The last decade has heralded strategies to identify the population of children with medical complexity (CMC),13  quantify the striking magnitude of CMC health care costs,2,47  and document812  and address8,12,13  their unmet needs. Although dedicated programs designed to better coordinate CMC care (ie, “complex care”) have materialized rapidly,14  the rate of program growth has outpaced the generation of evidence for their effectiveness. Observational and uncontrolled studies have consistently suggested that complex care may lower costs by reducing hospital use1518 ; however, 2 randomized controlled trials have yielded mixed results.19,20  The discrepancies in these randomized controlled trials introduce uncertainty about the anticipated cost savings from complex care programs around the country, whereas the array of distinct complex care program models creates ambiguity about how health systems and policymakers should promote implementation.

In this month’s issue of Pediatrics, Bergman et al21  report findings from the Coordinating All Resources Effectively (CARE) learning collaborative, which sought to transform 10 children’s hospital complex care programs and 42 referring primary care pediatrician practices across the United States. Using the Institute for Healthcare Improvement’s Breakthrough Series Collaborative model,22  local teams implemented 4 key change concepts: (1) family-driven “dynamic care teams,” (2) shared plans of care, (3) access plans that included individualized contingency planning for acute concerns, and (4) patient registries for population management.

Between 2015 and 2017, sites enrolled a convenience sample of 8096 CMC (defined by Clinical Risk Group categories 5b–923 ). Using statistical process control and propensity-matched analyses, the authors observed significant reductions in hospital and emergency department use and corresponding reductions in annual total, inpatient, and emergency department spending (4.6%, 7.7%, and 11.6%, respectively) during the collaborative. Perhaps as expected,24,25  the cost in both groups decreased over the study period; however, the CARE group reductions were larger despite simultaneous increases in pharmacy and home health spending. CARE’s geographic reach and the corresponding racial, ethnic, and cultural diversity of the CMC involved support the generalizability of these findings.

The painstaking efforts required for collaboration and data sharing across the CARE network not only are commendable but also advance the complex care field by adding another link in the growing evidence chain for complex care programs and lower cost of CMC care. The pragmatic nature of this study makes its contribution particularly unique; Bergman et al21  demonstrate that “common sense” actions may demonstrably decrease the total cost of care for CMC, a finding that apparently translates to both dedicated specialty programs and traditional primary care clinics. By embedding activities within a learning collaborative, clinicians retained flexibility to operationalize the workflows for their local context. The creation and sharing of a summary of health conditions, a list of who to call when and for what, and step-by-step instructions to address acute illness or changes from baseline presumably contributed to the successful management of CMC at home rather than in acute care settings.

It is worth noting that a learning collaborative design imposes some inherent scientific boundaries, and it will be valuable to view these results alongside those from the large multisite randomized controlled complex care trial currently underway in Ontario.26  Despite a rigorous propensity-matching process in the CARE collaborative, observable baseline differences existed between eligible and enrolled (and enrolled and matched) CMC. This underscores the need for research to clarify motivators for complex care referral, enrollment, and retention. With respect to changes in acute care use, children likely respond to complex care models in different ways. By extension, what complex care achieves and how it achieves it for any given child is likely not uniform in cross section or over time.

To more completely understand the influence of interventions on the total cost of CMC care, future economic analyses should account for the cost of family-delivered care at home (person-hours) and determine if that changes with complex care enrollment; the analyses should also account for the potential effects on parent employment or workforce re-entry. Whether certain CARE sites achieved similar activities with more efficiency could be an informative corollary in future work. Additionally, if CMC spend less time in the inpatient setting, understanding the effect on health systems may not be straightforward in that it can be both challenging for systems in traditional payment arrangements and beneficial in risk-sharing alternative payment models.

As the concept of value from complex care evolves, inclusion of noncost outcomes will be important. In their recent work, Bergman et al21  take an important step on a long journey toward better understanding the nuances and tools needed to optimize health and intelligent spending for CMC. CARE continues to light the path forward for investigating strategies that have a positive impact on this important population.

Opinions expressed in these commentaries are those of the authors and not necessarily those of the American Academy of Pediatrics or its Committees.

FUNDING: No external funding.

COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2020-2401.

     
  • CARE

    Coordinating All Resources Effectively

  •  
  • CMC

    children with medical complexity

1
Berry
JG
,
Hall
M
,
Cohen
E
,
O’Neill
M
,
Feudtner
C
.
Ways to identify children with medical complexity and the importance of why
.
J Pediatr
.
2015
;
167
(
2
):
229
237
2
Neff
JM
,
Sharp
VL
,
Muldoon
J
,
Graham
J
,
Myers
K
.
Profile of medical charges for children by health status group and severity level in a Washington state health plan
.
Health Serv Res
.
2004
;
39
(
1
):
73
89
3
Cohen
E
,
Kuo
DZ
,
Agrawal
R
, et al
.
Children with medical complexity: an emerging population for clinical and research initiatives
.
Pediatrics
.
2011
;
127
(
3
):
529
538
4
Cohen
E
,
Berry
JG
,
Camacho
X
,
Anderson
G
,
Wodchis
W
,
Guttmann
A
.
Patterns and costs of health care use of children with medical complexity
.
Pediatrics
.
2012
;
130
(
6
). Available at: www.pediatrics.org/cgi/content/full/130/6/e1463
5
Glendinning
C
,
Kirk
S
,
Guiffrida
A
,
Lawton
D
.
Technology-dependent children in the community: definitions, numbers and costs
.
Child Care Health Dev
.
2001
;
27
(
4
):
321
334
6
Srivastava
R
,
Downie
J
,
Hall
J
,
Reynolds
G
.
Costs of children with medical complexity in Australian public hospitals
.
J Paediatr Child Health
.
2016
;
52
(
5
):
566
571
7
Simon
TD
,
Berry
J
,
Feudtner
C
, et al
.
Children with complex chronic conditions in inpatient hospital settings in the United States
.
Pediatrics
.
2010
;
126
(
4
):
647
655
8
Berry
JG
,
Agrawal
R
,
Kuo
DZ
, et al
.
Characteristics of hospitalizations for patients who use a structured clinical care program for children with medical complexity
.
J Pediatr
.
2011
;
159
(
2
):
284
290
9
Kirk
S
,
Glendinning
C
.
Developing services to support parents caring for a technology-dependent child at home
.
Child Care Health Dev
.
2004
;
30
(
3
):
209
218; discussion 219
10
Kuo
DZ
,
Cohen
E
,
Agrawal
R
,
Berry
JG
,
Casey
PH
.
A national profile of caregiver challenges among more medically complex children with special health care needs
.
Arch Pediatr Adolesc Med
.
2011
;
165
(
11
):
1020
1026
11
Kuo
DZ
,
Houtrow
AJ
;
Council on Children with Disabilities
.
Recognition and management of medical complexity
.
Pediatrics
.
2016
;
138
(
6
):
e20163021
12
Kuo
DZ
,
Berry
JG
,
Glader
L
,
Morin
MJ
,
Johaningsmeir
S
,
Gordon
J
.
Health services and health care needs fulfilled by structured clinical programs for children with medical complexity
.
J Pediatr
.
2016
;
169
:
291
296.e1
13
Pordes
E
,
Gordon
J
,
Sanders
LM
,
Cohen
E
.
Models of care delivery for children with medical complexity
.
Pediatrics
.
2018
;
141
(
suppl 3
):
S212
S223
14
Cohen
E
,
Berry
JG
,
Sanders
L
,
Schor
EL
,
Wise
PH
.
Status complexicus? The emergence of pediatric complex care
.
Pediatrics
.
2018
;
141
(
suppl 3
):
S202
S211
15
Gordon
JB
,
Colby
HH
,
Bartelt
T
,
Jablonski
D
,
Krauthoefer
ML
,
Havens
P
.
A tertiary care-primary care partnership model for medically complex and fragile children and youth with special health care needs
.
Arch Pediatr Adolesc Med
.
2007
;
161
(
10
):
937
944
16
Casey
PH
,
Lyle
RE
,
Bird
TM
, et al
.
Effect of hospital-based comprehensive care clinic on health costs for Medicaid-insured medically complex children
.
Arch Pediatr Adolesc Med
.
2011
;
165
(
5
):
392
398
17
Cohen
E
,
Friedman
JN
,
Mahant
S
,
Adams
S
,
Jovcevska
V
,
Rosenbaum
P
.
The impact of a complex care clinic in a children’s hospital
.
Child Care Health Dev
.
2010
;
36
(
4
):
574
582
18
Cohen
E
,
Lacombe-Duncan
A
,
Spalding
K
, et al
.
Integrated complex care coordination for children with medical complexity: a mixed-methods evaluation of tertiary care-community collaboration
.
BMC Health Serv Res
.
2012
;
12
:
366
19
Simon
TD
,
Whitlock
KB
,
Haaland
W
, et al
.
Effectiveness of a comprehensive case management service for children with medical complexity
.
Pediatrics
.
2017
;
140
(
6
):
e20171641
20
Mosquera
RA
,
Avritscher
EB
,
Samuels
CL
, et al
.
Effect of an enhanced medical home on serious illness and cost of care among high-risk children with chronic illness: a randomized clinical trial
.
JAMA
.
2014
;
312
(
24
):
2640
2648
21
Bergman
D
,
Keller
D
,
Kuo
D
, et al
.
Costs and utilization for children with medical complexity in a care management program
.
Pediatrics
.
2020
;
145
(
4
):
e20192401
22
Kilo
CM
.
A framework for collaborative improvement: lessons from the Institute for Healthcare Improvement’s Breakthrough Series
.
Qual Manag Health Care
.
1998
;
6
(
4
):
1
13
23
Hughes
JS
,
Averill
RF
,
Eisenhandler
J
, et al
.
Clinical Risk Groups (CRGs): a classification system for risk-adjusted capitation-based payment and health care management
.
Med Care
.
2004
;
42
(
1
):
81
90
24
Agrawal
R
,
Hall
M
,
Cohen
E
, et al
.
Trends in health care spending for children in Medicaid with high resource use
.
Pediatrics
.
2016
;
138
(
4
):
e20160682
25
Peltz
A
,
Hall
M
,
Rubin
DM
, et al
.
Hospital utilization among children with the highest annual inpatient cost
.
Pediatrics
.
2016
;
137
(
2
):
e20151829
26
Orkin
J
,
Chan
CY
,
Fayed
N
, et al
.
Complex care for kids Ontario: protocol for a mixed-methods randomised controlled trial of a population-level care coordination initiative for children with medical complexity
.
BMJ Open
.
2019
;
9
(
8
):
e028121

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.