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Law Enforcement Response to "Frequent Fliers": An Examination of High-Frequency Contacts Between Police and Justice-Involved Persons With Mental Illness

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This article examines a subset of justice-involved persons with mental illness who have repeated contacts with law enforcement officers. Previous work has alluded to this sub-population—often termed “frequent fliers”—but little research has empirically examined its size and nature. This study proposes a method of identifying frequent fliers that is based on the amount of time elapsed between multiple mental-health-related contacts with police. Using more or less stringent thresholds, the analysis defines several groups of frequent fliers, including rapid cyclers, those having very frequent contacts with police. In considering policy responses to the problem of justice-involved persons with mental illness, addressing the needs of the frequent flier population proves to be a way of targeting limited resources for the most impact.
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Running Head: POLICE CONTACTS WITH FREQUENT FLIERS
Law Enforcement Response to “Frequent Fliers”: An Examination of High-Frequency Contacts
between Police and Justice-Involved Persons with Mental Illness
Scott Akins, Oregon State University
Brett C. Burkhardt, Oregon State University
Charles Lanfear, University of Washington
Acknowledgements: Chief Jon Sassaman (Corvallis Police Department), Sheriff Scott Jackson
(Benton County Sheriff’s Office), and Chief Ken Elwer (Philomath Police Department) provided
helpful insights into the local law enforcement context. Chief Sassaman and Jennifer Hendricks
(Corvallis Police Department) assisted in acquiring the data used in the analyses. Mariana
Amorim and Katelyn Stevens made valuable contributions to the larger project of which this
article is a part.
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Law Enforcement Response to “Frequent Fliers”: An Examination of High-Frequency Contacts
between Police and Justice-Involved Persons with Mental Illness
Prepared for submission to Criminal Justice Policy Review (special issue on "Justice-Involved
Offenders with Mental Health and/or Substance Abuse Problems")
Word count (omitting notes, refs): 6217
Abstract: This article examines a subset of justice-involved persons with mental illness who
have repeated contacts with law enforcement officers. Previous work has alluded to this sub-
population—often termed “frequent fliers”—but little research has empirically examined its size
and nature. This study proposes a method of identifying frequent fliers that is based on the
amount of time elapsed between multiple mental health-related contacts with police. Using more
or less stringent thresholds, the analysis defines several groups of frequent fliers, including rapid
cyclers, those with very frequent contacts with police. In considering policy responses to the
problem of justice-involved persons with mental illness, addressing the needs of the frequent
flier population proves to be a way of targeting limited resources for the most impact.
3
The disproportionate rate of arrest and incarceration of people with mental illnesses
(PwMI) is an issue of growing concern of police, policymakers, and academic researchers
throughout the United States (Reuland, Schwarzefeld, & Draper, 2009; Teller, Munetz, Gil &
Ritter, 2006).
1
While those with mental illnesses that severely compromise unassisted living
constitute at most 5 percent of the general population, they are disproportionately represented at
multiple levels of the justice system. The prevalence of mental health-related police contacts has
been found to vary significantly by locale; several studies have found PwMI to be involved in
between 7 and 10 percent of all police contacts (e.g. Borum, Swanson, Swartz, & Hiday, 1997)
though others have found the proportion of such contacts to be significantly lower (Engel &
Silver, 2001) or higher (White, Goldkamp & Campbell, 2006). Additionally, PwMI represent at
least 16 percent of the U.S. prison and jail population (Torrey, Kennard, Eslinger, Lamb &
Pavle, 2010). The overrepresentation of this population at various levels of the justice system
has been attributed to several factors, including deinstitutionalization (Lamb, 1998; Slovenko,
2012), cutbacks in federal mental health funding (Teplin, 2000) and enforcement consequences
of the war on drugs (Honberg & Gruttadaro, 2005; Lurigio, 2011). While there is some
disagreement over the relative importance of the causes, observers agree that the failure to
coordinate the services of local mental health, substance use, and criminal justice agencies is an
important factor exacerbating the ongoing problem of justice-involved PwMI (Honberg &
Gruttadaro, 2005; Lurigio, 2011; Reuland et al., 2009).
Research informing contacts between law enforcement and PwMI is important for a
number of reasons. From the perspective of police, such contacts are often frustrating, time-
1
The term people with mental illnesses is used to refer to people who are perceived by law enforcement agents as displaying
symptoms of mental illness.
4
consuming and, on occasion, may escalate into volatile and potentially violent situations, placing
all parties at risk (Reuland et al., 2009). Law enforcement officials have long been called on as
first responders to situations in which people are having crises related to mental illness (Bittner,
1967), but the prevalence of such contacts appears to be increasing (Santos & Goode, 2014;
Teplin & Pruett, 1992) and the nature of these interactions are distinct from those more
commonly handled by police (Hoover, 2007). Although the police are charged with the
responsibility to protect the safety and welfare of the public by removing dangerous persons
from the community, they are also charged with providing protection for vulnerable citizens,
including those with mental illness or those in a state of mental crisis (Teplin & Pruett, 1992).
When responding to mental crisis calls police typically have three options: they may execute a
formal arrest, they may detain the person and transport him or her to a mental health facility or
they can resolve the situation informally. Determining which response is most appropriate often
places police in the role of a “street-corner psychiatrist” (Teplin, 1984), something police often
report feeling ill-prepared to do (Franz & Borum, 2011). From the perspective of those
accessing mental health services and their loved ones, the limited options available to individuals
needing help can place PwMI at heightened risk of justice system involvement and, most
tragically, situations in which people are injured or killed when due to illness they fail to comply
with police commands and/or present a perceived threat to officer safety (Police Executive
Research Forum, 2012; Santos and Goode, 2014). Across parties there appears to be agreement
that the “traditional police response” to persons in mental crisis neither improves the mental state
of the person being contacted nor facilitates the safe and controlled resolution of the call for
service (Reuland, Draper & Norton, 2010).
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Frequent Fliers
The focus of the present study is on a subset of justice-involved PwMI: those that have
repetitive and frequent (sometimes very frequent) contacts with police due to their mental illness.
Commonly referred to as frequent fliers
2
in law enforcement circles (Santos & Goode, 2014),
these individuals often cycle between jail, halfway houses, hospital emergency rooms, to the
streets and back again. Frequent fliers are thought to be a relatively small subset of the broader
justice-involved PwMI population (Reuland et al., 2009). They may be disproportionately likely
to be homeless (Green, 1997) and dual diagnosis mental health and substance use disorder
(White et al., 2006) as compared to other persons contacted by police for mental health reasons.
Although anecdotally reported as a population of particular concern (Santos and Goode,
2014; Szabo, 2014), few studies have empirically analyzed the size and nature of the frequent
flier population. Green (1997) documented that a majority (63.5%) of police contacts with
PwMI in Honolulu were with individuals “known on sight” by police, likely indicating some
level of repetitive contact. Similarly, the Los Angeles Police Department identified 67 PwMI
involved in a total of 536 calls for service for in an eight-month span in 2004 (in Reuland et al.,
2008). The Houston Police Department (2010) identified 30 PwMI that generated 194 offense
reports and 165 Emergency Detention Orders in a span of six months. The most rigorous
2
The term “frequent flier” is used in public accounts (Santos and Goode, 2014) and anecdotally by police to refer to
PwMI who have frequent contacts with law enforcement. Additionally, the term “frequent fliers” has been used in
academic research (and anecdotally) to refer to habitual offenders and/or those that commonly cycle through
correctional institutions, regardless of mental health status (Ford, 2005; Johnson & Williams, 2012). Following
convention, and for purposes of clear communication, we refer to “frequent fliers” in referencing individuals who
have repeated contact with law enforcement due to a real or perceived mental illness. We use the phrase to simplify
a complex concept, not to trivialize persons suffering from mental illnesses or their heightened likelihood of coming
to the attention of law enforcement. This population has also been referred to as “chronic consumers” by some
(Houston Police Department, 2010).
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analysis of frequent fliers comes from White, Goldkamp, and Campbell (2006), who randomly
sampled individuals taken into police custody for either an arrest, a protective custody hold
(commonly intoxication), or a mental health hold in Santa Fe, New Mexico. They found that
those individuals with multiple prior holds, and those with mental health and substance abuse
problems, were significantly more likely to experience an arrest or involuntary hold in the future
(White et al., 2006).
3
Although the available information on the topic is primarily anecdotal, there is evidence
to suggest that the frequent flier population is comparatively small but generates a high,
sometimes very high, frequency of contacts (e.g., Houston Police Department, 2010). Because
all police contacts with PwMI take significantly longer to resolve, and often require more
specialized training than “traditional” police contacts (Reuland et al. 2009), the frequent flier
population may generate substantial cost in terms of officer hours invested and expenses related
to incarceration (White et al. 2006). Further, these individuals appear to heavily access other
social service agencies including emergency departments. As one example, over a recent six
year span in Austin, Texas, nine patients made 2,678 visits to Austin emergency departments at a
cost of more than 3 million dollars. Eight of the nine patients were substance abusers, seven of
the nine were mentally ill and three were homeless (Associated Press, 2009). In sum, the
frequent flier population appears to be relatively small but very “high cost” making policy
recommendations needed and feasible.
3
An additional study by Biebel and Corner (2003) noted the geographic concentration of calls for service in
response to a situation with a PwMI. Of the 507 such calls in Lexington, Kentucky, in a one-year span, twenty
percent were attributed to just 17 locations, and each of these locations received a minimum of three visits from law
enforcement. Because institutional residences (i.e., hospitals, shelters, group homes) were included in these 17
locations, it is unclear to what extent repeat visits were caused by the same or multiple individuals.
7
The contribution of the present study is to propose a method of identifying frequent fliers
by calculating the amount of time elapsed between a PwMI's multiple contacts with police.
Using more or less stringent thresholds, the analysis defines several groups of frequent fliers,
including rapid cyclers, those with very frequent contacts with police. Once frequent fliers are
identified, descriptive analyses will document the size of the frequent flier population and its
contact with police in one county in Oregon.
Method
Research Location: Benton County, Oregon
Benton County is in the central Willamette Valley region of western Oregon. The county has
approximately 86,000 residents, the majority of which live in the county seat, Corvallis, which is
the location of Oregon State University. In 2012, heads of local law enforcement in Benton
County, Oregon, requested a meeting with researchers at Oregon State University to discuss a
collaborative investigation of the amount of contact between local law enforcement and suspects
displaying symptoms of mental illness, prompting the work described in this study.
As in other places, police in Benton County have limited options when dealing with
PwMI. They may resolve the matter informally, arrest the person if they have committed a
crime, or perform a Peace Office Custody (POC), which is a type of arrest that occurs because an
individual is believed to be a danger to self or others due to mental illness. According to ORS
426.228, the officer completing a POC is directed to take the individual detained to the nearest
hospital or nonhospital facility approved by the Oregon Health Authority.
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Benton County generally and Corvallis in particular have a number of traits that likely
contribute to a larger than would be expected population of PwMI, particularly those that are
dual diagnosis and homeless. Corvallis is home to a major regional medical center with an
inpatient mental treatment facility. PwMI from a wide geographic area in Oregon are brought to
this facility under the POC process described above.
4
Based on interviews with local officers
and mental health officials, upon release from the inpatient medical center, many individuals
choose to remain in the area, particularly those that have few or no ties in their place of origin
(see XXX - insert full report citation following review). Additionally the city provides a
relatively large range of services and housing for homeless persons that may increase the
mentally ill population (XXX).
Data
The analysis below relies on two distinct sets of data: arrests and incidents resolved
informally by police. The arrest data comprise all arrests (including charge information) made by
the Corvallis Police Department (CPD) or the Benton County Sheriff's Office (BCSO) in the six
years between January 1st, 2007 and December 31st, 2012.
5
Both suspects and arresting officers
were identified with random numbers to preserve anonymity. The arrest data capture 13,650
unique suspects with 22,875 arrests and 33,064 charges.
6
The analysis below examines a
subsample of arrests that involve a suspect perceived to have a mental illness. These individuals
were identified in the data on the basis of having a Peace Officer Custody (POC) charge in an
4
This is particularly the case since a state-run mental hospital in Salem, a neighboring city, was recently closed. As
of this writing facilities designed to accommodate some of those displaced by this closure remain under
construction.
5
This omits arrests performed by the Philomath Police Department (PPD) or Oregon State Police (OSP),
particularly on the Oregon State University campus where OSP have sole jurisdiction.
6
In the original dataset of 34,629 charges, 182 (0.5%) charges had an invalid suspect ID and 1,383 (4.0%) had data
entry errors. These were removed from the analytic sample.
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arrest (described above). Within the arrest data, there were 914 POC charges applied to 697
individuals. This data set allows examination of POCs charging in aggregate, as well as
characteristics of individuals charged with a POC.
POC charging may be subject to net-widening, in which officers begin to use their POC
authorities in cases that previously would have produced no police action. As such, it is
important to know about incidents involving persons with mental illness that do not result in a
POC. As a complement to the POC dataset, a second dataset contains all contacts that did not
result in an arrest or case number (i.e., it omits POCs). Despite not yielding an arrest, all informal
contacts made by BCSO or CPD are recorded in a database, which contains a wealth of
information from the responding officer and (where applicable) a 911 dispatcher. Informally
resolved contacts involving a person suspected of having a mental illness were identified if they
met one of two criteria. First, responding officers included the word "mental" or the associated
code, "12-60", in a free-text field of an incident report. Here, the "mental" designation is based
on officers' subjective, non-clinical assessment of the situation. Second, a 911 dispatcher
flagged the field "mental" in the computer-aided dispatch system. Dispatchers for these agencies
are trained to record information from the caller, and thus the designation of a case as "mental"
originates with subjective interpretation of the situation by the caller. Using these criteria, the
informal resolution data contain 1,388 informally resolved encounters with PwMI in the six year
span. The informal resolution data therefore complement the POC data. Combined, the two sets
of data should capture all known contactsboth formal and informalin which the officer
and/or dispatcher records a mental health issue.
Results
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Figure 1 depicts yearly counts of POCs, informal resolutions, and the ratio of POC to
non-POC arrests. Informally resolved contacts with persons with mental illness were stable from
2007 to 2010, hovering around 200 per year. In 2011, informal resolutions abruptly rose to over
300, a roughly 50% increase. Informal resolutions declined slightly in 2012, but remained above
the historical average. Formally resolved POC arrests were also stable throughout much of the
series, but they show a later rise. Unlike informal resolutions, POCs increased dramatically in
2012, going from 144 to 245. The ratio of POC arrests to all other (non-POC) arrests rules out
the possibility that the rise in POC arrests was an artifact created by a rising overall arrest rate.
The rising ratio from 2011 to 2012 indicates that POC arrests were increasing faster than non-
POC arrests.
The increase in both POCs and informal resolutions translates to an increase in the
amount of time police spent on such interactions. The POC and informal resolution data contain
start and end times for each interaction, and these were used to calculate the duration of each
event. These durations were then aggregated to produce yearly sums of hours spent responding
0
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Ratio of POCs to Other Arrests
POC Arrests and Informal Resolutions
Year
Figure 1. Types of Police Contacts by Year
POC Arrests Informal Resolutions POC / Arrest Ratio
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to these incidents (Figure 2).
7
Hours spent responding closely track the number of POCs and
informal resolutions seen in Figure 1. Durations for both forms of response were relatively stable
until 2011, when time spent on informal resolutions suddenly increased, followed by time spent
on POCs the following year. For the year 2012, the two major police agencies in Benton County
spent nearly 500 hours responding to calls for service involving suspects perceived to have
mental illness, twice the level from 2007.
8
As noted above, frequent fliers are thought to be a relatively small subset of the broader
justice-involved PwMI population that prompts a high frequency of contacts with law
enforcement personnel. Analysis of the current data indicates that over the six years examined,
7
Due to data limitations, durations could only be established for 197 POCs. For missing cases, yearly mean POC
durations were imputed. Informal resolution durations were reported completely, but may be underestimates due to
exclusion of informal encounters that were not flagged as “mental” by either dispatchers or responding officers.
8
The duration estimates assume a response by a single officer (the only measure available in our data) and as such
are conservative estimates of the total consumption of officer-hours.
2007 2008 2009 2010 2011 2012
Informal Hours 89.5 113.0 147.7 127.7 249.9 184.0
POC Hours 159.2 174.1 171.6 159.6 178.1 305.0
0.0
100.0
200.0
300.0
400.0
500.0
600.0
Figure 2. Estimated Total Duration of POCs and Informal Resolutions
by Year
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697 individuals received at least one POC. Of these, 117 individuals received multiple POCs.
9
These 117 individuals resulted in 334 POC arrests for an average of 2.85 POCs per person over
six years.
Previous work has not explicitly defined frequent fliers beyond saying that they are
justice-involved PwMI that have repeat contacts with law enforcement. Using data on the timing
of POC arrests, it is possible to precisely define the frequent flier population. For each individual
with multiple POC arrests in the data, an inter-POC span is calculated as the difference between
the current POC date and the prior POC date, if one exists in the data. The distribution of these
spans is depicted in Figure 3. It reveals that many POC spans are very short. Nearly half (47.9%,
or 104) of all repeat POC arrests occured within 60 days of the initial POC arrest. In fact, over a
quarter (25.8%, or 56) of repeat POC arrests occurred within just 14 days of the initial POC
arrest.
Figure 3: Time Elapsed since Previous POC Arrest
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This is necessarily a conservative count, as it does not capture individuals with additional POCs prior to 2007 or
after 2012.
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The spans between POCs can be used as bandwidths for identifying frequent flyers. The
analyses below utilize three bandwidths of POC spans to identify frequent flyers: (1) 365 days;
(2) 60 days; and (3) 14 days. If an individual has two POC arrests within the given bandwidth, he
is classified as a frequent flyer for the entire six year period covered by the data. For example, an
individual with one POC in 2008 and another 364 days later in 2009 would be counted as a 365-
day frequent flyer for the entire 2007-2012 period. Similarly, an individual with two POCs
within a 14 day span in 2007 would be counted as a 14-day frequent flyer for the entire period.
(This person would also qualify as a 60-day frequent flyer and a 365-day frequent flyer.) Shorter
bandwidths offer a stringent definition of frequent fliers and will only capture rapid cyclers,
those who experience multiple police contacts in rapid succession (here, 14 days). Expanding the
bandwidth allows less frequent cyclers to be considered frequent fliers. A longer bandwidth (e.g.,
010 20 30 40 50
Percent
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Days
Note: Initial POCs in the data are omitted due to inability to calculate time since last POC
14
365 days) thus will result in a larger estimated size of the population, as it includes individuals
with infrequent but recurring contacts with police.
For each bandwidth considered here, Table 1 depicts the number of frequent flyers,
number of POC arrests from frequent flyers, and the mean number of POCs in the data for
frequent flyers and non-frequent flyers. Narrowing the bandwidth that determines frequent flier
status reduces the count of frequent fliers and POCs but simultaneously increases the rate of
POC arrests. For example, while 365-day frequent fliers averaged 3.06 POC arrests in the data,
14-day frequent fliers averaged 3.68. Frequent fliers (of all bandwidths) have a disproportionate
effect on the total number of POC arrests. The 365-day frequent fliers represent 13.3 percent of
all POC'ed individuals but 31.2 percent of all POC arrests that occurred in the six year period
under study. Similarly, the 14-day frequent fliers represent 5.5 percent of all POC'ed individuals
but 15.3 percent of all POC arrests.
Individuals
Arrests
POC Span
Bandwidth
FFs
% FFsa
FF POCs
% from
FFsb
FF Mean
POCs
Non-FF
Mean
POCs
365 days
93
13.34%
285
31.18%
3.06
1.04
60 days
65
9.33%
216
23.63%
3.32
1.15
14 days
38
5.45%
140
15.32%
3.68
1.17
a: Percentage of all individuals with a POC who are frequent fliers.
b: Percentage of all POC arrests contributed by frequent fliers.
The outsized contribution of frequent fliers to POC counts can be seen over time in
Figure 4, which graphs the annual number of POC individuals and arrests by frequent flier status
using various bandwidths. For all bandwidths, the numbers of POC arrests and POC individuals
track each other closely among non-frequent fliers. This is not surprising, since a non-frequent
15
flier will either have a single POC or, at most, multiple POCs spread over long time. Among
frequent fliers, however, there is a large and growing divergence between the number of POC
individuals and POC arrests. For each bandwidth, the number of frequent flier-related POC
arrests grew faster than the number of frequent flier individuals. Consider the 14-day bandwidth
in 2012: 19 frequent fliers accounted for 65 POC arrests. Looking at the 365-day bandwidth in
2012, 47 frequent fliers contributed 108 POC arrests, nearly as many as contributed by the 137
non-frequent fliers (137 POC arrests). Thus, while the populations of both frequent fliers and
non-frequent flier individuals have grown, the nature of frequent fliersrepeated POCs, often in
rapid successionmeans that they contribute disproportionately to the total number of POCs.
It is likely that the POC figures shown here understate the true impact of frequent fliers
on law enforcement, since they omit informal resolutions. The informal resolution data did not
contain information on the contacted citizen, and thus could not be used to identify (or match to)
frequent flyers. Two plausible assumptions can be made about the frequent flyers identified on
the basis of repeated POCs: (1) they also have informally resolved contacts with law
enforcement, and (2) such contacts are more frequent than individuals without repeated POCs. If
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2009
2010
2011
2012
2007
2008
2009
2010
2011
2012
2007
2008
2009
2010
2011
2012
14-day bandwidth 60-day bandwidth 365-day bandwidth
Figure 4: POC arrests of individuals, by FF status and bandwidth
POCs from non-FF POCs from FF Non-FF persons FF persons
16
these assumptions are correct, then frequent flyers engage more law enforcement resources than
what is suggested in the analyses here.
Discussion
Despite the significant attention being directed to mentally ill and dual diagnosis justice-
involved individuals, little explicit attention has been directed to so-called called “frequent
fliers,” those justice-involved PwMI that have repeat, often high frequency contacts with law
enforcement. This article proposed a simple method of identifying frequent fliers using varying
time bandwidths based on the difference between the current and prior police contact (if one
existed). Using this method of defining frequent fliers, the article proceeded to document the
disproportionate contribution that frequent fliers made to the aggregate amount of contact
between law enforcement and PwMIs over a six year span in Benton County, Oregon.
The analyses revealed that for many individuals the elapsed time between mental health-
related police contacts is very short. Nearly half of all repeat POC arrests (an indicator of police
contact with PwMI) occured within 60 days of the initial POC arrest and over a quarter of repeat
POC arrests occurred within just 14 days of the initial POC arrest. Results further showed that
the 93 individuals with multiple POCs in a year (365 day bandwidth) accounted for 285 POC.
Narrowing the bandwidth used to define frequent fliers, the 38 individuals with multiple POCs in
a two week period (14 day bandwidth) accounted for 140 POC arrests. As noted above, these
figures omit informal resolutions and therefore understate the true impact of frequent fliers on
law enforcement. This is consistent with existing research indicating that PwMI that are
regularly contacted by police are also significantly more likely to be handled with “no action”
17
(Green, 1997), as handling the situation in this way minimizes paperwork and unwanted “down
time” (Tepplin 1984, 2000). Thus, these results confirm that a small subset of justice-involved
PwMI disproportionately impact the justice system.
Research indicates that contacts between justice-involved PwMI and police are typically
prompted by non-criminal behaviors or minor misdemeanors (Borum et al., 1997) and limited
research on the frequent flier subset of this population suggests this behavior is primarily
motivated by chronic, co-occurring mental health and substance use disorders (Green, 1997;
Houston Police, 2010; White et al., 2006). Although, by default, law enforcement is typically
the primary initial responder to these individuals, failure to address the underlying conditions
that led to their interactions with law enforcement will waste limited justice system resources and
will likely exacerbate the mental health problems of the individual in the process (White et al.,
2006).
In the absence of a significant shift in policy addressing the non-institutionalized
mentally ill, significant numbers of individuals with mental health disorders and co-occurring
substance abuse will continue to be encountered by law enforcement (White et al., 2006).
Preventing PwMI from penetrating further into the criminal justice system is a major challenge,
but research suggests a number of steps that may help accomplish this. Most broadly, intensive
collaboration between law enforcement agencies and mental health agencies is a foundational
step in thoroughly addressing the rise in law enforcement contacts with PwMIs (e.g., Almquist &
Dodd, 2009; Council of State Governments, 2002; Deane et al., 1999). Inter-agency
collaboration is not so much a discrete policy intervention, but rather an overarching philosophy
that informs and facilitates various possible interventions. Specifics may vary substantially by
locale but this may involve regularly schedule meetings between agencies, mental health agents
18
providing trainings on crisis intervention, a shared case manager (or liaison) specializing in
justice-involved mental health cases, and formalized information sharing between mental health
and law enforcement on persons of high need.
Frequent fliers are likely to be citizens with high (and possibly unmet) needs. The
analytic methods for identifying frequent fliers could prove valuable for facilitating knowledge
exchange and cooperation between law enforcement and mental health agencies with shared
clients. Exchange of personal health information between agencies is complicated by federal
privacy regulations. Although the Health Insurance Portability and Accountability Act (HIPAA)
does place real restrictions on private health information sharing, it also offers allowances for
disclosure of such information to law enforcement in some instances (Petrila, 2007; Petrila &
Fader-Towe, 2010). Recently, Leon Rodriguez, Director of the Office for Civil Rights at the
Department of Health and Human Services, stated that the “Privacy Rule [in HIPAA] does not
prevent your ability to disclose necessary information about a patient to law enforcement, family
members of the patient, or other persons, when you believe the patient presents a serious danger
to himself or other people” (U.S. Department of Health and Human Services, 2013, p.1). By
using the frequent flier identification method described above to prioritize those in the
community with the highest need, law enforcement and mental health can collaboratively
determine what approaches are most promising for ensuring future mental health and minimizing
contact with police (e.g., Houston Police Department, 2010).
For persons suffering from mental illness that have been charged criminally, mental
health courts provided a specialized venue to address treatment. Mental health courts generally
have a specialized docket of cases involving PwMI. They feature a collaborative and non-
adversarial team, comprising a judge, prosecutor, defense attorneys, representatives from parole
19
and probation, and representatives from a mental health agency (Almquist & Dodd, 2009;
Sirotich, 2009). These parties can tailor a response plan to fit the needs of the defendant, which
may involve a referral to the local mental health and substance abuse resources and may include
compliance monitoring (Wolff, 2002).
Reviews of research on mental health courts provide reason for optimism. Although the
body of work on mental health courts is limited in terms of the number of studies and their
scope, some studies have found that participation in mental health courts reduces recidivism or
re-incarceration (see Almquist & Dodd, 2009; DeMatteo, LaDuke, Locklair, & Heilbrun, 2013;
Sarteschi, Vaughn, & Kim, 2011). There is also evidence that mental health courts have positive
mental health consequences for participants (see Almquist & Dodd, 2009; DeMatteo et al.,
2013), although the evidence here is not definitive (Sarteschi et al., 2011; Sirotich, 2009). And
while mental health courts may require new expenses (e.g., court staff, additional treatment
expenses), there is some evidence that these costs would be offset by savings to the traditional
criminal justice system, particularly in the form of reduced frequency of jail stays for those with
mental illness (Almquist & Dodd, 2009; Ridgely et al., 2007).
10
While this study presents a straightforward methodology for identifying PwMI with high
frequency contacts with law enforcement for intervention, there are notable limitations and
opportunities for future research. First, the analysis was conducted on a single county in Oregon.
Replication in other locales should be conducted to examine variation in the size and impact of
the frequent flier population in other areas. Identifying and quantifying the impact of the frequent
flier subpopulation among all arrestees can allow communities and law enforcement agencies to
10
One might also consider the extensive literature on other problem-solving courts, most notably drug courts, which
supports their efficacy both in terms of reduced recidivism (Mitchell, Wilson, Eggers, & MacKenzie, 2012) and
cost-savings (Downey & Roman, 2010).
20
develop effective mitigation strategies tailored to the local context, both in terms of resources
available and scale of the problem. Communities with very limited treatment resources, for
instance, would be best served by diverting the highest risk individuals with very narrow spans
between contacts with police. Large communities with more substantial resources may prefer to
use wider bandwidths to divert more individuals into community or residential treatment
programs. Second, as noted above, data limitations do not allow for a complete analysis of
repeated PwMI contacts that are resolved informally. The inability to calculate repeated informal
contacts means that the estimates above understate the true amount of contact between police and
PwMI. Third, the data analyzed here do not capture individuals' experience with other parts of
the criminal justice system. Notably, the data do not contain information on jail or prison spells.
Long spans between contacts with law enforcement may appear positive on paper (at least
compared to contacts in rapid succession). However, these long spells may simply be due to
incarceration, during which time a person cannot experience a police contact. Future work
should therefore be attentive not just to PwMI contacts with law enforcement but also contacts
with carceral agencies. Finally, the costs of responding to individuals with mental illnesses are
often hidden in overall law enforcement budgets, obscuring the severity of impacts of untreated
mental illnesses on communities. Future cost analyses of police contacts with these individuals,
derived from service call duration data or similar metrics, may allow law enforcement agencies
to better justify expansion of diversion programs or adjustment of police budgets to address these
issues.
Since frequent fliers, by definition, experience multiple contacts with law enforcement,
they are a critical sub-population in efforts to address the overall amount of police contacts with
PwMI. The method described above is a simple yet effective means for police agencies or
21
researchers to estimate the size of this population and to target interventions, perhaps in
collaboration with mental health service providers or agencies. As the worlds of mental illness
and criminal justice increasingly intersect, addressing the frequent flier population proves to be a
way of targeting limited resources for the most impact.
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... 28,29,45,46 While most people in crisis may only have a single encounter with police, an increasing number with mental illness and/or substance use disorder have repeat encounters. 3,46,47 Those who have repetitive and frequent contacts with police due to their mental illness are of growing concern to communities, police, policy-makers, and researchers globally. Commonly referred to as super utilizers (note 3) in law enforcement circles, 3,13,14,46-48 these individuals often cycle between hospital emergency rooms, jail, shelters, transition housing, regional correctional centres, to the streets and back again. ...
... 3,27,50 People with repeat encounters with police are a priority for various reasons. 10,47 The elevated risk of criminal victimization associated with mental illness increases the rate of police contacts with PwMI. 18,45 Increasingly, the police have assumed an expanded role of maintaining social order and responding to individuals experiencing mental health crises. ...
... 18,45 Increasingly, the police have assumed an expanded role of maintaining social order and responding to individuals experiencing mental health crises. 43,45,47 The police have also become the principal first responders to situations involving PwMI, which has earned them the title of "psychiatrists in blue." 4,6,8,13,14 The role of policing PwMI has been controversial for many years, and more recently, as a result of the Black Lives Matter movement, there is a notion that not only should this role not exist but that the presence of the police in the mental health system is proof positive that the system is "broken." ...
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A key theme of this article is the need to view the intersection of public safety and public health through a new lens to break down the traditional information silos of the many agencies that serve vulnerable populations and the impact of inadequate community-based mental health services that contribute to the increasing number of calls to police in responding to people in or approaching a mental health crisis. The manifestation of this crisis in the community is that the police are too often the first port in the storm. This article suggests the system is broken and needs fixing. Implementing a population health approach to identifying the high utilizers in the community and building a case for sustained funding, partnerships, resources, and accountability together with data sharing agreements, community partners and police collaboratively design and evaluate outcome approaches aimed at prevention and recovery to minimize contact with the police.
... Individuals with mental illness tend to cycle through the justice system rapidly (i.e., multiple arrests per year). Prior studies demonstrate repeat arrestees frequent hospital emergency rooms (Akins, Burkhardt, & Lanfear, 2016), are disproportionately homeless (Green, 1997;Harding & Roman, 2017;Tentner et al., 2019), and have co-occurring mental health and SUD diagnoses (White et al., 2006). For instance, nearly half of individuals arrested for a mental health protection hold were rearrested within 60 days, and nearly a quarter of those were rearrested within the first 14 days of release from incarceration (Akins et al., 2016). ...
... Prior studies demonstrate repeat arrestees frequent hospital emergency rooms (Akins, Burkhardt, & Lanfear, 2016), are disproportionately homeless (Green, 1997;Harding & Roman, 2017;Tentner et al., 2019), and have co-occurring mental health and SUD diagnoses (White et al., 2006). For instance, nearly half of individuals arrested for a mental health protection hold were rearrested within 60 days, and nearly a quarter of those were rearrested within the first 14 days of release from incarceration (Akins et al., 2016). This work, however, relied on police officers' perceptions of mental illness (Akins et al., 2016) and not on clinical diagnoses. ...
... For instance, nearly half of individuals arrested for a mental health protection hold were rearrested within 60 days, and nearly a quarter of those were rearrested within the first 14 days of release from incarceration (Akins et al., 2016). This work, however, relied on police officers' perceptions of mental illness (Akins et al., 2016) and not on clinical diagnoses. Furthermore, prior research has relied on different definitions to identify individuals who have frequent contact with the justice system, taking into account only arrests for a protective hold (Akins et al., 2016), or only jail or incarcerated individuals (Baillargeon et al., 2009;Hwang et al., n.d.;Kopak, Guston, Maness, & Hoffmann, 2019;White et al., 2006), or only anecdotal evidence from police departments or news media (Santos & Goode, 2014). ...
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... Once PMIs become involved in the legal system, they may enter into a cycle of frequent future contact. For PMIs, an arrest was predictive of future criminal and civil detainment (White et al., 2006;Akins et al., 2016). In a sample of homeless persons with mental illnesses, 30% had been arrested either for multiple non-violent offenses or a single theft offense and both groups were more likely to have repeated arrests (Roy et al., 2016). ...
... Success of admissions may be based on symptom profiles of the individual being admitted and availability of hospital beds rather than referral source (Watson et al., 1993). Similar to arrests, within the context of police encounters, a small number of individuals represent a high number of admissions and readmissions to hospitals and mental health facilities (Akins et al., 2016). ...
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... Evidence suggests that a subset of persons with mental illness (PMI) is at risk for becoming involved with the criminal justice system (CJS) (Becker, Andel, Boaz, & Constantine, 2011;Fisher et al., 2011). Research also suggests that a subset of this population will have multiple and/or habitual contact over their life course, leading to their entrenchment within the CJS, particularly with the police (Akins, Burkhardt, & Lanfear, 2014;Reuland, Schwarzefeld, & Draper, 2009). Some scholars suggest that the police act as "street corner psychiatrists", controlling access to the CJS and the mental healthcare system for many PMI (Teplin & Pruett, 1992). ...
... Prior research has indicated that a subset of persons with mental illness (PMI) is at risk of coming into contact with the criminal justice system (CJS) (Becker, Andel, Boaz, & Constantine, 2011;Fisher et al., 2011). An even smaller subset is at risk of having multiple and/or habitual contacts over their life course, leading to their entrenchment within the CJS, particularly with police services (Akins, Burkhardt, & Lanfear, 2014;Reuland, Schwarzefeld, & Draper, 2009). Much like criminal events in general, there are a variety of contextual factors that add to the complexity of PMI-police interactions when criminal laws are to be enforced. ...
... Evidence suggests that a subset of persons with mental illness (PMI) is at risk for becoming involved with the criminal justice system (CJS) (Becker, Andel, Boaz, & Constantine, 2011;Fisher et al., 2011). Research also suggests that a subset of this population will have multiple and/or habitual contact over their life course, leading to their entrenchment within the CJS, particularly with the police (Akins, Burkhardt, & Lanfear, 2014;Reuland, Schwarzefeld, & Draper, 2009). Some scholars suggest that the police act as "street corner psychiatrists", controlling access to the CJS and the mental healthcare system for many PMI (Teplin & Pruett, 1992). ...
... Prior research has indicated that a subset of persons with mental illness (PMI) is at risk of coming into contact with the criminal justice system (CJS) (Becker, Andel, Boaz, & Constantine, 2011;Fisher et al., 2011). An even smaller subset is at risk of having multiple and/or habitual contacts over their life course, leading to their entrenchment within the CJS, particularly with police services (Akins, Burkhardt, & Lanfear, 2014;Reuland, Schwarzefeld, & Draper, 2009). Much like criminal events in general, there are a variety of contextual factors that add to the complexity of PMI-police interactions when criminal laws are to be enforced. ...
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Legal limits on institutionalization. As patients were being discharged into the community, a series of legal decisions also had an impact on whether one could be readmitted or stay in a hospital setting. As early as 1866, after E.P.W. Packard was committed by her husband to an Illinois state mental institution, efforts to “reform” the system were under way. In her account of the episode, two physicians came to her home, took her pulse, and declared her insane [9]. She was confined for 3 years and, upon her release, led a successful campaign across the country to change the laws to safeguard people’s rights in the hospitalization process [9, 10]. Today every state has civil commitment laws outlining the requirements necessary to hospitalize someone with SMI. Reduced beds in state facilities. Changing federal laws have also contributed significantly to reducing the number of available beds in state facilities. The passage of the 1963 Community Mental Health Construction Act, which made federal grants available to states for establishing local community mental health centers, was intended to provide treatment in the community in anticipation of the release of patients from state hospitals [9]. Laws providing income subsidies through the Aid to the Disabled Program (latter called Supplemental Security Income or SSI), food stamps, and housing subsidies has made it ostensibly possible for people with SMI to live in the community, although many still cannot survive in any dignified or independent manner given that the subsidies are below the poverty level of $11,490 for an individual [15] (current 2013 federal SSI payment is $8,529.32 per year for an individual [16]). Perhaps the most important change in federal law was the introduction of Medicaid, which shifted funding for people with SMI in state hospitals from the states’ responsibility to a shared partnership with the federal government [17]. This created an incentive for states to close the facilities they funded on their own and move patients into community hospitals and nursing homes partially paid for by Medicaid and the federal government. With the Omnibus Budget Reconciliation Act of 1981, the federal government ended direct federal funding for community-based nursing homes that primarily treated patients with mental health problems and required the screening of patients entering nursing homes to assure they had legitimate medical illness [18]. It required states to return to funding non-nursing homes for the long-term care of people with SMI in the community [18], basically segregating many people with SMI into large, underfunded facilities. These facilities were often for profit and privately owned, creating an incentive to reduce costs and care in the name of profits. The perils of this were aptly illustrated in a series of articles by Clifford Levy in the New York Times in 2002 [19].
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PurposeThe objective of this research was to systematically review quasi-experimental and experimental evaluations of the effectiveness of drug courts in reducing offending.Methods Our search identified 154 independent evaluations: 92 evaluations of adult drug courts, 34 of juvenile drug courts, and 28 of DWI drug courts. The findings of these studies were synthesized using meta-analysis.ResultsThe vast majority of adult drug court evaluations, even the most rigorous evaluations, find that participants have lower recidivism than non-participants. The average effect of participation is analogous to a drop in recidivism from 50% to 38%; and, these effects last up to three years. Evaluations of DWI drug courts find effects similar in magnitude to those of adult drug courts, but the most rigorous evaluations do not uniformly find reductions in recidivism. Juvenile drug courts have substantially smaller effects on recidivism. Larger reductions in recidivism were found in adult drug courts that had high graduation rates, and those that accepted only non-violent offenders.Conclusions These findings support the effectiveness of adult drug courts in reducing recidivism. The evidence assessing DWI courts' effectiveness is very promising but more experimental evaluations are needed. Juvenile drug courts typically produce small reductions in recidivism.