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Building a Medicaid Ambulatory Complex Care Program Within an Urban Medical Home


Abstract and Figures

Five percent of Medicaid patients account for 50% of total costs. Preventable costs are often incurred by patients with complex medical, behavioral, and social needs who disproportionately utilize acute care services. Evidence for design, implementation, and evaluation of complex care programs in the urban Medicaid population is lacking. The article provides a description of a complex care program (CCP), challenges, and early outcomes based on a pre-post evaluation. The CCP was located within an existing urban medical home. Patients were eligible if they lived within 10 miles of the clinic and had at least 2 inpatient visits and/or 3 emergency room visits within the prior 6 months. Ambulatory Care Groups®were used to predict estimated total costs of patients, who were included if potential cost savings exceeded $5000. Patient experience and quality of care were assessed using validated measures and costs. Return on investment was calculated based on investment and cost savings. Costs include visits (clinic, specialty, and emergency room), hospital admissions, medications, tests and services, as well as salary and benefits of clinical staff. Eighty-six of 211 eligible patients (41%) were enrolled during the first 18 months of the pilot program. There were positive trends in quality metrics and patient satisfaction. The pre-post evaluation demonstrated a reduction in emergency room visits and hospitalizations (67% and 65%, respectively), which resulted in a 2.2:1 return on investment. This article offers lessons learned to colleagues considering population health approaches in the care of high-risk Medicaid patients.
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Original Article
Building a Medicaid Ambulatory Complex Care
Program Within an Urban Medical Home
Laura D. Sander, MD, MPH,
Michael Albert, MD,
Nkem Okeke, MD, MPH, MBA,
Steven Kravet, MD, MBA,
Katherine Rediger, MSN, CRNP,
Sarah Johnson Conway, MD,
and Maura J. McGuire, MD
Five percent of Medicaid patients account for 50% of total costs. Preventable costs are often incurred by
patients with complex medical, behavioral, and social needs who disproportionately utilize acute care services.
Evidence for design, implementation, and evaluation of complex care programs in the urban Medicaid population
is lacking. The article provides a description of a complex care program (CCP), challenges, and early outcomes
based on a pre–post evaluation. The CCP was located within an existing urban medical home. Patients were
eligible if they lived within 10 miles of the clinic and had at least 2 inpatient visits and/or 3 emergency room visits
within the prior 6 months. Ambulatory Care Groups
were used to predict estimated total costs of patients, who
were included if potential cost savings exceeded $5000. Patient experience and quality of care were assessed
using validated measures and costs. Return on investment was calculated based on investment and cost savings.
Costs include visits (clinic, specialty, and emergency room), hospital admissions, medications, tests and services,
as well as salary and benefits of clinical staff. Eighty-six of 211 eligible patients (41%) were enrolled during the
first 18 months of the pilot program. There were positive trends in quality metrics and patient satisfaction. The
pre–post evaluation demonstrated a reduction in emergency room visits and hospitalizations (67% and 65%,
respectively), which resulted in a 2.2:1 return on investment. This article offers lessons learned to colleagues
considering population health approaches in the care of high-risk Medicaid patients.
Keywords: complex care, high-need high-cost patients, population health
Health care spending in the United States is expected
to rise from 17.8% of gross domestic product in 2015
to 19.9% by 2025.
In 2015, Medicaid spending accounted
for 17% of national health expenses and 28.2% of all state
Because 5% of Medicaid beneficiaries drive
50% of total spending, it is critical that programs be devel-
oped to optimize care of high-need, high-cost (HNHC) pa-
tients to mitigate rising health care costs.
Innovative approaches are needed to support HNHC pa-
tients, who incur excess costs through complications of
chronic illness or avoidable emergency room or inpatient
During the last decade, numerous ‘‘complex
care’’ programs addressing the needs of HNHC patients
have been developed and evaluated.
Successful pro-
grams incorporate connections with patients and families,
provide access and coordination of care, and support care
transitions. They maintain reasonable clinician workload
and increased visit times. They also employ data and ana-
lytics to target patients who are most likely to benefit, and
monitor outcomes. Although some programs provide ex-
ternal case management services to complement existing
primary care, most successful programs provide these ser-
vices as part of direct patient care programs.
A recent
systematic review found mixed effectiveness on reducing
outcomes such as mortality and hospitalizations; these
studies included predominately elderly, nonwhite females.
The Medicaid population has unique challenges including
housing instability, food insecurity, and psychosocial needs.
Evidence shows that addressing social determinants such as
housing and food may reduce medical expenditures.
Johns Hopkins Community Physicians, Baltimore, Maryland.
Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Johns Hopkins Healthcare LLC, Glen Burnie, Maryland.
Volume 00, Number 00, 2018
ªMary Ann Liebert, Inc.
DOI: 10.1089/pop.2017.0200
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addition, because of the prevalence of substance abuse and
mental illness in Medicaid beneficiaries, access to behav-
ioral health services also is critical.
Questions remain about how to translate these principles into
practice. Gaps in knowledge, sustainability, and achievement of
program goals have resulted in calls for ongoing study and
experimentation with program design and supporting partner-
ships and policies.
In socially complex Medicaid popu-
lations, strategies to increase patient engagement and retention
are needed.
The study team recently implemented a new complex
care program (CCP) targeting Medicaid HNHC patients
within an existing urban medical home (UMH) practice.
This preliminary study sought to (1) develop a referral, re-
tention, and transition framework, (2) characterize patients
and their care needs, (3) pilot new analytics, (4) test staffing
models, and (5) demonstrate feasibility of value-based care
collaboration between a payer and provider group. While
analysis is under way, the team presents some preliminary
quality and cost outcomes from the first 18 months that have
supported continuation of this program.
The study team developed a comprehensive CCP for
Medicaid patients and launched this as a pilot in Baltimore,
MD, a city that reflects disparities realized across the United
States. The pilot was jointly sponsored by a large, regional
medical group practice and a payer group that administered
a Medicaid Managed Care Organization (MCO). Both were
part of a large integrated academic health system. The health
system used an electronic health record (EHR) with cen-
tralized data management and decision support, and the state
offered a regional health information exchange system to
link non–system hospitals and providers.
Key elements of the complex care delivery model
The CCP was developed as a separate service center within
an existing UMH that provided care to a panel of 6500 adult
patients. This practice identified more than 200 patients who
were high utilizers despite ongoing efforts within the UMH. To
focus resources on these more complex patients, the new CCP
was designed to increase access, care coordination, continuity,
and comprehensiveness of care, while providing social and
behavioral services within the care team. Figure 1 depicts
the conceptual framework of the complex care model. Pa-
tients transition back to standard primary care when indi-
vidualized targets, such as disease control, utilization, and
self-management skills (eg, schedule and attend appointments,
request medication refills) are achieved.
Payer–provider partnership. The Medicaid MCO and
provider group entered into a 2-year agreement in Novem-
ber 2014. The payer allocated half of the grant up front, with
the remainder contingent on meeting program metrics and
milestones in year 2. The provider group also billed fee for
service for patient care. Cost savings realized during the
pilot phase went solely to the MCO, as it was the risk-
bearing organization. Bidirectional data exchange between
the clinical team and the payer was developed to identify
patients and to monitor the program. The MCO provided
claims data to determine patient eligibility and conducted
quarterly pre–post claims utilization analysis. The provider
group reported monthly on outreach, enrollment, and real-
time utilization.
Clinical staff. The CCP clinical team consisted of 5 core
team members: a community health worker (CHW) for con-
nection to social services and to assist with outreach to new
patients, a licensed clinical professional counselor (LCPC) for
therapy and connection to mental health services, an office-
based certified medical assistant (CMA) who served as a
‘‘health navigator’’ with both clinical and administrative du-
ties, and a certified registered nurse practitioner (CRNP). The
team was led by a doctor of medicine (MD) medical director
who, together with the CRNP, provided primary care. All staff
worked together in 1 office. The team participated in daily
FIG. 1. Conceptual framework of the complex care program, Priority Access Primary Care. ER, emergency room; LCPC,
licensed clinical professional counselor; PAPC, Priority Access Primary Care.
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work rounds, weekly summary rounds, and monthly meetings
included leadership and payer representatives.
Primary care delivery. The clinic held office hours be-
tween 8 am and 5 pm and accommodated scheduled visits and
walk-in care. The surrounding UMH offered radiology, lab-
oratory, and pharmacy services on site. During and after office
hours, patients had 24-hour/7-day direct access to CCP pro-
viders via phone, text messaging, email, Facebook, and/or
FaceTime. Coverage was shared by the physician and CRNP.
Office visits were 40–60 minutes in duration; visits were
initially scheduled every week and then spaced out based on
each patient’s needs. Home visits were offered to supplement
office visits when needed. Of note, because of the prevalence
of chronic pain in the patients, all providers complete special
training in pain management, and a patient education module
was developed to improve the care of patients with chronic
Behavioral health services. All team members were
trained in motivational interviewing and trauma-informed care,
while the LCPC led behavioral health services and coordinated
care with community mental health providers. All patients
received baseline screenings for depression (Patient Health
Questionnaire-9), anxiety (Generalized Anxiety Disorder-7),
trauma (Posttraumatic Stress Disorder Symptom Scale), and
substance abuse. Patients participated in regular counseling and
engaged in art therapy within the clinic (Fig. 2). The MD on
the team was certified to prescribe buprenorphine for opiate
misuse disorders. Patients were referred to higher level be-
havioral health services, such as intensive outpatient programs
or residential treatment programs, when needed.
Social services. The team’s CHW coordinated social
services and social needs screening. Screening included
baseline and periodic assessment of barriers to care, such as
food access, legal aid, child care, social security income,
transportation, utilities, and housing. The CHW also ac-
companied patients on visits to social services agencies as
needed. The program provided vouchers for taxi services to
medical appointments until public transportation access was
secured, and waived co-pays for formulary medications.
Care management. To address preventive care and
chronic illnesses in the population, the CCP provided a team-
based approach to assuring delivery of general preventive
services and disease-specific care, assisted by decision-support
tools built into the EHR. The entire team assisted with care
coordination and care management. In addition to traditional
care management roles of reminding patients of appointments
and coordinating care, on admission to the program, patients
developed a treatment plan in conjunction with the team’s
LCPC. The treatment plan identified medical, behavioral, and
social goals, and was used to prioritize complex health needs
and improve patient engagement by focusing on goals that are
most important to the patient. The treatment plan was re-
assessed every 3–6 months.
Program monitoring and evaluation
Program metrics were developed to monitor program im-
plementation in 3 areas: (1) patient characteristics, experience,
and activation, (2) quality of care, and (3) utilization. A
dashboard of key metrics was developed and monitored during
the pilot to assist ongoing program improvement and process
Patient metrics. Patient satisfaction was measured by
the Clinician and Group Consumer Assessment of Health-
care Providers and Systems (CGCAHPS) survey methodol-
ogy. Patient engagement was assessed every 3 months using
the Patient Activation Measure (PAM) tool, a validated as-
sessment of the patient’s interest and ability to engage in
improving their own health.
Medication adherence was as-
sessed with the Medication Adherence Questionnaire (MAQ-
8) every 3 months, and the patient’s experience of care
delivery was measured with the Patient Assessment of Care
for Chronic Conditions (PACIC) survey every 6 months.
Data from these validated assessments informed the program
evaluation and were used during team meetings to guide ed-
ucation and interventions.
Quality metrics. Quality of care was evaluated in several
areas, focusing on value-based purchasing incentives iden-
tified by the state and payer. Although numerous metrics
were monitored by the larger group practice, the metrics of
most interest in this Medicaid population included breast
cancer screening, cervical cancer screening, diabetic eye
examination, and controlling high blood pressure.
Utilization metrics. The number of hospitalization and
emergency room visits were determined at a year’s baseline
prior to entering the program (to account for seasonal vari-
ability), and compared to after starting the program. Utiliza-
tion metrics included costs of clinic, specialty, and emergency
room visits, hospital admissions, as well as medications and
testing services. Investment included salary and benefits of
team members, along with costs of practice incurred. Return
on investment for the program was calculated quarterly.
FIG. 2. Art therapy in complex care program.
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Patient eligibility
The payer and program leadership developed eligibility
criteria based on demographics, utilization, complexity, and
potential savings. Patients were eligible if they lived within
10 miles of the clinic and were ‘‘high utilizers’’ (2 inpa-
tient visits and/or 3 emergency room visits; 1 standard
deviation above the mean) or ‘‘super-utilizers’’ (3 inpatient
visits and/or 9 emergency room visits; 2 standard devia-
tions above the mean). Complexity and potential savings
were modeled using Ambulatory Care Groups to predict
patients’ estimated total costs. This was compared to actual
costs and patients with a potential cost savings $5000 met
the inclusion criteria. Patients were excluded if they had
active cancer or predominately pregnancy-related utiliza-
tion. Only MCO members were eligible for this pilot.
Identification and enrollment
Patients meeting eligibility criteria were identified by the
payer and referred to the CCP team. Providers and staff
from the UMH and other local practices also could refer
patients to the CCP. Regardless of referral source, patients
were reviewed by the CCP medical director to assure they
met standard criteria and were appropriate candidates for the
program. Eligible patients were approached by primary care
providers and a CHW. To further aid enrollment, the MCO
contracted a call company. Interested patients completed a
secondary interview explaining the program goals of im-
proved health and self-management. Participants signed an
agreement upon enrollment to set the expectations of their
role, and to agree to the additional payer benefits.
Patients were included in the quality analyses if they had
maintained membership in the CCP for at least 6 months.
Quality outcomes employed a matched cohort in the UMH
practice. Significance was determined using z-statistics.
Preliminary hospital and emergency room utilization were
based on pre- and post-enrollment data, and percent change
was calculated. Monthly expenditures were calculated for
each month’s enrollment cohort and compared to costs prior
to enrollment for the same duration. The Medicaid MCO’s
program investment was then used to calculate return on in-
vestment. This program was approved by the Johns Hopkins
Medicine Institutional Review Board.
The 18-month pilot began in November 2014. Despite pre-
program planning, the program underwent iterative change as
problems were identified and solved. The high acuity of patients
in this population and challenges in understanding and im-
plementing this new care model led to staff turnover such that
only 1 of 5 starting staff, the medical director, remained with the
program through the pilot phase. Ultimately, clinical staff best
suited for this work were identified for program operations.
Recruitment and enrollment
Overall, 211 patients were identified as eligible and 86
(41%) eligible patients were enrolled during the pilot (Fig. 3).
Multiple modalities were employed to recruit and enroll pa-
tients. Direct outreach by CCP providers yielded 38 (44%)
enrollees, whereas 21 (24%) were recruited by the call
company, 14 (16%) by direct outreach from a CHW, and 13
(15%) from community primary care providers. Among 191
patients identified by the payer, 70 (37%) enrolled, 45 (24%)
could not be reached, and the remainder declined the program
or failed to show after multiple scheduling attempts. A total of
78 patients were referred from providers from the UMH or
surrounding practices: 20 (26%) were eligible, and 16 (80%)
eligible patients were enrolled.
Program management
Once enrolled, the average participant remained in the pro-
gram for 8 months. During the first 18 months of the pilot, the
average census was 40 patients, with a maximum enrollment of
69 patients for this 5-person team. A total of 23 patients have
been discharged: 11 changed insurance or moved out of state,
5 failed to engage because of substance use disorders, 3 were
transitioned successfully to their previous primary care pro-
vider, and 4 were deceased. Most visits were face-to-face in-
teractions in the clinic (76%); the remainder took place in the
patient’s home, at specialist appointments, or in acute care
settings. Telephone encounters were used to assist with follow-
FIG. 3. Flow diagram for complex care program patient recruitment and enrollment during the first 18 months of the pilot phase.
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up and appointment reminders. On average, there were 3 after-
hours calls per day.
Population and patient characteristics
Baseline clinical characteristics of the patients compared
to the surrounding UMH are shown in Table 1. Among 86
patients cared for, average age at enrollment is 44.5 years,
and more than 60% are female. The majority of patients are
African American. On average, patients are faced with 7.1
chronic medical and/or behavioral health conditions. Nearly
all patients (97%) had at least 1 behavioral health (mental
illness or substance abuse) condition. All patients had low
incomes, and common social needs included inadequate ac-
cess to transportation, low health literacy, food insecurity,
unstable housing, and difficulty paying for utilities (Table 1).
Patient metrics
The PAM survey was completed at least once by 72 (84%)
patients, with an average activation level of 3 and a mean
score of 60.8. The medication adherence survey was com-
pleted by 67 (78%) patients and the results showed that 66%
reported low adherence, 25% medium adherence, and the
remainder high adherence. The PACIC survey was completed
by 67 (78%) patients with an average score of 4.2/5.0. A
CGCAHPS survey was completed by a random sample of 12
patients and it demonstrated >90% patient satisfaction. De-
spite efforts to prioritize surveys, patient acuity and time
often affected completion rates during appointments. Trust in
the relationship with the team influences these results, as well
as information bias, as patients who regularly attend ap-
pointments and complete the survey are more engaged. Be-
cause of small enrollment numbers at the time of this
evaluation, it was not possible to identify trends in activation
or adherence during serial patient assessments.
Table 2 displays quality metrics for 55 patients who were
enrolled in the program for 6 months. There was a statisti-
cally significant increase in completion of cervical cancer
screening (from 61.8% at baseline to 88.2% for enrolled
patients, P<0.05), and nonsignificant increases in diabetic
eye examination (P=0.056) and hypertension control
Table 3 displays pre and post outcomes for the pilot phase
of the program. Overall, the CCP resulted in a 65% reduc-
tion in hospitalizations and a 67% reduction in emergency
room visits. CCP investment was $750,000. The program
achieved a net $1.6M cost savings, resulting in a 2.2:1 return
on investment.
Table 1. Characteristics of Priority Access
Primary Care Patients at Enrollment Compared
to the Surrounding Urban Medical Home (n=86)
Number 86 6463
Age (mean, SD) 44 (13) 50.1 (16)
Female 55 (64%) 4243 (65.7%)
Medicaid MCO 86 (100%) 2122 (32.8%)
Average Panel ACG 3.31 1.41
African American 79 (92%) 5299 (82%)
White 3 (3%) 259 (4%)
Native American 2 (2%) 41 (<1%)
South Asian 1 (1%) 184 (<1%)
Average Number of Chronic
7.1 3.2
Chronic pain 66 (77%) **
Depression 62 (72%) 983 (15.2%)
Hypertension 56 (65%) 3448 (53.3%)
Trauma 56 (65%) **
Anxiety 55 (64%) **
Degenerative joint disease 40 (47%) **
Diabetes 30 (35%) 1540 (23.8%)
Substance abuse 30 (35%) **
Asthma 25 (29%) 985 (15.2%)
Congestive heart failure 23 (27%) 274 (4.2%)
Coronary artery disease 23 (27%) 377 (5.8%)
Chronic hepatitis C 19 (22%) **
Chronic obstructive
pulmonary disease
17 (20%) 426 (6.6%)
Axis II disorder 16 (19%) **
Chronic kidney disease 15 (17%) 534 (8.3%)
Social Needs
Inadequate transportation 74 (86%) **
Low health literacy 45 (52%) **
Food insecurity 36 (42%) **
Unstable housing 30 (35%) **
Difficulty paying for
24 (28%) **
**No data available.
ACG, Ambulatory Care Group; MCO, managed care organiza-
tion; SD, standard deviation.
Table 2. Healthcare Effectiveness Data and Information Set Quality Metrics
for Patients Enrolled in the Complex Care Program for at Least 6Months (n=55)
Cervical cancer
screening Diabetic eye exam Hypertension control
Eligible for service 15 34 20 37
Completed at baseline 10 21 8 22
% Meeting measure at baseline 66.7% 61.8% 40.0% 59.5%
Completed by discharge 11 30 14 27
% Meeting measure at discharge 73.3%* 88.2% 70.0%** 73.0%
% Increase from Baseline 10.0% 42.9% 75.0% 22.7%
P value 0.35 <0.05 0.06 0.22
Average for metrics in surrounding medical home practice: *77%, **61.5%, 49%.
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To improve efficiency of the health care system, high-risk
patients with disproportionately high utilization must be
matched with commensurate health care resources. The
study team developed a program for HNHC Medicaid pa-
tients as a special service center within an existing large,
urban patient-centered medical home practice, in partner-
ship with a Medicaid MCO and a large regional medical
group. Within the first 18 months, the team developed a new
practice and care team, enrolled 86 patients, and has dem-
onstrated positive patient experiences, improvements in
quality, and cost savings. The detailed description of pro-
gram characteristics bridges knowledge gaps in how CCPs
are designed.
The model provided a home for complex and costly pa-
tients within an existing medical home practice. The study
team effectively carved out a niche of high-value service for
an underserved population within a large, complex health
care system. It is unique as the payer and medical group
both had evidence that the existing UMH was not caring
effectively for the subset of HNHC patients eventually tar-
geted by the CCP program. By identifying a specific cohort
and targeting services accordingly, the program conformed
to known best practices in complex care.
Although it was
necessary to invest in hiring and training new team members
to staff the complex care practice, the partnership allowed
for the optimization of costs by leveraging infrastructure
that was already in place, including pharmacy, radiology,
laboratory services, office space, and an integrated EHR.
The unique provider–payer partnership provided real-time
sharing of clinical and claims data, and has been particularly
useful for patient selection and utilization management.
However, with several major stakeholders involved, the pilot
was subject to a complex management structure and frequent
staffing changes. Lessons learned during the pilot have been
applied to improve the team and function of the CCP. For
example, to assure continuity and connection, 2 providers ini-
tially shared call 24 hours/7 days. During the year, the schedule
was adapted to offset call coverage needs of the program with a
small pool of additional clinicians. Overall, patients adjusted
well to this iteration. Although the team was able to manage
the patient cohort effectively, expanding the program may re-
quire additional clinical support. Future iterations of the pro-
gram may include risk sharing between the payer and the
provider, allowing for distribution of the actualized cost sav-
ings, and further alignment of performance incentives.
The CCP was located within an existing medical home
practice for several reasons. That practice already included a
subpopulation of HCHN patients who both leadership and
providers felt would benefit from the intensive services that
the CCP program provided. The EHR and regional health
information exchange allowed for care coordination both
within the health system and with surrounding health sys-
tems. In addition, because medical home practices have
been shown to be more successful in achieving appropriate
care transitions,
it was hoped that locating the CCP
within an existing medical home would (1) assist partner-
ships between the regular care team and the CCP team and
(2) assist with efforts to transition management back to
primary care providers once self-sufficiency was attained.
Integrated behavioral health and social services were
critical in the study high-risk Medicaid population because
97% had at least 1 mental health disorder and all had at least
1 social need. Consistent with other programs, the CCP team
was trained to be flexible and to adapt to iterations of a new
care model.
Others have observed the special impact of
poor mental health care and substance abuse on utilization,
and the CCP program sought to address this by training all
members of the team and providing a full-time embedded
clinical counselor.
The team’s weekly meetings
served as a time for reflection on patient care challenges and
also supported the resiliency of the team’s members. Near
the conclusion of the pilot, direct support and collaboration
was requested from psychiatry colleagues to provide clinical
oversight and specialized care of the complex patients,
based on the experiences of others that these behavioral
resources were critical for patient engagement, medication
adherence, and overall success.
As anticipated, enrolling patients was time intensive and
Knowledge of CCP enrollment processes is
and this study uniquely describes this component of
the program. In addition, this study reports on recruitment
efforts: 41% of the targeted cohort ultimately enrolled in the
CCP, while 21% of total eligible patients were unreachable.
The highest recruitment rate – 80% – was among patients
referred to the CCP by primary care providers in the sur-
rounding UMH. Although not surprising, it supports the im-
portance of engaging primary care providers when developing
and recruiting patients to programs such as this CCP.
Preliminary results from the monitoring and evaluation
plan are encouraging. The majority of patients have completed
PAM, MAQ-8, and PACIC surveys, and further analysis is
planned for the comprehensive program evaluation. Early
measures of patient satisfaction are promising. Quality mea-
sures showed trends toward improvement in completion of
clinical preventive services, with a statistically significant in-
crease in cervical cancer screening completion. Of note, some
measures, such as blood pressure control, were met at higher
rates than in the surrounding UMH.
Consistent with other complex care models, CCP patients
utilized health resources at lower rates compared with their
pre-enrollment baseline.
Emergency room utilization
may be inappropriately promoted by referrals outside the
CCP, psychosocial needs (anxiety, substance abuse, and
unstable housing in particular), and lack of disincentives.
In the study team’s experience, cultural and family pressure
to seek emergency room services also plays a role, and
changing these behaviors takes time. Hospitalizations, in
Table 3. Preliminary Pre–Post Outcomes
for Patients Enrolled in the Complex
Care Program Pilot (n=86)
Pre CCP Post CCP
Total hospitalizations
in 18 months
306 106 -65%
Total emergency room
visits in 18 months
487 160 -67%
Expenditures for
enrollment period
$5,607,378 $3,990,721 -29%
CCP, complex care program.
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contrast, were impacted by care coordination and intensive
outpatient follow-up.
Several limitations affect these results. Evaluation of CCPs
such as this one must consider the impact of ‘‘regression to
the mean’’ – a tendency for costs to decline over time re-
gardless of interventions; others have observed that more than
70% of saving in programs such as this one can be attributed
to this phenomenon.
Although ongoing data collection
will soon permit analysis against an adequate control, an
adjusted return on investment exceeded the target of $5000
per patient, sufficient for continued investment in the pro-
gram. This CCP was developed in an academic medical
practice in 1 state, and may not be generalizable to other
settings. The state has a ‘‘carve out’’ for behavioral health
services so predictive models were based on only medical
claims data, and the predictive model may have missed other
complex patients. Finally, very few of the patients transi-
tioned back to routine primary care during this preliminary
study, so the success of those transitions is unknown. Re-
search is ongoing in these areas.
Building on other high-risk care models that have
emerged to care for the nation’s sickest and costliest pa-
tients, this unique CCP was developed with the goals of
improving patient experiences, enhancing health in the tar-
geted population, and decreasing costs. Based on promising
preliminary outcomes, the study team is sharing their ex-
perience as a base for ongoing research, and in the hope that
it will assist others to create successful programs.
Author Disclosure Statement
Dr. Okeke received consultancy fees for management
consulting for Veterans Health Administration - Booz Allen
Hamilton. The other authors declare that there are no con-
flicts of interest. The authors received no financial support
for this article.
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Address correspondence to:
Laura D. Sander, MD, MPH, FACP
Internal Medicine & Preventive Medicine
Sibley Memorial Hospital
Medical Director, Community Outreach
and Population Health
Medical Director, Sibley Primary Care
5215 Loughboro Road NW
Washington, DC 20016
Downloaded by Johns Hopkins Univ e-journal package from at 04/11/18. For personal use only.
... 1,2 The most promising interventions have involved rethinking the roles of providers and the practices that care for these patients. [3][4][5] Complex patients benefit most from a high degree of continuity of care and attention from their primary care providers. [6][7][8][9][10][11][12][13] However, maximizing provider accessibility to match the needs of this population places heavy demands on the time and availability on those clinicians. ...
The management of high-utilizing patients is an area of active research with broad implications for the healthcare system. There are significant operational challenges to designing primary care models for these medically complex, high-needs patients. Although it is crucial to provide a high degree of continuity of care for this population, managing a cohort of these patients can lead to provider over-work and attrition. This may be magnified by the lack of training dedicated to addressing the unique care needs of these patients. While academic medical centers would seem well suited to care for individuals with multimorbidity needing intensive and specialized treatment, primary care providers in this setting need additional support to be clinically available for patients while pursuing scholarship and teaching. Formally recognizing intensive outpatient care as a specialty within internal medicine would help overcome some of these challenges. This would require a committed effort to high-level systems changes including a new focus on graduate medical education, the creation of division-level infrastructure within academic departments of medicine, and realistic levels of financial support to make this a viable career path.
Purpose of study: This scoping review explored research literature on the integration and coordination of services for high-need, high-cost (HNHC) patients in an attempt to answer the following questions: What models of transitional care are utilized to manage HNHC patients in the United States? and How effective are they in reducing low-value utilization and in improving continuity? Primary practice settings: U.S. urban, suburban, and rural health care sites within primary care, veterans' services, behavioral health, and palliative care. Methodology and sample: Utilizing the Joanna Briggs Institute and PRISMA guidelines for scoping reviews, a stepwise method was applied to search multiple databases for peer-reviewed published research on transitional care models serving HNHC adult patients in the United States from 2008 to 2018. All eligible studies were included regardless of quality rating. Exclusions were foreign models, studies published prior to 2008, review articles, care reports, and studies with participants younger than 18 years. The search returned 1,088 studies, of which 19 were included. Results: Four studies were randomized controlled trials and other designs included case reports and observational, quasi-experimental, cohort, and descriptive studies. Studies focused on Medicaid, Medicare, dual-eligible patients, veterans, and the uninsured or underinsured. High-need, high-cost patients were identified on the basis of prior utilization patterns of inpatient and emergency department visits, high cost, multiple chronic medical diagnoses, or a combination of these factors. Tools used to identify these patients included the hierarchical condition category predictive model, the Elder Risk Assessment, and the 4-year prognostic index score. The majority of studies combined characteristics of multiple case management models with varying levels of impact. Implications for case management practice: .
Interest in high users of acute care continues to grow as health care organizations look to deliver cost-effective and high-quality care to patients. Since “super-utilizers” of acute care are responsible for disproportionately high health care spending, many programs and interventions have been implemented to reduce medical care use and costs in this population. This article presents a systematic review of the peer-reviewed and grey literature on evaluations of interventions to decrease prehospital and emergency care use among U.S. super-utilizers. Forty-six distinct evaluations were included in the review. The most commonly evaluated intervention was case management. Although a number of interventions reported reductions in prehospital and emergency care utilization and costs, methodological and study design weaknesses—especially regression to the mean—were widespread and call into question reported positive findings. More high-quality research is needed to accurately assess the impact of interventions to reduce prehospital and emergency care use in the super-utilizer population.
Full-text available
Background: Health care spending is concentrated among a small number of high-cost patients, and the popularity of initiatives to improve care and reduce cost among such "superusers" (SUs) is growing. However, SU costs decline naturally over time, even without intervention, a statistical phenomenon known as regression-to-the-mean (RTM). Objectives: We assess the magnitude of RTM in hospital costs for cohorts of hospital SUs identified on the basis of high inpatient (IP) or emergency department (ED) utilization. We further examine how cost and RTM are associated with patient characteristics including behavioral health (BH) problems, multiple chronic conditions, and indicators of vulnerability. Study design: Using longitudinally linked all-payer hospital billing data, we selected patient cohorts with ≥2 IP stays (IP SUs) or ≥6 ED visits (ED SUs) during a 6-month baseline period, and additional subgroups defined by combinations of IP and ED superuse. Population studied: A total of 289,060 NJ hospital IP and treat-and-release ED patients over 2009-2011. Results: Hospital costs among IP and ED SUs declined 70% and 38%, respectively, over 8 quarters following the baseline period. The decrease occurs more quickly for IP SUs compared with ED SUs. Presence of BH problems was positively associated with costs among patients overall, but the relationship varied by SU cohort. Conclusions: Understanding patterns of RTM among SU populations is important for designing intervention strategies, as there is greater potential for savings among patients with more persistent costs (less RTM). Further, as many SU initiatives lack resources for rigorous evaluation, quantifying the extent of RTM is vital for interpreting program outcomes.
Full-text available
Introduction: Finding ways to provide better and less expensive health care for people with multiple chronic conditions or disability is a pressing concern. The purpose of this systematic review was to evaluate different approaches for caring for this high-need and high-cost population. Methods: We searched Medline for articles published from May 31, 2008, through June 10, 2014, for relevant studies. Articles were considered eligible for this review if they met the following criteria: included people with multiple chronic conditions (behavioral or mental health) or disabilities (2 or more); addressed 1 or more of clinical outcomes, health care use and spending, or patient satisfaction; and compared results from an intervention group with a comparison group or baseline measurements. We extracted information on program characteristics, participant characteristics, and significant (positive and negative) clinical findings, patient satisfaction, and health care use outcomes. For each outcome, the number of significant and positive results was tabulated. Results: Twenty-seven studies were included across 5 models of care. Of the 3 studies reporting patient satisfaction outcomes, 2 reported significant improvements; both were randomized controlled trials (RCTs). Of the 14 studies reporting clinical outcomes, 12 reported improvements (8 were RCTs). Of the 13 studies reporting health care use and spending outcomes, 12 reported significant improvements (2 were RCTs). Two models of care - care and case management and disease management - reported improvements in all 3 outcomes. For care and case management models, most improvements were related to health care use. For the disease management models, most improvements were related to clinical outcomes. Conclusions: Care and case management as well as disease management may be promising models of care for people with multiple chronic conditions or disabilities. More research and consistent methods are needed to understand the most appropriate care for these high-need and high-cost patients.
Background: Multicomponent, interdisciplinary intensive primary care programs target complex patients with the goal of preventing hospitalizations, but programs vary, and their effectiveness is not clear. In this study, we systematically reviewed the impact of intensive primary care programs on all-cause mortality, hospitalization, and emergency department use. Methods: We searched PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Reviews of Effects from inception to March 2017. Additional studies were identified from reference lists, hand searching, and consultation with content experts. We included systematic reviews, randomized controlled trials (RCTs), and observational studies of multicomponent, interdisciplinary intensive primary care programs targeting complex patients at high risk of hospitalization or death, with a comparison to usual primary care. Two investigators identified studies and abstracted data using a predefined protocol. Study quality was assessed using the Cochrane risk of bias tool. Results: A total of 18 studies (379,745 participants) were included. Three major intensive primary care program types were identified: primary care replacement (home-based; three RCTs, one observational study, N = 367,681), primary care replacement (clinic-based; three RCTs, two observational studies, N = 9561), and primary care augmentation, in which an interdisciplinary team was added to existing primary care (five RCTs, three observational studies, N = 2503). Most studies showed no impact of intensive primary care on mortality or emergency department use, and the effectiveness in reducing hospitalizations varied. There were no adverse effects reported. Discussion: Intensive primary care interventions demonstrated varying effectiveness in reducing hospitalizations, and there was limited evidence that these interventions were associated with changes in mortality. While interventions could be grouped into categories, there was still substantial overlap between intervention approaches. Further work is needed to identify program features that may be associated with improved outcomes.
Corresponding Author: David Blumenthal, MD, The Commonwealth Fund, 1 E 75th St, New York, NY 10021 ( Published Online: September 26, 2016. doi:10.1001/jama.2016.12388 Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. Funding/Support: The National Academy of Medicine’s Vital Directions initiative is sponsored by the California Health Care Foundation, The John A. Hartford Foundation, the Robert Wood Johnson Foundation, and the National Academy of Medicine’s Harvey V. Fineberg Impact Fund. Disclaimer: This Viewpoint on tailoring complex care management, coordination, and integration provides a summary of a discussion paper developed as part of the National Academy of Medicine’s initiative on Vital Directions for Health & Health Care ( Discussion papers presented in this initiative reflect the views of leading authorities on the important issues engaged, and do not represent formal consensus positions of the National Academy of Medicine or the organizations of the participating authors. Additional Contributions: Coauthors of the National Academy of Medicine discussion paper included Gerard Anderson, PhD (Johns Hopkins University), Sheila Burke, RN, MPA (Harvard University), Ashish Jha, MD (Harvard University), Terry Fulmer, PhD (The John A. Hartford Foundation), and Peter Long, PhD (Blue Shield of California Foundation). Elizabeth Finkelman, MPP (National Academy of Medicine) served as the initiative director.
The provision of supportive housing is often recognized as important public policy, but it also plays a role in health care reform. Health care costs for the homeless reflect both their medical complexity and psychosocial risk factors. Supportive housing attempts to moderate both by providing stable places to live along with on-site integrated health services. In this pilot study we used a mixture of survey and administrative claims data to evaluate outcomes for formerly homeless people who were living in a supportive housing facility in Oregon between 2010 and 2014. Results from the claims analysis showed significantly lower overall health care expenditures for the people after they moved into supportive housing. Expenditure changes were driven primarily by reductions in emergency and inpatient care. Survey data suggest that the savings were not at the expense of quality: Respondents reported improved access to care, stronger primary care connections, and better subjective health outcomes. Together, these results indicate a potential association between supportive housing and reduced health care costs that warrants deeper consideration as part of ongoing health care reforms.
Background: Intensive outpatient programs aim to transform care while conserving resources for high-need, high-cost patients, but little is known about factors that influence their implementation within patient-centered medical homes (PCMHs). Methods: In this mixed-methods study, we reviewed the literature to identify factors affecting intensive outpatient program implementation, then used semi-structured interviews to determine how these factors influenced the implementation of an intensive outpatient program within the Veterans Affairs' (VA) PCMH. Interviewees included facility leadership and clinical staff who were involved in a pilot Intensive Management Patient Aligned Care Team (ImPACT) intervention for high-need, high-cost VA PCMH patents. We classified implementation factors in the literature review and qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Results: The literature review (n=9 studies) and analyses of interviews (n=15) revealed key implementation factors in three CFIR domains. First, the Inner Setting (i.e., the organizational and PCMH environment), mostly enabled implementation through a culture of innovation, good networks and communication, and positive tension for change. Second, Characteristics of Individuals, including creativity, flexibility, and interpersonal skills, allowed program staff to augment existing PCMH services. Finally, certain Intervention Characteristics (e.g., adaptability) enabled implementation, while others (e.g., complexity) generated implementation barriers. Conclusions: Resources and structural features common to PCMHs can facilitate implementation of intensive outpatient programs, but program success is also dependent on staff creativity and flexibility, and intervention adaptations to meet patient and organizational needs. Implications: Established PCMHs likely provide resources and environments that permit accelerated implementation of intensive outpatient programs. Level of evidence: V.
Using literature review and interviews, we have identified 8 attributes of programs, such as accountable care organizations, readmission initiatives, special needs plans, care transition programs, and patient-centered medical homes, that successfully treat high-need, high-cost patients. These 8 attributes-illustrated here with specific examples-Are specific ways to target these types of individuals, promote leadership at various levels, emphasize interaction with the care coordinator, use data strategically to refine the program, update the program periodically, allow physicians to spend more time with patients, and promote interaction among clinicians and high-need, high cost patients and their families.
Patients who accumulate multiple emergency department visits and hospital admissions, known as super-utilizers, have become the focus of policy initiatives aimed at preventing such costly use of the health care system through less expensive community- and primary care-based interventions. We conducted cross-sectional and longitudinal analyses of 4,774 publicly insured or uninsured super-utilizers in an urban safety-net integrated delivery system for the period May 1, 2011-April 30, 2013. Our analysis found that consistently 3 percent of adult patients met super-utilizer criteria and accounted for 30 percent of adult charges. Fewer than half of super-utilizers identified as such on May 1, 2011, remained in the category seven months later, and only 28 percent remained at the end of a year. This finding has important implications for program design and for policy makers because previous studies may have obscured this instability at the individual level. Our study also identified clinically relevant subgroups amenable to different interventions, along with their per capita utilization and costs before and after being identified as super-utilizers. Future solutions include improving predictive modeling to identify individuals likely to experience sustained levels of avoidable utilization, better classifying subgroups for whom interventions are needed, and implementing stronger program evaluation designs. Project HOPE—The People-to-People Health Foundation, Inc.