“Predictors of Pretrial Jail Diversion in Houston Texas”
Gul Nowshad, Luisa Franzini, Scott Hickey
Division of Management, Policy & Community Health, School of Public Health Houston
Adjusted Odds Ratios for Jail Diversion
Introduction
Study site:
Methodology
Variable
Each year, more than 10 million people enter
US jails and this population is increasing each
year. The prevalence of serious mental illness in
the jail population is 7%. Over the last two
decades, Texas has experienced an eightfold
increase in the number of prisoners. More than
20% of Harris County (Texas) residents who are
in the county jails have a history of severe
mental illness. As a remedy for the problem the
federal government funds mental health
programs for this vulnerable population called
“Diversion Programs”.
Four Harris County jails in Houston with well-established
Mental Health and Mental Retardation Authority of Harris
County (MHMRA) services for inmates called Harris County
Jail-based programs (HCJBP). Similarly there are four facilities
in the community where mental health services are available to
MIOs who are referred called Harris County Jail Diversion
Programs (HCJDP).
We compared the characteristics of inmates in the Harris
County Jail Diversion Plan (HCJDP) with those in the
Harris County Jail-based program (HCJBP). MHMRA is
responsible for provision of mental health services for
both of these programs. The study cohort includes 3,414
individuals with at least one booking found in the Harris
County Justice Information System (JIMS) database.
These individuals accumulated 22,090 bookings over the
36-month period between January 2004 and December
2006, for an average of 6.5 bookings per person. The
individuals and their booking history were obtained by
matching all consumers served by MHMRA between
September 1999 and December 2006 with JIMS booking
records between January 2004 and December 2006. The
consumers were residents of Harris County, 18 years and
older MIO, who had been treated by MHMRA.
.
Age
< 25 years
25- 34 years
35- 44 years
> 45 years
Gender
Male
Female
Employment
Competitive job
Others
Not in labor force
Unemployed but seeking
jobs
Unknown
Homelessness
No
Yes
Primary Axis I Diagnosis
Schizophrenic Disorder
Major Depressive Disorder
Bipolar Disorder
Other Primary Diagnosis
Substance Abuse Disorder
Deferred
Offenses
Misdemeanor
State Jail Felony
Felony
Conceptual Model for Determinants of Pre-trial Diversion
(Donabedian/Kane)
Structure
Objectives
To study and compare the characteristics
of mentally ill offenders (MIO) treated in
jail to those diverted into community
facilities, in terms of socio-demographics,
types of mental illnesses and nature of
offenses.
Process
Outcome
Inmate’s factors
a. Sociodemographic
b. Clinical.
c. Criminal
Information
a. About inmate
b. Availability of
services in
community
Setting factors
a. Mental health
court
b. Traditional courts
Results
Judicial staff factors
a. Professional training
b. Attitude/Behavior
Outcome
Decision
Court decision
regarding
diversion
Diversion to the
community
65% of the offenders were diverted, 34% were females,
46% African American. Age, gender, employment,
homelessness, clinical history and nature of offense
were associated with diversion. Younger and homeless
inmates are more likely to be diverted (P < 0.000).
Similarly female offenders were 20% more likely to get
jail diversion than their male counterpart. MIOs with
employment “ unknown” were 53% less likely to be
diverted. Compared to schizophrenic offenders those
with a deferred diagnosis were 63% less likely to be
diverted. Felons were 51% less likely to be sent to the
community compared to those charged with
misdemeanors (P < 0.000).
Adjusted Odds ratio
(95%CI)
P-value
1.0 (reference)
0.63
0.58
0.52
(0.000)
(0.000)
(0.000)
1.0 (reference)
1.20
(0.001)
1.0 (reference)
0.47
0.75
0.81
0.49
(0.031)
(0.087)
(0.202)
(0.002)
1.0 (reference)
1.50
0.000)
1.0 (reference)
1.20
0.91
1.06
0.95
0.37
(0.230)
(0.436)
(0.632)
(0.790)
(0.005)
1.0 (reference)
0.92
0.487
(0.37)
(0.00)
Conclusion
These findings will enable mental
health care researchers, judicial
personnel, and policy makers to
understand the factors responsible and
the role they play in the complex
mechanism of jail diversion for this
vulnerable population