Skip to main content

A Simulation Modeling Approach for Planning and Costing Jail Diversion Programs for Persons with Mental Illness

  • Chapter
  • First Online:
Simulation Strategies to Reduce Recidivism
  • 1684 Accesses

Abstract

In jail diversion programs, individuals with serious mental illness (and often co-occurring substance use disorders) are diverted away from jails toward community-based treatment and support services instead. Such programs are one of the primary strategies recommended by the Subcommittee on Criminal Justice of the President’s New Freedom Commission on Mental Health (http://www.bipolarworld.net/pdf/CJ_ADACompliant.pdf). This chapter provides details on a simulation model for projecting the costs and benefits of these more comprehensive and evidence-based services. Two key findings from the simulations produced a net savings for the county: First, people charged with the most serious misdemeanors and low-level felonies must be included for diversion, or there will be no cost savings, as too few jails days are avoided. The simulations also suggest that the most significant cost savings are associated with post-booking jail diversion programs that serve individuals who have more severe clinical diagnoses and more serious criminal charges and who spend more time in the diversion program. Second, the cost burden shifts from the criminal justice system to the community-based service system, which is already strained for resources. However, the cost of community treatment can be shared with the federal government for those divertees enrolled in Medicaid. The Mental Health/Jail Diversion Simulation Model addresses an important public policy consideration: specifically, whether and to what extent jail diversion achieves current and future public-level cost savings. Results of the simulations provide stakeholders responsible for designing jail diversion programs with insight into how eligibility criteria affect the pool of individuals who can be intercepted, as well as the overall fiscal impact of the interception itself.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Consumer refers to person in need of or currently receiving services. This is often referred to as client in other systems, but consumer is used more often and used throughout the chapter.

References

  • Abram, K. M., & Teplin, L. A. (1991). Co-occurring disorders among mentally ill jail detainees. Implications for public policy. American Psychologist, 46, 1036–1045.

    Article  Google Scholar 

  • Abram, K. M., Teplin, L. A., & McClelland, G. M. (2003). Comorbidity of severe psychiatric disorders and substance use disorders among women in jail. The American Journal of Psychiatry, 160, 1007–1010.

    Article  Google Scholar 

  • Bala, M. V., & Mauskopf, J. A. (2006). Optimal assignment of treatments to health states using a markov decision model: An introduction to basic concepts. PharmacoEconomics 24 (4):345–354.

    Article  Google Scholar 

  • Berk, R. A., Bond, J., Lu, R., Turco, R., & Weiss, R. E. (2000). Computer simulations as experiments: Using program evaluation tools to assess the validity of interventions in virtual worlds. In L. Bickman (Ed.), Research design: Donald Campbell’s legacy (pp. 195–214). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Case, B., Steadman, H. J., Dupuis, S. A., & Morris, L. S. (2009). Who succeeds in jail diversion programs for persons with mental illness? A multi-site study. Behavioral Sciences & the Law, 27, 661–674.

    Article  Google Scholar 

  • Clark, R. E., Ricketts, S. K., & McHugo, G. J. (1999). Legal system involvement and costs for persons in treatment for severe mental illness and substance use disorders. Psychiatric Services, 50, 641–647.

    Google Scholar 

  • CMHS National GAINS Center. (2007). Practical advice on jail diversion: Ten years of learnings on jail diversion from the CMHS National GAINS Center. New York: Delmar.

    Google Scholar 

  • Cosden, M., Ellens, J., Schnell, J., & Yamini-Diouf, Y. (2005). Efficacy of a mental health treatment court with Assertive Community Treatment. Behavioral Science and the Law, 23, 199–214.

    Article  Google Scholar 

  • Cowell, A. J., Broner, N., & Dupont, R. (2004). The cost-effectiveness of criminal justice diversion programs for people with serious mental illness co-occurring with substance abuse. Journal of Contemporary Criminal Justice, 20, 292–314.

    Article  Google Scholar 

  • Frank, R. G., & Glied, S. (2006). Better but not well: mental health policy in the United States since 1950. Baltimore: Johns Hopkins University Press.

    Google Scholar 

  • Hargreaves, W. A. (1986). Theory of psychiatric treatment systems. An approach. Archives of General Psychiatry, 43(7), 701–705.

    Article  Google Scholar 

  • Heeg, B. M. S., Damen, J., Buskens, E., Caleo, S., De Charro, F., & Van Hout, B. A. (2008). Modelling approaches: The case of schizophrenia. PharmacoEconomics, 26(8), 633–648.

    Article  Google Scholar 

  • Herinckx, H. A., Swart, S. C., Ama, S. M., Dolezal, C. D., & King, S. (2005). Rearrest and linkage to mental health services among clients of the Clark County Mental Health Court Program. Psychiatric Services, 56, 853–857.

    Article  Google Scholar 

  • Hiday, V. A., & Ray, B. (2010). Arrests two years after exiting a well-established mental health court. Psychiatric Services, 61, 463–468.

    Article  Google Scholar 

  • James, G. M., Sugar, C. A., Desai, R., & Rosenheck, R. A. (2006). A comparison of outcomes among patients with schizophrenia in two mental health systems: A health state approach. Schizophrenia Research, 86(1), 309–320.

    Article  Google Scholar 

  • Korte, A. O. (1990). A first order Markov model for use in the human services. Computers in Human Services, 6(4), 299–312.

    Google Scholar 

  • Leff, H. S., Dada, M., & Graves, S. C. (1986). An LP planning model for a mental health community support system. Management Science, 32, 139–155.

    Article  Google Scholar 

  • Leff, H. S., Graves, S., Natkins, J., & Bryan, J. (1985). A system for allocating mental health resources. Administration in Mental Health, 12, 43–68.

    Article  Google Scholar 

  • Leff, H. S., Hughes, D. R., Chow, C. M., Noyes, S., & Ostrow, L. (2010). A mental health allocation and planning simulation model: A mental health planner’s perspective. In Y. Yih (Ed.), Handbook of healthcare delivery systems. Boca Raton, FL: Taylor & Francis.

    Google Scholar 

  • Miller, L., Brown, T., Pilon, D., Scheffler, R., & Davis, M. (2009). Measuring recovery from severe mental illness: a pilot study estimating the outcomes possible from California’s 2004 Mental Health Services Act.

    Google Scholar 

  • Naples, M., & Steadman, H. J. (2003). Can persons with co-occurring disorders and violent charges be successfully diverted? International Journal of Forensic Mental Health, 2(2), 137–143.

    Article  Google Scholar 

  • Naples, M., Morris, L. S., & Steadman, H. J. (2007). Factors in disproportionate representation among persons recommended by programs and accepted by courts for jail diversion. Psychiatric Services, 58, 1095–1101.

    Article  Google Scholar 

  • New Freedom Commission on Mental Health, Subcommittee on Criminal Justice. (2004). Background paper. Rockville, MD: Author. Retrieved from http://www.bipolarworld.net/pdf/CJ_ADACompliant.pdf

  • New Freedom Commission on Mental Health. (2003). Achieving the promise: Transforming mental health care in America—Final report. Rockville, MD: US Dept of Health and Human Services. DHHS Pub. No. SMA-03-3832.

    Google Scholar 

  • Norton, E. C., Yoon, J., Domino, M. E., & Morrissey, J. P. (2006). Transitions between the public mental health system and jail for persons with severe mental illness: A Markov analysis. Health Economics, 15(7), 719–733.

    Article  Google Scholar 

  • Patient Protection and Affordable Care Act, Pub. L. No. 111–148.

    Google Scholar 

  • Patten, S. B. (2005). Modelling major depression epidemiology and assessing the impact of antidepressants on population health. International Review of Psychiatry, 17(3), 205–211.

    Article  Google Scholar 

  • Pennsylvania General Assembly, Legislative Budget and Finance Committee. (2007). Lessons learned from three mental health diversion and post-release programs. Harrisburg, PA: Author.

    Google Scholar 

  • Perry, J. C., Lavori, P. W., & Hoke, L. (1987). A Markov model for predicting levels of psychiatric service use in borderline and antisocial personality disorders and bipolar type II affective disorder. Journal of Psychiatric Research, 21(3), 215–232.

    Article  Google Scholar 

  • Pierskalla, W. P., & Brailer, D. J. (1994). Applications of operations research in health care delivery. In S. M. Pollock, M. H. Rothkopf, & A. Barnett (Eds.), Operations research and the public sector (pp. 469–498). New York: North-Holland.

    Chapter  Google Scholar 

  • Ridgely, M. S., Engberg, J., Greenberg, M. D., Turner, S., DeMartini, C., & Dembosky, J. W. (2007). Justice, treatment, and cost: An evaluation of the fiscal impact of Allegheny County mental health court. Santa Monica, CA: RAND Infrastructure, Safety, and Environment.

    Google Scholar 

  • Shumway, M., Chouljian, T. L., et al. (1994). Patterns of substance use in schizophrenia: A Markov modeling approach. Journal of Psychiatric Research, 28(3), 277–287.

    Article  Google Scholar 

  • Solnit, A. (2004). The costs and effectiveness of jail diversion: A report to the joint standing committee of the General Assembly. Hartford, CT: Department of Mental Health and Addiction Services.

    Google Scholar 

  • Steadman, H. J., & Naples, M. (2005). Assessing the effectiveness of jail diversion programs for persons with serious mental illness and co-occurring substance use disorders. Behavioral Sciences & the Law, 23, 163–170.

    Article  Google Scholar 

  • Steadman, H. J., Osher, F., Robbins, P. C., Case, B., & Samuels, S. (2009). Prevalence of serious mental illness among jail inmates. Psychiatric Services, 60, 761–765.

    Article  Google Scholar 

  • Sweillam, A., & Tardiff, K. (1978). Prediction of psychiatric inpatient utilization: A Markov chain model. Administration in Mental Health, 6(2), 161–173.

    Article  Google Scholar 

  • U.S. Department of Health and Human Services. (1999). Mental Health: A Report of the Surgeon General. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institute of Health, National Institute of Mental Health.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David Hughes Ph.d. .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this chapter

Cite this chapter

Hughes, D. (2013). A Simulation Modeling Approach for Planning and Costing Jail Diversion Programs for Persons with Mental Illness. In: Taxman, F., Pattavina, A. (eds) Simulation Strategies to Reduce Recidivism. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6188-3_9

Download citation

Publish with us

Policies and ethics