To our knowledge, this is the first study that explores differences in LOS between IEH and housed individuals in both the ED and inpatient setting. It is also the first study to explore how these differences vary by demographics and the principle diagnoses that prompted acute care use. In keeping with previous studies, we found that a disproportionately high prevalence of IEH in the ED and admitted to hospital were men between the ages of 25 and 34, where the majority of individuals experiencing homelessness in the community are between the ages of 45–64 [24]. Most were admitted to hospital for substance-related concerns. On average, IEH spent 1.62 more hours in the ED and 3.02 more days in hospital than housed individuals. This average increase in inpatient LOS for IEH is slightly lower than a previous study from New York (where LOS for IEH was 4.1 more days than for housed individuals) but is in keeping with a Canadian study which found a mean difference of 2.32 days in LOS between IEH and those who are housed [11–12].
The trend towards increased ED and hospital LOS was consistent across many diagnoses, many of which have little physiologic or clinical overlap. This suggests that the increased LOS in IEH may be more attributable to their underlying state of homelessness rather than factors related to the particular medical diagnoses. There were surprisingly two diagnoses that were associated with increased LOS for HI compared to IEH including depression, and blood alcohol and drug tests. These differences appear small and of questionable clinical significance.
By exploring the differences in ED LOS, our study highlights potential points of intervention to optimize ED workflow and bed occupancy. Within ED, IEH contribute to reduced work flow, leading to ED crowding which has been associated with decreased quality of care, delays in treatment commencement, and increased mortality [25]. The majority of the primary diagnoses that are most frequently seen in the ED in the homeless population might be managed in an outpatient setting, though we are limited by the lack of severity data captured in administrative databases. For example, both cellulitis and epilepsy were associated with an increased ED LOS for IEH. These are ambulatory care sensitive conditions (ACSC) [26] where acute care use might be avoided if they able to be optimally managed in the outpatient setting. A large number of diagnoses associated with increased ED LOS are related to mental health and addiction concerns. Further investment into community based mental health and addictions resources may be warranted.
When looking at diagnosis associated with increased LOS within inpatients; coronary atherosclerotic disease (CAD) is associated with almost 25 more days spent admitted to hospital compared to housed individuals. While CAD is not classified as an ACSC, risk factors for CAD such as hypertension and diabetes, as well as their consequences such as angina and heart failure are included in ACSC. Furthermore, smoking is a known risk factor for CAD. There is a very high prevalence of smoking amongst IEH (57%) compared to housed individuals (27%) [27]. Our results highlight the need for interventions targeting CAD and their risk factors in IEH, such as focusing on resources for smoking cessation, hypertension, and diabetes. Maternal concerns associated with homelessness also demonstrated increased LOS with 6.45 more days spent in hospital, again demonstrating specific needs for community prenatal and fetal-maternal care for IEH.
The strengths of our study include detailed hospitalization and ED data collected from multiple acute care facilities. Furthermore, our findings are in keeping with prior evidence, suggesting that they are generalizable. The demographics of the Calgary population experiencing homelessness has also been demonstrated to be similar to IEH across the country [28][29].
There are limitations to our study. Due to our cohort identification methods, a small number of IEH were excluded from our study. For example, individuals without identification were excluded, though this comprised only 1/30 of our sample size. Furthermore, as we could not identify individuals who were precariously housed such as those who were couch surfing, our cohort likely represents individuals more severe or chronic homelessness. Another limitation was our inability to account for illness severity, despite matching IEH and controls based on demographics and primary diagnoses, as this information is not captured within the administrative databases. That is, IEH may present to acute care facilities with similar diagnoses as housed individuals, but at a later stage and/or with increased severity, which could also explain their increased lengths of stay.