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American Journal of Public Health logoLink to American Journal of Public Health
. 2013 Dec;103(Suppl 2):S380–S388. doi: 10.2105/AJPH.2013.301646

Predictors of Medical or Surgical and Psychiatric Hospitalizations Among a Population-Based Cohort of Homeless Adults

Catharine Chambers 1, Marko Katic 1, Shirley Chiu 1, Donald A Redelmeier 1, Wendy Levinson 1, Alex Kiss 1, Stephen W Hwang 1,
PMCID: PMC3969145  NIHMSID: NIHMS551480  PMID: 24148040

Abstract

Objectives. We identified factors associated with inpatient hospitalizations among a population-based cohort of homeless adults in Toronto, Ontario.

Methods. We recruited participants from shelters and meal programs. We then linked them to administrative databases to capture hospital admissions during the study (2005–2009). We used logistic regression to identify predictors of medical or surgical and psychiatric hospitalizations.

Results. Among 1165 homeless adults, 20% had a medical or surgical hospitalization, and 12% had a psychiatric hospitalization during the study. These individuals had a total of 921 hospitalizations, of which 548 were medical or surgical and 373 were psychiatric. Independent predictors of medical or surgical hospitalization included birth in Canada, having a primary care provider, higher perceived external health locus of control, and lower health status. Independent predictors of psychiatric hospitalization included being a current smoker, having a recent mental health problem, and having a lower perceived internal health locus of control. Being accompanied by a partner or dependent children was protective for hospitalization.

Conclusions. Health care need was a strong predictor of medical or surgical and psychiatric hospitalizations. Some hospitalizations among homeless adults were potentially avoidable, whereas others represented an unavoidable use of health services.


Homeless adults are frequent users of inpatient hospital services. In a nationally representative sample of homeless persons in the United States, almost 1 in 4 respondents reported being hospitalized in the past year, a rate 4 times higher than US norms.1

The frequent use of inpatient hospital services partially reflects the high prevalence of acute and chronic disease, injuries and assaults, substance use, and mental illness among this population.1–3 However, the high rates of hospitalization have also been attributed to a lack of access to primary and preventative care, particularly in the United States, where 50% of homeless people have no health insurance.1,4–7 In a nationally representative sample of persons who used homeless services in the United States, Kushel et al.1 showed that lack of health insurance and African American race/ethnicity, compared with non-Latino White race/ethnicity, were the only factors significantly associated with a lower odds of self-reported hospitalization. In a subsequent study, Kushel et al.4 showed that being uninsured significantly decreased the likelihood of self-reporting a nonmaternal hospitalization in the past year, whereas food instability and housing instability significantly increased the odds. Similarly, Lim et al.5 in their population-based study of homeless women in Los Angeles, California, showed that having health insurance was significantly associated with an increased likelihood of hospitalization.

These studies pointed to the enabling influence of health insurance on access to inpatient hospital services in the United States; however, these findings were likely not applicable in a Canadian setting in which individuals have access to universal health insurance coverage. Furthermore, most previous studies of health care utilization in the United States relied on self-reported data1,8–10 or restricted their analysis to a single health care institution.11,12 The purpose of this study was to identify factors associated with inpatient hospitalizations among a population-based cohort of homeless adults in Toronto, Ontario, using comprehensive administrative data. Analyses were stratified by type of inpatient service to examine the influence of predictors separately for medical or surgical and psychiatric hospitalizations.

METHODS

Recruitment and sampling methods for this study were previously described.13–15 Briefly, we selected a random sample of homeless adults from shelters and meal programs in Toronto over 12 consecutive months in 2004 and 2005. Recruitment was stratified to obtain a 2:1:1 ratio of single adult men (i.e., men without dependent children), single adult women (i.e., women without dependent children), and family adults (i.e., men or women accompanied by a partner or dependent children) to ensure adequate sample size for comparison and to approximate the demographic characteristics of Toronto’s homeless population.3 Findings from a pilot study showed that approximately 90% of homeless people in Toronto sleep at shelters, whereas 10% did not use shelters but did use meal programs.16 Therefore, 90% of the sample was recruited at shelters and the remaining 10% at meal programs.

Homelessness was defined as living within the last 7 days at a shelter, public place, vehicle, abandoned building, or someone else’s home, and not having a home of one’s own.17 Participants were excluded if they did not meet the definition of homelessness, were unable to communicate in English, were unable to provide informed consent, or were meal program users who had not used a shelter in the past 7 days. Participants were also excluded if they did not have a valid provincial health insurance number, because this information was required for linkage to administrative data. All participants provided written informed consent and received $15 for their participation.

For the purposes of recruitment, families were considered as units. In instances in which 2 adults of the same family unit were present, we randomly selected 1 adult for inclusion in the analysis. Of the 2516 single adults and family units we screened, 882 (35%) were ineligible to participate, an additional 443 (18%) individuals declined to participate, and 2 were identified as duplicate or invalid records. In total, 1189 adults were included in the study, corresponding to a response rate of 73%.

Survey Instrument

Predisposing, enabling, and need factors were assessed using structured, in-person interviews at baseline within the framework of the Behavioral Model of Health Services Utilization for Vulnerable Populations.18 Predisposing factors included demographic (e.g., age, family status) and social structural characteristics that affected the propensity to use services. Enabling factors included personal, family, and community factors (e.g., social support, perceived barriers to care) that impeded or facilitated health service use. Need factors included symptoms or conditions (e.g., physical or mental health status) that precipitated service use.

We assessed alcohol, drug, and mental health problems using the Addiction Severity Index.19,20 Addiction Severity Index scores were dichotomized for each subscale (≥ 0.17 for alcohol problems, ≥ 0.10 for drug problems, and ≥ 0.25 for mental health problems) using cut-off scores for homeless persons.17 Propensity to underseek care was assessed on a 4-point scale for seeking health care for (1) weight loss of more than 10 pounds in a month when not dieting; (2) shortness of breath with light exercise or light work; (3) chest pain when exercising; (4) loss of consciousness, fainting, or passing out; or (5) bleeding other than nosebleeds and not caused by accident or injury.21 One point was assigned for each symptom rated as “a little important” or “not at all important.”

Competing priorities were based on difficulty in meeting shelter, food, clothing, washing, or bathroom needs over the past 30 days using a 4-point scale.22 Participants were classified as having competing priorities if they responded “usually” to any of the 5 items. Health locus of control, a measure of a person’s belief that their health is determined by their own behavior, was assessed using Form A of the Multidimensional Health Locus of Control (MHLC) instrument for subscales of internal control, external control from powerful others, and external control because of chance.23 Perceived access to financial, instrumental, and emotional social support from informal social networks, based on items adapted from Lam and Rosenheck,24 was dichotomized to indicate the presence or absence of social support.25

Perceived health status was measured using the validated 12-item Short Form (SF-12) Health Survey.26,27 SF-12 physical component summary (PCS) and mental component summary (MCS) scores were calculated according to the publishers’ specifications and were standardized to the general US population (mean = 50; SD = 10), with higher scores representing better overall health status.27 Chronic health conditions were based on items from the National Survey of Homeless Assistance Providers and Clients, and included diabetes; anemia; high blood pressure, heart disease, or stroke; liver problems including hepatitis; arthritis or joint problems; cancer; problems walking; lost limb or other handicap; and HIV infection or AIDS.17

Administrative Data Linkage

Administrative data were accessed through the Institute for Clinical Evaluative Sciences (ICES), an independent, nonprofit organization partially funded by the Ontario Ministry of Health and Long-Term Care. Homeless participants were linked to administrative data using a unique 10-digit provincial health number for eligible individuals under the Ontario Health Insurance Plan. In instances where either the participants’ health number could not be obtained (3% of the sample) or the health number provided was not valid (an additional 3%), we attempted to perform the linkage based on the participant’s first and last name, gender, and date of birth. Overall, linkage was successful for 1165 (98%) of the study participants.

We obtained hospitalization data from the Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD) and the Ontario Mental Health Reporting System (OMHRS). OMHRS was created in October 2005 to capture clinical, administrative, and resource information for all adult inpatient admissions to mental health beds in the province; it includes inpatient admissions to general hospitals with designated adult inpatient mental health beds, as well as inpatient admissions to specialty psychiatric hospitals and provincial psychiatric hospitals. Before October 1, 2005, discharge data for adult inpatient mental health beds were captured in CIHI-DAD. To identify these mental health records in CIHI-DAD, we extracted hospital discharge records in which the most responsible service provider was coded as “psychiatry”; these records were merged with the OMHRS records to create a separate psychiatric hospitalizations data set. Institutions with designated adult inpatient mental health beds that had previously reported to CIHI-DAD were required to report to both CIHI-DAD and OMHRS during a dual reporting period from October 1, 2005, to March 31, 2006 (end of fiscal year). These duplicate psychiatric hospitalization records were identified in CIHI-DAD using an ICES-derived key variable and excluded from the merged data set. Encounters related to pregnancy and childbirth were excluded to eliminate the effect of these discharges on gender-specific differences in hospitalization rates.

Analysis

Hospitalization rates were calculated by dividing the total number of discharges by the total period under observation. Dates of death were obtained from the Registered Persons Database (RPDB) and used to adjust person–time of observation. Rates were calculated separately for medical or surgical and psychiatric discharges. Reasons for medical or surgical hospitalization were derived based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canadian Enhancement (ICD-10-CA) codes for the most responsible diagnosis (i.e., the diagnosis that contributed to the longest duration of stay in hospital).28 Reasons for psychiatric hospitalization were derived based on ICD-10-CA codes for the most responsible diagnosis (for DAD records) or the Diagnostic and Statistical Manual of Mental Disorders, 4th Revision (DSM-IV) diagnostic codes for the primary provisional diagnosis at admission (for OMHRS records).29 ICD-10-CA diagnoses were converted into DSM-IV classifications according to specifications provided in Appendix H of the DSM-IV.29

Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) comparing (1) homeless participants with at least 1 medical or surgical discharge during the study with those without a medical or surgical discharge, and (2) homeless participants with at least 1 psychiatric discharge during the study with those without a psychiatric discharge. Backward stepwise selection was used to identify significant predictors, using P less than .1 as the significance level for entry into the model and P greater than .05 as the significance level for removal. The demographic group variable was forced into all multivariate regression models, regardless of significance. Interaction terms between demographic group and all significant variables were examined to test for effect modification; none of the tested interaction terms were significant. Independent variables were assessed for multicollinearity, and no problems were detected. Social support variables were added to the survey partway through the study enrollment period; consequently, social support data were missing for approximately 20% of participants. These variables were examined in univariate analyses but were not included in multivariate analyses to maximize our analytic sample size. All analyses were performed using SAS 9.2 statistical analysis software (SAS Institute, Cary, NC).

RESULTS

The sample of 1165 homeless adults included 587 (50.4%) single adult men, 296 (25.4%) single adult women, and 282 (24.2%) adults in families who were mostly single mothers accompanied by their dependent children (n = 201/282; 71.3%; Table 1). During the study, 227 (19.5%) participants had a medical or surgical hospitalization and 134 (11.5%) had a psychiatric hospitalization, including 48 (4.1%) who had both a medical or surgical and psychiatric hospitalization. These individuals had a total of 921 hospitalizations during the study, of which 548 (59.5%) were medical or surgical and 373 (40.5%) were psychiatric.

TABLE 1—

Characteristics of Study Participants: Toronto, Ontario, 2005–2009

Characteristic Overall (n = 1165), No. (%) or Mean ±SD Medical/Surgical Hospitalization (n = 227), No. (%) or Mean ±SD Psychiatric Hospitalization (n = 134), No. (%) or Mean ±SD
Predisposing factors
Demographic group
 Single adult men 587 (50.4) 127 (56.0) 70 (52.2)
 Single adult women 296 (25.4) 60 (26.4) 52 (38.8)
 Family adult 282 (24.2) 40 (17.6) 12 (9.0)
Age, y 36.1 ±12.4 40.1 ±13.4 35.6 ±11.4
Lifetime duration of homelessness, y
 < 2 584 (50.1) 106 (46.7) 55 (41.0)
 ≥ 2 581 (49.9) 121 (53.3) 79 (59.0)
Race/ethnicity
 White 650 (55.8) 139 (61.2) 76 (56.7)
 Black 260 (22.3) 36 (15.9) 30 (22.4)
 Aboriginal 96 (8.2) 29 (12.8) 12 (9.0)
 Other visible minorities 159 (13.7) 23 (10.1) 16 (11.9)
Place of birth
 Canada 796 (68.3) 173 (76.2) 97 (72.4)
 Outside Canada 369 (31.7) 54 (23.8) 37 (27.6)
Highest level of education
 ≤ some high school 587 (50.5) 123 (54.2) 72 (53.7)
 High school diploma or equivalent 248 (21.3) 39 (17.2) 25 (18.7)
 ≥ college/vocational training 327 (28.1) 65 (28.6) 37 (27.6)
History of traumatic brain injury 553 (47.6) 115 (50.7) 63 (47.4)
Physical assault in past 12 mo 330 (28.6) 70 (31.1) 35 (26.1)
Sexual assault in past 12 mo 63 (5.5) 20 (8.9) 12 (9.0)
Current smoker 826 (71.0) 173 (76.2) 110 (82.1)
Alcohol problem in past 30 da 339 (29.1) 72 (31.7) 36 (26.9)
Drug problem in past 30 da 458 (39.1) 96 (42.3) 57 (42.5)
Mental health problem in past 30 da 438 (37.6) 91 (40.1) 83 (61.9)
Propensity to underseek care score
 0 670 (57.5) 135 (59.5) 64 (47.8)
 1 228 (19.6) 45 (19.8) 32 (23.9)
 ≥ 2 267 (22.9) 47 (20.7) 38 (28.4)
Enabling factors
Monthly income, Can $
 < 500 562 (49.5) 96 (43.1) 62 (46.6)
 500–999 313 (27.6) 74 (33.2) 47 (35.3)
 ≥ 1000 260 (22.9) 53 (23.8) 24 (18.1)
Has a primary care provider 865 (74.4) 190 (83.7) 107 (79.9)
Unmet need for health care 192 (16.5) 37 (16.3) 23 (17.2)
Unmet need for mental health care 121 (10.5) 28 (12.4) 28 (21.1)
Competing priorities 62 (5.3) 11 (4.9) 10 (7.5)
MHLC internal control subscale score 27.6 ±5.5 27.2 ±6.0 26.2 ±6.3
MHLC external control from chance subscale score 19.6 ±6.4 19.8 ±6.3 19.8 ±6.8
MHLC external control from powerful others subscale score 21.0 ±6.9 22.4 ±6.5 21.9 ±6.5
Social support—loan 647 (68.0) 110 (64.7) 64 (59.3)
Social support—ride to appointment 551 (58.0) 88 (51.8) 48 (44.4)
Social support—suicide 655 (69.5) 114 (67.1) 56 (51.9)
Need factors
PCS-12 score 46.0 ±11.2 41.4 ±12.5 43.7 ±12.1
MCS-12 score 40.7 ±13.2 40.0 ±12.8 38.2 ±12.8
No. of chronic health conditionsb
 None 470 (40.4) 54 (23.8) 49 (36.6)
 1 324 (27.8) 58 (25.6) 34 (25.4)
 2 202 (17.4) 54 (23.8) 25 (18.7)
 ≥ 3 168 (14.4) 61 (26.9) 26 (19.4)

Note. MCS = Mental Component Summary; MHLC = Multidimensional Health Locus of Control; PCS = Physical Component Summary.

a

Alcohol, drug, and mental health problems in the past 30 days were assessed using the Addiction Severity Index.18–20

b

Chronic health conditions include diabetes, anemia, hypertension, heart disease and stroke, liver problems (including chronic viral hepatitis), arthritis or joint problems, cancer, physical handicaps, or HIV/AIDS.

The mean rate of medical or surgical hospitalizations was 0.17 discharges per person-year (SD = 0.79; range = 0.00–14.91 discharges per person-year), and the mean rate of psychiatric hospitalizations was 0.09 discharges per person-year (SD = 0.38; range = 0.00–4.82 discharges per person-year). The mean duration of follow-up was 3.9 years (SD = 0.3 years; range = 1.1–4.3 years). Injuries, poisonings, and other external causes (n = 103) were the most common reasons for medical or surgical hospitalization, whereas schizophrenia and other psychotic disorders (n = 147) were the most common reasons for psychiatric hospitalization (Table 2).

TABLE 2—

Most Responsible Diagnosis for Hospitalization of Study Participants: Toronto, Ontario, 2005–2009

Most Responsible Diagnosisa No. (%)
Medical/surgical hospitalizationsb
 Infectious and parasitic diseases 38 (6.9)
 Neoplasms 23 (4.2)
 Endocrine, nutritional and metabolic diseases 17 (3.1)
 Mental and behavioral disorders 19 (3.5)
 Diseases of the nervous system 18 (3.3)
 Diseases of the circulatory system 48 (8.8)
 Diseases of the respiratory system 48 (8.8)
 Diseases of the digestive system 90 (16.4)
 Diseases of the skin and subcutaneous tissue 23 (4.2)
 Diseases of the musculoskeletal system and connective tissue 32 (5.8)
 Diseases of the genitourinary system 33 (6.0)
 Symptoms, signs and abnormal clinical and laboratory findings 34 (6.2)
 Injury, poisoning and certain other consequences of external causes 103 (18.8)
 Factors influencing health status and contact with health services 14 (2.6)
 Other diagnoses 8 (1.5)
Total 548 (100.0)
Psychiatric hospitalizationsc
 Delirium, dementia, and amnestic and other cognitive disorders 6 (1.6)
 Substance-related disorders 52 (13.9)
 Schizophrenia and other psychotic disorders 147 (39.4)
 Mood disorders 67 (18.0)
 Adjustment disorders 6 (1.6)
 Personality disorders 11 (2.9)
 Other diagnoses 10 (2.7)
 Missing diagnosesd 74 (19.8)
Total 373 (100.0)
a

For Canadian Institute for Health Information Discharge Abstract Database records: based on most responsible diagnosis using International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canadian Enhancement diagnostic codes. For Ontario Mental Health Reporting System (OMHRS) records: based on primary provisional diagnosis at admission using Diagnostic and Statistical Manual of Mental Disorders, 4th Revision diagnostic codes.

b

Among 227 (19.5%) homeless participants with medical or surgical hospitalizations during the study period.

c

Among 134 (11.5%) homeless participants with psychiatric hospitalization during the study period.

d

Before fiscal year 2008–2009, provisional diagnosis at admission was not a mandatory field in OMHRS for hospital stays < 72 hours.

Medical or Surgical Hospitalizations

Family adults, compared with single adult men, were relatively less likely to have a medical or surgical discharge during the study (Table 3). Predisposing factors significantly associated with medical or surgical hospitalization in univariate analyses were older age, Black race/ethnicity (compared with White), birth in Canada, higher monthly incomes, and sexual assault in the past 12 months. Enabling factors significantly associated with medical or surgical hospitalization were having a primary care provider and higher MHLC for external control from powerful others subscale scores. In terms of need factors, participants with lower PCS-12 scores and those with a greater number of chronic health conditions were more likely to have a medical or surgical hospitalization.

TABLE 3—

Odds Ratios (ORs) and 95% Confidence Intervals (CIs) for Predictors of Medical or Surgical Hospitalization: Toronto, Ontario, 2005–2009

Univariate Model
Multivariate Model
Characteristic OR (95% CI) P AOR (95% CI) P
Predisposing factors
Demographic group
 Single adult men (Ref) 1.00 1.00
 Single adult women 0.92 (0.65, 1.30) .639 0.84 (0.58, 1.21) .339
 Family adult 0.60 (0.41, 0.88) .01 0.63 (0.42, 0.96) .031
Age, y 1.03 (1.02, 1.05) < .001
Lifetime duration of homelessness, y
 < 2 (Ref) 1.00
 ≥ 2 1.19 (0.89, 1.59) .249
Race/ethnicity
 White (Ref) 1.00
 Black 0.59 (0.40, 0.88) .01
 Aboriginal 1.59 (0.99, 2.56) .055
 Other visible minorities 0.62 (0.39, 1.01) .052
Place of birth
 Outside Canada (Ref) 1.00 1.00
 Canada 1.62 (1.16, 2.26) .005 1.48 (1.03, 2.12) .035
Highest level of education
 ≤ some high school (Ref) 1.00
 High school diploma or equivalent 0.70 (0.47, 1.05) .082
 ≥ college/vocational training 0.94 (0.67, 1.31) .7
History of traumatic brain injury 1.17 (0.87, 1.56) .302
Physical assault in past 12 mo 1.16 (0.85, 1.60) .352
Sexual assault in past 12 mo 2.01 (1.16, 3.48) .014
Current smoker 1.39 (1.00, 1.95) .053
Alcohol problem in past 30 da 1.17 (0.85, 1.60) .333
Drug problem in past 30 da 1.17 (0.87, 1.57) .306
Mental health problem in past 30 da 1.14 (0.85, 1.53) .388
Propensity to underseek care score
 0 (Ref) 1.00
 1 0.97 (0.67, 1.42) .893
 ≥ 2 0.85 (0.59, 1.22) .374
Enabling factors
Monthly income, Can $
 < 500 (Ref) 1.00
 500–999 1.50 (1.07, 2.11) .019
 ≥ 1000 1.24 (0.86, 1.81) .254
Has a primary care provider 1.99 (1.36, 2.90) < .001 1.77 (1.18, 2.67) .006
Unmet need for health care 0.98 (0.66, 1.45) .92
Unmet need for mental health care 1.27 (0.81, 2.00) .293
Competing priorities 0.89 (0.45, 1.73) .719
MHLC internal control subscale score 0.98 (0.96, 1.01) .214
MHLC external control from chance subscale score 1.01 (0.98, 1.03) .583
MHLC external control from powerful others subscale score 1.04 (1.02, 1.06) < .001 1.03 (1.01, 1.06) .006
Social support—loan 0.83 (0.59, 1.18) .305
Social support—ride to appointment 0.74 (0.53, 1.03) .07
Social support—suicide 0.87 (0.61, 1.25) .453
Need factors
PCS-12 score 0.96 (0.94, 0.97) < .001 0.98 (0.96, 0.99) .003
MCS-12 score 1.00 (0.98, 1.01) .373
No. of chronic health conditionsb
 None (Ref) 1.00 1.00
 1 1.68 (1.12, 2.51) .011 1.46 (0.95, 2.22) .081
 2 2.81 (1.84, 4.28) < .001 2.09 (1.31, 3.33) .002
 ≥ 3 4.39 (2.88, 6.71) < .001 2.59 (1.55, 4.31) < .001

Note. AOR = adjusted odds ratio; MCS = Mental Component Summary; MHLC = Multidimensional Health Locus of Control; PCS = Physical Component Summary.

a

Alcohol, drug, and mental health problems in the past 30 days were assessed using the Addiction Severity Index.19,20

b

Chronic health conditions include diabetes, anemia, hypertension, heart disease and stroke, liver problems (including chronic viral hepatitis), arthritis or joint problems, cancer, physical handicaps, or HIV/AIDS.

In adjusted analyses, family adult status remained significantly and independently associated with medical or surgical hospitalization. Other significant factors included birth in Canada, having a primary care provider, lower MHLC for external control for powerful others subscale scores, lower PCS-12 scores, and a greater number of chronic health conditions.

Psychiatric Hospitalizations

Family adults were also relatively less likely to have a psychiatric hospitalization during the study, whereas single adult women were more likely to have a psychiatric hospitalization compared with single adult men (Table 4). Predisposing factors significantly associated with psychiatric hospitalization in univariate analyses were having a cumulative lifetime duration of homelessness of 2 or more years, being a current smoker, having a mental health problem in the past 30 days, and higher scores for the propensity to underseek care. Enabling factors significantly associated with psychiatric hospitalization were self-reported unmet needs for mental health care, lower MHLC internal control subscale scores, and an absence of social support. In terms of need factors, both lower PCS-12 and lower MCS-12 scores were associated with psychiatric hospitalization.

TABLE 4—

Odds Ratios (ORs) and 95% Confidence Intervals (CIs) for Predictors of Psychiatric Hospitalization: Toronto, Ontario, 2005–2009

Univariate Model
Multivariate Model
Characteristic OR (95% CI) P AOR (95% CI) P
Need factors
Demographic group
 Single adult men (Ref) 1.00 1.00
 Single adult women 1.57 (1.07, 2.32) .023 1.49 (0.99, 2.26) .059
 Family adult 0.33 (0.18, 0.62) < .001 0.36 (0.18, 0.69) .002
Age, y 1.00 (0.98, 1.01) .601
Lifetime duration of homelessness, y
 < 2 (Ref) 1.00
 ≥ 2 1.51 (1.05, 2.18) .026
Race/ethnicity
 White (Ref) 1.00
 Black 0.99 (0.63, 1.54) .948
 Aboriginal 1.08 (0.56, 2.07) .819
 Other visible minorities 0.85 (0.48, 1.49) .562
Place of birth
 Outside Canada (Ref) 1.00
 Canada 1.25 (0.83, 1.86) .283
Highest level of education
 ≤ some high school (Ref) 1.00
 High school diploma or equivalent 0.80 (0.50, 1.30) .369
 ≥ college/vocational training 0.91 (0.60, 1.39) .671
History of traumatic brain injury 0.99 (0.69, 1.42) .957
Physical assault in past 12 mo 0.87 (0.58, 1.31) .5
Sexual assault in past 12 mo 1.89 (0.98, 3.65) .057
Current smoker 2.01 (1.27, 3.19) .003 1.78 (1.08, 2.95) .025
Alcohol problem in past 30 da 0.88 (0.59, 1.32) .545
Drug problem in past 30 da 1.16 (0.81, 1.68) .417
Mental health problem in past 30 da 3.10 (2.14, 4.49) < .001 2.74 (1.86, 4.03) < .001
Propensity to underseek care score
 0 (Ref) 1.00
 1 1.55 (0.98, 2.43) .06
 ≥ 2 1.57 (1.02, 2.41) .039
Enabling factors
Monthly income, Can $
 < 500 (Ref) 1.00
 500–999 1.43 (0.95, 2.14) .088
 ≥ 1000 0.82 (0.50, 1.35) .433
Has a primary care provider 1.42 (0.91, 2.21) .125
Unmet need for health care 1.05 (0.65, 1.70) .832
Unmet need for mental health care 2.67 (1.67, 4.26) < .001
Competing priorities 1.52 (0.75, 3.06) .245
MHLC internal control subscale score 0.95 (0.92, 0.98) .002 0.95 (0.92, 0.98) .003
MHLC external control from chance subscale score 1.00 (0.98, 1.03) .753
MHLC external control from powerful others subscale score 1.02 (1.00, 1.05) .107
Social support—loan 0.65 (0.43, 0.98) .039
Social support—ride to appointment 0.54 (0.36, 0.81) .003
Social support—suicide 0.42 (0.28, 0.64) < .001
Need factors
PCS-12 score 0.98 (0.97, 1.00) .012
MCS-12 score 0.98 (0.97, 1.00) .018
No. of chronic health conditionsb
 None (Ref) 1.00
 1 1.01 (0.63, 1.60) .975
 2 1.21 (0.73, 2.03) .459
 ≥ 3 1.57 (0.94, 2.63) .083

Note. AOR = adjusted odds ratio; MCS = Mental Component Summary; MHLC = Multidimensional Health Locus of Control; PCS = Physical Component Summary.

a

Alcohol, drug, and mental health problems in the past 30 days were assessed using the Addiction Severity Index.19,20

b

Chronic health conditions include diabetes, anemia, hypertension, heart disease and stroke, liver problems (including chronic viral hepatitis), arthritis or joint problems, cancer, physical handicaps, or HIV/AIDS.

In adjusted analyses, family adult status remained significantly and independently associated with psychiatric hospitalization during the study. The association between single adult women and psychiatric hospitalization was marginally significant in adjusted analyses. Current smokers, those who had mental health problems, and those who had lower MHLC internal control subscale scores had significantly higher odds of psychiatric hospitalization in adjusted analyses.

DISCUSSION

In this study, we examined predisposing, enabling, and need factors associated with medical or surgical and psychiatric discharges from inpatient care among a population-based cohort of homeless adults under a system of universal health insurance. We found that 20% participants had a medical or surgical discharge and 12% had a psychiatric discharge over the course of the study, corresponding to an average annual rate of 0.17 discharges per person-year for medical or surgical hospitalizations and 0.09 discharges per person-year for psychiatric hospitalizations. These findings were consistent with self-reported rates of overnight hospitalization in the past year, which ranged from 10% to 30% among homeless populations,1,3–5 and were considerably higher than annual age-standardized acute inpatient hospitalization rates of 7% for the general population of Ontario.30

Our findings showed that homeless adults in families, predominantly homeless women accompanied by their dependent children, were less likely to be hospitalized compared with single adult men. The association was stronger for psychiatric discharges. Homeless families in our study, compared with single men and women, possessed fewer predisposing, enabling, and need factors that influenced the likelihood of health services use. Homeless families in our sample were younger, were homeless for shorter durations of time, were more likely to be minorities or immigrants, had more education and higher monthly incomes, had fewer chronic health conditions, and were less likely to have recent mental health or substance use problems.31 Together with previous work, these findings suggested that homeless families were a distinct population who were healthier overall and might have had less need for health services, perhaps reflecting a lower burden of physical and psychiatric illness.32 Alternatively, homeless families might have been recruited into our study when they were experiencing temporary or episodic homelessness and might not have been exposed to the same degree of physical, mental or emotional, and social stressors as their single adult counterparts who experienced long-term homelessness.9,33 However, the inverse association between family status and hospitalization remained significant even after adjusting for predisposing, enabling, and need factors, suggesting the presence of other, possibly unmeasured, factors that might confound this relationship. Immigrants in our study were also less prone to medical or surgical hospitalization during the study. As with homeless families, recent immigrants might be a distinct subgroup of the homeless population who tended to be healthier with less need for health services.14 A similar protective effect of immigrant status was observed for emergency department visits.34

Homeless participants who had a primary care provider tended to have a higher likelihood of medical or surgical hospitalization. This finding was contrary to studies of nonhomeless populations that showed that continuity of care might prevent hospitalization.35,36 The contradictory finding might be a result because having a primary care provider improved access to inpatient acute care for homeless adults, independent of the effects of health status. Alternatively, having a primary care provider might serve as a marker for more serious, complex health conditions that require frequent management in primary care settings. Participants who had stronger beliefs that their health was under external control by powerful others—for example, physicians—were also more likely to have a medical or surgical hospitalization.23 This finding again highlighted the important association between having a primary care provider and the likelihood of hospitalization.

Not surprisingly, need factors were strong predictors of medical or surgical hospitalization. These factors were also associated with the likelihood of psychiatric hospitalization in univariate analyses, although they did not remain significant in the final multivariate model. For psychiatric hospitalization, having a mental health problem in the past month was the strongest predictor of hospitalization in adjusted analyses. These findings were consistent with previous research that suggested that substance abuse and mental illness together account for the majority of hospitalizations among homeless persons.37,38 Hospitalizations because of substance abuse and mental illness, as well as preventable conditions such as injuries, poisonings, and other circumstances of external causes, were the primary reasons for medical or surgical and psychiatric hospitalizations in this study.

Current smoking status was also associated with an increased likelihood of psychiatric hospitalization, a somewhat surprising finding, but one that might indicate that substance use was a coping mechanism for mental health problems. The extremely high smoking rates among study participants (> 70%) was notable, given that only 17% of Canadians report being current smokers.39 Finally, participants who believed that their health status was the result of their own behavior, as opposed to chance or external control from others, had a decreased likelihood of psychiatric hospitalization.23

Limitations

Certain limitations to this study should be acknowledged. Health care utilization was assessed using administrative data in Ontario; as such, hospitalizations that occurred out-of-province might have been missed. Predictors of hospitalization were assessed at 1 point in time using a cross-sectional survey and could not be assumed to be constant for the entire duration of follow-up. The sampling strategy excluded individuals who did not use shelters or meal programs; however, previous research suggested that this unsheltered homeless population in Toronto was very small.40 Homeless participants were required to have a valid provincial health number, which might have biased the sample toward individuals who had better health care access. Furthermore, 18% of homeless individuals who were screened declined to participate, which might have decreased the representativeness of the sample.

Conclusions

The frequent use of inpatient services among homeless persons could have considerable consequences for the health care system, such as longer inpatient stays and higher attributable costs.37,41 In this study, poor health status and the presence of mental health problems were strong predictors of medical or surgical and psychiatric hospitalizations, respectively. The findings also suggested that many of these hospitalizations were potentially avoidable, particularly for medical or surgical hospitalizations in which the largest number of diagnoses could be attributed to injuries, poisonings, and other external causes. By contrast, the large number of psychiatric hospitalizations for schizophrenia and other psychotic disorders might represent a necessary and unavoidable use of mental health services. Improved access to primary and preventative health services for homeless individuals as well as improvements to their social circumstances and living situations, including access to affordable and stable housing,37,41 merit further consideration. Doing so has the potential to reduce the use of costly inpatient health care.

Acknowledgments

This project was supported by operating grants from the Agency for Healthcare Research and Quality (1 R01 HS014129-01) and the Canadian Institutes of Health Research (MOP-62736), and by an Interdisciplinary Capacity Enhancement grant on Homelessness, Housing, and Health from the Canadian Institutes of Health Research (HOA-80066). This study was supported by the Institute for Clinical Evaluative Sciences (ICES) and the Centre for Research on Inner City Health, which are funded by annual grants from the Ontario Ministry of Health and Long-Term Care.

Note. The funders had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the article. The opinions, results and conclusions reported in this article are the views of the authors and do not necessarily reflect the views of any of the previously named organizations. No endorsement by ICES or the Ontario Ministry of Health and Long-Term Care should be intended or inferred.

Human Participant Protection

This study was approved by the Research Ethics Board at St. Michael’s Hospital, Toronto. All participants provided written informed consent.

References

  • 1.Kushel MB, Vittinghoff E, Haas JS. Factors associated with the health care utilization of homeless persons. JAMA. 2001;285(2):200–206. doi: 10.1001/jama.285.2.200. [DOI] [PubMed] [Google Scholar]
  • 2.Hwang SW, Dunn JR. Homeless people. In: Galea S, Vlahov D, editors. Handbook of Urban Health: Populations, Methods, and Practice. New York, NY: Springer; 2005. pp. 21–41. [Google Scholar]
  • 3.Khandor E, Mason K. The Street Health Report 2007. Toronto, ON: Street Health; 2007. [Google Scholar]
  • 4.Kushel MB, Gupta R, Gee L, Haas JS. Housing instability and food insecurity as barriers to health care among low-income Americans. J Gen Intern Med. 2006;21(1):71–77. doi: 10.1111/j.1525-1497.2005.00278.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Lim YW, Andersen R, Leake B, Cunningham W, Gelberg L. How accessible is medical care for homeless women? Med Care. 2002;40(6):510–520. doi: 10.1097/00005650-200206000-00008. [DOI] [PubMed] [Google Scholar]
  • 6.Lewis JH, Andersen RM, Gelberg L. Health care for homeless women. J Gen Intern Med. 2003;18(11):921–928. doi: 10.1046/j.1525-1497.2003.20909.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Weinreb L, Perloff J, Goldberg R, Lessard D, Hosmer DW. Factors associated with health service utilization patterns in low-income women. J Health Care Poor Underserved. 2006;17(1):180–199. doi: 10.1353/hpu.2006.0036. [DOI] [PubMed] [Google Scholar]
  • 8.Kushel MB, Perry S, Bangsberg D, Clark R, Moss AR. Emergency department use among the homeless and marginally housed: results from a community-based study. Am J Public Health. 2002;92(5):778–784. doi: 10.2105/ajph.92.5.778. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.O’Toole TP, Gibbon JL, Hanusa BH, Fine MJ. Utilization of health care services among subgroups of urban homeless and housed poor. J Health Polit Policy Law. 1999;24(1):91–114. doi: 10.1215/03616878-24-1-91. [DOI] [PubMed] [Google Scholar]
  • 10.Padgett DK, Struening EL, Andrews H, Pittman J. Predictors of emergency room use by homeless adults in New York City: the influence of predisposing, enabling and need factors. Soc Sci Med. 1995;41(4):547–556. doi: 10.1016/0277-9536(94)00364-y. [DOI] [PubMed] [Google Scholar]
  • 11.Ku BS, Scott KC, Kertesz SG, Pitts SR. Factors associated with use of urban emergency departments by the U.S. homeless population. Public Health Rep. 2010;125(3):398–405. doi: 10.1177/003335491012500308. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.D’Amore J, Hung O, Chiang W, Goldfrank L. The epidemiology of the homeless population and its impact on an urban emergency department. Acad Emerg Med. 2001;8(11):1051–1055. doi: 10.1111/j.1553-2712.2001.tb01114.x. [DOI] [PubMed] [Google Scholar]
  • 13.Hwang SW, Colantonio A, Chiu S et al. The effect of traumatic brain injury on the health of homeless people. CMAJ. 2008;179(8):779–784. doi: 10.1503/cmaj.080341. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Chiu S, Redelmeier DA, Tolomiczenko G, Kiss A, Hwang SW. The health of homeless immigrants. J Epidemiol Community Health. 2009;63(11):943–948. doi: 10.1136/jech.2009.088468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Hwang SW, Ueng JJ, Chiu S et al. Universal health insurance and health care access for homeless persons. Am J Public Health. 2010;100(8):1454–1461. doi: 10.2105/AJPH.2009.182022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Hwang SW, Chiu S, Kiss A et al. Use of meal programs and shelters by homeless people in Toronto (abstract) J Urban Health. 2005;82(Suppl 2):ii46. [Google Scholar]
  • 17.Burt MR, Aron LY, Douglas T . Homelessness: Programs and the People They Serve. Findings of the National Survey of Homeless Assistance Providers and Clients (Rep. No. 6-2-6-3) Washington, DC: Interagency Council on the Homeless; 1999. [Google Scholar]
  • 18.Gelberg L, Andersen RM, Leake BD. The behavioral model for vulnerable populations: application to medical care use and outcomes for homeless people. Health Serv Res. 2000;34(6):1273–1302. [PMC free article] [PubMed] [Google Scholar]
  • 19.McGahan PL, Griffith JA, Parente R, McLellan AT. Addiction Severity Index: Composite Scores Manual. Philadelphia, PA: The University of Pennsylvania/Veterans Administration Centre for Studies of Addiction; 1986. [Google Scholar]
  • 20.McLellan AT, Kushner H, Metzger D et al. The fifth edition of the Addiction Severity Index. J Subst Abuse Treat. 1992;9(3):199–213. doi: 10.1016/0740-5472(92)90062-s. [DOI] [PubMed] [Google Scholar]
  • 21.Bindman AB, Grumbach K, Osmond D et al. Preventable hospitalizations and access to health care. JAMA. 1995;274(4):305–311. [PubMed] [Google Scholar]
  • 22.Gelberg L, Gallagher TC, Andersen RM, Koegel P. Competing priorities as a barrier to medical care among homeless adults in Los Angeles. Am J Public Health. 1997;87(2):217–220. doi: 10.2105/ajph.87.2.217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Wallston KA, Wallston BS, DeVellis R. Development of the Multidimensional Health Locus of Control (MHLC) Scales. Health Educ Monogr. 1978;6(2):160–170. doi: 10.1177/109019817800600107. [DOI] [PubMed] [Google Scholar]
  • 24.Lam JA, Rosenheck R. Social support and service use among homeless persons with serious mental illness. Int J Soc Psychiatry. 1999;45(1):13–28. doi: 10.1177/002076409904500103. [DOI] [PubMed] [Google Scholar]
  • 25.Hwang SW, Kirst MJ, Chiu S et al. Multidimensional social support and the health of homeless individuals. J Urban Health. 2009;86(5):791–803. doi: 10.1007/s11524-009-9388-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Larson CO. Use of the SF-12 instrument for measuring the health of homeless persons. Health Serv Res. 2002;37(3):733–750. doi: 10.1111/1475-6773.00046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Ware JE, Kosinski M, Keller D. SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales. Vol 2. Boston, MA: The Health Institute; 1995. New England Medical Center. [Google Scholar]
  • 28.Canadian Institute for Health Information. International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10-CA) Ottawa, ON: Canadian Institute for Health Information; 2006. [Google Scholar]
  • 29.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) Arlington, VA: American Psychiatric Association; 2000. [Google Scholar]
  • 30.Canadian Institute for Health Information. Highlights of 2007–2008 Inpatient Hospitalizations and Emergency Department Visits. Ottawa, ON: Canadian Institute for Health Information; 2008. [Google Scholar]
  • 31.Hwang SW, Chambers C, Chiu S et al. A comprehensive assessment of health care utilization among homeless adults under a system of universal health insurance. Am J Public Health. doi: 10.2105/AJPH.2013.301369. In press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Chambers C, Chiu S, Scott AN et al. Factors associated with poor mental health status among homeless women with and without dependent children. Community Ment Health J. 2013 doi: 10.1007/s10597-013-9605-7. Epub ahead of print, February 20, 2013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Kertesz SG, Larson MJ, Horton NJ, Winter M, Saitz R, Samet JH. Homeless chronicity and health-related quality of life trajectories among adults with addictions. Med Care. 2005;43(6):574–585. doi: 10.1097/01.mlr.0000163652.91463.b4. [DOI] [PubMed] [Google Scholar]
  • 34.Chambers C, Chiu S, Katic M et al. High utilizers of emergency health services in a population-based cohort of homeless adults. Am J Public Health. doi: 10.2105/AJPH.2013.301397. In press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Gill JM, Mainous AG., 3rd The role of provider continuity in preventing hospitalizations. Arch Fam Med. 1998;7(4):352–357. doi: 10.1001/archfami.7.4.352. [DOI] [PubMed] [Google Scholar]
  • 36.Saultz JW, Lochner J. Interpersonal continuity of care and care outcomes: a critical review. Ann Fam Med. 2005;3(2):159–166. doi: 10.1370/afm.285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Salit SA, Kuhn EM, Hartz AJ, Vu JM, Mosso AL. Hospitalization costs associated with homelessness in New York City. N Engl J Med. 1998;338(24):1734–1740. doi: 10.1056/NEJM199806113382406. [DOI] [PubMed] [Google Scholar]
  • 38.Martell JV, Seitz RS, Harada JK, Kobayashi J, Sasaki VK, Wong C. Hospitalization in an urban homeless population: the Honolulu Urban Homeless Project. Ann Intern Med. 1992;116(4):299–303. doi: 10.7326/0003-4819-116-4-299. [DOI] [PubMed] [Google Scholar]
  • 39.Health Canada. Canadian Tobacco Use Monitoring Survey (CTUMS) 2011. Available at: http://www.hc-sc.gc.ca/hc-ps/tobac-tabac/research-recherche/stat/ctums-esutc_2011-eng.php. Accessed June 21, 2013. [Google Scholar]
  • 40.City of Toronto. Street Needs Assessment Results. Toronto: Shelter, Support, and Housing Administration, City of Toronto; 2009. [Google Scholar]
  • 41.Hwang SW, Weaver J, Aubry T, Hoch JS. Hospital costs and length of stay among homeless patients admitted to medical, surgical, and psychiatric services. Med Care. 2011;49(4):350–354. doi: 10.1097/MLR.0b013e318206c50d. [DOI] [PubMed] [Google Scholar]

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