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. Author manuscript; available in PMC: 2020 May 1.
Published in final edited form as: J Community Psychol. 2019 Aug 19;47(8):1893–1908. doi: 10.1002/jcop.22233

Unmet Mental Health and Substance Use Treatment Needs Among Older Homeless Adults: Results from the HOPE HOME Study

Lauren M Kaplan 1,2, Lea Vella 3,4, Elise Cabral 5, Lina Tieu 1,2, Claudia Ponath 1,2, David Guzman 1,2, Margot B Kushel 1,2
PMCID: PMC7046319  NIHMSID: NIHMS1559666  PMID: 31424102

Abstract

Aims:

To examine the prevalence of and factors associated with unmet need for mental health and substance use treatment in older homeless adults.

Methods:

Among 350 homeless adults aged ≥50, we examined prevalence of mental health and substance use problems and treatment. Using logistic regression, we examined factors associated with unmet treatment need.

Results:

Among those with a mental health problem, being aged ≥65 was associated with an increased odds, while having a regular healthcare provider and case manager were associated with a decreased odds of having unmet need for mental health treatment. A first homelessness episode at age ≥50 was associated with increased, while spending time in jail/prison or having a case manager was associated with decreased odds of unmet needs for substance use treatment.

Conclusion:

Older homeless adults have a high prevalence of unmet behavioral health treatment need. There is a need for targeted services for this population.

Keywords: mental health, substance abuse, aging, homelessness, suicidal ideation, depressive symptoms, outpatient care

INTRODUCTION

The homeless population is aging (Culhane, Metraux, Byrne, Stino, & Bainbridge, 2013). People born in the second half of the “baby-boom” have an elevated risk of homelessness (Culhane et al., 2013). Homeless adults develop aging-related conditions, including functional impairment, earlier than individuals in the general population. For this reason, homeless adults aged 50 and older are considered “older” despite their relatively young age (Brown, Kiely, Bharel, & Mitchell, 2012; Cohen; Gelberg, Linn, & Mayer-Oakes, 1990).

The homeless population has a higher prevalence of mental health and substance use problems than the general population (Fazel, Khosla, Doll, & Geddes, 2008; Kessler et al., 2010; Lapp, Agbokou, & Ferreri, 2011; Spinelli et al., 2017; Walker, Cummings, Hockenberry, & Druss, 2015). Individuals experiencing homelessness report barriers to mental health services, due to lack of insurance coverage, high cost of care, and inability to identify sources of care (Baggett, O’connell, Singer, & Rigotti, 2010; Lebrun-Harris et al., 2013; Zur & Jones, 2014). These barriers can prevent their using services to treat mental health and substance use problems, such as outpatient counseling, prescription medication, and community-based substance use treatment. Without these, homeless populations may experience more severe behavioral health problems and rely on acute care to address these chronic conditions. Homeless individuals have higher rates of Emergency Department (ED) use for mental health and substance use concerns (Bharel et al., 2013), and are more likely to use psychiatric inpatient or ED services and less likely to use outpatient treatment than those who are housed (Folsom et al., 2005).

Homeless adults with substance use disorders face multiple barriers to engaging in substance use treatment. Competing needs (i.e. finding shelter, food, or other necessitates), financial concerns, lack of knowledge about or connection to available services, and lack of insurance are barriers to substance use treatment among homeless adults (Koegel, Sullivan, Burnam, Morton, & Wenzel, 1999; Krausz et al., 2013; O’Toole, Pollini, Ford, & Bigelow, 2008; Wenzel et al., 2001; Zur & Jones, 2014). Older adults face additional barriers to mental health or substance use treatment due to cognitive and functional impairment, such as difficulty navigating and traveling to healthcare systems (Kuerbis, Sacco, Blazer, & Moore, 2014; Wuthrich & Frei, 2015). However, there is little known about older adults experiencing homelessness.

According to Gelberg and Anderson’s Behavioral Model for Vulnerable Populations, predisposing factors, enabling factors, and need, shape health care utilization (Gelberg, Andersen, & Leake, 2000). Although prior research has used this model for homeless populations, this work has not included older homeless adults (Stein, Andersen, & Gelberg, 2007). Little is known about the prevalence of mental health or substance use problems in older homeless adults, the level of unmet need for services, or the factors associated with that need. In order to understand the factors associated with unmet need for mental health and substance use treatment in older homeless adults, in a population-based sample of homeless adults age 50 and older, we identified those with a need for mental health and substance use services. Then, we applied the Gelberg and Anderson model to examine predisposing and enabling factors associated with unmet need, which we defined as not receiving mental health and substance use treatment among participants with mental health or substance use problems (Gelberg et al., 2000).

METHODS

Study Overview

The Health Outcomes of People Experiencing Homelessness in Older Middle Age (HOPE HOME) Study is a longitudinal study of physical and mental health, life course events, and functional status among older homeless adults. The University of California, San Francisco Institutional Review Board approved all study activities.

Sample and Recruitment

From July 2013 to June 2014, we used population-based sampling to recruit 350 homeless individuals age 50 and older in Oakland, California (Burnam & Koegel, 1988; Lee, Ponath, Tieu, Riley, & Kushel, 2016). (Figure 1) We recruited participants from all overnight homeless shelters serving single adults over age 25 (n=5), all low-cost meal programs serving at least three meals per week (n=5), one recycling center, and places where unsheltered homeless individuals stayed. We constructed our sampling frame to approximate the source population; we randomly selected potential participants at each recruitment site (Henry, Watt, Rosenthal, & Shivji, 2017; Lee et al., 2016).

Figure 1. Recruitment Flow Chart.

Figure 1.

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The figure shows the number of individuals enrolled at baseline

Participants who declined after being approached (335) declined before being assessed for eligibility. Therefore, the number of participants who were ineligible for the study may have been higher than the numbers presented in this table.

Eligibility criteria included the ability to communicate in English, age 50 or older, currently homeless as defined in the Homeless Emergency Assistance and Rapid Transitions to Housing (HEARTH) Act (US Congress, 2009), and ability to give written informed consent as determined using a teach-back method (Dunn & Jeste, 2001). After informed consent, study staff conducted an in-depth structured baseline interview. They entered responses into electronic data capture software. Individuals received a $25 gift card to a major retailer for completing the eligibility screen and baseline interview.

Measures

Predisposing Factors

Predisposing factors are demographic, social-structural, and attitudinal-belief factors that make it more likely that individuals will use health services. (Andersen & Newman, 1973; Andersen, 2008; Gelberg et al., 2000). We included demographic, educational, housing, involvement with the criminal justice system, and physical health factors as predisposing factors.

Demographics.

Participants reported their age, gender, race/ethnicity, and marital status.

Education.

We asked participants to report their highest level of education (i.e. less than high school, high school or General Educational Development (GED) degree, or any college).

We used the validated health literacy question “How confident are you filling out medical forms by yourself?” (not at all, a little bit, somewhat, quite a bit, extremely) (Chew, Bradley, & Boyko, 2004). We categorized somewhat or less confident as inadequate health literacy.

Housing history.

Participants reported their duration of homelessness in each of three age ranges: 18–25, 26–49, and ≥50. We combined these responses to calculate total years homeless as an adult. We assessed when participants had their first episode of homelessness, dichotomizing responses to ≥50 years versus younger than 50 years.

Involvement with the criminal justice system.

Consistent with prior research, we included incarceration as a predisposing factor (Stein et al., 2007). To assess if participants had spent time in jail or prison, we asked if they had (1) spent a night in a city or county jail and/or (2) served any time in state or federal prison during the last six months.

Physical health status.

To assess general health status, we asked participants to rate their health (fair or poor versus good, very good, or excellent) (Ware, Kosinski, & Keller, 1996). To assess functional status, we asked participants if they had difficulty performing any of five activities of daily living (ADLs; bathing, dressing, eating, transferring, toileting) (Katz, 1983). We defined ADL impairment as self-reported difficulty performing at least one ADL. We assessed cognition using the Modified Mini-Mental State Exam (3MS). We categorized scores below the 7th percentile (1.5 standard deviations below a reference cohort mean) as cognitive impairment (Bland & Newman, 2001; Bravo & Hebert, 1997).

Enabling Factors

Enabling factors are conditions that allow individuals to access health care, or conditions that allow systems to make these services available (Andersen & Newman, 1973; Andersen, 2008; Gelberg et al., 2000). We included measures of access to physical health care, veteran status, and social support as enabling factors.

Usual source of care.

We assessed whether participants had a usual source of care for physical health problems using items adapted from the National Health and Nutrition Examination Survey (NHANES) (Centers for Disease Control and Prevention, 2009).We asked participants if they had a usual place of care, defined as a place they usually go when sick or in need of health advice, excluding emergency departments. If participants identified a usual place of care, we asked if they had a primary care provider (i.e. physician, nurse practitioner, or physician’s assistant). As a separate measure, we asked whether participants had a case manager, defined as someone working at an agency who talked about services or helped them to get services, in the past six months.

Veteran status.

Because veterans may have access to additional services through the Veterans Affairs Medical Centers, we considered being a veteran to be an enabling factor. To assess veteran status, we asked participants if they had ever been on active duty in the Armed Forces, military reserves, or National Guard.

Social support.

To assess social support, we asked participants to report how many close friends or family members they had to confide in (Gielen, McDonnell, Wu, O’Campo, & Faden, 2001). We categorized responses as having 0, 1–5, or at least 6 members in their social network.

Need for behavioral health care.

Andersen defined need as illness level, which includes an individual’s perceived illness. (Andersen & Newman, 1973; Gelberg et al., 2000) We assessed need using validated screening tools, examining mental health and substance use needs separately.

Need for mental health treatment.

We defined having a need for mental health treatment by having a positive screen for depressive symptoms or post-traumatic stress disorder (PTSD) symptoms or reporting symptoms of other mental health problems, including anxiety, hallucinations, thoughts of suicide, or attempted suicide in the past 6 months. To assess current depressive symptoms, we used the Center for Epidemiologic Studies Depression Scale (CES-D), considering a score of ≥22 to be evidence of depressive symptoms (Cheng & Chan, 2005; Haringsma, Engels, Beekman, & Spinhoven, 2004; Radloff, 1977). We evaluated current PTSD symptoms using the Primary Care PTSD Screen (PC-PTSD), which asks participants to report whether they experienced any of four symptoms in the previous month due to a past experience: nightmares, avoidance of situations that reminded them of it, hypervigilance, or emotional numbing to their surroundings (Prins et al., 2003). We considered a score of four to be consistent with PTSD symptoms. To assess additional mental health problems (i.e. anxiety, hallucinations, thoughts of suicide, or attempted suicide), we used questions from the National Survey of Homeless Assistance Providers and Clients (NSHAPC), as adapted from the Addiction Severity Index (ASI) (Burt et al., 1999; McLellan et al., 1992) and considered a report of any of those symptoms to be evidence of other mental health problems. We considered anyone who met criteria for depressive symptoms, PTSD symptoms or other mental health problems to have a mental health need.

Need for substance use treatment.

We assessed for alcohol use problems using the Alcohol Use Disorders Identification Test (AUDIT) (Babor & Higgins‐Biddle, 2002) and considered a score of ≥8 to indicate need for treatment. We assessed for problems with cannabis, cocaine, amphetamines, or opioids on the World Health Organization’s (WHO) Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST). We considered a score of ≥4 for any of the substances to indicate the need for treatment (Humeniuk, Henry-Edwards, Ali, Poznyak, & Monteiro, 2010). We considered anyone who met criteria for either alcohol or substance use problems to have a substance use need.

Receipt of mental health or substance use treatment

To assess receipt of mental health treatment in the prior six months, we asked participants whether they had received outpatient care or whether a health care provider had prescribed medication(s) for an emotional or mental health problem in the prior six months. To define receipt of substance use treatment, we asked participants whether they had received treatment for an alcohol problem or been treated for a drug problem in the prior six months.

Dependent variables

Unmet need for mental health treatment.

To define unmet need for mental health treatment, we restricted the sample to those who met criteria for having a mental health need using the criteria above. We defined not having received treatment as not having received outpatient mental health treatment or not having been prescribed a medication for an emotional or mental health problem.

Unmet need for substance use treatment.

To define unmet need for substance use treatment, we restricted the overall sample to those with an identified substance use need as defined above. We assessed the proportion of participants within this subsample who did not report having received any alcohol or drug use treatment in the prior six months.

Statistical Analysis

Drawing on Gelberg and Anderson’s model, we examined factors associated with not having received mental health treatment amongst those with a mental health need (Gelberg et al., 2000). We included the factors listed above, which we identified a priori. In the model with unmet need for mental health services, we examined whether having an alcohol or drug use problem was associated with unmet need, considering them to be need factors. (Koegel et al., 1999; Wenzel et al., 2001) We conducted a separate analysis to examine factors associated with not having received substance use treatment amongst those with an identified need; we again used the Gelberg and Anderson model and used factors listed above, which we identified factors a priori. In the substance use model, we tested whether having depressive symptoms, PTSD symptoms, or additional mental health problems, conceptualized as need factors, were associated. (Koegel et al., 1999; Wenzel et al., 2001) We used logistic regression in these analyses.

To construct our model, we included only hypothesized variables with a bivariate p-value of <0.20 in the full multivariate model. To define our reduced model, we conducted backward elimination, retaining independent variables with p values ≤0.05. Due to a skip pattern error, we incorrectly assessed 33 individuals using the AUDIT. To correct for this, we used multiple imputation to estimate the relationship between the treatment variables and the total AUDIT scores. We conducted multiple imputation analysis in STATA 14.2 (2015). We used SAS 9.4 (2013) to conduct our descriptive and logistic regression analyses.

RESULTS

Predisposing Factors

We enrolled 350 participants, of whom 77.1% were men and 79.7% were Black American (Table 1). The median age was 58 (range 50–80). Five percent (4.9%) of the sample was married or partnered. Seventy-four (74.3%) percent of participants obtained, at minimum, a GED or high school diploma. Less than half (41.6%) reported inadequate health literacy. The cohort had a median duration of years homeless as an adult of 2.2 years (IQR=0.8–8.0) and 43.4% had their first episode of homelessness after age 50. Ten percent (10.6%) of participants had spent time in jail or prison within the past six months.

Table 1.

Baseline characteristics of homeless adults, aged 50 and older in Oakland, CA (n=350)

All participants (n=350) Positive mental health screen† (n=195) Positive substance use screen‡ (n=254)
Characteristic n or Median, (% or Interquartile Range (IQR)) n or Median, (% or Interquartile Range (IQR)) n or Median, (% or Interquartile Range (IQR))
Predisposing factors
 Demographics
  Age
   50–54 102 (29.1) 66 (33.8) 86 (33.9)
   55–59 117 (33.4) 71 (36.4) 81 (31.9)
   60–64 89 (25.4) 43 (22.1) 61 (24.0)
   ≥65 42 (12.0) 15 (7.7) 26 (10.2)
  Gender
   Men 270 (77.1) 146 (74.9) 206 (81.1)
  Race/ethnicity
   Black American 279 (79.7) 147 (75.4) 205 (80.7)
   White 38 (10.9) 27 (13.8) 27 (10.6)
   Hispanic/Latino 16 (4.6) 10 (5.1) 11 (4.3)
   Asian American 3 (0.9) 2 (1.0) 1 (0.4)
   Mixed/Other 14 (4.0) 9 (4.6) 10 (3.9)
  Marital Status
   Never married/partnered 145 (41.4) 89 (45.6) 108 (42.5)
   Separated/divorced 150 (42.9) 73 (37.4) 105 (41.3)
   Widowed 38 (10.9) 23 (11.8) 29 (11.4)
   Married/partnered 17 (4.9) 10 (5.1) 12 (4.7)
 Education
  Less than high school 90 (25.7) 52 (26.7) 70 (27.6)
  High school diploma/GED 75 (21.4) 42 (21.5) 53 (20.9)
  Some college or more 185 (52.9) 101 (51.8) 131 (51.6)
  Inadequate health literacy 144 (41.6) 94 (48.7) 117 (46.4)
Housing history
 Total years homeless as adult 2.2 (0.8–8.0) 3.04 (0.71, 9.00) 3.00 (0.92, 8.75)
 Age first homeless ≥50 years 152 (43.4) 69 (35.4) 99 (39.0)
Jail or prison in past 6 months 37 (10.6) 24 (12.3) 33 (13.0)
Health status
 Fair or poor health status 195 (55.7) 129 (66.2) 143 (56.3)
  ≥ 1 ADL impairment§ 136 (38.9) 92 (47.2) 100 (39.4)
  Cognitive Impairment 90 (25.8) 49 (25.3) 67 (26.5)
Enabling factors
 Social support
  0 Friends/family members 113 (32.5) 66 (34.0) 76 (30.0)
  1–5 Friends/family members 205 (58.9) 115 (59.3) 156 (61.7)
  ≥6 Friends/family members 30 (8.6) 13 (6.7) 21 (8.3)
 Usual place for health care 252 (72.0) 142 (72.8) 181 (71.3)
 Identified a primary care provider 184 (52.6) 100 (51.3) 131 (51.6)
 Case manager 134 (38.3) 80 (41.0) 95 (37.4)
 Veteran 76 (21.7) 37 (19.0) 54 (21.3)
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†

Center for Epidemiologic Studies Scare (CES-D) score ≥ 22, Primary Care Post Traumatic Stress Disorder Screen (PC-PTSD) score ≥ 4, or Addiction Severity Index (ASI) severe anxiety, hallucinations, thoughts of suicide, or attempted suicide in past 6 months.

‡

Alcohol Use Disorders Identification Test (AUDIT) score ≥ 8 or Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) score ≥ 4

§

Activities of daily living (ADLs); bathing, dressing, eating, transferring, toileting.

Cognitive impairment defined as a Modified Mini-Mental State Examination score below the 7th percentile (i.e. 1.5 standard deviations below the demographically-adjusted cohort mean).

Half of participants (55.7%) rated their health as fair or poor. Over one-third (38.9%) had at least one ADL impairment. A quarter (25.8%) screened positive for cognitive impairment below the 7th percentile.

Enabling Factors

Most participants (67.5%) reported at least one friend/family member. Most participants (72.0%) identified a usual place of care, half (52.6%) had a primary care provider, and 38.3% had a case manager (Table 1). One-fifth (21.7%) of participants had served in the military.

Need for Mental Health Treatment

One-third (38.3%) screened positive for depression (CES-D ≥22). (Table 2) Approximately one-fifth (17.7%) of the sample screened positive for posttraumatic symptoms (PC-PTSD ≥4). During the past six months, 39.0% experienced anxiety, and 14.5% experienced visual or auditory hallucinations (Table 2). Twenty-seven individuals (7.8%) endorsed experiencing suicidal ideation, two of whom reported making a suicide attempt within the past six months. More than half of the cohort (55.7%) met criteria for having a mental health need, by having a positive screen for any of these conditions.

Table 2.

Mental health and substance use problems (n=350)

n or Mean % or Standard Deviation (SD)
Current symptoms (past 6 months)
 CES-D ≥ 22† 133 38.3
 PC-PTSD‡
  Nightmares 104 29.7
  Avoidance 158 45.1
  Hypervigilance 155 44.3
  Emotional numbing 135 38.6
  PC-PTSD ≥ 4 62 17.7
ASI§ mental health questions
 Anxiety 134 39.0
 Hallucinations 50 14.5
 Thoughts of suicide 27 7.8
 Suicide attempt 2 0.6
Any mental health problem 195 45.4
AUDIT†† ≥ 8 94 26.9
ASSIST‡‡ ≥ 4 226 64.6
 Cocaine 151 43.1
 Cannabis 137 39.1
 Amphetamine 28 8.0
 Opioids 45 12.9
Any substance use problem§§¶¶ 254 72.6
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†

Center for Epidemiologic Studies Scare (CES-D).

‡

Primary Care Post Traumatic Stress Disorder Screen (PC-PTSD).

§

Addiction Severity Index (ASI).

Center for Epidemiologic Studies Scale (CES-D) score ≥ 22, Primary Care Post Traumatic Stress Disorder Screen (PC-PTSD) score ≥ 4, or Addiction Severity Index (ASI) severe anxiety, hallucinations, thoughts of suicide, or attempted suicide

††

Alcohol Use Disorders Identification Test (AUDIT).

‡‡

Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST).

§§

10 participants who had low use of illicit drugs were incorrectly assessed with the AUDIT but were included in the denominator.

¶¶

Alcohol Use Disorders Identification Test (AUDIT) score ≥ 8 or Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) score ≥ 4 in past 6 months.

Need For Substance Use Treatment

Approximately one-fifth (26.9%) had an alcohol problem; 64.6% met criteria for an illicit drug use problem. Cocaine was the most prevalent substance (43.1%), followed by cannabis (39.1%), opioids (12.9%), and amphetamine (8.0%). Almost three-quarters (72.6%) met criteria for substance use need.

Receipt of Mental Health and Substance Use Treatment

In the past six months, 25.1% received outpatient treatment/counseling or prescription medication. Fewer than one-fifth (16.0%) received outpatient mental health treatment and 22.0% had been prescribed prescription medication. Ten percent (10.3%) received any substance use treatment: less than five percent (4.6%) had received alcohol treatment and 7.1% had received illicit drug treatment.

Among those with mental health need, 38.5% received either outpatient or medication treatment: 24.6% received outpatient treatment and 34.4% had been prescribed medication. Among those with substance use need, 12.6% received alcohol or illicit drug treatment: 5.1% received alcohol treatment and 9.5% received illicit drug treatment.

Factors Associated with Unmet Mental Health Treatment Need

In multivariable models assessing factors associated with unmet need for mental health care, we found that older age was associated with unmet need. Participants ages ≥65 years had a 9-fold increased odds (AOR = 9.6; 95% CI 2.0–47.1) compared to those ages 50–64. Having a regular healthcare provider (AOR = 0.2; 95% CI 0.1–0.5) and having a case manager (AOR = 0.4; 95% CI 0.2–0.8) were associated with a decreased odds. Being a woman, having substance use problems, having a regular healthcare location, and spending time in jail/ prison were associated with lower odds in unadjusted models but did not retain significance in multivariable analysis.

Factors Associated with Unmet Substance Use Treatment Need

In multivariable models assessing factors associated with unmet need for substance use care, we found that experiencing a first episode of homelessness at age 50 or older was associated with unmet need (AOR = 2.6; 95% CI 1.1–6.5). Having a case manager (AOR = 0.4; 95% CI 0.2–0.8) and spending time in jail/prison (AOR = 0.1; 95% 0.1–0.8) were associated with decreased odds. Depressive symptoms, additional mental health problems, and veteran status were associated with decreased odds but did not retain significance in multivariable models.

DISCUSSION

In a population-based sample of older adults experiencing homelessness, we found a high prevalence of unmet need for mental health and substance use treatment. While the majority of participants had mental health and substance use problems, few received treatment. One-third of those with mental health need received mental health care. Fewer than 13% of those with substance use need received substance use treatment.

We identified predisposing and enabling factors associated with unmet treatment need. Adults aged 65 and over (compared to those aged 50–64) had a higher odds of unmet need for mental health treatment. Older adults are more likely to have competing demands, including higher physical health needs, which can interfere with receiving behavioral health care (Kuerbis et al., 2014; Wuthrich & Frei, 2015). Due to a shortage of geriatric psychiatrists and geriatric mental health care services, older adults may not have access to treatment when they seek care (Avari & Meyers, 2017; Kirwin et al., 2016). The homeless population age 65 and older is expected to triple by the year 2020 (Culhane et al., 2019). Thus, there is a need to design care that meets the needs of this growing, but underserved, population.

We found that having a regular healthcare provider was associated with less unmet need. Having a regular provider can increase engagement because primary care providers may help identify needs and refer to care. In safety-net systems, such as the ones in which our participants receive care, primary care providers may be the primary source of mental health treatment, by prescribing psychotropic medication. Primary care providers are responsible for an increasing proportion of prescriptions for psychotropic medication (Barkil-Oteo, 2013; Frank, Conti, & Goldman, 2005). In addition to prescribing medication for mental health conditions, primary care providers can refer patients to outpatient mental health counseling and treatment with specialist staff or providers. In some safety-net settings, mental health services may be co-located with physical health services via collaborative care models.

Collaborative care models (CCMs) can enhance information sharing and treatment plan collaboration and reduce barriers to care (Camacho et al., 2018; Chwastiak et al., 2018; Goodrich, Kilbourne, Nord, & Bauer, 2013; Watkins et al., 2017; Woltmann et al., 2012). CCMs are effective at reducing depressive symptoms and suicidal ideation among older adults (Bruce et al., 2004; Unutzer et al., 2002). CCMs are cost-efficient and can increase the capacity of resource-constrained settings to provide care for patients with complex needs (Katon et al., 2011; Woltmann et al., 2012). Federally Qualified Health Centers (FQHC) can bill for both a medical and mental health visit on the same day (Centers for Medicare & Medicaid Services, 2017), and recent changes to FQHC payment codes (Centers for Medicare & Medicaid Services, 2018) allow billing for behavioral health care management services in addition to the FQHC billable visit. Pay-for-performance programs link public hospitals’ payments to care coordination and mental health treatment metrics (California Department of Health Care Services, 2018). It is possible that participants in our study were obtaining care in safety-net primary care settings with CCMs.

Alternatively, the reduced odds of unmet need amongst those who had regular care providers could reflect other factors that we did not measure. For example, having a regular care provider may be a marker for increased system engagement and reduced barriers to any type of care. Those who seek primary care may be more organized, knowledgeable about safety-net service availability, and have more access to transportation and other enabling resources. (Zur & Jones, 2014)

Having a case manager was associated with less mental health and substance use treatment need. In the case management brokerage model, case managers help people navigate care systems and provide a linkage to services. In the clinical case management model, case managers serve as care providers and may provide both mental health and substance use services directly (Mueser, Bond, Drake, & Resnick, 1998). In some models, such as intensive case management, case managers provide both brokerage and direct services (Hangan, 2006; Mueser et al., 1998). It is possible that the association between having a case manager and decreased odds of unmet need for both mental health and substance use services is a result of reverse causality; treatment programs may assign a case manager.

We found that participants who first became homeless at age 50 or older had a higher odds (compared to those with a first episode prior to age 50) of unmet substance use treatment need. Those with late onset homelessness had led more “typical” lives, with a higher likelihood of having been continuously employed and having been married or partnered (Brown et al., 2016). They were less likely to have had early onset of substance use problems, thus, they may have developed substance use problems more recently. These individuals may have been less aware of safety-net resources in general or resources for substance use treatment in particular.

Spending time in jail/prison in the past six months was associated with reduced unmet substance use treatment need. It is possible that participants initiated substance use treatment while incarcerated. However, most incarceration settings do not provide adequate treatment services. (Safran et al, 2009.; Wilper et al., 2009) Alternatively, as a condition of release, participants may have been required to engage in substance use treatment. Our findings indicate there is a lack of community-based pathways into substance use care. By giving medication-assisted treatments, such as buprenorphine for opioid use disorder (Connery, 2015; Hser et al., 2016) and naltrexone for alcohol use disorder (Jonas et al., 2014) in primary care settings, primary care providers can begin to address this unmet need (Korthuis et al., 2017; O’Malley et al., 2003; Yeates & Thompson, 2008). However, there is a need for greatly expanded substance use services.

Our study has several limitations. We did not use a full psychiatric diagnostic interview. However, screening measures are important empirical tools for the referral of individuals to mental health treatment, especially when integrated care is available (Pignone et al., 2002). We did not ask participants where they received mental health services, thus we cannot determine whether they received care co-located with primary care, or treatment in mental health specific settings.

Conclusion

Older homeless adults have a high prevalence of mental health and substance use problems. Despite their need for treatment, few participants accessed mental health or substance use treatment. Homeless adults age 65 and older and those who become homeless later in life may need services tailored to their specific needs. Interventions that increase engagement with primary care, and integrate behavioral health care within primary care, could increase utilization of mental health and substance use treatment among older homeless adults.

Table 3.

Receipt of mental health and substance use treatment in the past six months

All participants Mental health problem† Substance use problem‡
n=350 n=195 n=254
Mental health n % n % n %
 Outpatient treatment/counseling 56 16.0 48 24.6 44 17.3
 Prescribed medicine for psychological/emotional problem 77 22.0 67 34.4 62 24.4
 Outpatient treatment/counseling and/or prescription 88 25.1 75 38.5 70 27.6
Substance use
 Alcohol treatment 16 4.6 9 4.6 13 5.1
 Illicit drug treatment 25 7.1 19 9.7 24 9.5
 Alcohol treatment or illicit drug treatment 36 10.3 25 12.8 32 12.6
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†

Center for Epidemiologic Studies Scare (CES-D) score ≥ 22, Primary Care Post Traumatic Stress Disorder Screen (PC-PTSD) score ≥ 4, or Addiction Severity Index (ASI) severe anxiety, hallucinations, thoughts of suicide, or attempted suicide in past 6 months.

‡

Alcohol Use Disorders Identification Test (AUDIT) score ≥ 8 or Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) score ≥ 4.

Table 4.

Unmet need for outpatient mental health treatment among those with mental health problems, n=195†‡

Bivariable Models§ Reduced Multivariable Model
Odds Ratio 95% Confidence Interval Adjusted Odds Ratio 95% Confidence Interval
Predisposing factors
 Age
  ≥65 years 4.4 1.0–20.5 9.6 2.0–47.1
  50–64 years Referent Referent
 Gender
  Men 2.2 1.1–4.3 -- --
  Women Referent
Illicit drug use problem 0.6 0.3–1.0 -- --
Jail or prison in past 6 months 0.5 0.2–1.2 -- --
Enabling factors
 Regular healthcare location 0.3 0.1–0.6 -- --
 Regular healthcare provider 0.3 0.1–0.5 0.2 0.1–0.5
 Case manager 0.4 0.2–0.8 0.4 0.2–0.8
Open in a new tab
†

Center for Epidemiologic Studies Scare (CES-D) score ≥ 22, Primary Care Post Traumatic Stress Disorder Screen (PC-PTSD) score ≥ 4, or Addiction Severity Index (ASI) severe anxiety, hallucinations, thoughts of suicide, or attempted suicide in past 6 months.

‡

7 cases were not included in the reduced multivariable model due to missing data.

§

We present bivariable p-values less than .20 in the unadjusted models.

Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) score ≥ 4 for amphetamines, cocaine, and opioids.

Table 5.

Factors associated with unmet need for substance use treatment among those with substance use problems, n=254†‡

Bivariable Models§ Reduced Multivariate Model
Odds Ratio 95% Confidence Interval Adjusted Odds Ratio 95% Confidence Interval
Predisposing factors
 Age first homeless
  ≥50 years 2.5 1.0–6.2 2.6 1.1–6.5
  <50 years Referent -- Referent --
 CES-D≥22 0.5 0.2--1.1 -- --
 Additional mental health problems†† 0.4 0.2–0.8 -- --
 Jail or prison in past 6 months 0.4 0.2–1.0 0.1 0.1–0.8
Enabling factors
 Case manager 0.4 0.2–0.9 0.4 0.2–0.8
 Veteran status 2.9 0.8–10.0 -- --
Open in a new tab
†

Alcohol Use Disorders Identification Test (AUDIT) score ≥ 8 or Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) score ≥ 4.

‡

5 cases were not included in the reduced multivariable model due to missing data.

§

We present bivariable p-values less than .20 in the unadjusted models.

Center for Epidemiologic Studies Scare (CES-D).

††

Addiction Severity Index (ASI) severe anxiety, hallucinations, thoughts of suicide, or attempted suicide in past 6 months.

Funding:

This work was supported by grants from the National Institute on Aging (NIA) at the National Institutes of Health (NIH) [K24AG046372 to Dr. Kushel and R01AG041860 to Dr. Kushel]. These funding sources had no role in the preparation, review, or approval of the manuscript.

Footnotes

Disclosures and acknowledgments: The authors have no conflict of interest to disclose.

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