integers from ‘Base case’ and ‘New scenario’ columns due to rounding.

Table 4. Impact of 20% decrease in annual anti-psychotic discontinuation on economic outcomes and psychiatric hospitalizations among individuals with schizophrenia 3 years after release from incarceration.

	Base case* (Total cumulative)		New scenario** (Total cumulative)		Difference (New - Base) †
	n	Per 100 individuals	n	Per 100 individuals	n	Per 100 individuals
Clinical outcomes
Total number of psychiatric hospitalizations	2,877	54.2	2,794	52.6	−83	−1.6
Economic outcomes	Total	Per individual	Total	Per individual	Total	Per individual
Direct cost to the criminal justice system	$21,145,992	$3,984	$21,031,545	$3,963	−$114,447	−$22
Psychiatric hospitalization cost	$25,616,442	$4,827	$24,884,017	$4,689	−$732,425	−$138
Total direct cost	$46,762,434	$8,811	$45,915,562	$8,651	−$846,871	−$160

*Discontinuation rate = 50.1% year 1, 11.9% year 2, 7.7% year 3.

**Discontinuation rate = 40.1% year 1, 9.5% year 2, 6.2% year 3.

†May not exactly reflect the difference in reported integers from ‘Base case’ and. New scenario’ columns due to rounding.

In terms of economic outcomes, a relative 20% increase in the proportion of individuals on anti-psychotic treatment upon release from incarceration decreased total direct costs by $1,871,000 over the 3-year model time horizon ($353 per individual with schizophrenia; $51 per individual in criminal justice costs, and $302 per individual in psychiatric hospitalization costs). A relative 20% decrease in anti-psychotic discontinuation per year resulted in a decrease in total direct costs of $847,000 over the 3-year model time horizon ($160 per individual with schizophrenia; $22 per individual in criminal justice costs, $138 per individual in psychiatric hospitalization costs).

Probabilistic sensitivity analysis resulted in a 95% confidence interval of $41,041,000–$55,425,000 for total direct costs (vs $46,762,000 base-case), $17,399,412–$27,204,000 in criminal justice costs (vs $21,146,000 base-case), and $21,700,000–$31,782,000 in psychiatric hospitalization costs (vs $25,616,000 base-case).

Discussion

Summary

This economic model used publicly-available criminal justice data and published literature to estimate the economic burden of relapse among schizophrenic individuals recently released from incarceration from a state government perspective. Multiple arrest and incarceration outcomes were examined, including infractions, felonies, and misdemeanors, and included model inputs that reflect the impact of treatment discontinuation on these criminal justice encounters.

While the model only estimated the criminal justice encounters for a small sub-set of the total incarcerated population (e.g., 5.3% of the total or 5307 from the Florida state-perspective), the economic impact to the state government was substantial, at ∼$47,000,000 over 3 years, or ∼$9000 per individual with schizophrenia. Over the 3-year time horizon, there were 54.2 psychiatric hospitalizations per 100 individuals with schizophrenia, with hospitalization rates tending to increase each year among the population. Over the 3-year time horizon, there were 58.5 felony/misdemeanor arrests per 100 individuals with schizophrenia and 2.3 felony/misdemeanor re-incarcerations per 100 individuals with schizophrenia over the 3-year time horizon. Total direct costs were similar in terms of criminal justice costs (∼$4000 per individual with schizophrenia over 3 years; including infraction, arrest, trial, and incarceration costs) and psychiatric hospitalization costs (∼$5000 per individual with schizophrenia over 3 years).

Implications of our work

Recent analyses in schizophrenia, such as the 2013 Florida Medicaid analysis by Van Dorn et al.3, have quantified the impact of anti-psychotic treatment utilization on the likelihood of arrest, and the impact of arrests on total medical expenditures. While results from the Van Dorn et al. analyses demonstrated a reduced risk of arrest among individuals receiving anti-psychotic treatment and a high economic burden among schizophrenic individuals involved in the criminal justice system, the economic model in the current study extrapolates these findings to a long-term, population-based perspective. Furthermore, the current model focused on schizophrenic individuals with a history of arrests/incarceration, a sub-population that has been shown to be at higher risk of recidivism1. While inputs from the current analysis used state-specific data from Florida, the model would allow other states (or counties) to use local criminal justice data to help assess the economic impact of psychiatric relapse among adults with schizophrenia released from incarceration from their own perspectives.

One-way sensitivity results demonstrated that increasing the proportion of individuals that received anti-psychotic treatment upon release from incarceration had a positive impact on model outcomes. A study conducted by Lovell et al.18 (from which our base-case model input was derived) evaluated the use of medical services among persons with mental illness after release from state prison. The study showed that, after a 1-year period post-release, only 61% of mentally ill patients received any type of mental health service. The current analysis estimates that increasing this proportion, particularly in terms of prescribing anti-psychotic treatment upon release, may have a positive impact on criminal justice costs from the state government perspective. One-way sensitivity results also demonstrated that anti-psychotic discontinuation was a major cost driver, and that a hypothetical decrease in the discontinuation rate had a positive impact on both psychiatric hospitalizations and incarceration rates.

Furthermore, previous analyses have shown that access to care, such as enrollment in Medicaid, is associated with a reduction in recidivism among patients with serious mental illnesses19. In addition to reducing recidivism, ensuring that persons with serious mental illness being released from incarceration have access to healthcare may also increase access to anti-psychotic treatment, potentially providing further economic benefits. In light of the recent expansion of Medicaid under the Affordable Care Act (ACA), insurance coverage has been made available through subsidies to qualified individuals with schizophrenia that were previously uninsured. Recent analyses have estimated that the expansion of Medicaid will result in an increase of ∼2.3 million individuals receiving mental health services by 201920. Additionally, under the ACA, patients also benefit directly from expanded treatment programs, including coverage for substance abuse21. With a growing number of individuals receiving a proper schizophrenia diagnosis and improved access to care, the findings from our model become more important and applicable to the modern healthcare landscape; particularly given that patients with chronic mental illnesses such as schizophrenia tend to lack adequate health insurance coverage. Immediate resumption of Medicaid coverage upon release from incarceration has been shown to have a positive impact on criminal justice outcomes among the population modeled in this study. A recent analysis among patients with schizophrenia in South Carolina demonstrated that delays in Medicaid eligibility after release from incarceration was significantly associated with recidivism during a 3-year period22. Enrollment in Medicaid was also associated with reductions in re-incarceration for individuals with schizophrenia in the 2007 study by Morrissey et al.19. This decreased rate of recidivism due to increased insurance eligibility may in turn help to decrease criminal justice costs from the state government perspective.

Limitations

This Markov model analysis is subject to various limitations. For instance, the inputs for this model draw upon publicly-available data from the state of Florida; therefore, model results may not be generalizable to other states. Specifically, the available trial and incarceration data for felony arrests (20.3% trial, 21.6% incarceration) were low compared to national averages14. Furthermore, in order to estimate outcomes over a 3-year time horizon, many model inputs from the published literature required extrapolation or assumptions beyond year one.

Due to limited recent criminal justice cost data among individuals with mental illness, cost estimates required multiple data sources for estimation, including published literature and retrospective database analyses. Additionally, only the direct costs of infraction, arrest, trial, and incarceration were included in criminal justice cost estimates. Indirect costs, such as the lost productivity of individuals with schizophrenia or caregiver burden, were not included in this analysis. Furthermore, the cost of anti-psychotic drugs was not included in this model given that the focus of the analysis was to estimate the cost of psychiatric relapse and recidivism among this patient population. The analysis was not designed to be a formal economic evaluation of any particular treatment, but rather an evaluation of what downstream benefits may be associated with improved therapy management. Consequently, the cost of anti-psychotic treatment was not included in this analysis. However, this core model can readily be extended to examine both costs and benefits of drug interventions.

Conclusions

The economic impact of psychiatric relapse and recidivism among individuals with schizophrenia recently released from incarceration is substantial from the state government perspective. Policy initiatives that help patients transition after release from incarceration to community (such as efforts to provide appropriate treatment, improve access to psychiatric care and services and aid compliance to antipsychotic therapy) may provide economic benefits in the form of reduced medical and criminal justice system costs.

Transparency

Declaration of funding and financial relationships

This study was sponsored by Janssen Scientific Affairs, LLC.

Declaration of financial relationships

EM & CB are employees of the study sponsor (Janssen Scientific Affairs, LLC, Titusville, NJ).

JME Peer Reviewers on this manuscript have no relevant financial relationships to disclose.