Professional Case Management
Vol. 17, No. 6, 267-275
Copyright 2012 © Wolters Kluwer Health | Lippincott Williams & Wilkins
CE
Community-Based Case Management
for Uninsured Patients With Chronic
Diseases
Effects on Acute Care Utilization and Costs
Alison Glendenning-Napoli, BSN, RN-BC, Beverly Dowling, CPA, CHFP, John Pulvino, PA-C,
Gwen Baillargeon, MS, and Ben G. Raimer, MD
ABSTRACT
Purpose of the Study: To examine the effects of a community-based case management program on acute
health care utilization and associated costs in uninsured patients with 1 or more chronic diseases.
Primary Practice Setting: Large regional academic medical center that provides health care services for the
vast majority of indigent patients in the area.
Methodology and Sample: This was a retrospective study of 83 patients who enrolled in a case management
program between April 2007 and August 2008 on the basis of 1 or more emergency department visits or acute
hospitalizations. Paired t tests were used to compare utilization and costs before and after enrollment.
Results: Overall, acute outpatient encounters decreased by 62% and inpatient admissions by 53%, whereas
primary care visits increased by 162%. Participation in the case management program was also associated with
a 41% reduction in overall aggregate costs, from $16,208 preintervention to $9,541 postintervention ( p ⫽ .004).
Implications for Case management Practice: The results of this study suggest that intensive case
management can reduce acute care utilization and costs and increase primary care follow-up among uninsured
patients with certain chronic diseases.
Key words: case management, chronic diseases, emergency care, medical indigency, primary health care
T
he United States is the only industrialized
nation that does not provide universal health
coverage for its citizens. In 1987, when the
Census Bureau began collecting data on health insurance coverage, an estimated 31 million U.S. residents
(12.9% of the population) lacked health insurance
(DeNavas-Walt, Proctor, & Smith, 2011). Although
the proportion of uninsured Americans has gradually
increased over the past two decades, the current economic recession has given rise to an unprecedented
number of people without health insurance. In 2010,
an estimated 49.9 million individuals (16.3% of the
population) were uninsured (DeNavas-Walt et al.,
2011). Because about 60% of Americans obtain
health insurance through their employers, the loss of
a job can lead to potentially catastrophic health consequences. Between 2008 and 2010, an estimated 15
million adults lost both their jobs and their job-based
health benefits. The majority of these individuals
(57%) were unable to find another source of health
care coverage and became uninsured (Collins, Doty,
Robertson, & Garber, 2011).
Many newly unemployed and uninsured Americans have turned to public insurance programs in the
wake of what has been characterized as the worst
financial meltdown since the Great Depression. Medicaid enrollment increased by 17.8% between the
start of the recession in December 2007 and June
2010. By the end of June 2010, more than 50 million persons were enrolled in Medicaid—the largest
number of enrollees in the history of the program
(Kaiser Commission on Medicaid and the Uninsured,
2011). Even though Medicaid has provided a safety
This study was presented in part at the 139th Annual
Meeting of the American Public Health Association,
Washington, DC, November 1, 2011.
Address correspondence to Alison Glendenning-Napoli,
BSN, RN-BC, Community Health Program, University of
Texas Medical Branch, 301 University Boulevard, Galveston, TX 77555 ([email protected]).
The authors report no conflicts of interest.
DOI: 10.1097/NCM.0b013e3182687f2b
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NCM200283.indd 267
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net for millions of Americans who have lost their jobs
and health insurance, millions more do not qualify
because of the program’s restrictive eligibility criteria. Most states now restrict Medicaid coverage to
pregnant women, children, and parents with very
low incomes; nondisabled adults without children
remain ineligible for Medicaid in the vast majority of
states (Heberlein, Brooks, Guyer, Artiga, & Stephens,
2011). The scheduled implementation of the Affordable Care Act in 2014 should expand eligibility for
Medicaid benefits (Collins et al., 2011). Until then,
however, the nation’s continuing economic problems
have forced many states to either impose or propose
cuts in Medicaid spending (Kaiser Commission on
Medicaid and the Uninsured, 2012; Parisi, 2010).
Compared with persons who have medical insurance, the uninsured face numerous barriers to health
care, resulting in poorer overall health status, delays in
accessing treatment, and increased morbidity and mortality (Ayanian, Weissman, Schneider, Ginsburg, &
Zaslavsky, 2000; Freeman, Kadiyala, Bell, & Martin,
2008; McWilliams, 2009; Wilper et al., 2009). Historically, the United States has relied on a patchwork
“system” of safety net providers to provide health care
for the uninsured (Institute of Medicine, 2000).
Unfortunately, the limited capacity of the system
to provide adequate access to preventive, primary,
and specialty care has forced many uninsured persons
to rely on hospital emergency departments as a major
source for their health care services (Grumbach,
Keane, & Bindman, 1993; Richardson & Hwang,
2001). For example, an analysis of emergency department usage patterns of the major safety net hospitals in Houston, TX, showed that approximately
one-half of all emergency department visits were for
Unfortunately, the limited capacity of
the system to provide adequate access to
preventive, primary, and specialty care has
forced many uninsured persons to rely on
hospital emergency departments as a major
source for their health care…. For example,
an analysis of emergency department usage
patterns of the major safety net hospitals in
Houston, TX, showed that approximately
one-half of all emergency department visits
were for nonemergent, primary care-related
conditions and that the uninsured were
responsible for 52% of such visits in 2002
and 54% in 2003.
268
Such reliance on the emergency department
for basic health care contributes to
fragmented services and the growing problem
of emergency department overcrowding and
rising health care costs.
nonemergent, primary care-related conditions and
that the uninsured were responsible for 52% of such
visits in 2002 and 54% in 2003 (Begley, Vojvodic,
Seo, & Burau, 2006). Preliminary reports suggest
that this problem has been exacerbated by the current
economic crisis. According to the National Association of Public Hospitals and Health Systems (2010),
emergency department visits at safety net health systems by uninsured patients increased by 10%–15%
in the last 6 months of 2009, when compared with
the beginning of the recession.
Uninsured patients with chronic diseases are more
likely to visit the emergency department for treatment
of their conditions than those who are insured (Collins,
Davis, Doty, Kriss, & Holmgren, 2006; Wilper et al.,
2008). They also are less likely to have a primary care
medical home (Wilper et al., 2008) and more likely
to be hospitalized for their conditions (Collins et al.,
2006). Such reliance on the emergency department for
basic health care contributes to fragmented services
and the growing problem of emergency department
overcrowding and rising health care costs.
Case management interventions to reduce inappropriate emergency department usage and its associated costs have met with some success among
populations covered by Medicaid (Grossman, Rich,
& Johnson, 1998; Hurley, Freund, & Taylor, 1989).
As an example, analysis of claims utilization data
from four Medicaid demonstration programs showed
that implementation of primary care case management in a population of both children and adults was
associated with substantial reductions in the proportion of persons making emergency department visits
(Hurley et al., 1989). Experience with case management programs targeted at uninsured populations is
more limited, however, and varying degrees of success in reducing acute health care utilization and
associated costs have been reported (see the Discussion section; Horwitz, Busch, Balestracci, Ellingson,
& Rawlings, 2005; Wetta-Hall, 2007).
To further examine the use of case management
interventions among the uninsured, we analyzed the
outcomes of an intensive case management program
among a cohort of uninsured patients with a history
of emergency department visits and/or hospitalizations for treatment of one or more chronic diseases
Professional Case Management Vol. 17/No. 6
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NCM200283.indd 268
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over a 17-month study period. We hypothesized that
patient participation in an intensive case management
program would reduce the number of acute health
care encounters and associated costs and increase the
use of primary care services.
METHODS
Sample
The study population consisted of a convenience
sample (i.e., nonprobability sample; see the Limitations section) of 83 patients without medical insurance who volunteered to participate in an intensive
case management program at the University of Texas
Medical Branch (UTMB) between April 1, 2007, and
August 31, 2008. Criteria for inclusion in the study
included: (1) a diagnosis of diabetes mellitus, essential hypertension, congestive heart failure, or coronary artery disease (alone or in combination); (2) a
history of at least one inpatient admission or acute
outpatient encounter (i.e., emergency department
visit, outpatient day surgery, or hospital observation
but not admission) at the UTMB within 12 months
before enrollment; and (3) participation in the case
management program for a minimum of 6 months,
including at least two encounters with a case manager. Patients with a co-occurring serious mental illness or substance abuse problem were not eligible for
enrollment. Each patient’s primary and secondary
diagnoses were established at the time of the initial
acute outpatient visit or inpatient admission and classified according to the International Classification
of Diseases, Ninth Revision, Clinical Modification.
During the 17-month study period, a total of 363
eligible patients were identified. In spite of multiple
attempts, 266 of the patients could not be contacted
for various reasons (e.g., did not return phone calls,
disconnected phones). Another 14 patients who were
contacted declined to enroll. This left a study sample
of 83 patients. Recruitment of additional study subjects and a longer follow-up period were not possible
because of Hurricane Ike, which made landfall in
Galveston, TX, in September 2008. The storm inundated more than 100 buildings on the UTMB campus
with up to 10 feet of water, necessitating the closure of
all clinics and hospitals and the temporary suspension
of most indigent care services, including the intensive
case management program (Lozano, 2008; Ortolon,
2009). The study was reviewed and approved by the
UTMB institutional review board.
Intervention
The UTMB Community Health Program implemented a case management program in 2007 with
the goal of reducing potentially avoidable hospitalizations and acute care visits, while increasing access
to primary care for uninsured patients with select
chronic diseases. Patients who are eligible for the
program are identified on the basis of a hospitalization, acute outpatient encounter, or recurring clinic
visits. A case manager, who is a registered nurse,
then contacts the patient by telephone, provides an
overall description of the program, and invites the
patient to enroll. If the patient agrees to participate,
the case manager schedules a home visit to enroll the
patient and conduct a needs assessment that focuses
on identifying barriers to accessing health care and
determining the patient’s health literacy level, especially knowledge of his or her medical condition and
how to manage it. The case manager then develops
a preventive care regimen tailored to the specific
needs of the patient. A master’s-level social worker
assists the case manager in identifying the patient’s
need for public health programs and social services
(e.g., county indigent health care program, Medicaid,
disability, housing, and food assistance). Additional
home visits are scheduled on an as-needed basis to
assist patients in the day-to-day management of their
chronic condition, such as education about the correct use of glucometers and blood pressure monitors, dietary and lifestyle modifications, and strategies to enhance adherence to prescribed medication
regimens. Case managers also provide medication
education sessions and help patients apply for pharmacy assistance programs. In addition, case managers accompany patients to their provider/clinic visits
in an effort to better engage the patients in their care
and promote a positive, effective relationship with
their primary care provider. The case manager then
reinforces the interventions with telephonic followup or further home visits or both to check progress,
answer questions, and provide support.
Data Collection
Two data sources were used: an administrative billing database maintained by the UTMB Department of
Finance and an electronic clinical information system
and registry (Patient Electronic Care System, Aristos
Group, Inc., Austin, TX) maintained by the UTMB
Community Health Program. The administrative
database was used to identify all clinical encounters
(i.e., inpatient admissions, acute outpatient encounters, and clinic visits) that occurred during the study
period and were related to treatment for any of the
four chronic diseases under study and also to identify the costs associated with these services. The clinical information system was used to determine the
patients’ demographic characteristics (age, gender, and
race/ethnicity) and the duration of active participation
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in the case management program. The two data sets
were linked using medical record numbers.
TABLE 1
Demographic and Clinical Characteristics
of Sample
Statistical Analysis
Health care utilization and associated costs before
enrollment in the case management program were
compared with an equal period of time after enrollment for each individual. For example, if a patient
was enrolled for 10 months, we compared utilization
and cost history for the period of 10 months prior to
enrollment with the 10-month period during enrollment. Because parallel health care utilization and cost
data were collected before and after enrollment in the
program, analyses were conducted such that each
patient served as his or her own historical control.
Statistical analyses were conducted using SAS software, version 9.1.3 (SAS Institute, Cary, NC). Paired
t tests were used to compare the mean differences
for both health care utilization and associated costs
before and after the intervention. All of the analyses were stratified across gender, race/ethnicity, and
age. Administrative costs of the intervention program
itself (e.g., enrolling patients, providing intervention
services) were not included in our cost analyses.
Statistical significance was defined as a p value of less
than .05.
RESULTS
Table 1 presents the demographic and clinical characteristics of the study cohort. Of the 83 patients in
the sample, 60.2% were female, 51.8% were nonHispanic White, and 73.5% were between 50 and
65 years of age. Patient age at the time of enrollment
in the case management program ranged between
18 and 65 years. Of the four chronic diseases under
study, hypertension was the most prevalent among
the cohort (88.0%), followed by diabetes (53.0%),
coronary artery disease (42.2%), and congestive heart
failure (30.1%). The vast majority of the patients
(84.3%) had more than one of the four chronic diseases. Most of the patients (67.5%) had participated
in the intervention program for 12 months or longer
(see Table 2).
Participation in the case management program was
associated with statistically significant reductions in
both acute outpatient encounters and inpatient admissions along with a concomitant increase in primary
care clinic visits (see Table 3). The mean number of
acute outpatient encounters declined from 0.70 before
enrollment in the program to 0.27 after enrollment
(p ⫽ .0007); inpatient admissions declined from a mean
of 1.24 to 0.58 (p ⬍ .0001). Conversely, clinic visits
increased from a mean of 4.13 to 10.82 (p ⬍ .0001).
All demographically stratified analyses showed similar
270
Total Sample
Males
Females
83 (100)
33 (39.8)
50 (60.2)
Non-Hispanic White
43 (51.8)
15 (45.5)
28 (56.0)
Hispanic
19 (22.9)
6 (18.2)
13 (26.0)
African American
21 (25.3)
12 (36.4)
9 (18.0)
N (%)
Dempographic characteristics
Race/ethnicity
Age range (years)
18–49
22 (26.5)
10 (30.3)
12 (24.0)
50–65
61 (73.5)
23 (69.7)
38 (76.0)
Diabetes
44 (53.0)
16 (48.5)
28 (56.0)
Hypertension
73 (88.0)
29 (87.9)
44 (88.0)
Congestive heart failure
25 (30.1)
14 (42.4)
11 (22.0)
Coronary artery disease
35 (42.2)
13 (39.4)
22 (44.0)
Clinical characteristics
Chronic diseases
Comorbidity
Only 1 chronic disease
13 (15.7)
4 (12.1)
9 (18.0)
2 chronic diseases
18 (21.7)
8 (24.2)
10 (20.0)
3 chronic diseases
28 (33.7)
13 (39.4)
15 (30.0)
4 chronic diseases
24 (28.9)
8 (24.2)
16 (32.0)
statistically significant decreases or increases, with
the exception of acute outpatient encounters for nonHispanic Whites (see Table 3). The total number of
acute outpatient encounters decreased by 62%, from
58 preenrollment to 22 postenrollment, whereas inpatient admissions decreased by 53%, from 103 to 48. In
contrast, the total number of primary care clinic visits
increased by 162%, from 343 to 898 (see Table 4).
Likewise, participation in the program was associated with statistically significant reductions in costs for
acute outpatient encounters (p ⫽ .009) and inpatient
hospitalizations (p ⫽ .002), and an increase in costs for
primary care clinic visits (p ⫽ .02) (see Table 5). Specifically, the mean per patient cost for acute outpatient
TABLE 2
Duration of Participation in Community
Health Program (Cohort of 83 Patients)
Months
n
%
6 to ⬍8
5
6.0
8 to ⬍10
2
2.4
10 to ⬍12
20
24.1
12 to ⬍14
48
57.8
-8
9.6
14–17
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TABLE 3
Comparison of Health Care Utilization Before and After Enrollment in Community Health Program
Acute Outpatient Encountersa
Pre-CHP,
M (SD)
Post-CHP,
M (SD)
0.70 (0.95)
Female (n ⫽ 50)
Male (n ⫽ 33)
Inpatient Admissions
p
Pre-CHP,
M (SD)
Post-CHP,
M (SD)
0.27 (0.61)
.0007
1.24 (1.09)
0.58 (1.00)
0.70 (1.05)
0.24 (0.59)
.008
1.18 (1.02)
0.60 (0.97)
0.70 (0.77)
0.30 (0.64)
.04
1.33 (1.19)
0.55 (1.06)
Non-Hispanic White (n ⫽ 43)
0.60 (0.93)
0.33 (0.71)
.12
1.33 (1.13)
0.74 (1.16)
Hispanic (n ⫽ 19)
0.84 (1.12)
0.11 (0.46)
.02
1.16 (0.96)
0.32 (0.48)
African American (n ⫽ 21)
0.76 (0.83)
0.29 (0.46)
.01
1.14 (1.15)
18–49 (n ⫽ 22)
1.09 (1.41)
0.32 (0.57)
.02
50–65 (n ⫽ 61)
0.56 (0.67)
0.25 (0.62)
.01
Characteristics
Total sample (N ⫽ 83)
Clinic Visits
p
Pre-CHP,
M (SD)
Post-CHP,
M (SD)
p
⬍.0001
4.13 (4.01)
10.82 (9.08)
⬍.0001
.0001
4.68 (4.29)
11.06 (8.84)
⬍.0001
.004
3.30 (3.44)
10.45 (9.56)
⬍.0001
.005
3.79 (4.39)
11.47 (9.53)
⬍.0001
.0003
4.79 (3.44)
9.42 (5.94)
.004
0.48 (0.98)
.02
4.24 (3.75)
10.76 (10.62)
.004
1.54 (1.41)
0.77 (1.07)
.03
3.59 (3.91)
11.32 (10.58)
.001
1.13 (0.94)
0.51 (0.98)
⬍.0001
4.33 (4.06)
10.64 (8.56)
⬍.0001
Gender
Race/ethnicity
Age range (years)
Note. CHP ⫽ Community Health Program.
a
Includes emergency department visit, outpatient day surgery, and hospital observation without admission.
encounters decreased by 62%, from $1,830 preenrollment to $700 postenrollment; mean cost for inpatient admissions decreased by 53%, from $13,341 to
$6,324; and mean cost for primary care visits increased
by 143%, from $1,036 to $2,517. When stratified by
gender, men showed a greater percentage decrease in
costs than women for both acute outpatient encounters (69% vs. 57%; p ⫽ .03) and inpatient admissions
(58% vs. 49%; p ⫽ .01). When stratified by race/ethnicity as well as age, statistically significant reductions
in inpatient admission costs were observed among
non-Hispanic Whites (p ⫽ .01), African Americans (p
⫽ .03), and patients between 50 and 65 years of age
(p ⫽ .01). However, a statistically significant reduction
in costs for acute outpatient encounters was observed
only among African American patients (p ⫽ .04). The
increase in the postenrollment costs for clinic visits did
not reach statistical significance when analyzed across
any of the demographic strata. The mean aggregate
health care utilization cost per patient decreased by
TABLE 4
Comparison of Health Care Encounters
Before and After Enrollment in Community
Health Program
Number of Encounters
Type of Encounter
Pre-CHP
Post-CHP
Percent
Change
58
22
⫺62.1
Inpatient admissions
103
48
⫺53.4
Primary care clinic visits
343
898
161.8
Acute outpatient encountersa
Note. CHP ⫽ Community Health Program.
a
Includes emergency department visit, outpatient day surgery, and hospital
observation without admission.
41%, from $16,208 preintervention to $9,541 postintervention (p ⫽ .004) (see Table 6). When stratified
by demographic characteristics, statistically significant
reductions in mean aggregate costs were observed
among men (p ⫽ .03), non-Hispanic Whites (p ⫽ .02),
and patients between 50 and 65 years of age (p ⫽ .01).
DISCUSSION
In this study of uninsured patients with one or more
chronic diseases, the introduction of an intensive case
management program was associated with statistically significant reductions in acute health care utilization and a concomitant increase in primary care
clinic visits. Overall, acute outpatient encounters
decreased by 62% and inpatient admissions by 53%
whereas primary care visits increased by 162%. Participation in the case management program was also
associated with a 41% reduction in overall aggregate
costs, from $16,208 preintervention to $9,541 postintervention (p ⫽ .004).
Only a few studies have evaluated the impact of
case management interventions on health care utilization and costs among patients without medical
insurance. A direct comparison of our results with
these earlier studies is difficult because of differences
in study designs, methods, and outcome measures.
Wetta-Hall (2007) analyzed the outcomes of a convenience sample of 492 uninsured patients who enrolled
in a case management program that was based on
a model similar to ours. Half of the sample had a
history of chronic illness. At 6 months postintervention, the total number of emergency department visits
among the sample had declined by 48%. On the basis
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TABLE 5
Comparison of Health Care Utilization Costsa Before and After Enrollment in Community Health
Program
Acute Outpatient Encountersb
Characteristics
Total sample (N ⫽ 83)
Pre-CHP,
M (SD)
Post-CHP,
M (SD)
1,830 (3,087)
Inpatient Admissions
Clinic Visits
p
Pre-CHP,
M (SD)
Post-CHP,
M (SD)
p
Pre-CHP,
M (SD)
Post-CHP,
M (SD)
700 (2,224)
.009
13,341 (21,400)
6,324 (12,390)
.002
p
1,036 (1,059)
2,517 (5,456)
.02
Gender
Female (n ⫽ 50)
1,801 (3,436)
776 (2,594)
.10
12,737 (24,056)
6,522 (12,291)
.05
1,178 (1,159)
2,206 (4,592)
.13
Male (n ⫽ 33)
1,875 (2,518)
584 (1,534)
.03
14,258 (16,911)
6,024 (12,724)
.01
822 (858)
2,998 (6,604)
.06
Non-Hispanic White
(n ⫽ 43)
1,453 (2,860)
941 (2,829)
.40
16,655 (22,158)
8,483 (15,079)
.01
941 (1,143)
2,277 (4,751)
.07
Hispanic (n ⫽ 19)
2,397 (3,813)
331 (1,441)
.05
11,822 (27,911)
4,616 (8,880)
.27
1,235 (1,007)
1,367 (981)
.63
African American
(n ⫽ 21)
2,090 (2,852)
541 (1,153)
.04
7,931 (9,431)
3,449 (7,709)
.03
1,052 (940)
4,049 (8,362)
.12
Race/ethnicity
Age range (years)
18–49 (n ⫽ 22)
1,909 (3,662)
438 (1,084)
.09
20,227 (31,238)
8,064 (14,002)
.09
862 (1,002)
2,700 (5,049)
.10
50–65 (n ⫽ 61)
1,802 (2,886)
794 (2,513)
.05
10,858 (16,146)
5,697 (11,818)
.01
1,099 (1,080)
2,450 (5,634)
.07
Note. CHP ⫽ Community Health Program.
a
Costs are given in U.S. dollars. Administrative costs of the intensive case management program were not included in cost calculations.
b
Includes emergency department visit, outpatient day surgery, and hospital observation without admission.
of the assumption that the rate of emergency department visits would remain the same in the absence of
interventions, the author not only estimated that case
management resulted in a charge avoidance of nearly
$1.5 million but also cautioned that the cost savings
might be overestimated because the costs of primary
care services were not measured directly. Like those
TABLE 6
Aggregate Costs of Health Care Utilization
Before and After Enrollment in Community
Health Program
Aggregate Costsa
Characteristics
Total sample (N ⫽ 83)
Pre-CHP,
M (SD)
16,208 (21,265)
Post-CHP,
M (SD)
9,541 (13,681)
p
.004
Gender
Female (n ⫽ 50)
15,715 (24,061)
9,504 (13,373)
.05
Male (n ⫽ 33)
16,954 (16,473)
9,597 (14,344)
.03
Non-Hispanic
White (n ⫽ 43)
19,048 (22,254)
11,700 (15,994)
.02
Hispanic (n ⫽ 19)
15,454 (27,423)
6,314 (9,180)
.16
African American
(n ⫽ 21)
11,073 (9,573)
8,039 (11,492)
.25
18–49 (n ⫽ 22)
22,998 (30,948)
11,203 (14,969)
.10
50–65 (n ⫽ 61)
13,759 (16,118)
8,942 (13,266)
.01
Race/ethnicity
Age range (years)
Note. CHP ⫽ Community Health Program.
a
Costs are given in U.S. dollars. Post-CHP aggregate costs do not include the
administrative costs of the CHP program.
272
of our study, the results reported by Wetta-Hall were
based on a convenience sample whereby each subject served as his or her own control. In addition,
approximately two thirds of those eligible for the
case management programs in the two studies failed
to respond to repeated attempts to contact them.
Horwitz et al. (2005) evaluated a case management program designed to increase access to primary
care and reduce emergency department usage among
uninsured patients. Using a randomized design, 230
patients who were seen at a Level 1 urban trauma
center were enrolled in the study and assigned to
either an intervention group or a comparison group.
Case managers used mail, telephone, and home visits
to contact patients in the intervention group and help
link them with a primary care provider. At 60 days
after enrollment, the intervention subjects were significantly more likely to have established a primary
care contact than the comparison subjects (51.2% vs.
13.8%, p ⬍ .0001). In contrast, at 6 months after
enrollment, there was no statistically significant difference between groups in either the number of postintervention emergency department visits or hospitalizations, although the average cost of a postenrollment
emergency department visit was 31% lower in the
intervention group than in the comparison group.
The failure of the case management interventions
to reduce emergency department visits in this study
may have been a result of several factors. The interventions described by Horwitz et al. appear to have
focused primarily on helping patients select a primary
care provider and then scheduling an appointment
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In this study of uninsured patients with one or more chronic diseases, the introduction
of an intensive case management program was associated with statistically significant
reductions in acute health care utilization and a concomitant increase in primary care
clinic visits. Overall, acute outpatient encounters decreased by 62% and inpatient
admissions by 53% whereas primary care visits increased by 162%. Participation in
the case management program was also associated with a 41% reduction in overall
aggregate costs, from $16,208 preintervention to $9,541 postintervention (p ⫽ .004).
with the provider. Although primary care contacts
were significantly increased with these interventions,
they may not have been sufficient to change longstanding emergency department utilization patterns.
In contrast, our study and that of Wetta-Hall (2007)
employed additional interventions that included case
managers making home visits to educate patients
about self-management of their chronic illnesses as
well as attending clinic visits with their patients. In
addition, social workers were paired with the nurse
case managers to help patients access an array of
social services and support networks. The length
of the intervention may also play a role in reducing
emergency department and other acute health care
usage; the vast majority (67.5%) of the patients in
our sample had participated in the case management
program for 12 months or longer.
When stratified by age, gender, and race/ethnicity,
our analyses showed that case management was
equally effective in reducing acute health care utilization and increasing primary care follow-up among
both men and women as well as among young and
older adults. The only exception was for non-Hispanic Whites, who failed to demonstrate a significant postintervention reduction in acute outpatient
encounters despite a substantial increase in primary
care contacts. Horwitz et al. (2005) found no association between these demographic characteristics (i.e.,
age, gender, and race/ethnicity) and the likelihood
of accessing primary care among case management
intervention subjects. They did, however, observe a
marginal relationship with language, in that nonEnglish-speaking subjects were more likely to visit a
primary care provider. In terms of costs, we found
that the reductions in postintervention expenditures
for both acute outpatient encounters and hospitalizations were significantly greater for men than for
women. Statistically significant reductions in hospitalization costs were observed among non-Hispanic
Whites, African Americans, and patients between 50
and 65 years of age. In contrast, a statistically significant reduction (74% decrease) in costs for emergency
department visits and other acute outpatient encounters was observed only among African American
patients. Although it is likely that the demographic
differences observed in our study were affected by
additional variables such as socioeconomic and
behavioral characteristics, our database did not permit us to perform such an analysis. Further studies with larger and more representative samples are
needed to further examine the potential effects of
demographic characteristics on health care usage and
costs in the uninsured population.
LIMITATIONS
The results of this study should be interpreted in
the context of several limitations. Because our study
utilized a nonprobability sample (i.e., a convenience
sample) rather than a probability sample (e.g., a
random sample), it is possible that our results were
affected by selection bias and are not generalizable to
the large group of eligible patients who did not enroll
in the program. That is, the subgroup of patients who
chose not to participate in the intervention may have
been less motivated to improve their health or may
have had more complex health or socioeconomic
problems (Wetta-Hall, 2007). Furthermore, because
our study was limited to an uninsured population
from a relatively small geographic area served by a
single hospital, it is unclear whether our findings can
be generalized to populations from other geographic
regions. In addition, our results may not generalize to
those patients who were ineligible for the intervention because of co-occurring psychiatric disorders.
Another limitation was the small sample size in our
study. Finally, because we did not factor in the administrative costs of the intervention program itself in
our calculations, it is possible that the cost savings
associated with the intervention were overestimated.
CONCLUSIONS
Clinical case management programs have become
increasingly popular as a strategy to curb excessive and expensive health care services, particularly
in persons with chronic diseases and those who are
uninsured or underinsured. Nonetheless, only a few
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studies have evaluated the effectiveness of case management interventions in meeting this goal. In spite of
its limitations, our study provides additional evidence
that intensive clinical case management can reduce
acute care utilization and costs and increase primary
care follow-up in uninsured patients with chronic diseases. We believe that the results of our study may
be applicable to other safety net institutions that are
struggling to cope with escalating health care costs
and the growing number of uninsured persons. Additional studies with randomized designs and large
sample sizes are needed to validate our findings and
to identify the most effective components of case
management interventions.
ACKNOWLEDGMENTS
We thank Mary Lou Wallin for assistance in data
compilation, Leonard Pechacek for editing and writing assistance, and Jacques Baillargeon, PhD, for critical review of the manuscript.
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Alison Glendenning-Napoli, BSN, RN-BC, is Director of outpatient
care management and oversees the Community Health Program at the
University of Texas Medical Branch. She has more than 16 years of
experience in program development, case management, and nursing
leadership. She is board certified in case management and is currently
pursuing chronic care professional certification.
Beverly Dowling, CPA, CHFP, is Assistant Vice President of the
University of Texas Medical Branch Community Health Network. She
has 20 years of experience in health care with a focus on implementing
new health care delivery models for uninsured and underinsured
populations.
John Pulvino, PA-C, is Senior Director of quality and outcomes for
the Correctional Managed Care Program at the University of Texas
Medical Branch. He has more than 20 years of experience in developing,
implementing, and refining quality improvement and case management
processes in the health care field.
Gwen Baillargeon, MS, is a biostatistician for the Correctional Managed Care Program at the University of Texas Medical Branch. Gwen has
more than 13 years of experience as a biostatistician and SAS programmer in the pharmaceutical industry and the academic setting and has
coauthored a number of publications in peer-reviewed medical journals.
Ben G. Raimer, MD, is Professor in the Departments of Pediatrics,
Family Medicine, and Preventive Medicine and Community Health at the
University of Texas Medical Branch and Senior Vice President of the Office
of Health Policy and Legislative Affairs. He has extensive experience in
developing programs to improve the delivery and quality of health care
for rural and underserved populations in Texas.
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