Impact of an addiction medicine consult team intervention in a Canadian inner city hospital on acute care utilization: a pragmatic quasi-experimental study
Substance Abuse Treatment, Prevention, and Policy volume 17, Article number: 20 (2022)
Inner city patients have a higher illness burden and need for care, but experience more unmet care needs. Hospital Addiction Medicine Consult Teams (AMCTs) are a promising emerging intervention. The objective of this study was to assess the impact of a Canadian AMCT-like intervention for inner city patients on reduction in high emergency department (ED) use, hospital admission, and inpatient length of stay.
Using a community-engaged, two-arm, pre-post, longitudinal quasi-experimental study design, 572 patients reporting active substance use, unstable housing, unstable income, or a combination thereof (302 at intervention site, 270 at control sites) were enrolled. Survey and administrative health service data were collected at baseline, six months post-enrolment, and 12 months post-enrolment. Multivariable regression models tested the intervention effect, adjusting for clinically important covariables (inpatient status at enrolment, medical complexity, age, gender, Indigenous identity, shelter use, opioid use).
Initial bivariable analyses demonstrated an intervention effect on reduction in admissions and length of stay, however, this effect was no longer significant after adjusting for covariables. There was no evidence of reduction in high ED use on either bivariable or subsequent multivariable analysis.
After adjusting for covariables, no AMCT intervention effect was detected for reduction in high ED use, inpatient admission, or hospital length of stay. Further research is recommended to assess other patient-oriented intervention outcomes.
Substance use is a growing threat to public health. An estimated 19% of Canadians exceed low risk drinking guidelines [1, 2], and 22% meet criteria for one or more substance use disorders (SUDs) in their lifetime (4% meet criteria in the past 12 months) . Mortality attributable to substance use has risen dramatically since 2016 , and problematic substance use is associated with infectious disease, trauma, mental illness, and other chronic diseases [5,6,7]. In 2015–16 there were 77,000 Canadian hospitalizations attributable to alcohol  and currently over 400 Canadians are hospitalized daily due to harms caused by alcohol and other drugs . Among adults age 18–64, SUDs were the second most common cause of inpatient hospitalization in Canada in 2019–20, exceeding all other causes of hospitalization with the exception of giving birth .
Deleterious substance-related health outcomes are more common among people living in adverse socioeconomic circumstances [11,12,13,14,15,16]. Concurrent poverty and substance use is particularly common in major urban centres [17, 18]. For example, 235,000 Canadians experience homelessness in a given year, the majority of whom are in urban centres ; and of these, a large proportion report alcohol or other drug use along with mental health concerns . Low income, low employment, repeated exposure to violence, and the experience of racism and systemic discrimination are other commonly cited adverse circumstances [20,21,22]. Lack of government-issued identification documents, inconsistent medication coverage or other health benefits, as well as inconsistent transportation or social supports all create barriers to accessing healthcare and other services [23, 24]. These socioeconomic barriers to timely, community-based care are reflected in the association between low socioeconomic position and more frequent ED use and hospitalization [25, 26].
Despite their higher burden of illness and need for care, health systems are ill-equipped to provide care to people with co-occurring adverse socioeconomic circumstances and substance use challenges. Inner city patients receive less primary and preventive care than other patients [27, 28]. Moreover, they report multiple unmet care needs including medication, information, skills training, harm reduction supports, and assistance with social issues [29,30,31]. A recent survey of Canadian inner city emergency department (ED) patients experiencing unstable housing and/or problematic substance use suggested that they would like to access wraparound supports beyond treatment of their acute medical condition, such as social stabilization and addiction stabilization, while accessing acute care .
Although community-based care plays an essential role in supporting the health of inner city populations, consistent access is a challenge, and illness severity may require hospital assessment more often than for general populations. As one of few available 24/7 points of access to care, hospitals present an opportunity to address multiple unmet care needs for people who use substances [11, 18]. However, due to expectations of abstinence and/or suboptimal SUD management, hospitals can also be a high-risk, relatively hostile environment for patients who use substances resulting in premature departure, untreated health problems, and unplanned readmission [33, 34].
Addiction Medicine Consult Teams (AMCTs) are a newly emerging approach to improving hospital care for patients with SUDs. These multidisciplinary consult teams work with attending physicians and unit staff to provide rapid access to addiction treatment for hospitalized patients and connection to ongoing treatment and wrap-around supports post-discharge. Research regarding the impact of this emerging response to the needs of hospitalized patients with SUDs is limited but promising: while there are no published randomized controlled trials measuring the efficacy of AMCTs, there is growing evidence outlining their impact. AMCTs successfully engage patients in addiction treatment  and this hospital-based, patient-centred SUD care is associated with reduced substance use and mortality [36, 37]. Evidence to date from the United States indicate that AMCTs in that setting can reduce inpatient length of stay for patients with SUDs, reduce 30-day unplanned readmission rates, and increase uptake into outpatient addiction treatment [38,39,40]. Patient-reported benefits of the AMCT model include: improved care experiences, reduced substance use, better mental and emotional well-being, and in some cases, enhanced socio-economic conditions . Beyond these positive clinical outcomes and patient benefits, AMCTs also positively influence the knowledge, attitudes, and experiences of care providers [37, 42, 43] further enhancing patient engagement and the development of care relationships.
Although the elements of AMCT-type interventions are evidence-informed from community settings, multi-component hospital interventions for people who use substances are comparatively novel, and evidence to guide implementation outside of the United States setting is limited. In light of the positive evidence generated to date from observational studies, controlled longitudinal research regarding AMCT-type interventions is warranted [33,34,35,36,37,38,39,40,41]. Moreover, the role of enhanced, whole person approaches to the AMCT model for people experiencing both adverse socioeconomic circumstances and SUDs has not been examined. Thus, the objective of this study was to determine whether an AMCT intervention implemented among inner city patients positively influenced acute healthcare utilization outcomes, specifically reduction in ED use, hospital admissions, and inpatient length of stay. We hypothesized a clinically significant intervention effect of a 20% reduction in high ED use, our primary outcome.
Overview and Study Design
The Enhanced Multidisciplinary Care for Inner City Patients Seeking Acute Health Care (EMCIH) study used a two-arm, pre-post, longitudinal quasi-experimental study design; details are described in our published protocol . A pragmatic, non-randomized design was chosen because individual-level randomization was not feasible for a site-level service innovation, and insufficient comparable and implementation-ready sites existed within the same Canadian province to permit site-level randomization. A community-engaged research approach was used throughout the study period; the study protocol, implementation, and interpretation received iterative guidance from a Community Advisory Group of people with lived experience of both substance use and the acute healthcare system.
Intervention arm participants were recruited from among inpatients and outpatients within two weeks of their initial assessment by the intervention site’s AMCT in Edmonton, Canada. Consult requests to the AMCT were initiated by the patients’ most responsible physician and could come from any inpatient service or the emergency department (ED). During the recruitment period, 611/1448 (42%) of AMCT referral requests originated from the internal medicine service, 422 (29%) from the ED, 162 (11%) from surgery, 91 (6%) from the hospitalist team, and the remainder from a variety of other specialty services. AMCT referral criteria were active substance use related concerns and/or social instability. These more inclusive intervention eligibility criteria were applied due to a large overlap in substance use and unstable housing in the target population based on intervention site clinical experience, and a lack of reliable pre-study data on which hospitalizations would benefit from referral. Control arm participants were recruited from inpatients (medical, surgical, and psychiatric) and outpatients (emergency and urgent care) seen in two acute care facilities serving a similarly disadvantaged patient population in the nearby city of Calgary, Canada. Potential participants were identified by treating clinicians. In both study arms, research assistants confirmed study eligibility (problematic substance use, unstable housing, and/or unstable income), explained the study, obtained informed consent for the overall study, and obtained additional consent for retrieval and linkage of administrative health service data to primary survey data. Research assistants then completed a detailed contact information sheet detailing both traditional and non-traditional means of contact (e.g. name of outreach worker, usual places frequented) to facilitate participant follow-up.
The intervention site AMCT was launched in July 2014, in response to patient-voiced unmet care needs. The intervention development team considered substance-use related care, health promotion, and interventions addressing the social determinants of health to be equally important. Feedback from our Community Advisory Group, and later from our parallel process evaluation, confirmed the importance of whole person care in acute health service delivery and the need to incorporate this approach into the AMCT model. The resulting multidisciplinary consultation service was co-designed with patients, clinicians, and other stakeholders. At study inception, the core clinician complement included rotating physicians with addiction medicine expertise (one physician available 0800 h–2100 h, seven days/week), a nurse practitioner, and a social worker; an addiction counselor and peer support worker were added in the latter half of the study period. Emphasizing bridging support to promote care continuity during the hospital-community care transition, the AMCT provided management of intoxication, withdrawal, and/or acute pain; initiation or continuation of opioid agonist treatment; referral to addiction treatment and recovery programs; overdose prevention interventions; screening for sexually transmitted and blood borne infections; and, social stabilization supports including assistance with housing, income, and/or obtaining healthcare coverage, photo identification or health care card. The AMCT provided consultation on referral by the attending clinical team to both hospital inpatients and ED patients, the latter of whom were offered follow-up assessment in a transitional clinic on site. The intensity, duration, and specific components offered were tailored to patient needs and preferences. Usual care at the control sites consisted of assessment and treatment by an attending team without specific expertise in addiction medicine or related individualized care plans to manage the unique health and social needs of patients who use substances; attending teams could access a nurse-clinician on select days for addiction medicine advice.
Participants completed a baseline quantitative survey administered by a research assistant. Survey variables (see supplementary file 1) included sociodemographic information (e.g. gender, ethnicity, housing status), substance use behaviour (e.g. alcohol and drug [45, 46] consumption patterns, experience of overdose), perceived health (EQ-5D ), and unmet need for care (Perceived Needs for Care Questionnaire ). Although follow-up survey data were collected for the purposes of secondary outcome analysis, only baseline survey data were used for the analyses presented herein.
The research team collaborated with the provincial administrative health service data custodian to retrieve and link administrative data for consenting participants. Data on healthcare encounters were retrieved for a 540-day period including 180 days prior to and 360 days following the baseline study enrolment date for each participant.
Main outcome measures were obtained from administrative health data. The primary outcome measure was reduction in high ED use, where the baseline measurement period was defined as 180 days prior to baseline study enrolment date, and the follow-up measurement period was defined as 180 days falling between six and 12 months after the baseline study enrolment date. Consistent with other studies of complex populations with high acute case use, “high ED use” was defined as more than two visits to either an ED or urgent care (UC) facility during either 180-day period [49, 50]. We considered using ED frequency counts across the 540-day study period, but decided to create a change variable omitting the 180-day period immediately after intervention start because we anticipated that 1) frequency of ED visits would be non-normally distributed [26, 51] and 2) ED visits would increase as a function of the acute care-based intervention before subsequently decreasing.
Secondary acute care utilization outcome measures included reduction in inpatient admissions and reduction in hospital length of stay, calculated using the same 180-day pre- and post-periods used for the primary outcome measure.
Covariables were identified a priori based on their potential to exert clinically meaningful effects on the intervention and/or outcome. Most covariables were collected via the baseline participant survey. These included age, gender (male, female, transgender), Indigenous ethnicity (coded as Indigenous if responses of “First Nations”, “Métis”, “Inuit”, “Cree”, “Aboriginal”, “Non-status Indian”, or “Treaty” were given to the question “What ethnic group do you identify with?”), and unmet need for care (as measured by the Perceived Needs for Care Questionnaire) . Shelter use was recorded as present if a participant reported sleeping in a hostel or shelter in the previous six months; it was chosen as our indicator of housing instability as the most common sleeping arrangement for those without housing. Opioid use was recorded as present if any non-prescribed use of intravenous or non-intravenous opioids was reported in the previous six months. Two non-survey covariables were also included. Clinical Risk Group (CRG , a diagnosis-based indicator of medical complexity that takes into account disease chronicity and severity and its expected impact on morbidity, mortality, and future service needs) was retrieved from the recruitment hospital admission or ED/UC visit and was coded low, medium or high risk. Recruitment location was documented by research staff as inpatient (ward) or outpatient (ED, UC).
We hypothesized a clinically significant intervention effect of a 20% reduction in high ED use, which a power analysis indicated would require 103 participants per study arm for detection (two-sample test of proportions, α = 0.05, power = 80%). We anticipated 50% study attrition as well as administrative data validation challenges (consistent with studies of similar cohorts [53, 54]), and therefore set a recruitment target of 300 for each study arm.
Generalized linear mixed models were used for analysis. The unit of analysis was the participant and all analyses were performed in R . Summary statistics (e.g., frequencies, percentages, means, standard deviation [SD], median, interquartile range [IQR] represented as 25th percentile, 75th percentile) described covariables and outcomes by study arm. Initially, two-sample tests of proportions, chi-square tests, and t-tests compared outcomes by study arm and covariables. This was followed by multiple logistic regression analyses to compare outcomes across study arms, adjusted for age, self-identified gender, Indigenous status, housing status, opioid use, unmet need for care, CRG category, and recruitment location. Given the small number of participants that identified as transgender (n = 2), transgender was combined with the female category in all regression analyses. As CRG had 11 missing values, missing values were assumed to be missing at random and five imputed datasets using the multivariate imputation by chained equations (MICE ) package were created and regression models pooled. Odds ratios (ORs) and associated 95% confidence intervals (CIs) are presented and a p-value less that 0.05 was considered statistically significant.
A total of 572 patients (302 intervention arm, 270 control arm) were enrolled into the study and completed baseline survey data collection between August 2014 and June 2016 (Fig. 1). At the time of recruitment over 90% of the sample reported recent alcohol or substance use, and over 70% reported unstable housing, unstable income, or both (Table 1). Almost all participants (n = 554; 97%) consented to the retrieval and linkage of their longitudinal administrative health services data. After removing invalid personal healthcare identifiers, identifying study withdrawals, and a small number of control arm participants potentially exposed to local case management co-interventions, the final sample included 516 participants (290 intervention arm, 226 control arm) for analysis (Fig. 2). Attrition due to death, study withdrawal, or inability to contact was similar across both study arms. There were no significant deviations from the original study protocol throughout the data collection period.
Study arms differed at baseline across a number of covariables (Table 1). More intervention arm participants used opioids and were Indigenous compared to control arm participants; whereas fewer intervention arm participants had used a shelter in the past six months. Intervention arm participants were more likely to be recruited as inpatients, and also had a higher level of medical complexity, as defined by the CRG.
Acute Care Outcomes
With respect to the primary outcome, 28.3% (82/290) of the intervention arm participants experienced a reduction in high ED use compared to 33.6% (76/226) in the control arm (Table 2, p = 0.225). There was no difference between study arms in the proportion of participants experiencing a reduction in high ED use. When these bivariate results were adjusted by covariables in a logistic regression analysis, study arm remained non-significant and only CRG predicted the primary outcome (Table 3). During preliminary analysis we explored additional modeling using an ED visit count variable rather than a change variable, however, the result of this analysis were similar and thus are not included herein.
For secondary outcomes, bivariate results indicated that pre- to post-test reductions in inpatient admissions were more common among participants in the intervention arm (212/290, 73.1%, Table 2) compared to control arm participants (132/226, 58.4%, p = 0.001). However, in subsequent multivariable analyses adjusted by covariables (Table 3), study arm was no longer statistically significant, and recruitment location and baseline opioid use were the variables associated with this outcome.
Finally, more intervention arm participants exhibited reductions in the inpatient length of stay (212/290, 73.1%, Table 2) than control arm participants (138/226, 61.1%; p = 0.005). When adjusted by study covariables (Table 3), study arm was no longer statistically significant and age and recruitment location were the variables most associated with outcome.
Because of baseline site-level differences between the study arms, the research team and administrative data partners created a second geographic comparison group at the intervention site, using a diagnosis-based sampling frame definition developed for the study. Intervention site controls were matched with intervention recipients according to available variables of date and admission status (inpatient vs outpatient) of index encounter, complexity (CRG), age, and sex. Healthcare utilization measures retrieved for this additional cohort included ED use, inpatient admissions, and length of stay. Patterns of acute care use for the internal matched controls did not differ from those observed among the formal study control arm. Nevertheless, there may be important macroeconomic and/or healthcare throughput differences between the two cities in this study that may have influenced our results.
Though preliminary bivariable analyses from this quasi-experimental comparison of an AMCT intervention to usual care for inner city patients suggested that the intervention reduced acute care utilization, full modeling with inclusion of covariables did not provide statistically significant evidence of an intervention effect. These multivariable analyses indicated that illness complexity and severity – specifically CRG and outpatient recruitment status– accounted for the differences observed across study arms. Our findings contrast with some studies of AMCT interventions [38,39,40] but align with other studies . In the studies demonstrating an intervention effect, one focussed on patients with opioid use disorder specifically where opioid agonist therapy initiation could be expected to confer significant stabilization and benefit in terms of acute care use . Another included universal screening for substance use disorder which may have identified patients with less severe, and more easily treated addiction . Variable intervention effects observed in the literature could also suggest that such interventions may be beneficial but insufficient in reducing acute care utilization without addressing intersecting system barriers; conversely, positive findings elsewhere may reflect the influence of unmeasured confounding factors. Identifying whether an intervention for complex needs works is particularly challenging, given that local contextual factors such as housing availability, toxicity of drug supply, and community-based supports contribute to variance in acute care utilization [13, 58]. Broader contextual factors such as health system organization (e.g. structure of, and access to care) and sociopolitical environment may also be contributing to the contrasting results between this Canadian study and many of the largely US-based prior AMCT studies.
Health systems are understandably concerned with making efficient use of resources, and there has been an increased system focus on reducing potentially avoidable ED visits, including the development of measures for tracking ED visits for Family Practice Sensitive Conditions (FPSC) . In the EMCIH study sample, the proportion of patients with ED visits for FPSCs was small (16%), lower even than that for the general population (20%). Moreover, the relatively high mortality rate experienced by complex high needs populations  (including participants in both arms of this study) underscores their high illness burden and need for acute medical care. This suggests that most ED visits by study participants were unavoidable, and unlikely to change based on the availability of team-based primary care or hospital bridging supports. Given the lower level of health among inner city populations, and the likely ongoing need for periodic hospital-based care, health system leaders may find greater efficiency from addressing modifiable social determinants of health, improving care integration, and enhancing care continuity for inner city patients undergoing transitions between hospital and community-based care.
The length of follow-up period in this study may be considered relatively short for such a complex healthcare intervention evaluation. Indeed, many changes in healthcare utilization occur after more than 12 months for other complex interventions (e.g. patient centred medical home models) [60, 61]. However, there are a number of other patient-oriented outcomes to consider that could confer intervention benefit beyond acute healthcare utilization, and may be associated with a reduction in acute healthcare utilization patterns over the longer term. Rather than rapidly reducing acute care use, the complex team intervention may be better designed to effect changes in quality of life, unmet care needs, and visits to primary care providers, all of which have important healthcare utilization implications. The intervention also addressed several social determinants of health (e.g. housing, income support, medication coverage) and substance use which the EMCIH study was not primarily designed to assess. Finally, patient satisfaction —a prominent theme in our parallel process evaluation —is another outcome that may unintentionally have generated ED visit demand over the shorter term. Our qualitative research reported elsewhere  showed that patients receiving the intervention reported improved hospital care experiences involving the development of trust in the healthcare team. For patients who are conventionally underserved and discriminated against, the intervention team’s nonjudgmental and relationship-oriented approach may well have encouraged patients to seek needed care when they previously would have otherwise delayed or avoided it.
We employed a quasi-experimental study design for feasibility reasons; the null findings may in part be due to the lack of power inherent to this approach. Moreover, we detected baseline inequivalence in outcome measures. The multi-pronged complex intervention under study served multiple subgroups of patients (e.g. different primary substances of concern) with services tailored to individual needs. To address these differences at the individual participant level, we adjusted for observed baseline inequivalence across study arms and included clinically important covariables in the statistical models. However, a number of unmeasurable contextual factors are likely at play. We considered propensity weighting, but determined that this approach would not fully account for observed differences.
It is plausible that due to understandable limitations in the capacity of the newly formed intervention team, and benefits of the intervention perceived by referring clinicians, recruited participants were a group who not only met eligibility criteria but had a high level and acuity of need that stood out within eligible patients. This is reflected in the high level and acuity of need seen in the baseline questionnaire data and particularly high complexity (CRG) in the intervention group. Thus selection bias may have influenced our results.
The rollout of the EMCIH study at the control arm sites was met with excitement at the possibility of future intervention spread to other geographic regions within the same health system. Research staff on site were well received by staff and participants alike. A Hawthorne effect resulting from control arm participants responding favourably to their encounters with study and clinical staff following study enrolment cannot be ruled out; however, given the lack of support options available to participants beyond three structured quantitative data collection sessions and usual care, we believe a Hawthorne effect is unlikely to have exerted a significant enough influence to change acute care utilization.
The EMCIH study protocol occurred during the early intervention implementation period. The intervention has since undergone significant refinement (e.g. enhanced team composition, dedicated team expansion to the ED, addition of specific harm reduction supports such as managed alcohol programming, naloxone kit distribution, and a supervised consumption service) in response to referral patterns and consultation with program recipients and stakeholders. Intervention adaptation was also critical to address evolving population needs, most notably the advent of Canada’s opioid poisoning epidemic shortly after the launch of the intervention, and the subsequent prioritization of harm reduction and immediate access to opioid use disorder treatment options. The study findings reported herein reflect an earlier iteration of the intervention prior to intervention refinements having occurred. The team is engaged in ongoing program data collection and quality improvement work to assess the impact of such refinements.
As originally conceived and implemented, an AMCT intervention was not associated with significant reductions in ED use, inpatient admission, or hospital length of stay. The relationships built between AMCT staff and patients may encourage patients to seek out care when they may otherwise have avoided it. The intervention continues to evolve in response to early study findings, stakeholder input, and emerging population needs. Further research is recommended to assess other patient-oriented intervention outcomes such as changes in the burden of unmet care needs, housing, income support, and substance use stabilization.
Availability of data and materials
The datasets generated and/or analysed during the current study are not publicly available due to data sharing agreements with participating administrative data custodians, but are available from the corresponding author on reasonable request.
Addiction Medicine Consult Team
Clinical Risk Group
Enhanced Multidisciplinary Care for Inner City Patients Seeking Acute Health Care
Family Practice Sensitive Conditions
Substance Use Disorder
Government of Canada SC. Heavy drinking, by age group. Published June 26, 2018. Accessed 5 Dec 2019. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310009611
Canada H. Canadian Tobacco Alcohol and Drugs (CTADS) Survey: 2017 summary. aem. Published October 30, 2018. Accessed 5 Dec 2019. https://www.canada.ca/en/health-canada/services/canadian-tobacco-alcohol-drugs-survey/2017-summary.html
Government of Canada SC. Mental and substance use disorders in Canada. Published September 18, 2013. Accessed 11 Dec 2019. https://www150.statcan.gc.ca/n1/pub/82-624-x/2013001/article/tbl/tbl1-eng.htm
Special Advisory Committee on the Epidemic of Opioid Overdoses. Opioids and Stimulant-Related Harms in Canada. 2020. Public Health Agency of Canada; https://health-infobase.canada.ca/substance-related-harms/opioids-stimulants
Degenhardt L, Whiteford HA, Ferrari AJ, et al. Global burden of disease attributable to illicit drug use and dependence: findings from the Global Burden of disease study 2010. Lancet. 2013;382(9904):1564–74. https://0-doi-org.brum.beds.ac.uk/10.1016/S0140-6736(13)61530-5.
Patra J, Taylor B, Rehm JT, Baliunas D, Popova S. Substance-attributable morbidity and mortality changes to Canada’s epidemiological profile. Can J Public Health. 2007;98(3):228–34. https://0-doi-org.brum.beds.ac.uk/10.1007/BF03403718.
US Burden of Disease Collaborators. The State of US Health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013;310(6):591. https://0-doi-org.brum.beds.ac.uk/10.1001/jama.2013.13805.
Canadian Institute for Health Information. Alcohol Harm in Canada: examining hospitalizations entirely caused by alcohol and strategies to reduce alcohol harm. CIHI. 2017:52 https://www.cihi.ca/sites/default/files/document/report-alcohol-hospitalizations-en-web.pdf.
Hospital Stays for Harm Caused by Substance Use · CIHI. Accessed 5 Dec 2019. https://yourhealthsystem.cihi.ca/hsp/inbrief?lang=en&_ga=2.112451015.275434200.1575570846-196755278.1572980542#!/indicators/080/hospital-stays-for-harm-caused-by-substance-use/;mapC1;mapLevel2;/
Canadian Institute for Health Information. Inpatient Hospitalization, Surgery and Newborn Statistics. CIHI; 2021.
Zhang L, Norena M, Gadermann A, et al. Concurrent disorders and health care utilization among homeless and vulnerably housed persons in canada. J Dual Diagn. 2018;14(1):21–31. https://0-doi-org.brum.beds.ac.uk/10.1080/15504263.2017.1392055.
Aldridge RW, Story A, Hwang SW, et al. Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. Lancet. 2018;391(10117):241–50. https://0-doi-org.brum.beds.ac.uk/10.1016/S0140-6736(17)31869-X.
Palepu A, Gadermann A, Hubley AM, et al. Substance use and access to health care and addiction treatment among homeless and vulnerably housed persons in three Canadian cities. PLoS One. 2013;8(10):e75133.
Rehm J, Probst C. Decreases of life expectancy despite decreases in non-communicable disease mortality: the role of substance use and socioeconomic Status. Eur Addict Res. 2018;24(2):53–9. https://0-doi-org.brum.beds.ac.uk/10.1159/000488328.
Tjepkema M, Wilkins R, Long A. Cause-specific mortality by income adequacy in Canada: A 16-year follow-up study. Health Rep. 2013;24(7):14-22.
Probst C, Rehm J. Alcohol use, opioid overdose and socioeconomic status in Canada: A threat to life expectancy? Can Med Assoc J. 2018;190(44):E1294–5. https://0-doi-org.brum.beds.ac.uk/10.1503/cmaj.180806.
Krausz RM, Clarkson AF, Strehlau V, Torchalla I, Li K, Schuetz CG. Mental disorder, service use, and barriers to care among 500 homeless people in 3 different urban settings. Soc Psychiatry Psychiatr Epidemiol. 2013;48(8):1235–43. https://0-doi-org.brum.beds.ac.uk/10.1007/s00127-012-0649-8.
Maremmani AGI, Bacciardi S, Gehring ND, et al. Substance use among homeless individuals with schizophrenia and bipolar disorder. J Nerv Ment Dis. 2017;205(3):173–7. https://0-doi-org.brum.beds.ac.uk/10.1097/NMD.0000000000000462.
Gaetz S, Dej E, Richter T. The State of Homelessness in Canada 2016. Canadian Observatory on Homelessness; 2016. Accessed 5 May 2020. http://www.deslibris.ca/ID/10065873
Daiski I. Perspectives of homeless people on their health and health needs priorities. J Adv Nurs. 2007;58(3):273–81. https://0-doi-org.brum.beds.ac.uk/10.1111/j.1365-2648.2007.04234.x.
Omerov P, Craftman ÅG, Mattsson E, Klarare A. Homeless persons’ experiences of health- and social care: A systematic integrative review. Health Soc Care Commun. 2020;28(1):1–11. https://0-doi-org.brum.beds.ac.uk/10.1111/hsc.12857.
Poremski D, Distasio J, Hwang SW, Latimer E. Employment and income of people who experience mental illness and homelessness in a large Canadian sample. Can J Psychiatr. 2015;60(9):379–85. https://0-doi-org.brum.beds.ac.uk/10.1177/070674371506000902.
LeBrón AMW, Lopez WD, Cowan K, et al. Restrictive ID policies: implications for health equity. J Immigr Minor Health. 2018;20(2):255–60. https://0-doi-org.brum.beds.ac.uk/10.1007/s10903-017-0579-3.
Campbell DJT, O’Neill BG, Gibson K, Thurston WE. Primary healthcare needs and barriers to care among Calgary’s homeless populations. BMC Fam Pract. 2015;16:139. https://0-doi-org.brum.beds.ac.uk/10.1186/s12875-015-0361-3.
Reid KW, Vittinghoff E, Kushel MB. Association between the level of housing instability, economic standing and health care access: a meta-regression. J Health Care Poor Underserved. 2008;19(4):1212–28. https://0-doi-org.brum.beds.ac.uk/10.1353/hpu.0.0068.
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):778–84. https://0-doi-org.brum.beds.ac.uk/10.2105/AJPH.92.5.778.
Huynh C, Ferland F, Blanchette-Martin N, Ménard JM, Fleury MJ. Factors influencing the frequency of Emergency Department utilization by individuals with substance use disorders. Psychiatr Q. 2016;87(4):713–28. https://0-doi-org.brum.beds.ac.uk/10.1007/s11126-016-9422-6.
Salhi BA, White MH, Pitts SR, Wright DW. Homelessness and Emergency Medicine: A Review of the Literature. Acad Emerg Med. 2018;25(5):577–93. https://0-doi-org.brum.beds.ac.uk/10.1111/acem.13358.
Urbanoski K, Inglis D, Veldhuizen S. Service use and unmet needs for substance use and mental disorders in Canada. Can J Psychiatr. 2017;62(8):551–9. https://0-doi-org.brum.beds.ac.uk/10.1177/0706743717714467.
Jaworsky D, Gadermann A, Duhoux A, et al. Residential stability reduces unmet health care needs and emergency department utilization among a cohort of homeless and vulnerably housed persons in Canada. J Urban Health. 2016;93(4):666–81. https://0-doi-org.brum.beds.ac.uk/10.1007/s11524-016-0065-6.
Kertesz SG, McNeil W, Cash JJ, et al. Unmet need for medical care and safety net accessibility among Birmingham’s homeless. J Urban Health. 2014;91(1):33–45. https://0-doi-org.brum.beds.ac.uk/10.1007/s11524-013-9801-3.
Hyshka E, Anderson JT, Wild TC. Perceived unmet need and barriers to care amongst street-involved people who use illicit drugs. Drug Alcohol Rev. 2017;36(3):295–304. https://0-doi-org.brum.beds.ac.uk/10.1111/dar.12427.
Velez CM, Nicolaidis C, Korthuis PT, Englander H. “It’s been an Experience, a Life Learning Experience”: a qualitative study of hospitalized patients with substance use disorders. J Gen Intern Med. 2017;32(3):296–303. https://0-doi-org.brum.beds.ac.uk/10.1007/s11606-016-3919-4.
Toward Cultural Safety: Nurse and Patient Perceptions of Illicit Substance Use in a Hospitalized Setting | Ovid. Accessed 5 Dec 2019. https://oce-ovid-com.ahs.idm.oclc.org/article/00012272-201504000-00008/HTML
Trowbridge P, Weinstein ZM, Kerensky T, et al. Addiction consultation services – Linking hospitalized patients to outpatient addiction treatment. J Subst Abus Treat. 2017;79:1–5. https://0-doi-org.brum.beds.ac.uk/10.1016/j.jsat.2017.05.007.
Englander H, Dobbertin K, Lind BK, et al. Inpatient addiction medicine consultation and post-hospital substance use disorder treatment engagement: a propensity-matched analysis. J Gen Intern Med. 2019;34(12):2796–803. https://0-doi-org.brum.beds.ac.uk/10.1007/s11606-019-05251-9.
Wakeman SE, Metlay JP, Chang Y, Herman GE, Rigotti NA. Inpatient addiction consultation for hospitalized patients increases post-discharge abstinence and reduces addiction severity. J Gen Intern Med. 2017;32(8):909–16. https://0-doi-org.brum.beds.ac.uk/10.1007/s11606-017-4077-z.
Marks LR, Munigala S, Warren DK, Liang SY, Schwarz ES, Durkin MJ. Addiction medicine consultations reduce readmission rates for patients with serious infections from opioid use disorder. Clin Infect Dis. 2019;68(11):1935–7. https://0-doi-org.brum.beds.ac.uk/10.1093/cid/ciy924.
Thompson HM, Faig W, VanKim NA, Sharma B, Afshar M, Karnik NS. Differences in length of stay and discharge destination among patients with substance use disorders: the effect of Substance Use Intervention Team (SUIT) consultation service. PLoS One. 2020;15(10):e0239761. https://0-doi-org.brum.beds.ac.uk/10.1371/journal.pone.0239761.
The Substance Use Intervention Team: A Preliminary Analysis of a Population-level Strategy to Address the Opioid Crisis at an Academic Health Center | Ovid. Accessed 19 Dec 2019. https://oce-ovid-com.ahs.idm.oclc.org/article/01271255-201912000-00008/HTML
Hyshka E, Morris H, Anderson-Baron J, Nixon L, Dong K, Salvalaggio G. Patient perspectives on a harm reduction-oriented addiction medicine consultation team implemented in a large acute care hospital. Drug Alcohol Depend. 2019;204:107523. https://0-doi-org.brum.beds.ac.uk/10.1016/j.drugalcdep.2019.06.025.
Englander H, Englander H. “We’ve Learned It’s a Medical Illness, Not a Moral Choice”: Qualitative study of the effects of a multicomponent addiction intervention on hospital providers’ attitudes and experiences. J Hosp Med. 2018;13(11). https://0-doi-org.brum.beds.ac.uk/10.12788/jhm.2993.
Gorfinkel L, Klimas J, Reel B, et al. In-hospital training in addiction medicine: A mixed-methods study of health care provider benefits and differences. Subst Abus. 2019Published online. No Pagination Specified. https://0-doi-org.brum.beds.ac.uk/10.1080/08897077.2018.1561596.
Salvalaggio G, Dong KA, Hyshka E, et al. Enhanced multidisciplinary care for inner city patients with high acute care use: study protocol. Can J Addict. 2016;7(3):34–41.
Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Arch Intern Med. 1998;158(16):1789–95. https://0-doi-org.brum.beds.ac.uk/10.1001/archinte.158.16.1789.
Voluse AC, Gioia CJ, Sobell LC, Dum M, Sobell MB, Simco ER. Psychometric properties of the Drug Use Disorders Identification Test (DUDIT) with substance abusers in outpatient and residential treatment. Addict Behav. 2012;37(1):36–41.
Herdman M, Gudex C, Lloyd A, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.
Meadows G, Harvey C, Fossey E, Burgess P. Assessing perceived need for mental health care in a community survey: development of the Perceived Need for Care Questionnaire (PNCQ). Soc Psychiatry Psychiatr Epidemiol. 2000;35(9):427–35. https://0-doi-org.brum.beds.ac.uk/10.1007/s001270050260.
Vinton DT, Capp R, Rooks SP, Abbott JT, Ginde AA. Frequent users of US emergency departments: characteristics and opportunities for intervention. Emerg Med J. 2014;31(7):526–32. https://0-doi-org.brum.beds.ac.uk/10.1136/emermed-2013-202407.
Locker TE, Baston S, Mason SM, Nicholl J. Defining frequent use of an urban emergency department. Emerg Med J. 2007;24(6):398–401. https://0-doi-org.brum.beds.ac.uk/10.1136/emj.2006.043844.
Government of Alberta. Emergency department (ED) visits related to opioids & narcotics among First Nations people in Alberta. Published online September 15, 2016.
Averill R, Goldfield N, Eisenhandler J, et al. Development and Evaluation of Clinical Risk Groups (CRGs). Final Report to the National Institutes of Standards and Technology. US Department of Commerce; 1999.
Kerr T, Small W, Buchner C, et al. Syringe Sharing and HIV incidence among injection drug users and increased access to sterile syringes. Am J Public Health. 2010;100(8):1449–53. https://0-doi-org.brum.beds.ac.uk/10.2105/AJPH.2009.178467.
DeBeck K, Kerr T, Li K, et al. Smoking of crack cocaine as a risk factor for HIV infection among people who use injection drugs. Can Med Assoc J. 2009;181(9):585–9. https://0-doi-org.brum.beds.ac.uk/10.1503/cmaj.082054.
R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; 2019. https://www.R-project.org/
van Buuren S, Groothuis-Oudshoorn K. mice: Multivariate Imputation by Chained Equations in R. J Stat Softw. 2011;45(3). https://0-doi-org.brum.beds.ac.uk/10.18637/jss.v045.i03.
Finkelstein A, Zhou A, Taubman S, Doyle J. Health Care Hotspotting — A Randomized, Controlled Trial. N Engl J Med. 2020;382(2):152–62. https://0-doi-org.brum.beds.ac.uk/10.1056/NEJMsa1906848.
Canadian Centre on Substance Use and Addiction. Changes Related to COVID-19 in the Illegal Drug Supply and Access to Services, and Resulting Health Harms; 2020.
Canadian Institute for Health Information. Sources of Potentially Avoidable Emergency Department Visits. CIHI; 2014:82. Accessed 21 Jan 2021. https://secure.cihi.ca/free_products/ED_Report_ForWeb_EN_Final.pdf
Green LA, Chang HC, Markovitz AR, Paustian ML. The Reduction in ED and Hospital admissions in medical home practices is specific to primary care–sensitive chronic conditions. Health Serv Res. 2018;53(2):1163-79.
Paustian ML, Alexander JA, El Reda DK, Wise CG, Green LA, Fetters MD. Partial and Incremental PCMH Practice Transformation: Implications for Quality and Costs. Health Serv Res. 2014;49(1):52–74. https://0-doi-org.brum.beds.ac.uk/10.1111/1475-6773.12085.
Will KK, Johnson ML, Lamb G. Team-Based Care and Patient Satisfaction in the Hospital Setting: A Systematic Review. J Patient-Centered Res Rev. 2019;6(2):158–71. https://0-doi-org.brum.beds.ac.uk/10.17294/2330-0698.1695.
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81. https://0-doi-org.brum.beds.ac.uk/10.1016/j.jbi.2008.08.010.
We wish to thank the contributions of co-investigators Meira Louis, Jen Nichol, and Shireen Surood; study staff Karine Lavergne, Stacy Lockerbie, Sean Bristowe, and Jane Leske; community liaisons Shanell Twan and Chelsea Burnham; and administrative healthcare data analysts Jeff Bakal and Josh Hathaway.
Direct funding for this study was provided by the Royal Alexandra Hospital Foundation and Alberta Innovates. In kind support was provided by Alberta Health Services and Streetworks. Study data were managed using REDCap  electronic data capture tools hosted and supported by the Women and Children’s Health Research Institute at the University of Alberta. Funding bodies played no role in study design, data collection, data analysis, study interpretation, or manuscript writing.
Ethics approval and consent to participate
The study received ethics approval from the University of Alberta Health Research Ethics Board – Panel B and the University of Calgary Conjoint Health Research Ethics Board. All data presented are from people who provided written informed consent to participate in the study.
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The authors declare that they have no competing interests.
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Salvalaggio, G., Dong, K.A., Hyshka, E. et al. Impact of an addiction medicine consult team intervention in a Canadian inner city hospital on acute care utilization: a pragmatic quasi-experimental study. Subst Abuse Treat Prev Policy 17, 20 (2022). https://0-doi-org.brum.beds.ac.uk/10.1186/s13011-022-00445-7