Case Management may Reduce Emergency Department Frequent use in a Universal Health Coverage System: a Randomized Controlled Trial
J Gen Intern Med
Case Management may Reduce Emergency Department Frequent use in a Universal Health Coverage System: a Randomized Controlled Trial
Venetia-Sofia Velonaki 1
Judith L. Griffin 3
Stéphanie Baggio 0
Katia Iglesias 6 7
Karine Moschetti 4 5 6
Psych D 9
Bernard Burnand 6
Francis Vu 3
Olivier Hugli 8
Jean-Bernard Daeppen 2
0 Life Course and Social Inequality Research Center, Faculty of Social and Political Sciences, University of Lausanne , Lausanne , Switzerland
1 Institute of Higher Education and Research in Healthcare, Department of Community Medicine and Public Health, Lausanne University Hospital and University of Lausanne , Lausanne , Switzerland
2 Alcohol Treatment Center, Lausanne University Hospital , Lausanne , Switzerland
3 Vulnerable Populations Center, Department of Ambulatory Care and Community Medicine, University of Lausanne , Lausanne , Switzerland
4 IEMS - Plateforme interfacultaire en économie et management de la santé, University of Lausanne , Lausanne , Switzerland
5 Technology Assessment Unit, Lausanne University Hospital , Lausanne , Switzerland
6 Institute of social and preventive medicine, Lausanne University Hospital , Lausanne , Switzerland
7 Center for the Understanding of Social Processes, University of Neuchâtel , Neuchâtel , Switzerland
8 Emergency Department, Lausanne University Hospital , Lausanne , Switzerland
9 Department of Community Medicine and Public Health, Lausanne University Hospital , Lausanne , Switzerland
Trial registration ClinicalTrials.gov Identifier: NCT01934322 KEY RESULTS: At 12 months, there were 2.71 (±0.23) ED visits in the intervention group versus 3.35 (±0.32) visits among controls (ratio = 0.81, 95 % CI = 0.63; 1.02). In the multivariate model, the effect of the CM intervention on the number of ED visits approached statistical significance (b = −0.219, p = 0.075). The presence of poor social determinants of health was a significant predictor of ED use in the multivariate model (b = 0.280, p = 0.048). CONCLUSIONS: CM may reduce ED use by frequent users through an improved orientation to the health care system. Poor social determinants of health significantly increase use of the ED by frequent users.
case management; vulnerable populations; utilization; clinical trials
BACKGROUND: Frequent emergency department (ED)
users account for a disproportionately high number of
ED visits. Studies on case management (CM)
interventions to reduce frequent ED use have shown mixed
results, and few studies have been conducted within a
universal health coverage system.
OBJECTIVE: To determine whether a CM
intervention—compared to standard emergency care—reduces ED
DESIGN: Randomized controlled trial.
PARTICIPANTS: Two hundred fifty frequent ED users (5
or more visits in the prior 12 months) who visited a public
urban ED at the Lausanne University Hospital between
May 2012 and July 2013 were allocated to either an
intervention (n = 125) or control (n = 125) group, and
monitored for 12 months.
INTERVENTIONS: An individualized CM intervention
consisting of concrete assistance in obtaining income
entitlements, referral to primary or specialty medical care,
access to mental health care or substance abuse
treatment, and counseling on at-risk behaviors and health
care utilization (in addition to standard care) at baseline
and 1, 3, and 5 months.
MAIN MEASURES: We used a generalized linear model for
count data (negative binomial distribution) to compare
the number of ED visits during the 12-month follow-up
between CM and usual care, from an intention-to-treat
Frequent emergency department (ED) users account for
3 to 8 % of all patients and 12 to 28 % of all ED
visits,1,2 contributing to overcrowding.3 Common
reasons for such frequent use include pain, chronic physical
and mental illness, and substance abuse.1,2,4,5 Frequent
ED users are mainly men, are between 40 and 50 years
of age, are sicker and have higher rates of mortality
than occasional ED users.1,2,6 As such, they merit
focused attention, and research on interventions to meet
their needs is needed.6
Case management (CM) is an intervention designed to assist
frequent ED users in reducing their ED utilization.7,8 CM aims to
meet patients’ individual needs and to optimize resource
allocation for the frequent user and payer.9,10 To our knowledge, only
three randomized controlled trials (RCTs) have examined the
impact of CM on ED use.11–13 Two RCTs12,13 found that CM
reduced the number of ED visits among frequent users, while the
third11 found no significant impact. A randomized
informationsharing intervention did not result in a significant reduction in ED
use.14 Health care system characteristics and insurance coverage
are factors that influence ED use,15 and may explain discrepancies
among these studies.
According to a study conducted in Switzerland,16 frequent
ED users accounted for 4.4 % of all ED patients and 12.1 % of
all ED visits at the Lausanne University Hospital in 2008–
2009. Like the majority of developed countries (91 % of
OECD member nations),17 Switzerland has universal health
coverage, established in 1994. The system relies on mandatory
individual health insurance, with government subsidies
available, and less than 1 % of the population is uninsured.18
In response to calls for a unified definition of frequent ED
use and primary care-based interventions4, this RCT examined
whether an interdisciplinary CM intervention, compared to
standard emergency care, would reduce ED utilization among
frequent users through an improved orientation to primary
care and other community-based services within a universal
health coverage system.
Study design, setting and participants
Details on the study design and protocol were published
in our previous work.19 Briefly, we conducted an RCT
with a parallel design to compare CM with standard
care among frequent ED users of the Lausanne
University Hospital (Switzerland) ED between May 2012 and
July 2013. The Lausanne University Hospital is one of
five EDs in the canton (state) of Vaud, and serves
770,000 people, with over 35,000 ED visits annually.20
We defined frequent ED users as those who made five
or more ED visits during the prior 12 months, including
the index visit, using a validated definition.1 Participants
were randomized to the CM intervention or control
group, and were monitored over 12 months. The
primary outcome was the number of ED visits made by
participants over the 12 month follow-up.
Participants were required to be at least 18 years of
age and able to communicate in any language spoken by
the team (French, English, Spanish, German, or Italian)
or through a professional interpreter. Patients were
excluded from the study if they 1) were unable to give
informed consent, 2) planned to stay in Switzerland less
than 18 months, 3) were not expected to survive at least
18 months (based on clinical judgment of research team,
with systematic, proactive input from clinical providers,
e.g. cardiologists or oncologists), 4) were awaiting
incarceration or currently incarcerated, 5) had already
received CM services, or 6) had a family member
already enrolled in the study.
The trial was approved by the Human Research Ethics
Committee of the Canton of Vaud, Switzerland (no. 32/12),
and all participants provided written informed consent. The
trial was funded by the Swiss National Science Foundation
(no. 32003B_135762) and was registered on
Based on results from a systematic review of the
literature,7 the sample size estimate was calculated to detect an
average difference of two ED visits annually between the
two groups (i.e. four fewer intervention group visits
compared to two fewer control group visits, with an anticipated
standard deviation of four in both groups). Eighty-five
participants were needed in both groups using a
significance level of 0.05 and power of 0.9. We anticipated a
dropout rate of 30 %, based on the increased mortality rate
of frequent ED users,21past research19,22 and clinical
experience of the CM team (serving populations including
forced migrants and homeless persons), due to the
instability in this population. Thus, we aimed to enroll 250
frequent ED users (125 in each group).
Recruitment, randomization, allocation and blinding
We identified frequent users using a continuous
automated detection system linked with ED patient tracking
software. Study staff provided frequent users with oral
and written information about the study. Due to
pragmatic constraints (e.g. after hours; simultaneous
participants), the single research nurse was not able to
approach all eligible frequent users. If a frequent user left
the ED prior to contact with the study staff, a team
member attempted to reach him/her by telephone up to
three times within 24–72 hours, to explain the study
and schedule a meeting. If a frequent user declined to
enroll, we asked an open-ended question on the reason
for declining. With the participants’ permission, a CM
team member contacted their primary care physician
(PCP), if present, to inform him/her about the study
and gather information.
Randomization was computer-generated and concealed
from patients.19 The research nurse, CM team, ED staff and
data collection manager were not blinded to participant
allocation, due to their activities and contacts. We informed study
participants that they might receive CM services, without
informing them of their group allocation. The statistician was
blinded until the analyses were completed.
The CM team administered the intervention for 6 months
following enrollment (until January 2014); patients were
followed during the 6-month intervention and for an additional
6 months, for a total of 12 months (through July 2014).
CM intervention and control groups
In addition to standard emergency care, participants in
the intervention group received the CM intervention at
baseline and at 1, 3, and 5 months (Online Appendix 1).
The baseline visit lasted 1.5 h, and follow-up visits took
30–60 min. An interdisciplinary mobile team consisting
of four nurse practitioners and a chief resident23
provided the intervention in an ambulatory care, hospital, or
home setting. With our Bopen-door policy,^ participants
were given the telephone number and address of the
CM team and could make contact between scheduled
The CM team provided individualized services to each
participant in the intervention group, emphasizing care
coordination and facilitating communication between health care
team members. Specifically, CM team members provided
counseling, based on motivational interviewing and
crosscultural competences, on substance abuse (if applicable) and
use of medical services. After assessing individual participant
needs, we offered assistance to obtain income entitlements,
improved housing (e.g. homeless shelters or asylum seeker
housing), health insurance, domestic violence support and
educational opportunities, to address these social determinants
of health (SDH). Referrals were made to mental health
services, substance abuse treatment or a new PCP on a
case-bycase basis. As part of the CM intervention, we created a
comprehensive care plan (Online Appendix 2) with practical
recommendations for all of the participants’ health care
providers (PCP, psychiatrist, etc.). A key element of the
intervention was establishing a link between providers and services at
the hospital and community levels, promoting care continuity
and improved orientation in the health care system.
Control group participants received only standard
emergency care, but also met with a researcher during the 12 month
follow-up (at 2, 5.5, 9 and 12 months), completing
questionnaires related to outcomes which are not the focus of this paper
(e.g. quality of life and the perception of discrimination24).
Control group participants also received the CM team contact
information, and anyone who contacted the team was eligible
to receive CM services after the study.
Study Data and Outcome Measures
The primary outcome (number of ED visits) was obtained via
the Lausanne hospital/ambulatory electronic records system
and hospital/ambulatory administrative databases for each
participant during the 12 months prior to and 12 months
Using validated standardized scales at baseline, we
collected data on patient sociodemographic characteristics, SDH
(including Medical Outcomes Study [MOS] survey25 and
subjective social status26), somatic (Charlson comorbidity
index27) and mental health factors (Patient Health
Questionnaire [PHQ]28, Mini-International Neuropsychiatric Interview
[M.I.N.I.]29), at-risk behaviors (Alcohol, Smoking and
Substance Involvement Screening Test [ASSIST]30), and
health care utilization.22
Statistical analyses were performed using STATA software
(version 14; StataCorp LP, College Station, TX, USA), with
the significance level set at p = 0.05. All analyses followed
intention-to-treat standards. Descriptive statistics were
computed using means and standard deviations for continuous
variables, and absolute frequencies and percentages for
categorical variables. We applied a generalized linear model for
count data (negative binomial distribution) using the number
of ED visits during the 12 months following enrollment as the
dependent variable. We included an offset variable
(corresponding to the logarithm of survival time) to account
for participants who died during the study. First, we performed
bivariate analyses to test the effect of the participant group
(intervention or control), the number of visits at baseline
(12 months before enrollment), age, gender, education,
citizenship, French proficiency, PCP, somatic, mental and social
determinants, and at-risk behaviors as independent variables
on the use of ED services during the 12 month follow-up.
Second, we ran a stepwise regression including all these
independent variables in order to select the predictive variables
(p = 0.10) to be included in the multivariate model. Ratio and
95 % confidence intervals were computed to estimate the
Of the 1145 frequent ED users identified during the
recruitment period, we could not approach 217 (Fig. 1) due to
pragmatic constraints for the single research nurse recruiting
during periods of heavy patient influx, and 231 did not meet
eligibility criteria. We were unable to contact 171 (after initial
contact in the ED, they did not respond to follow-up calls), and
276 refused to participate. Reasons for declining included no
expected benefit, not being satisfied with the hospital, and
recent participation in another study. Those who refused did
not differ in sex or nationality, but were older than enrolled
participants (52.3 vs. 48.6 years old, p = 0.03). Overall, 250
(47.5 %) agreed to participate and were allocated to the
intervention (n = 125) or control group (n = 125).
Participant Characteristics (Table 1)
The mean age of the participants was 48.5 years (±18.9),
and 57.2 % were men. The intervention group had
significantly lower educational attainment than controls. Participants
reported high levels of poor SDH, including inadequate
housing, lack of employment, and problems with immigration
status. The majority suffered from a chronic condition,
medical co-morbidity or psychiatric illness, and a third reported
atrisk behaviors. Only 14 % did not have a PCP. The groups had
an equal number of ED visits in the 12 months prior to
All 125 intervention group participants received the
intervention at baseline, 106 (84.8 %) at 1 month, 98 (78.4 %) at
3 months, and 93 (74.4 %) at 5 months; 108 (86.4 %)
intervention group participants contacted the CM team between
study visits. No control group participants contacted the CM
team proactively. Twenty participants (10 in each group) died
during the study.
The CM team referred 66 participants (52.8 %) to mental health
professionals and 34 (27.2 %) to substance abuse treatment. Sixty
participants (48.0 %) received additional social services, and 83
(66.4 %) were referred to specialized medical doctors.
Outcome (Table 2)
During the 12 month follow-up, control group participants
made an average of 3.35 ± 0.32 ED visits, whereas
intervention group participants made 2.71 ± 0.23 visits, corresponding
to 19 % fewer ED visits (ratio = 0.81, 95 % CI = 0.63 to1.02).
The effect of the CM intervention (i.e. group) on the number
of ED visits was not statistically significant in the bivariate
model, (b = −0.217, p = 0.080) (Table 2). The association
between social determinants and the number of visits approached
statistical significance (b = 0.272, p = 0.055), with poor SDH
being associated with higher ED use, in the bivariate model.
Group assignment (intervention or control) and social
determinants were used in the stepwise multivariate regression. In this
model, the effect of the group approached significance (b =
−0.219, p = 0.075), with the intervention group making fewer
ED visits compared to the control group. The presence of poor
SDH was significant in the final model (b = 0.280, p = 0.048).
In this randomized controlled trial, a CM intervention led to
19 % fewer ED visits by frequent users, which approached
statistical significance, through an improved orientation to and
coordination of services within the health care system. Our
results also demonstrate that the presence of poor
SDH—including social isolation, housing instability, or
financial insecurity—was associated with higher ED use
among frequent users.
**MOS Social Support Survey25 and subjective social support survey26
‡PHQ28 and M.I.N.I.29
While our main results do not achieve statistical
significance, 19 % fewer ED visits is clinically relevant, given the
significant time and resources required to care for frequent ED
users.31–33 For example, in the USA (21-28 % of 130 million
total visits), a reduction of the magnitude found in our study
would translate into 5.1–6.8 million avoided visits
annually.15,34 The non-significant reduction in ED use found in this
study underscores the mixed evidence in the literature. At least
seven prior studies12,13,35–39 showed ED use reductions
following a CM or similar intervention, while five
studies9,11,14,40,41 did not. In terms of study design, sample size
and intervention (i.e. in-person CM intervention), our trial
most closely matches that of Shumway,12 who found an
additional reduction of one ED visit. A 1997 RCT did not
find a reduction in number of ED visits following a CM-like
intervention11; however, they defined frequent use as greater
than 10 annual ED visits, and thus their results may be difficult
to compare to our own. Two RCTs conducted in Sweden used
a lower threshold to define ED frequent use (>3 visits), and
implemented interventions different from ours.13,14
Differences in the definition of frequent use and in intervention design
and setting may have contributed to these varying results. Our
results may have been influenced by the fact that despite our
use of a validated definition,1 most participants had only 5–6
visits at enrollment, and CM may be of greater benefit for
those with higher baseline ED use, given the increased
vulnerability of this group.12,42 Furthermore, over one-third of
participants were from Africa, Latin America or Asia, regions
of origin common for asylum seekers, refugees or
undocumented immigrants living in Switzerland. The limited primary
care services in these regions43 may have led to increased ED
use among these participants. Finally, significantly lower
education among intervention group participants may have
increased ED use in this group.44
Number of ED visits at enrollment (prior 12 months)
Other (e.g. Africa, Asia, Lat Am)
High school/vocational school
Do not know/other
Limited French proficiency
No primary care physician
aGeneralized linear model for count data (negative binomial distribution)
b Stepwise regression (p = 0.10)
c Bb^ is the coefficient of the regression model
dReference category: controls
eReference category: female
f Reference category: Swiss nationality
gReference category: compulsory school only
hSocial determinants (at least one determinant): complex family situation, social isolation, financial hardship, inadequate housing, lack of employment,
limited French proficiency, problems with immigration status
iSomatic determinants (at least one determinant): chronic and/or acute severe illness, comorbidity, polypharmacy, treatment non-adherence
jMental determinants (at least one determinant): depression, anxiety, personality disorder, psychotic disorder
kAt-risk behaviors (at least one determinant): alcohol use, tobacco use, Illicit drug use
Another important consideration is that the number of ED
visits decreased in both groups. Contact between control
group participants and the research team may have introduced
contamination bias, contributing to a reduction in ED use
among controls. However, despite receiving information
about the CM team at enrollment, no control group participant
proactively contacted the team to seek out services. A second
explanation is that ED use becomes less frequent over time
(i.e. regression to the mean), even without intervention.7,19
Finally, the Hawthorne effect—that people have a tendency to
change their behavior when under observation—may have
influenced ED use among these participants. In the Reinius
study,13 control participants were passively observed in a
Zelen’s design, adopted in part to avoid a Hawthorne effect.
This pragmatic RCT has several limitations and strengths.
First, we conducted this study at a single site, the sole tertiary
care center in the canton of Vaud and one of five academic
medical centers in Switzerland. However, in order to
maximize the generalizability of our findings, we recruited a
representative study sample of frequent ED users.16,45 In addition,
the design of the Swiss health system—privatized but with
universal coverage—allows for generalization of our findings
to North America, Europe and parts of Asia. Second, the
enrollment rate of 47.5 % could have biased or contributed
to our non-significant results. This suggests that CM services
may not appeal to some frequent users, who may benefit from
alternative outreach strategies. However, this enrollment rate
is comparable to those of other studies,13 and we recruited an
adequate number of participants based on power calculations.
Although we anticipated a dropout rate of 30 %, we retained
78 % of study participants. Our intention-to-treat analysis also
reflects a Breal world^ scenario of caring for this highly
vulnerable population. Third, we were unable to track the ED use
of participants who visited an outside hospital or moved out of
the area. Fourth, our small but experienced team was unable to
approach 217 individuals during recruitment and were not
blinded to allocation given their role in delivering the
intervention; thus we cannot exclude a possible selection bias,
despite specifically instructing our team against this. Fifth,
excluding frequent users who had previously received CM
services may have impacted our results. However, the
characteristics of the frequent users we enrolled were qualitatively
similar to participants in previous studies,16,22 suggesting that
we recruited a representative sample. Finally, the 12-month
study duration may have limited our ability to demonstrate the
full scope of the benefit (or lack thereof) over a longer period.
However, Shumway12 performed sensitivity analyses
demonstrating similar cost-effectiveness of a CM intervention at
12 months and 24 months, suggesting that 1 year may be an
appropriate study length.
Evidence regarding the impact of the CM on ED use
remains inconclusive. A key goal of this CM intervention
was to offer improved orientation and redirection to a range
of hospital and community-based services. While most
participants already had a PCP, caring for these highly vulnerable
patients independently in the community is challenging. The
main contribution of this intervention was to facilitate and
coordinate care of frequent users, with the PCP integrated into
this approach. The development of effective and efficient
strategies to improve care for frequent users of the ED and
other health services is an area of great interest. CM could
serve as a link between disparate parts of complex health
systems, with the PCP as the nexus for care continuity. CM
teams should focus on modifiable SDH—such as housing or
employment—in addition to traditional biomedical risk
factors. Research investigating the impact of CM on specific
highly vulnerable frequent users, such forced migrants or
those with low health literacy, is warranted. Future research
should explore patient-reported outcomes, and analyze costs at
the institutional and community levels, taking into account the
long-term needs of patients.
This study was funded by the by the Swiss National Science
Foundation (no: 32003B_135762).
The authors wish to thank the research team–Séverine Alary, Jolanta
Nobs, and Sarah Kahnt–and the CM team (Corine Ansermet, Marina
Canepa-Allen, and Laetitia LeNocher) for their contribution to the collection
of the data and the medical care provided to the frequent users of the
emergency department. We would also like to acknowledge Valentin
Rousson for his invaluable guidance regarding our methodology and
Phillipe Staeger for his clinical contributions to this study.
Prior Presentations:: Preliminary study findings were presented at
Society of General Internal Medicine (SGIM) 38th Annual Meeting,
, Toronto, ON, Canada, oral presentation (plenary
Swiss Society of General Internal Medicine 83rd Annual Congress,
, Basel, Switzerland (oral presentation, 2nd prize
among oral presentations)
Corresponding Author: Patrick Bodenmann, MD, MSc; Vulnerable
Populations Center, Department of Ambulatory Care and Community
MedicineUniversity of Lausanne, Lausanne, Switzerland
Compliance with Ethical Standards:
Conflict of Interest: The authors declare that they do not have a
conflict of interest.
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