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  ORIGINAL PAPER The Reality of Homeless Mobility and Implicationsfor Improving Care R. David Parker  ã Shana Dykema Published online: 15 March 2013   Springer Science+Business Media New York 2013 Abstract  Homeless persons are perceived as a highlymobile population, and have high rates of co-morbid con-ditions, including mental health and substance use issues.This study sought to determine the characteristics of themobility and reported health conditions of homeless per-sons. The sample for this cross sectional study ( n  =  674)accounted for 88 % of the homeless population in a mediumsized southern city in the United States. Participants wererecruited from a homeless shelter operating during thewinter season. Homeless persons were less mobile than thegeneral state population (46.11 % were born in-state vs.40.7 % of the general population) and less transient than thegeneral state population (78 % reported an in-state zip codefor the last permanent residence). 31.9 % reported a dis-abling condition of a serious and long term nature. Thesefindings challenge the concept that homeless persons areprimarily a mobile population. Furthermore, homeless per-sons in this sample were more likely to remain in the statewhere they lived after becoming homeless. Thus, providerperceptions that homeless persons would not benefit fromreferral to a regular source of outpatient care may be mis-informed. As homeless persons often seek care in emer-gency departments for conditions that could be addressedthrough outpatient care, if a medical care system imple-mentedstandardpracticesspecificallyforhomelesspatients,this could decrease recidivism. Such interventions representsignificantopportunitiestoreducecosts,conserveresources,and improve care through policy modification that ensures afocus on a successful, active linkage to outpatient care andprograms specific to the homeless population. Keywords  Homeless persons    Emergency medicine   Health planning    Health services research Introduction Homelessness remains a significant social challenge in theUnited States. According to data from the Annual Home-less Assessment Report (AHAR) compiled by the Housingand Urban Development (HUD), 1,502,196 persons expe-rienced homelessness in the United States in 2011 [25].This means that homelessness is more prevalent (0.48 %)in the United States than any of leading causes of death,including heart disease, cancer, and stroke [24, 9]. Unlike these illnesses, there is no national health-based campaignagainst homelessness, despite its intricate ties to publichealth.Homelessness is not commonly identified as a healthproblem, yet it is both an etiologic factor and outcome of multiple health issues, directly and indirectly [5, 7, 26]. Homeless persons are more likely to have comorbid con-ditions, poorer health outcomes, and decreased access tohealth care than other population subgroups [2, 6, 8, 19, 20]. Among homeless persons who were sheltered duringthe previous year ( n  =  1,593,794), nearly 43 % reported adisabling health condition [25]. As many homeless personsare uninsured or underinsured, any problems accessing careare further exacerbated by the fact that a relatively smallnumber of health care systems in the United States aredesigned to provide consistent care for these persons. Ahealthcare system’s efficacy tends to decrease when R. D. Parker ( & )    S. DykemaDepartment of Medicine, University of South CarolinaSchool of Medicine, 2 Medical Park, Suite 502,Columbia, SC 29203, USAe-mail: david.parker@uscmed.sc.eduS. Dykemae-mail: shana.dykema@uscmed.sc.edu  1 3 J Community Health (2013) 38:685–689DOI 10.1007/s10900-013-9664-2  attempting to provide support to large numbers of unin-sured persons who also lack stable housing, especiallywhen those patients have active mental illness issues,addiction issues, or chronic health conditions [7]. Becauseof many of these challenges, homeless persons are muchmore likely to present to the emergency department (ED)for their medical care, which can worsen ED overcrowding[2, 6, 10, 13, 15, 18, 19, 22]. Not only does homelessness have a major impact onhealthcare systems, but the reverse is also true: healthcaresystems can have negative impacts on homeless persons [7].The cumulative effects of errors and delays in medical carecan have a negative compounding effect on homeless per-sons,whomayexperiencebarrierstoaccessingmedicalcareor have difficulty navigating complex systems. In this light,medical care systems, both inpatient and outpatient, presentchallenges for homeless persons. Active and executedreferrals to outpatient care could greatly reduce emergencydepartment (ED) use; however, the lack of outpatient caresystems designed to effectively engage homeless personscontributes to the documented ED overuse and lack of continuity of medical care for homeless persons [14].The relocation and mobility of homeless persons is notwell studied, with relatively few published articles in thelast decade. Older research has indicated that the homelesspopulation is highly mobile, which could lead to problemswith access to care and continuity of care [1, 3, 17]. The few more recent articles have indicated that the idea of homeless mobility may be attributable to anecdotal evi-dence which has created and perpetuated the stereotype of the ‘‘homeless transient’’ [12, 22]. Empirical research on this subject is needed to informhealth care systems. This project seeks to increase theunderstanding in this area and to describe the mobilitycharacteristics of a homeless population so that providersmay use this knowledge to improve health care delivery tothem. Since it has been shown that the homeless are morelikely to use the ED for care, this research may informpolicies leading to more active linkage of homeless personsto outpatient primary care, as well as increasing continuityof care over a homeless patient’s course of treatment. Methods This study was approved by the University of South Car-olina’s Institutional Review Board (IRB). This cross sec-tional study recruited a convenience sample of homelesspersons from a homeless registry retained from the city’slargest homeless shelter. Deidentified data from all personswho stayed in the shelter between November 1, 2009 andMarch 31, 2010 were included. Data were extracted fromthe Service Point Homeless Management InformationSystem (HMIS) system and STATA 10 IC was used foranalyses. We defined ‘‘mobility’’ as relocation from thestate of birth, and ‘‘transience’’ as relocation post-homelessness.Sociodemographic data included sex, age, race, ethnic-ity, veteran status, income, income source, non-cashincome, employment status, highest level of education,domestic violence status, total monthly income, disabilitystatus, years of residence in city/state, and insurance status.Homeless information included prior housing situation,length of stay, current housing status, extent of homeless-ness (frequency and duration), chronic homeless status,primary and secondary reasons for homelessness, and zipcode of last permanent residence. Chronic homelessnesswas defined by Housing and Urban Development (HUD) asfour or more occurrences of homelessness in the last 3 yearsor 1 year or more of homelessness among an unaccompa-nied adult with a disabling condition. Since participants andstudy staff may not have understood this definition, thisvariable was operationalized during data collection.For univariate analyses, Chi square tests were used toanalyze differences among categorical variables and t-testswere used for numeric data. If the cell sizes were small, thenthe nonparametric equivalent was usedtoincrease statisticalreliability. Logistic regression was conducted in multivari-able analyses with - 2 log likelihood ratio tests to comparemodels ensuring adherence to the rule of parsimony. Results Demographics are presented in Table 1. Participants( n  =  674) were primarily (79.53 %) male. 112 persons(16.62 %) reported military service. A majority (62.76 %)identified their primary race as Black American. Less thanhalf (36.80 %) were high school graduates or equivalent,and nearly one-third (31.90 %) reported a disabling condi-tion. The median age was 45.37 years. Criminal domesticsurvivorship was reported among almost one-third of women ( n  =  40, 31.25 %), versus 3.72 % ( n  =  20) of men.Homeless markers are reported in Table 2. Over one-third ( n  =  260, 38.58 %) reported ‘‘first time homeless’’and one quarter ( n  =  171, 25.37 %) reported ‘‘one or twoepisodes of homelessness.’’ Chronic homelessness wasreported by 28.93 % of participants. Almost half of par-ticipants ( n  =  308, 45.70 %) were born in-state, while thegeneral adult population reports 40.7 % of persons wereborn in-state [16]. The majority of persons sur-veyed ( n  =  519, 77.02 %) also lived in South Carolinawhen they became homeless. The most commonly reportedprior living situations were outdoors ( n  =  141, 20.92 %), ashelter ( n  =  129, 19.14 %), staying with family ( n  =  96,14.39 %) and staying with friends ( n  =  76, 11.38 %). 686 J Community Health (2013) 38:685–689  1 3  Common reasons for homelessness included un/under-employed/low income ( n  =  199, 29.53 %) and loss of job( n  =  93, 13.80 %) along with lack of affordable housing(9.13 %). A chronic medical condition was reported among5.24 % ( n  =  35) of participants. Men were more likely toreport military service ( v 2 (1)  =  18.94,  p \ 0.01) and instate birth ( v 2 (1)  =  6.74,  p  =  0.03) than women.Logistic regressions were modeled for in state birth aswell as further comparisons between in-state born partici-pants and out-of-state born participants. The odds of beingborn in South Carolina for men were 1.68 times that of theodds for in-state birth among women [95 % CI (1.13,2.49)]. The logistic regression used to explore differencesbetween participants born in state and out of state includedthe covariates: chronic homelessness, gender, and primaryrace. The findings are provided in Table 3. While con-trolling for the presence of each variable, statistically sig-nificant findings indicated that persons born in state were1.52 times more likely to be chronically homeless [95 % CI(1.06, 2.18)], male [OR  =  1.75, 95 % CI (1.14, 2.66)], andBlack American [2.87, 95 % CI (2.01, 4.09)]. Discussion This study found that homeless persons were actually lessmobile and less transient than the general state population,with 45.70 % of the homeless born in-state and 78 %reporting their last permanent residence before becoming Table 1  Basic demographics ( n  =  674)Measure N PercentMedian age: 45.37 yearsSexMale 536 79.79Female 132 19.61Missing/omitted 6 0.60Veteran statusNon-veteran 542 80.42Veteran 112 16.62Missing/omitted 20 2.96Primary raceBlack American 426 62.76White American 213 31.60Other 38 5.64Hispanic/Latino ethnicityNo 633 93.92Yes 18 2.67Missing/omitted 23 3.41Survivor of criminal domestic violenceNo 593 87.98Yes 60 8.90Missing/omitted 21 3.12Report of a disabilityNo 449 66.62Yes 215 31.90Missing/omitted 10 1.48Born in-stateNo 366 54.30Yes 308 45.70 Table 2  Overview of homelessness ( n  =  674)Measure N PercentZip code of residence at homeless onsetIn-state 519 77.00Out-of-state 149 22.11Missing/omitted 6 0.89Chronically homeless a No 475 70.47Yes 195 28.93Missing/omitted 4 0.59Extent of homelessnessFirst time 260 38.581–3 times in past 173 25.674 times or more in past 3 years 97 14.391 year or more 123 18.25Missing/omitted 21 3.12Prior living situationOutdoors 141 20.92Emergency shelter 129 19.14Staying with family/friends 172 33.53Renting apartment 47 6.97Owned their own home 40 4.94Jail/prison 29 4.30Other b 116 17.21Primary reason for homelessnessUnderemployed or low income 199 29.53Loss of job 93 13.80No affordable housing 61 9.13Medical condition 35 5.24Other c 286 42.43 a ‘‘Chronically homeless’’: unaccompanied individual with a dis-abling condition who has been continuously homeless for a year ormore OR has had at least four episodes of homelessness in the past3 years (HUD definition) b ‘‘Other’’ includes: car, care home, doubled up, foster care, hospital,hotel/motel, place not for habitation, psychiatric hospital, refused,substandard structure, subsidized housing, substance abuse treatmentfacility, transitional housing, and missing c ‘‘Other’’ includes: criminal activity, domestic violence, health/ safety, loss of child care, loss of public assistance, loss of transpor-tation, mental health issues, foreclosure, substandard housing, sub-stance abuse, released from institution, eviction, and missingJ Community Health (2013) 38:685–689 687  1 3  homeless as in-state. These findings challenge the popularstereotype of a highly mobile homeless population. Thesefindings may help dispel the notion among health careproviders that as a result of their mobility and transience,homeless persons are unlikely to follow up on their medicalcare or outside referrals.Homeless persons who were born in-state were morelikely to be chronically homeless, male, and Black Amer-ican. The chronically homeless have been found to havefewer financial resources, poorer physical and mentalhealth outcomes, and less family support [2]. Their lowerlevels of social support and socioeconomic status mayincrease retention in the state of birth, as these persons maylack the necessary resources to relocate. Additionally, thelack of financial stability may affect their choice of whereto seek medical care, as the chronically homeless are morelikely to utilize the ED [6, 18]. If the perception among clinicians, especially in the ED,is that homeless persons would not benefit from referral toa regular outpatient source of primary care, one interven-tion to combat ED overuse by the homeless is providereducation. Standard practice in many EDs is to advise thepatient to return in case the symptoms that brought them tothe ED persist [4, 11, 21]. However, if patients are pre- senting for non-emergent care issues and are encouraged toreturn because providers do not believe they will follow upwith their care elsewhere, this could create an unendingdependence on ED use and exacerbate overcrowdingissues. Thus, an effective intervention for health caredelivery systems could be an intentional effort to activelyrefer these patients to outpatient care providers and retainthose patients there once referred, ensuring continuity of care. Active referral to non-ED sources of care could alsoresult in significant cost savings, both for the organizationand the health care system as a whole [23, 18]. In the US, the Federally Qualified Health Center (FQHC) System iscomprised of publicly funded centers which see patients onan income based sliding fee scale. In many communities,these clinics also receive funding to provide health care forhomeless individuals, and are therefore primed to beinvolved in such interventions, as well as future research onhealth care provision for the homeless.Considering the individual barriers to care among thehomeless such as cost, transportation, and socialstigma, anyintervention aimed at increasing homeless patients’involvement in medical care while funneling them to moreappropriatesourcesofsaidcaremustbepatient-centeredandprovide real time referrals. Since nurses are the primaryprovidersresponsiblefordischargeplanningininpatientandoutpatient settings, an intervention should be designed toalso be clinician focused. Any such intervention to increaseoutpatient primary care for the homeless would require asignificantemphasisonandcommitmenttocommunication,integration and sharing of resources and responsibilities.There are limitations to this study based on the studydesign, including the convenience sampling method. Thecross-sectional methodology means that we were unable toestablish causation. Convenience sampling increases thepotential for bias versus random sampling; however, thesample to population percentage of this project (88 %)should mitigate bias in the population within the city.Additionally, given the high percentage of sample to pop-ulation, generalizability to other homeless populations insimilar cities may be valid, though any extrapolation shouldbe done with caution. Another limitation was the ability of the multivariable logistic regression model to fit the data.While the associations were strong, these data only accountfor 5 % of the variability in the data to explain whether ornot a person is born in state. This indicates that there areother influencing factors not explored in this project whichwould more stronglyaccountfor the reasons that a homelessperson remains in his/her state of srcin.Future research should further evaluate concepts of active engagement and direct intervention by shiftingtreatment for non-acute and chronic care to outpatient careproviders. Research could include a prospective cohort of homeless persons measured on multiple markers to includehealth, service access, mobility and other key factors thatcould improve care. Acknowledgments  Research was funded by the City of Columbia,SC. Conflict of interest  The authors report no conflict of interest. References 1. Bachrach, L. L. (1987). Geographic mobility and the homelessmentally ill.  Hospital & Community Psychiatry, 38 , 27–28.2. Baggett, T. P., O’Connell, J. J., Singer, D. E., & Rigotti, N. A.(2010). The unmet health care needs of homeless adults: Anational study.  American Journal of Public Health, 100 (7),1326–1333. Table 3  Final reduced logistic regression comparing in-state birth toout-of-state birthVariable OddsratioStandarderror  p  value 95 % CIChronically homeless a 1.52 0.28 0.02 (1.06, 2.18)Male sex b 1.75 0.38 0.01 (1.14, 2.66)Black American race c 2.87 0.51 0.00 (2.01, 4.09) a Reference group: non-chronically homeless b Reference group: female sex c Reference group: non-Black American race688 J Community Health (2013) 38:685–689  1 3
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