Multiple Chronic Conditions: Prevalence, Health Consequences,
and Implications for Quality, Care Management, and Costs
Christine Vogeli, PhD1,2, Alexandra E. Shields, PhD1,2, Todd A. Lee, PharmD PhD4,5,
Teresa B. Gibson, PhD3, William D. Marder, PhD3, Kevin B. Weiss, MD MPH4,5,
and David Blumenthal, MD MPP1,2
1Institute for Health Policy in the Department of Medicine, Massachusetts General Hospital, Boston, MA, USA;2Harvard Medical School, Boston,
MA, USA;3Thomson Healthcare, Ann Arbor, MI, USA;4Institute for Healthcare Studies, Feinberg School of Medicine, Northwestern University,
Chicago, IL, USA;5Center for Complex Chronic Care, Hines VA Hospital, Hines, IL, USA.
Persons with multiple chronic conditions are a large
and growing segment of the US population. However,
little is known about how chronic conditions cluster,
and the ramifications of having specific combinations of
chronic conditions. Clinical guidelines and disease
management programs focus on single conditions, and
clinical research often excludes persons with multiple
chronic conditions. Understanding how conditions in
combination impact the burden of disease and the costs
and quality of care received is critical to improving care
for the 1 in 5 Americans with multiple chronic condi-
tions. This Medline review of publications examining
somatic chronic conditions co-occurring with 1 or more
additional specific chronic illness between January
2000 and March 2007 summarizes the state of our
understanding of the prevalence and health challenges
of multiple chronic conditions and the implications for
quality, care management, and costs.
KEY WORDS: chronic disease; comorbidity; prevalence; quality of health
J Gen Intern Med 22(Suppl 3):391–5
© Society of General Internal Medicine 2007
Typically, we study experience with health care conditions,
including health care costs and quality, as if these conditions
occur in isolation, one at a time. The vast majority of extant
clinical guidelines and disease management programs focus
on a single condition, although the experience of multiple
chronic illnesses is the reality for many patients—particularly
among the elderly and near elderly. The Institute of Medicine’s
report “Crossing the Quality Chasm” highlights the problem
with health system fragmentation and stresses the need for
health care systems that promote continuity of care and
integration of services.1Realigning the focus of health services
research to be more in line with the complex experience of
patients is central to developing solutions that work. This
paper provides information on what we know about multiple
chronic conditions, specifically the prevalence and health
challenges of multiple chronic conditions, and the ramifica-
tions of specific combinations of chronic conditions on quality,
patient management, and costs.
We performed a semistructured literature review to identify
relevant articles. Specifically, we queried MEDLINE for peer-
reviewed publications that examined the prevalence, out-
comes, costs, and patient management challenges associated
with multiple chronic conditions.
We first selected all articles the Mesh terms ‘chronic disease’
and ‘comorbidity,’ and limited our search to articles on adults
published in English between January 2000 and March 2007
(n=643). This set was further paired down using 2 different
strategies. The first strategy used a set of specific Mesh terms
related to prevalence, quality, access, delivery of care, patterns
of care, morbidity, mortality, and expenditures. To ensure that
we did not overlook any important articles in the original set,
we also limited the original set to articles published in core
journals. The final set of 123 articles was the union of
abstracts gained from these 2 approaches. Articles without
abstracts or whose author was anonymous were not reviewed.
The remaining abstracts were reviewed by the first author and
abstracts that did not mention at least 1 specific somatic
chronic illness, abstracts that did not examine specific comor-
bidities, and articles that focused on an acute illness or
procedure were removed. Information summarized in this
review stem from the remaining articles and prior publications
cited by these articles.
PREVALENCE OF MULTIPLE CHRONIC CONDITIONS
The number of persons in the United States who have not just
a single chronic condition, but multiple co-occurring chronic
conditions is large and growing. In 2005, 21% or roughly
63 million Americans had more than 1 chronic condition, or
multiple illnesses or impairments expected to last a year or
The authors are members of the Consortium on Complex Chronic
Illness, Quality, and Equity. The Consortium, directed by Dr. A. Shields, is
a collaboration of investigators from Harvard, MGH, Northwestern, the
VA, Thomson Healthcare, and Ingenix committed to accelerating research
on complex chronic illness and its implications for quality and the health
of vulnerable populations.
longer. A persons’ risk of having more than 1 chronic
condition, henceforth referred to as multiple chronic condi-
tions or MCC, increases with age: 62% of Americans over 65
have MCC. With the aging of the US population, the number of
Americans with MCC is projected to be 81 million by 2020.2
The Institute of Medicine’s seminal report “Crossing the
Quality Chasm” noted that 23% of Medicare beneficiaries have
5 or more chronic conditions.1
Prior research has documented the prevalence of individual
conditions in the U.S. population generally and among the
elderly and near elderly in particular. For example, based on
data from the Medicare Current Beneficiary Survey (MCBS),
the most prevalent individual conditions among the over-65
population include: arthritis (57%), hypertension (55%), pul-
monary disease (38%), diabetes (17%), cancer (17%) and
osteoporosis (16%).2However, there has been very little
research to date exploring the prevalence of particular combi-
nations or clusters of chronic conditions, and almost all
studies examining specific comorbidities do so from the
perspective of a specific index disease rather than examining
all co-occurring chronic conditions.3
Only a fragmentary portrait of the prevalence of MCC
emerges from studies examining comorbidities among patients
with specific index conditions. A case-control study of asth-
matics found that diabetes was more common in concert with
asthma, but obesity was more common in patients without
asthma4Of patients with Alzheimer’s disease, 28% also have
congestive heart failure, 27% chronic obstructive pulmonary
disease, 22% diabetes mellitus, and 20% cancer.2In comparison
to the general population, persons receiving care for schizophre-
nia or affective disorders in community-based treatment centers
were more likely to suffer from asthma, chronic bronchitis,
diabetes, and liver problems.5Finally, persons suffering from
epilepsy have higher rates of a host of chronic conditions,
including bowel disorders, bronchitis/emphysema, heart dis-
ease, and stroke in comparison to the general population.6
Fewer studies have explored the natural clustering of
chronic conditions. Using cross-sectional Medicare claims
data, Wolff and colleagues grouped a national sample of
Medicare patients into Major Diagnostic Categories (MDC)
based on a well-validated grouping algorithm. They found that
the tendency of patients to have comorbid conditions varied
from 80% among individuals in the MDC “myeloproliferative
disorders” to 32% in the “circulatory disorders” MDC. These
investigators found that specific combinations of chronic
conditions occurred more frequently than expected, and
proposed that perhaps underlying biological vulnerabilities
may help explain the clustering of diseases within individuals.7
A subsequent more limited study used cluster analysis to
identify conditions that tend to co-occur among elderly
American Indians. The specific conditions in this group
include heart disease, stroke, hypertension, diabetes, urinary
or bladder conditions, and tuberculosis. Interestingly, al-
though arthritis is 1 of the 2 most common chronic conditions
in this population, it does not commonly occur in concert with
Perhaps the most widely known example of the clustering of
chronic conditions in a biologically and clinically meaningful
way is the so-called metabolic syndrome. Found in 24% of the
U.S. population,9the metabolic syndrome is present when
patients have at least 3 of 5 chronic conditions: obesity,
hypertriglyceridemia, low-serum high-density lipoprotein
(HDL), hypertension, and glucose intolerance.10,11The meta-
bolic syndrome is associated with increased risk of cardiovas-
cular disease and all cause mortality12,13and may reflect
underlying genetic predispositions to this combination of
The health consequences of multiple chronic conditions are
poorly understood. Overall, specific chronic conditions have a
stronger relationship with functional impairment than others,
and persons with more chronic conditions become more
functionally impaired sooner than persons with fewer chronic
conditions.16The picture, however, appears to be more
complex. One of the most revealing studies to date found that
after controlling for the presence of individual conditions,
specific MCC were associated with disability far greater than
expected based on the disability observed for each disease in
isolation. The authors suggested that some diseases may be
associated with disability only in the presence of other specific
diseases, and that “a new, potentially effective strategy for
prevention or amelioration of disability would be to decrease
targeted disease-disease interactions”.17Fultz et al.18also
found synergistic interactions between some pairings of men-
tal and physical conditions, but not others. For example,
persons with stroke and cognitive impairment had a higher
level of impairment in activities of daily living than predicted by
the presence of stroke and cognitive impairment alone. Other
combinations, such as stroke and depression, did not have the
same synergistic effect on activities of daily living impair-
ments.18A recent analysis of near-elderly veterans found that
in general the risk of 5-year mortality increased with the
number of co-occurring chronic conditions; however, osteoar-
thritis in combination with any other chronic condition
actually lowered the risk of 5-year mortality.19
QUALITY AND CARE MANAGEMENT CHALLENGES
Persons with multiple chronic conditions are particularly
vulnerable to suboptimal quality care.2They tend to use
services more frequently and to use a greater array of services
than other consumers of care. This makes coordination of care
more difficult for individuals with multiple chronic conditions.
The number of different physicians seen annually by the
average Medicare patient with a chronic condition ranges from
4 with 1 condition to 14 with 5 or more. As the number of
providers involved in patients’ care increases, patients are
likely to find it increasingly challenging to understand, re-
member, and reconcile the instructions of those providers.20
Because patients with more than 1 chronic condition take on
average more medications, they are more likely to suffer
adverse drug events (ADEs), including ADEs that result from
drug-drug interactions,21–24or in the specific case of heart
failure coupled with chronic obstructive pulmonary disease,
present challenges to appropriate pharmacological manage-
ment.25Having multiple chronic conditions also makes it more
challenging for patients to participate effectively in their own
care.26Surveys of physicians confirm that they believe quality
problems are increased among their patients with multiple
Vogeli et al.: Multiple Chronic Conditions: Prevalence and Cost
However, the link between co-occurring chronic conditions
and poor quality is far from clear. An assessment of quality
among Canadians over 65 with specific combinations of
chronic conditions found deficiencies in care associated with
some combinations of conditions, but not all. For example,
patients with hyperlipidemia and chronic obstructive pulmo-
nary disease were less likely than patients with hyperlipidemia
alone to receive lipid-lowering medications. Individuals with
psychoses and arthritis were less likely to receive arthritis
medications than individuals with arthritis alone. However,
glaucoma patients with breast cancer are no less likely to
receive glaucoma medications than those without breast
cancer.28A well-known study of the predictors of initiating
psychiatric treatment found that “competing demands” from
physical problems hindered the initiation of psychiatric care.29
However, other studies have found that co-occurring chronic
conditions are actually associated with more appropriate care.
Contrary to prior expectations, researchers examining a cohort
of diabetic patients enrolled in a heart failure disease manage-
ment program found that despite their targeted heart failure
care, these patients also received comprehensive diabetes
care.30Patients with somatic chronic conditions may actually
receive more appropriate care for depression or other psychi-
atric disorders. Among elderly persons, depression care was
more likely to be adequate among elderly persons with co-
occurring diabetes than without,31and neither the number nor
specific comorbid conditions were found to impact the effective-
ness of interventions aimed at improving depression care.32
More general measures of quality also yielded mixed results.
Braunstein et al.33found that the occurrence of hospitaliza-
tions for ambulatory care sensitive conditions increased
among elderly heart failure patients when they suffered from
other comorbidities. Hospitalizations for ambulatory care
sensitive conditions are considered preventable by good pri-
mary care.34The odds of experiencing these so-called “pre-
ventable” hospitalizations were largest when heart failure
occurred in combination with hypertension or chronic renal
insufficiency. However, for unknown reasons, certain comor-
bidities, such as hypercholesterolemia or dementia, seemed to
protect heart failure patients against hospitalization for am-
bulatory care sensitive conditions.33Among vulnerable per-
sons age 65 and over, Min et al.35found that overall, persons
with more chronic conditions had higher (better) risk-adjusted
quality scores. However, specific combinations such as diabe-
tes and cardiovascular disease were associated with worse
quality of care as measured by a composite of up to 207 quality
It is reasonable to hypothesize that clinicians systematically
vary in the provision of indicated services when caring for
patients with particular combinations of conditions, just as
they systematically overlook certain issues in caring for single
illnesses.36For example, systematic differences in colon cancer
screening rates among elderly persons with chronic conditions
may reflect conscious decisions to concentrate screening on
patients whose life expectancy can be improved through
Several observers have argued that current strategies
including disease-specific health guidelines may not be suit-
able in many cases to optimizing care of individuals with
MCC.21,24Instead, it is argued, guidelines need to be tailored
to clusters of illnesses in ways that acknowledge not only the
biology of those clusters, but also the special challenges and
threats to quality of care associated with MCC in general and
specific clusters in particular. Moreover, single-disease-oriented
disease management programs, which frequently offer services
provided outside traditional health care facilities (call centers
care. Even Wagner’s Chronic Care Model, which emphasizes
coordination ofcare around chronic illness,focuses primarily on
single illnesses, not multiple chronic conditions,38so that its
relevance and effects on multiple chronic conditions remain to
The intrinsic challenges to optimizing quality and value of
care among individuals with multiple chronic conditions, the
evidence that quality may be suboptimal for some indivi-
duals with multiple chronic conditions, and indications that
quality may vary with the specific clusters of chronic
conditions, all suggest the need to explore more systemati-
cally the relationship between quality of care and clusters of
COSTS OF CARE
In a country with health care expenditures exceeding
$1.7 trillion and 15% of gross domestic product,39controlling
costs of care has become an overwhelming concern among pub-
lic and private policy makers and managers. From this perspec-
tive, individuals with multiple chronic conditions pose special
challenges and opportunities. The care of individuals with
chronic conditions is estimated to account for 78% of health
expenditures in the United States. Patients with more than 1
chronic condition are estimated to account for 95% of all
Medicare spending; those with more than 5 account for two
thirds.2The Congressional Budget Office reports that among
high-cost Medicare beneficiaries (e.g., the 25% of beneficiaries
accounting for 85% of programmatic costs), about 30% had 4
co-occurring chronic illnesses: coronary artery disease, diabe-
tes, congestive heart failure, and chronic obstructive pulmo-
nary disease.40The likelihood that patients with a particular
condition such as heart failure or diabetes will use expensive
health care resources such as hospital care increases sub-
stantially with the presence of other comorbidities.33,41For
example, the likelihood that a Medicare patient with a chronic
medical condition will use emergency department services
doubles when depression is present as a comorbidity.42
Medicare beneficiaries with heart failure who have comorbid-
ities are more likely to be readmitted for heart failure than
patients without comorbidities.43
The concentration of health care expenditures in subpopu-
lations with chronic conditions has led to the widespread
proliferation of disease management programs. In 2004, 97%
of private health plans had disease management programs for
diabetes, 86% for asthma, 83% for heart failure, and 70% for
ischemic heart disease.44State Medicaid programs have also
begun implementing similar disease management pro-
grams.45,46Under provisions of the Medicare Modernization
Act, Congress instructed the Centers for Medicare and Medic-
aid Services to undertake a variety of initiatives to improve care
for high-cost, chronically ill patients, including the Chronic
Care Improvement Program (CCIP), a large national experi-
ment with applying disease management programs to patients
in the traditional Medicare program.47,48The CCIP will target
more than 30,000 beneficiaries with 3 conditions (diabetes,
Vogeli et al.: Multiple Chronic Conditions: Prevalence and Cost
heart failure, and chronic obstructive pulmonary disease) in
10 regions of the country.
Despite the conceptual attractiveness of the disease man-
agement approach, evidence of clinical and cost-effectiveness
remain limited.49,50Recent analyses have found that cost
savings and return on investments varied by diagnosis.51,52
Most disease management programs focus on management of a
single chronic condition. This raises concerns about whether
they may undermine coordination of care for patients with
MCC,53thereby introducing new inefficiencies and potential
threats to quality of care.21,24,54Furthermore, by focusing on a
single illness, programs fail to account for the synergistic
impact of chronic conditions occurring in combination. The
Medicare program has begun experimenting with improving
management of patients with MCC under other demonstrations
including its Medicare Coordinated Care Demonstration and its
Care Management for High-Cost Beneficiaries Demonstration.
More recently, some private health plans have also shifted
toward intensive case management programs aimed at high-
risk patients with multiple complex conditions,50often using
predictive modeling applications to identify members whose
past utilization suggests they are likely to generate high health
care costs in the future.55However, even these initiatives may
suffer from the fact that they lack information necessary to take
into account the potential variation in costs and quality
associated with particular MCC and information on the most
efficacious treatments for specific disease combinations.
Understanding how to care effectively for persons with multiple
chronic conditions is among the most important challenges
our health care system faces. Despite the depth of research
into specific chronic conditions, there is little information
about the prevalence of MCC, and the health and cost impacts
of specific combinations of chronic conditions. The small
amount we do know suggests that specific chronic conditions
combine and impact health and costs in unpredictable ways,
and that specific combinations have particularly large impacts
of health or costs of care.
Currently, there are a number of methodological challenges
to research on MCC, including, fundamentally, the need for
large and preferably longitudinal, clinically meaningful data
that can be used to identify the natural history of disease, and
control for the severity of individual conditions when assessing
outcomes for MCC. The increasing adoption of health infor-
mation technology has the potential to greatly improve the
level of clinical detail of widely available data,56and may help
accelerate clinically meaningful research.
Such research should help illuminate why certain clusters
of comorbid illness may be more prone to quality lapses or be
associated with significant but unexpected clinical outcomes,
and lead to the development of targeted strategies, including
tailored MCC-specific clinical guidelines, to improve the man-
agement of patients with key MCC. Similarly, research on more
clinically detailed data may be used to develop computerized
decision support that incorporates new knowledge regarding
within a patient and anticipate the tendency of clinicians to
overlook or overprescribe certain elements in the process of
care. Although payers have begun to target high cost combina-
tions, far more research is needed to understand the clinical
impact of the clustering of chronic illness and to incorporate
this more refined understanding into targeted quality improve-
ment and clinical management strategies. With the aging of
population, these needs are ever more pressing.
Acknowledgments: No authors received funding, either internal or
external, to support this work.
Conflicts of interest: None disclosed.
Corresponding Author: Christine Vogeli, PhD; Institute for Health
Policy in the Department of Medicine, Massachusetts General
Hospital, 50 Staniford Street, 9th Floor, Boston, MA 02114, USA
1. Committee on Quality of HealthCare in America, Institute of Medicine.
Crossing the Quality Chasm: A New Health System for the 21st century.
Washington D.C.: National Academies Press; 2001.
2. Partnership for Solutions. Chronic Conditions: Making the Case for
Ongoing Care: Robert Wood Johnson Foundation; 2002.
3. Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van
den Bos GA. Causes and consequences of comorbidity: a review. J Clin
4. Ben-Noun L. Characteristics of comorbidity in adult asthma. Public
Health Rev. 2001;29(1):49–61.
5. Sokal J, Messias E, Dickerson FB, Kreyenbuhl J, Brown CH,
Goldberg RW. Comorbidity of medical illnesses among adults with
serious mental illness who are receiving community psychiatric services.
J Nerv Ment Dis. 2004;192(6):421–7.
6. Tellez-Zenteno JF, Matijevic S, Wiebe S. Somatic comorbidity of
epilepsy in the general population in Canada. Epilepsia 2005;46
7. Wolff JL, Starfield B, Anderson GF. Prevalence, expenditures, and
complications of multiple chronic conditions in the elderly. Arch Intern
8. John R, Kerby DS, Hennessy CH. Patterns and impact of comorbidity
and multimorbidity among community-resident American Indian elders.
9. Park YW, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB.
The metabolic syndrome: prevalence and associated risk factor findings
in the US population from the Third National Health and Nutrition
Examination Survey, 1988–1994. Arch Intern Med. 2003;163(4):427–36.
10. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome
among US adults: findings from the Third National Health and Nutrition
Examination Survey. J Am Med Assoc. 2002;287(3):356–9.
11. Grundy SM, Brewer HB, Cleeman JI, Smith SC, Lenfant C. Definition
of metabolic syndrome: Report of the National Heart, Lung, and Blood
Institute/American Heart Association Conference on Scientific Issues
Related to Definition. Circulation 2004;109:433–8.
12. Hu G, Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Pyorala K.
Prevalence of the metabolic syndrome and its relation to all-cause and
cardiovascular mortality in nondiabetic European men and women. Arch
Intern Med. 2004;164(10):1066–76.
13. Lakka HM, Laaksonen DE, Lakka TA, et al. The metabolic syndrome
and total and cardiovascular disease mortality in middle-aged men.
14. Guettier JM, Georgopoulos A, Tsai MY, et al. Polymorphisms in the
fatty acid-binding protein 2 and apolipoprotein C-III genes are associated
with the metabolic syndrome and dyslipidemia in a South Indian
population. J Clin Endocrinol Metab. 2005;90(3):1705–11.
15. Wyszynski DF, Waterworth DM, Barter PJ, et al. Relation between
atherogenic dyslipidemia and the Adult Treatment Program-III definition
of metabolic syndrome (Genetic Epidemiology of Metabolic Syndrome
Project). Am J Cardiol. 2005;95(2):194–8.
16. Dunlop DD, Lyons JS, Manheim LM, Song J, Chang RW. Arthritis and
heart disease as risk factors for major depression: the role of functional
limitation. Med Care. 2004;42(6):502–11.
Vogeli et al.: Multiple Chronic Conditions: Prevalence and Cost
17. Fried LP, Bandeen-Roche K, Kasper JD, Guralnik JM. Association of Download full-text
comorbidity with disability in older women: The Women’s Health and
Aging Study. J Clin Epidemiol. 1999;52(1):27–37.
18. Fultz NH, Ofstedal M, Herzog AR, Wallace RB. Additive and interactive
effects of comorbid physical and mental conditions on functional health.
J Aging Health. 2003;15(3):465–84.
19. Lee TA, Pickard AS, Bartle B, Weiss KB. Osteoarthritis: a comorbid
marker for longer life? Ann Epidemiol. 2007;17:380–4.
20. National Academy of Social Insurance. Medicare in the 21st Century:
Building a Better Chronic Care System. Washington, DC: National
Academy of Social Insurance; 2003.
21. Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice
guidelines and quality of care for older patients with multiple comorbid
diseases: implications for pay for performance. J Am Med Assoc.
22. Gandhi TK, Weingart SN, Borus J, et al. Adverse drug events in
ambulatory care. N Engl J Med. 2003;348(16):1556–64.
23. Gurwitz JH, Field TS, Harrold LR, et al. Incidence and preventability of
adverse drug events among older persons in the ambulatory setting. J
Am Med Assoc. 2003;289(9):1107–16.
24. Tinetti ME, Bogardus ST, Agostini JV. Potential pitfalls of disease-
specific guidelines for patients with multiple conditions. N Engl J Med.
25. Le Jemtel TH, Padeletti M, Jelic S. Diagnostic and therapeutic
challenges in patients with coexistent chronic obstructive pulmonary
disease and chronic heart failure. J Am Coll Cardiol. 2007;49(2):171–80.
26. Townsend A, Hunt K, Wyke S. Managing multiple morbidity in mid-life:
a qualitative study of attitudes to drug use. Br Med J 2003;327
27. Anderson GF. Physician, public, and policymaker perspectives on
chronic conditions. Arch Intern Med. 2003;163:437–42.
28. Redelmeier DA, Tan SH, Booth GL. The treatment of unrelated
disorders in patients with chronic medical diseases. N Engl J Med.
29. Nutting PA, Rost K, Smith J, Werner JJ, Elliot C. Competing demands
from physical problems. Arch Fam Med 2000;9:1059–64.
30. Ware MG, Flavell CM, Lewis EF, Nohria A, Warner-Stevenson L,
Givertz MM. Heart failure and diabetes: collateral benefit of chronic
disease management. Prev Manag Congest Heart Fail 2006;12
31. Harman JS, Edlund MJ, Fortney JC, Kallas H. The influence of
comorbid chronic medical conditions on the adequacy of depression
care for older Americans. J Am Geriatr Soc 2005;53(12):2178–83.
32. Harpole LH, Williams JW Jr, Olsen MK, et al. Improving depression
outcomes in older adults with comorbid medical illness. Gen Hosp Psych
33. Braunstein JB, Anderson GF, Gerstenblith G, et al. Noncardiac
comorbidity increases preventable hospitalizations and mortality among
Medicare beneficiaries with chronic heart failure. J Am Coll Cardiol.
34. Kruzikas DT, Jiang HJ, Remus D, Barrett ML, Coffey RM, Andrews R.
Preventable Hospitalizations: A Window into Primary and Preventive
Care, 2000. Washington, DC: Agency for Healthcare Research and
35. Min LC, Reuben DB, MacLean CH, et al. Predictors of overall quality
of care provided to vulnerable older people. J Am Geriatr Soc. 2005;53
36. McGlynn EA, Asch SM, Adams J, et al. The quality of health care
delivered to adults in the United States. N Engl J Med. 2003;348
37. Gross CP, McAvay GJ, Krumholz HM, Paltiel AD, Bhasin D, Tinetti
ME. The effect of age and chronic illness on life expectancy after a
diagnosis of colorectal cancer: implications for screening. Ann Intern
38. Wagner EH, Austin BT, Von Korff M. Organizing care for patients with
chronic illness. Milbank Quarterly 1996;74:511–44.
39. Smith C, Cowan C, Sensenig A, Catlin A. Health Accounts Team.
Health spending growth slows in 2003. Health Affairs 2005;24(1):
40. Congressional Budget Office. High Cost Medicare Beneficiaries.
Washington, DC: The Congress of the United States; 2005.
41. Niefeld M, Braunstein JB, Wu AW, Saudek CD, Weller W, Anderson
GF. Preventable hospitalization among elderly Medicare beneficiaries
with Type 2 diabetes. Diabetes Care 2003;26(5):1344–9.
42. Himelhoch S, Weller W, Wu AW, Anderson GF, Cooper LA. Chronic
medical illness, depression, and use of acute medical services among
Medicare beneficiaries. Med Care 2004;42(6):512–21.
43. Krumholz HM, Parent EM, Tu N, et al. Readmission after hospitaliza-
tion for congestive heart failure among Medicare beneficiaries. Arch
Intern Med. 1997;157(1):99–104.
44. Center on an Aging Society. Disease management programs: Improving
health while reducing costs? Washington, DC: Georgetown University;
45. Smith V, Ramesh R, Gifford K, Ellis E, Wachino V. States Respond to
Fiscal Pressure: State Medicaid Spending Growth and Cost Containment
in Fiscal Years 2004 and 2005: Results from a 50-state Survey.
Washington, DC: The Henry J. Kaiser Family Foundation; 2004.
46. Sprague L. Disease Management to Population-Based Health: Steps in
the Right Direction? National Health Policy Forum Issue Brief
47. Glendinning D. New Medicare demo project focuses on chronic health
care. American Medical News 2005;Government & Medicine:5, 8.
48. Gold M, Lake T, Black WE, Smith M. Challenges in improving care for
high-risk seniors in Medicare: lessons and observations from past field
demonstrations. Health Affairs 2005;Web Exclusive(26 April):W5-199–
49. Congressional Budget Office. An Analysis of the Literature on Disease
Management Programs. Washington, DC: Congressional Budget Office;
2004 October 13.
50. Short AC, Mays GP, Mittler J. Disease Management: A Leap of Faith to
Lower-Cost, Higher-Quality Health Care. HSC Issue Brief 2003;No. 69.
51. Bodenheimer T. Disease management in the American market. Br Med
52. Goetzel R, Ozminkowski R, Villagra V, Duffy J. Return on investment
in disease management: A review. Health Care Financ Rev 2005;26:1–19.
53. Blumenthal D, Beeuwkes Buntin M. Carve-outs for Medicare: Possible
benefits and risks. In: Reischauer RD, Butler S, Lave JR, eds.
Medicare: Preparing for the Challenges of the 21st Century. Washington,
DC: National Academy of Social Insurance; 1998:152–83.
54. Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collabo-
rative management of chronic illness. Ann Intern Med. 1997;127
55. Mays GP, Claxton G, White J. Managed care rebound? Recent changes
in health plans’ cost containment strategies. Health Affairs 2004;Web
56. Robert Wood Johnson Foundation, MGH Institute for Health Policy,
George Washington University. Health Information Technology in the
United States, the information base for progress; 2006, available at
(accessed July 17 2006).
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