Chronic disease management: a primer for physicians I. A. Scott

Internal Medicine Journal (2008)
REVIEW
Chronic disease management: a primer for physicians
I. A. Scott
Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital, Brisbane, Queensland, Australia
Key words
chronic disease management, chronic care
model, narrative meta-review.
Correspondence
Ian A. Scott, Level 5A, Medical Specialties,
Princess Alexandra Hospital, Ipswich Road,
Woollongabba, Brisbane, Qld 4102, Australia.
Email: [email protected]
Received 28 June 2007; accepted 22 August
2007.
doi:10.1111/j.1445-5994.2007.01524.x
Abstract
Approximately one in three Australians or 6.8 million individuals suffer from one
or more chronic diseases, the most prevalent being ischaemic heart disease,
congestive heart failure, chronic obstructive lung disease, diabetes and renal
disease. Potentially avoidable hospitalizations related to chronic disease comprise
5.5% of all admissions nationally and cluster in older age groups and socioeconomically disadvantaged regions. In an effort to reduce mortality and morbidity,
programmes of chronic disease management have evolved with the aim of
achieving formalized, population-wide implementation of elements of the chronic
care model developed by Wagner et al. Results of rigorous evaluations of such
programmes suggest improved survival and/or disease control with reductions in
hospitalizations and adverse clinical events. This paper aims to provide an overview of available evidence for chronic disease management programmes for
practising physicians who will be increasingly invited to take an active leadership
role in designing and operationalizing such programmes.
Introduction
All health-care systems face the challenge of providing
the most effective and cost-effective forms of care to the
growing numbers of individuals with chronic disease.
Approximately one in three Australians or 6.8 million
individuals suffer from one or more chronic diseases,
the most prevalent being ischaemic heart disease (IHD,
prevalence 1.9%),1 congestive heart failure (CHF, 4%),1
chronic obstructive lung disease (COPD, 3.5%),1 diabetes
(7.6%)1 and renal disease (11%).2 Potentially avoidable
hospitalizations related to chronic disease number
352 558 per annum, equal to 5.5% of all admissions, with
diabetic complications, COPD, IHD and CHF accounting
for 40, 16, 15 and 12% of these admissions, respectively.3
Approximately two-thirds of these admissions involve
patients aged more than 45 years, with frequency of hospitalisation in socioeconomically disadvantaged regions
being 61% higher than wealthier areas.3
To improve delivery of care to such patients, Wagner et al.
proposed an evidence-based model of chronic care com-
Funding: None
Potential conflicts of interest: None
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
prising the elements listed in Table 1.4 Subsequently, programmes of chronic disease management (CDM)5 have
evolved in several countries including Australia, and promoted by newly established CDM associations, with the aim
of achieving formalized, population-wide implementation
of the chronic care model aimed at reducing mortality,
hospitalizations and burden of illness and disability.6,7
But how effective are such programmes, what programme elements are most critical to success, and do they
provide reasonable return on investment compared with
traditional care models? This paper aims to provide an
overview of available evidence for CDM programmes for
practising physicians who will be increasingly invited to
take an active leadership role in designing and operationalizing such programmes. The working definition of CDM
programmes used here is that of a programme using
a systematic, coordinated, evidence-based approach to
care based on one or more of the elements of the chronic
care model (Table 1).
Search of published work and
data synthesis
The author searched PubMed, Cochrane Library,
Cochrane Effective Practice and Organization of Care
1
Scott
Table 1 Elements of chronic disease management programmes
Multidisciplinary care
Creation of multidisciplinary teams for creating both cooperation and division of labour in which non-doctors can help improve patient care
New professional roles for enhancing capacity of community care and raising threshold for hospital referral (e.g. nurse specialists,
GPs with special interests, outreach clinical pharmacists etc.)
Multidisciplinary assessments of disease risk and severity
Patient self-management
Patient/carer education and support provided one-on-one or in a group setting tailored to specific needs and circumstances
Systematic patient self-monitoring (which may include telemedicine strategies) with feedback and psychological support
Systems for enabling patients and carers to acquire skills, confidence and tools to better care for chronic illness
Provision of problem solving, coping and assertiveness strategies that allow patient-mediated adjustments in treatment and
patient-initiated contact with providers
Coordinated care
Case management defined as intensive, individually tailored, goal-oriented care, which is planned, coordinated and managed by a
single individual (case manager) or members of a team.
Systems for integrating care across multiple conditions and provider settings
Delivery system redesign
Improved access to community resources
Changes to hospital and primary care services that facilitate integrated care across different clinical settings
Different financing arrangements to support community-based, multidisciplinary chronic care
Clinical information systems
Use of registries and call-back systems that identify all patients within a given practice who have a given chronic disease
Routine reporting and feedback loops that include communication with patient, physician and funding agency
Use of data for care management and evaluation/feedback of provider performance embodied in process and outcome measures
Evidence-based care
Decision support to providers with guidelines and prompts
Targeted provider education and expert support
Group, the Chronic Care Bibliography, and the RAND/
University of California, Berkeley Improving Chronic
Illness Care Evaluation website8 and reviewed reference
lists of retrieved articles in locating systematic reviews of
controlled trials published between 1 January 1996 and
31 March 2007 comparing CDM programmes with usual
care for five chronic diseases (COPD, IHD, CHF, diabetes
and renal insufficiency). Search terms included ‘disease
management’, ‘chronic disease management’, ‘chronic
care’ and terms for diseases stated. Where multiple
reviews were found for the same topic, the most recent,
methodologically rigorous (based on the Oxman and
Guyatt index)9 and informative review in terms of clinical
end-points was selected for detailed analysis. A Medline
search was also carried out in identifying trials on topics
for which no systematic review could be found, as well
as more recent, large-scale studies considered likely to
materially alter estimates of effect reported in previously
published systematic reviews. Although numerical data
are presented for each study whenever reported, not
all reviews undertook meta-analyses which reported
pooled estimates of effect in a standardized form. Hence
overall findings relating to efficacy end-points are
summarized here in qualitative fashion as a narrative
meta-review.
2
Efficacy of CDM models of care
Twenty-one studies comprising 19 systematic reviews of
trials10–28 and three individual trials were included in the
detailed analysis.29–31 Systematic reviews selected met all
eight criteria of the Oxman and Guyatt index.9 There was
considerable variation between studies in: (i) operational
definitions of CDM, (ii) type, number and intensity of
CDM strategies used in each trial, (iii) numbers and settings of participants (from a few hundred to tens of thousands), (iv) target audience, with interventions targeted
directly to physicians, patients or both, (v) choice of
primary outcome measure (clinical events, disease control measures, such as, blood pressure or glucose levels,
quality of life/symptoms/functional capacity, processes of
care or provider-patient education/knowledge/satisfaction)
with several reviews reporting pooled results as effect sizes
devoid of clinically meaningful units of effect and (vi) in
the case of systematic reviews, selection criteria used (only
randomized controlled trials (RCT) vs any controlled trial
with or without before-after studies).
Most trials focused on a single disease or clinical setting or
provider type and were limited by insufficient descriptions
of interventions undertaken, low to moderate methodological quality, high dropout rates, short-term (<1 year)
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
Chronic disease management
follow up, observation-induced (Hawthorne) effects,32 little
analysis of costs and component-specific incremental benefit on health, and, in some reviews, publication bias for
positive trials. CDM interventions relating to IHD, CHF and
diabetes were the most frequently studied.
Efficacy of disease-specific CDM
Table 2 reports reviews that assessed CDM effects within the
context of a single disease.10–22 A recent meta-analysis of
CDM programmes for COPD showed no reductions in mortality, but a significant 42% reduction in emergency department and unscheduled clinic visits and 22% reduction in
hospitalizations.10 Pulmonary rehabilitation programmes11
and self-management programmes12 by themselves
improved symptoms and functional status, but had no effect
on other end-points. Regarding IHD, a comprehensive
review of 63 RCT of nurse-led CDM programmes showed
an overall 15% reduction in mortality and 17% reduction in
recurrent acute myocardial infarction.13 Multidisciplinary
CDM approaches to CHF for all of 29 studies combined
yielded 17% reduction in mortality and 16% and 27%
reductions in all-cause and CHF-related hospitalizations,
respectively,14 with similar findings being reported in other
systematic reviews of CDM in CHF.33,34 Patients with
diabetes who received one of several CDM interventions
showed no decrease in mortality, hospitalizations or cardiovascular events in any of seven systematic reviews but most
studies showed significant improvements in measures of
disease control (as assessed by 0.4% to 1.0% decrease in
haemoglobin (Hb)A1c), screening processes for diabetic complications, blood pressure control and patient self-care.16–22
A review of nine trials of patient education for preventing
diabetic foot complications showed 50–70% reductions in
incidence of ulcers and rates of amputation.21 One single site
RCT of intense case management for 246 patients with
poorly controlled diabetes reported no change in disease
control measures, mortality or hospitalizations. In contrast,
another single site RCT of intensive, multidisciplinary targetbased CDM for diabetes involving 160 patients with
extended follow up over nearly 8 years showed 53% reduction in cardiovascular events and between 58% and 63%
reduction in the incidence of microvascular complications.30
Only one trial assessed CDM programmes for chronic
renal insufficiency and showed no evidence of benefit.31
No study assessed a model of CDM predicated on close
integration between hospital specialists and general practitioners (GPs).35
Relative efficacy of individual elements of CDM
Most CDM programmes focus more on patient-centred
than on provider-centred strategies. As an example, in one
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
analysis of 102 trials of CDM, the frequencies of use of
a particular strategy were, in decreasing order: patient
education (79%), multidisciplinary approach (57%), provider education (37%), provider feedback (27%), patient
reminders (26%), patient financial incentives (6%) and
organizational financial incentives (1%).26 In a separate
analysis, the same authors noted that of 118 programmes
assessed, 48 (41%) used one strategy, 41 (34%) used two,
22 (19%) used three and only 7 (6%) used four; no study
used more than four strategies.28
Several studies have attempted to identify which CDM
elements are more effective than others across multiple
trials for the same16 or different conditions (Table 3).23–27
Caution is warranted in interpreting their results given
differences between trials in: (i) schemes for classifying
interventions, (ii) focus on assessing single elements in
isolation versus combinations of elements, (iii) analytic
techniques, (iv) choice of outcome measures and (v)
publication bias. Also, very few trials assessed effects of
financial incentives, access to community resources or
health-care re-organization.
Multidisciplinary care significantly improved quality of
life and dyspnoea in COPD,10 reduced all-cause mortality
and recurrent myocardial infarction as separate endpoints in IHD,13 reduced all-cause and heart failure-related
hospitalizations in CHF14 and improved disease control measures (blood pressure, HbA1c, serum lipids) in
diabetes.16,17,19
Patient self-management significantly improved quality
of life and dyspnoea and tended to reduce mortality and
number of hospitalizations in COPD,10 improved disease
control (coronary risk factors) in IHD,13 reduced hospitalizations in CHF14 and improved disease control measures
in diabetes.18,22,23 CDM irrespective of which element(s)
were labelled primary appeared to consistently improve
patient satisfaction and adherence although effects in
reducing overall costs and health-care utilization were
inconsistent.
Case management as a sole intervention was assessed in
two reviews20,25 and a single trial.29 In a review of six trials
of diabetic case managers20 and a single trial of case
managers targeting only patients with poorly controlled
diabetes, no differences were seen between groups for
disease or risk factor control, quality of life or hospitalizations.29 In a study that pooled data from 12 trials
involving patients with CHF and COPD, there were no
significant effects on hospitalizations or total bed days.25
However, different reviews gave conflicting results
depending on the outcome measure. In a meta-regression
analysis of 66 CDM trials relating to diabetic management
with HbA1c as the outcome measure, multidisciplinary
care teams and case management were identified as the
most effective strategies (reductions in HbA1c of 0.67%
3
4
Intervention (no. trials;
no. participants)
Multidisciplinary, nurse-led secondary
prevention programmes with patient
education and counselling, telephone
follow up, and algorithm-based risk
factor management, with or without
an exercise component; 63 RCT,
21 295 patients.
McAlister et al.14
All-cause mortality RR (95%CI)
Recurrent AMI RR (95%CI)
All-cause mortality
RR (95%CI)
All-cause
readmissions
RR (95%CI)
HF hospitalizations
RR (95%CI)
All studies combined
0.83 (0.70–0.99)
0.84 (0.75–0.93)
0.73 (0.66–0.82)
Multidisciplinary heart failure clinics
0.66 (0.42–1.05)
0.76 (0.58–1.01)
0.76 (0.58–0.99)
Multidisciplinary teams
0.75 (0.59–0.96)
0.81 (0.72–0.91)
0.74 (0.63–0.87)
Discharge planning and telephone follow up
0.91 (0.67–1.29)
0.98 (0.80–1.20)
0.75 (0.57–0.99)
Enhanced patient self-care activities
1.14 (0.67–1.94)
0.73 (0.57–0.93)
0.66 (0.52–0.83)
29 trials (1126 patients) with NYHA II and III symptoms: No study specifically assessed effects on mortality, hospitalizations
or cardiac events. Improvements seen in exercise duration, work capacity, 6-min walk test and, when measured,
health-related QOL.
Intervention
All groups
0.85 (0.77–0.94)
0.83 (0.74–0.94)
CDM + exercise
0.88 (0.74–1.04)
0.62 (0.44–0.87)
CDM only
0.87 (0.76–0.99)
0.86 (0.72–1.03)
Exercise
0.72 (0.54–0.94)
0.76 (0.57–1.01)
8/22 trials showed significantly greater rates of use of at least one drug (lipid-lowering agents up twofold;
beta-blockers up by 19%; antiplatelet drugs up by 7%).
17/35 trials showed significant but modest improvements in risk factor profiles (serum lipids, blood pressure, weight, etc.).
24/42 trials showed significant but small improvements in QOL/functional status.
Study type
(i) Multidisciplinary heart failure clinics featuring
nurse-led education and treatment protocols,
patient self-management and regular telephone
contact (7 RCT, 1183 patients); (ii) multidisciplinary
teams providing specialized follow up in non-clinic
settings, including home visits, with social services
consultation and home support (8 RCT, 1391
patients); (iii) discharge planning, patient aids,
pharmacist review and nurse-led education and
telephone follow up with attendance to GPs
if patient deteriorating (10 RCT, 1897
patients); (iv) enhanced patient self-care activities
with nurse-led education and telephone follow up
(4 RCT, 568 patients).
Congestive heart failure
Clark et al.13
Results
No significant effects on symptoms of dyspnoea, QOL (as measured by SGRQ), lung function, functional status (as measured by 6-min
walk tests), or mortality. Reduced ED and unscheduled clinic visits (RR = 0.58 (95%CI 0.42–0.79)) and hospitalizations (RR = 0.78
(95%CI 0.66–0.94)) in pooled results from 3 and 7 RCT, respectively. Hospital stay reduced (WMD, 2.51 days (95%CI 3.40 to21.61))
in pooled results for 2 RCT that involved multiple CDM elements. Reductions in health-care costs of 34–70% in 4 RCT; 11–23% in
3 before–after studies.
Intervention significantly improved dyspnoea (WMD = 1.0 points (95%CI 0.8–1.2) on CRQ dyspnoea score), fatigue (WMD = 0.9 (95%CI
0.7–1.1) on CRQ fatigue score), emotional function (WMD = 0.7 (95%CI 0.4–1.0) on CRQ emotional function score), sense of control
(WMD = 0.9 (95%CI 0.7–1.2) on CRQ mastery score) and exercise capacity (WMD = 49 m (95%CI 26–72) on 6-min walking distance test).
No data reported on mortality or hospitalization rates.
Self-management programme with
Intervention resulted in near-significant reductions in all-cause mortality (RR = 0.86, 95%CI 0.68–1.08) and all-cause hospitalizations
patient education and use of peak
(RR = 0.63, 95%CI 0.38–1.04), and significantly improved QOL as measured by decrease in scores on SGRQ (WMD = 22.5 points,
flow metres coupled with telephone
95%CI, 24.8 to20.1).
or other enhanced means of follow
up. 8 RCT, 1780 patients.
Interventions with at least 1 CDM
element. 32 studies (20 RCT,
5 controlled trials,
7 before-after studies),
patient numbers not reported
Pulmonary rehabilitation with
exercise training and education.
23 RCT, 650 patients.
Ischaemic heart disease
Sin et al.12
Lacasse et al.11
Adams et al.10
Chronic obstructive pulmonary disease
Reference
Table 2 Systematic reviews of CDM interventions directed at single disease conditions
Scott
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
Valk et al.21
Loveman et al.20
Renders et al.19
Deakin et al.18
Knight et al.17
Shojania et al.16
Diabetes
Rees et al.15
Table 2 Continued
Only one trial assessed clinical events, which showed intervention reduced cardiac mortality at 3 years
(OR = 0.32; 95%CI 0.13–0.8) and readmissions for heart failure (OR = 0.28; 95%CI 0.09–0.85). All trials
showed significant improvement in exercise duration (WMD = 2.4 min; 95%CI 1.9–2.8), work capacity
(WMD = 15 W; 95%CI 13–18), and distance on 6-min walk test (WMD = 41 m; 95%CI 17–65).
At 13 months follow up, intervention reduced HbA1c values by mean of 0.42% (95%CI 0.29–0.54),
with larger effect seen (mean reduction 0.54% versus 0.20%) in trials with mean baseline HbA1c of
8.0% or greater. No data reported on mortality, hospitalizations or events. Two intervention types,
multidisciplinary care teams and case management, were associated with reductions in HbA1c
of 0.67% and 0.52%, respectively, and conferred significant incremental reductions
in HbA1c (0.33 and 0.22%, respectively) compared with trials that did not respectively
feature multidisciplinary care teams or case management. Interventions in which nurse or
pharmacist case managers could make medication adjustments without awaiting physician
authorization achieved the highest reductions in HbA1c compared with all other interventions (0.80%,
95%CI 0.51–1.10 versus 0.32%, 95%CI 0.14–0.49).
Structured, multifaceted approaches to
Statistically significant changes in favour of CDM were seen for: glycaemic control (9/20 studies) with
care for diabetes. 19 RCT, 5 controlled
pooled reduction in HbA1c of 0.5% (95%CI 0.3–0.6%); frequency of HbA1c monitoring (2/4 studies);
screening for retinopathy (2/3 studies); screening for nephropathy (1/3 studies); foot screening and
trials; 6421 patients.
referral to podiatrist (1/3 studies); better foot self-care (1/3 studies); blood pressure control (1/5 studies);
LDL cholesterol levels (1/8 studies). No data reported on mortality, hospitalizations or events.
Group-based, self-management training
Results in favour of intervention patients at 12 months were: reduced HbA1c (WMD = 1.0%, 95%CI
in type 2 patients with diabetes.
0.5–1.4), reduced fasting blood glucose (WMD = 1.2 mmol/l, 95%CI 0.7–1.6), reduced bodyweight
8 RCT, 3 controlled trials; 1532 patients.
(WMD = 1.6 kg, 95%CI 0.3–3.0), reduced systolic blood pressure at 4–6 months (WMD = 5 mmHg,
95%CI 1–10), reduced need for diabetes medication (OR = 11.8, 95%CI 5.2–26.9, NNT = 5), and
improved diabetes knowledge (WMD = 1.0, 95%CI 0.7–1.2). When reported, no effect on
hospitalizations, QOL or HbA1c. No data reported on mortality or morbid events.
(i) Provider-targeted interventions (education,
No data reported on mortality, hospitalizations or morbid events in any of the 3 groups of trials. The
reminders, audit/feedback (12 trials; 2400 patients); trials were very heterogeneous for interventions and outcomes assessed. Most of the trials in all
(ii) care system interventions (follow-up visits,
3 groups reported significantly improved processes of care and physiological end-points (blood
patient recall/reminders, patient education,
pressure, HbA1c) favouring intervention patients.
multidisciplinary team care (20 trials; 21 000
patients); (iii) combined provider and care system
changes (20 trials; 25 000 patients). 41 studies,
27 RCT, 12 controlled trials, 2 interrupted
time-series; 48 000 patients.
Specialist nurses or case managers. 6 trials;
No significant differences between groups in hospitalizations, HbA1c, hypoglycaemic episodes,
1382 patients.
hyperglycaemic incidents or QOL. No data reported on mortality or morbid events.
Patient education for preventing diabetic foot
Weak evidence suggesting interventions reduced foot ulcer incidence and amputation rates in high-risk
ulcerations. 9 RCT. Participant numbers
patients. One trial of high-risk patients reported reduced ulcer incidence (OR = 0.28, 95%CI 0.13–0.59)
not reported.
and amputation rate (OR = 0.32, 95%CI 0.14–0.71). Another trial with complex interventions directed
at patient and doctor reduced incidence of serious foot lesions (OR = 0.41, 95%CI 0.16–1.00).
Foot-care knowledge and patient behaviour positively influenced by patient education in the short term.
Interventions targeting some aspect of
clinician behaviour or organisational
change. 50 RCT, 3 quasi-randomized trials,
13 controlled trials; 29 066 patients
Exercise-based rehabilitation programmes.
29 RCT, 1126 patients with NYHA II
and III symptoms.
Chronic disease management
5
6
ADL, activities of daily living; AMI, acute myocardial infarction; CDM, chronic disease management; CI, confidence interval; CRQ, Chronic Respiratory Questionnaire; ED, emergency department; GDS,
geriatric depression scale; GP, general practitioner; HbA1c, glycosylated haemoglobin; HF, heart failure; NNT, number needed to treat; NYHA, New York Heart Association; OR, odds ratio; QOL, quality of life;
RCT, randomized controlled trial; RR, relative risk; SGRQ, St George respiratory questionnaire; WMD, weighted mean difference.
Norris et al.
Self-management training with interventions
No change seen in cardiovascular events or mortality. Intervention patients at 6 months showed greater
Diabetes Care22 grouped as (i) didactic knowledge and information; reductions in HbA1c (0.8%, 0.4–1.9%), fasting blood glucose (1.2 mmol/L, 0.7–1.6 mmol/L), bodyweight
(1.6 kg, 0.3–3.0 kg), systolic blood pressure (5 mmHg, 1–10 mmHg), need for diabetes medication and
(ii) collaborative knowledge and information;
improved diabetes knowledge and self-monitoring. Effects on lipids, physical activity and weight were
(iii) lifestyle interventions; (iv) skills teaching
variable. Longer-term follow-up interventions using regular reinforcement and educational
interventions; coping skills interventions.
interventions involving patient collaboration (vs didactic interventions) tended to be more
72 RCT. Participant numbers not reported.
effective in improving glycaemic control.
Table 2 Continued
Scott
and 0.52%, respectively), with greatest effect (0.80%
reduction) associated with nurse or pharmacist case managers who could adjust medication regimens without
awaiting authorization from doctors.16 In one review of
112 CDM trials pertaining to several disease conditions,24
more pronounced effects on clinical outcomes were seen
with multidisciplinary care and patient self-management
than for provider decision support, although self-management and decision support were more effective than multidisciplinary care in improving processes of care (Table 4).
In another evaluation of 102 CDM trials for different
disease conditions, provider feedback and reminders were
more effective than provider education in optimizing provider adherence to evidence-based guidelines (Table 4).28
However, in the same study, if disease control was the
outcome measure, patient financial incentives and provider education were more effective than patient
reminders or education and provider feedback.
In summary, multidisciplinary care, care coordination,
patient self-management and provider education showed
the greatest and most consistent effects on clinical outcomes and process-of-care measures with provider decision support and feedback having intermediate effects.
Case management conferred some benefit in patients with
diabetes, but its effects in other diseases are unknown.
Whether clinical information systems,16,36 telehealth
strategies,36 health-care system redesign16,36 and access
to community resources7 exert effects independent of
other strategies was unable to be determined with any
level of certainty. This was due to the paucity of controlled
studies, although a recently reported systematic review of
telemonitoring or telephone support for patients with CHF
showed savings in all-cause deaths and disease-related
hospitalizations.37
Cost-effectiveness of CDM
In US studies, it has been estimated that two-thirds of CDM
programme costs are accounted for by the 20% of patients
with chronic disease who have five or more conditions.38
Overall the evidence on cost savings from CDM is limited
as: (i) comparatively few studies measured costs, (ii) selection bias pertained to those that did, (iii) regression to the
mean in costings was likely as base year costs were derived
from time periods well before commencement of CDM
programmes, (iv) not all costs were ascertained, with
emphasis on direct medical costs only, (v) there was failure
to account for other confounders in expenditure and
(vi) generalizability was limited as most studies evaluated
short-term practice change at a single site.
In analyses of randomized trials, which included cost
data, 8 of 13 in COPD,10 4 of 5 in CHF39 and 7 of 9 in
diabetes17 suggested cost savings as a result of CDM
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
Various CDM programmes. 112 controlled trials (asthma 27;
CHF 21; depression 33; diabetes 31). Participant
numbers not reported.
Hospital-based, nurse-led case management programmes for
patients with heart failure (4 trials), stroke (2 trials), COPD
(1 trial), epilepsy (1 trial), critically ill patients (1 trial) and
frail elderly (3 trials). 12 RCT, 2876 patients
Various CDM programmes. 102 controlled studies (asthma 9;
back pain 6; COPD 6; chronic pain 2; CHF 9; IHD 6;
depression 20; diabetes 22; hyperlipidaemia 6;
hypertension 7; rheumatoid arthritis 9). Participant
numbers not reported.
Patient self-management education programmes for patients
with diabetes, hypertension, asthma and osteoarthritis;
71 controlled trials. Participant numbers not reported.
Tsai et al .24
Kim, Soeken
200525
Warsi et al.27
Percentage of comparisons showing significantly improved processes of care in favour of CDM interventions:
depression: 48% (41/86); hyperlipidaemia 45% (5/11); IHD 39% (7/18); hypertension 37% (7/19); diabetes
mellitus 36% (24/66); asthma 25% (9/36); rheumatoid arthritis 24% (7/29); CHF 18% (6/33); back pain 16%
(3/19); COPD 9% (2/22) and chronic pain 8% (1/12); Percentage of comparisons showing significantly
improved outcomes in favour of CDM interventions: patient satisfaction 71% (12/17); patient adherence
47% (17/36); disease control 45% (33/74); provider adherence 40% (14/35); patient knowledge 31% (4/13);
morbidity 29% (7/24); mortality 24% (4/17); physical functioning 20% (7/35); health status/QOL 16% (5/31);
other utilization 16% (4/25); cost 14% (1/7); emergency visits 11% (1/9), hospitalizations 11% (3/28).
Interventions in patients with diabetes showed reductions in glycosylated haemoglobin levels ((ES) = 0.45,
95%CI 0.17–0.74) and systolic blood pressure levels (ES = 0.20, 95%CI 0.01–0.39). Asthmatic patients
experienced fewer asthma attacks (log rate ratio = 0.59, 95%CI 0.35–0.83). Arthritis patients showed
a trend towards a small benefit.
Overall
20.23 (20.31 to 20.15)
0.84 (0.78–0.90)
0.11 (0.02–0.21)
1.19 (1.10–1.28)
Asthma
NE
0.82 (0.69–0.98)
0.01 (20.19 to 0.20)
1.61 (0.56–4.64)
CHF
NE
0.81 (0.71–0.92)
0.28 (0.06–0.51)
1.13 (1.00–1.28)
Depression
20.25 (20.37 to 20.13)
0.83 (0.74-0.93)
0.18 (0.08–0.28)
1.28 (1.11–1.48)
Diabetes
20.19 (20.29 to 20.10)
0.92 (0.81–1.05)
20.02 (20.20 to 0.17)
1.10 (1.01–1.19)
No overall significant reductions in LOS or readmissions for all trials combined. Case management was
effective in reducing LOS for heart failure patients (ES = 0.24; 95%CI 0.01–0.47), but not for other
disease conditions.
Pooled data showed overall significant ESy of 20.36 (95%CI 20.52 to20.21) on adverse events, decrease in
mean HbA1c of 0.81% in patients with diabetes and mean reductions of 5.0 mmHg and 4.3 mmHg in systolic and
diastolic blood pressure, respectively, in hypertensive patients. Clinically trivial improvements in pain
and functional outcomes for patients with osteoarthritis. No changes seen in weight or other measures
of functional status. No data reported on mortality, hospitalizations or health resource utilization.
Pooled estimates according to condition
Condition
Clinical outcome (lower is better)
QOL (Higher is
Care process (Higher
Continuous ES
Dichotomous RR
better) ES (95%CI)
is better) EF (95%CI)
(95%CI)
(95%CI)
Results
CDM, chronic disease management; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive pulmonary disease; EG, ejection fraction; ES, effect size; IHD, ischaemic heart disease;
LOS, length of stay; NE, not evaluated; RCT, randomized controlled trial; RR, relative risk; QOL, quality of life. yEffect size (more correctly standardised effect size) is used as the measure of effect when
outcomes are measured in different trials using different measurement scales. The observed differences between groups are converted into a unit-free standardised measure based on z-scores, which can
then be pooled across multiple trials. By convention, an ES > 0.6 represents a large clinical effect, ES 0.4–0.6 moderate effect, 0.2–0.4 small to modest effect and < 0.2 an effect of little importance.
Ofman
et al.26
Patient self-management programmes. 53 RCT
(26 diabetes, 14 osteoarthritis, 13 hypertension).
Participant numbers not reported.
Intervention (no. trials/participants)
Chodosh
et al.23
Reference
Table 3 Systematic reviews of CDM interventions directed at multiple disease conditions
Chronic disease management
7
Scott
Table 4 Relative efficacy of CDM strategies in two systematic reviews
Study
CDM component
CDM component
Effects
Process-of-care
outcome ESy (95%CI)
Tsai et al.
Multidisciplinary care
112 trials24 Self-management support
Provider decision support
Clinical information systems
1.16
1.31
1.29
1.08
(1.01–1.34)
(1.00–1.71)
(1.08–1.54)
(0.91–1.28)
Clinical event
outcome ESy or
RR (95%CI)
ES
ES
ES
ES
=
=
=
=
20.21
20.22
20.14
20.06
(20.40
(20.38
(20.33
(20.27
to
to
to
to
20.02); RR
20.05); RR
0.05); RR =
0.15); RR =
Quality-of-life
outcome ESy (95%CI)
= 0.77 (0.62–0.96)
= 0.81 (0.66–0.99)
0.87 (0.69–1.09)
0.83 (0.64–1.07)
Adherence guidelines ESy (95%CI)
Weingarten et al.
102 trials28
Provider-directed interventions
Education
Feedback
Reminders
Patient-directed interventions
Education
Reminders
Financial incentives
0.33 (20.10 to 0.76)
20.03 (20.25 to 0.19)
0.04 (20.36 to 0.45)
20.28 (21.08 to 0.51)
Disease control ESy (95%CI)
0.44 (0.19–0.68)
0.61 (0.28–0.93)
0.52 (0.35–0.69)
0.35 (0.19–0.51)
0.17 (0.10–0.25)
0.22 (0.10–0.37)
NA
NA
NA
0.24 (0.07–0.40)
0.27 (0.17–0.36)
0.40 (0.26–0.54)
y
Effect size (more correctly standardized effect size, ES) is used as the measure of effect when outcomes are measured in different trials using different
measurement scales. The observed differences between groups are converted into a unit-free standardized measure based on z-scores, which can then be
pooled across multiple trials. By convention, an ES > 0.6 is a large clinical effect, ES 0.4–0.6 moderate effect, 0.2–0.4 small to modest effect and < 0.2 an
effect of little importance. CI, confidence interval; CDM, chronic disease management; NA, not applicable; RR, relative risk.
programmes. The highest return on investment, averaging
$US3.66 cost saving per-participant for every dollar spent
(or $2.66 net saving), was seen for CHF programmes compared with less than $1.00 net savings with diabetes programmes.39 Cost savings were thought to be greatest when
CDM was targeted to high-risk individuals identified
by appropriate risk-stratification procedures. However,
a time-series analysis of US trends in historical in-hospital
costs, discharges, mean length of stay and emergency
department visits for patients with IHD, CHF, asthma and
diabetes deduced that in order to cover CDM programme
costs alone (estimated at US90c per patient per month),
CDM interventions would need to decrease admissions
related to chronic disease by between 10% and 20% depending on hospital cost per day ($US2000–1000, respectively).38
Study limitations
This analysis has several limitations. First, an exhaustive
systematic review of all relevant trials for all nominated
diseases was not carried out, instead a more pragmatic
review of reviews and of selected trials. Thus efficacy
results should be regarded as indicative rather than definitive, although it is unlikely any well-designed and
materially important studies were missed. Second, investigation of complex, multifaceted interventions using linear methods of meta-analysis, as occurred in most studies,
may have caused certain interactions between disease
condition and elements of CDM that were significant to
have been lost in pooled analyses. A related limitation is
8
the inability to assess the intensity of implementation of
study interventions. Finally, the synergistic effect on effectiveness of CDM of clinician leadership, infrastructure
support and team dynamics could not be determined as
no study assessed these factors independently.
Implications for clinical practice
Based on US Medicare data, approximately two-thirds of
persons 65 years or older have two or more chronic diseases40 and it is probable that the same holds true for
Australia. Of patients with CHF or diabetes, 65% and 56%,
respectively, have four or more additional diseases. Experience with large-scale CDM models of care in this country
is confined to primary care settings and has recently been
reviewed.41,42 Key initiatives have included:
l Comprehensive multidisciplinary health assessments
and care plans instigated by GPs and financed through
an Enhanced Primary Care (EPC) item on the Medicare
Benefits Schedule (MBS) introduced in November 1999.
However, EPC consultations currently account for less
than 0.5% of GP encounters43 and evidence of efficacy
is limited to small before-after studies assessing quality of
care.44
l Practice Incentive Programmes (PIP) and Service Incentive Payments for care of diabetes and asthma, which have
not been subject to formal evaluation.
l Specific funding for team care arrangements through
Medicare items and for practice nurses through both PIP
and Medicare.
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
Chronic disease management
l National Primary Care Collaboratives Programme introduced in 2004 that ‘to date’ have involved 600 general
practices and shown some improvements in measures of
quality of care for patients with coronary heart disease.45
Nevertheless, CDM in this country is receiving strong
support from the federal government which, for the 2006–
2007 financial year, allocated an unprecedented $AU515
million over 5 years for implementation of chronic disease
self-management education and training activities under
the Australian Better Health Initiative,46 including an
MBS item for a focused health check by GPs for persons
aged approximately 45 years who have one or more risk
factors that predispose to a chronic disease. This was in
addition to $36.2 million already committed to various
educational initiatives under the Sharing Health Care
Initiative.47 Private health funds are also experimenting
with CDM programmes that feature care coordination and
patient counselling by a range of different health professionals.46 The role of consultant physicians in future CDM
initiatives has recently been strengthened by the inclusion
in the MBS from November 2007 of new consultation
items (MBS 111 for first consultation and 117 for review
consultation), which deal specifically with patients who
have complex, chronic disease and need more consultant
time and effort in providing a coordinated, multifaceted
approach to disease management.48
However, large-scale CDM programmes in other countries have not been without their problems49,50 and in light
of these experiences and the preceding discussion on
efficacy, CDM programmes in this country must satisfy
several prerequisites if they are to realize their full
potential.
First, multidisciplinary care, patient self-management,
care coordination across networks and groups of providers
and targeted provider education should be mandatory
components of any evidence-based CDM programme.
Second, CDM programmes need to be patient centred
(not disease centred): flexible; risk-based; geographically
accessible; responsive to the needs of local populations
including those with multiple disease conditions and from
disadvantaged and minority groups (especially those of
non-English-speaking backgrounds) who may have low
health literacy levels;51 and able to care for patients who
transit between different risk levels and clinical settings.
Third, financing arrangements must provide income
streams dedicated to CDM programmes that includes
‘up-front’ or ‘seed’ funding for developing interventions
and establishing robust, integrated clinical information
systems, with the realization that return on investment
in the form of reduced health-care utilization may take
some years to materialize.39 Fourth, CDM programmes
must use information systems to allow patients and carers
to access needed resources, to share patient information
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
among providers, to track patient progress and care processes, and to allow programme costs and outcomes to be
evaluated over the medium to long term using standardized measures.52,53 Fifth, CDM programmes must evoke
physician and managerial buy-in from different sectors
of the health-care system54 and build strong linkages
with primary care.35 Finally, CDM programmes should
use proactive population-based approaches to improving
health that include structured referral procedures for
at-risk individuals rather than simply rely on ad hoc
referrals of patients with symptomatic disease.4,52
One proposed hierarchical model for escalating CDM
intensity according to patient need consists of the following levels:55
l Low-intensity CDM for low-risk patients (75% of those
with chronic disease) undertaken by multiskilled nurses
located in community or hospital clinics, supervised by GPs
or hospital specialists, respectively, and trained to undertake disease-specific assessments and patient counselling
combined with patient self-management strategies that
may include telephone-based ‘coaching’ methods.56
l Mid-intensity CDM for the 15–20% of mid-risk patients
carried out by multiple medical specialists of different
disciplines (e.g. diabetologist, nephrologist, cardiologist,
general physician/geriatrician), nurse specialists and allied
health professionals who are colocated in a community or
hospital-based ‘integrated’ clinic and comanage eligible
patients. Such clinics would ideally be geographically
situated among catchment populations with a high prevalence of such patients to maximize patient access and
the effect of the programme on health.
l High-intensity CDM for the 5–10% of high-risk patients
that features case managers (or care co-ordinators) who
manage patients in a one-to-one relation, either full time
or part time, undertaking regular home visits and telephone contact, overseeing and adjusting treatments as
appropriate, liaising closely with GP and specialist, negotiating services with community health, social services,
palliative care and other agencies and providing patient
support and advocacy.
Conclusion
In selected circumstances, models of CDM show promise in
reducing illness and hospitalizations compared with traditional forms of care. However, more high-quality clinical
trials coupled with rigorous evaluations of existing programmes are required to shed more light on those strategies and designs of CDM that yield consistent and
reasonable returns on investment. To be sustainable,
CDM programmes need to be carefully designed, implemented and targeted to the most appropriate patient
groups and elicit commitment from providers and funders
9
Scott
over the long term. Given the role of physicians in providing expert care to large numbers of patients with
chronic diseases, it is imperative physicians understand
what CDM is and what it aspires to achieve and take
a leadership role in its successful evolution.57,58
References
1 Australian Institute of Health and Welfare. Australia’s Health
2004. Canberra: AIHW; 2004.
2 Chadban SJ, Briganti EM, Kerr PG, Dunstan DW, Welborn
TA, Zimmet PZ et al. Prevalence of kidney damage in
Australian adults: The AusDiab kidney study. J Am Soc
Nephrol 2003; 14 (7 Suppl. 2): S131–8.
3 Page A, Ambrose S, Glover J, Hetzel D. Atlas of Avoidable
Hospitalisations in Australia: Ambulatory Care-Sensitive
Conditions. Adelaide: PHIDU; University of Adelaide; 2007.
4 Wagner EH, Austin BT, Von Korff M. Organizing care for
patients with chronic illness. Milbank Q 1996; 74: 511–44.
5 Ellrodt G, Cook DJ, Lee J, Cho M, Hunt D, Weingarten S.
Evidence-based disease management. JAMA 1997; 278:
1687–92.
6 Disease Management Association of America: Definition of
Disease Management. Available from URL: www.dmaa.
org/definition.html
7 Australian Disease Management Association. [cited 2007
Mar]. Available from URL: www.adma.org.au
8 The RAND/University of California-Berkeley Improving
Chronic Illness Care Evaluation (ICICE). [cited 2007 Mar].
Available from URL: www.rand.org/health/ICICE
9 Oxman AD, Guyatt GH. Validation of an index of the quality
of review articles. J Clin Epidemiol 1991; 44: 1271–8.
10 Adams SG, Smith PK, Allan PF, Anzueto A, Pugh JA, Cornell
JE. Systematic review of the chronic care model in chronic
obstructive pulmonary disease prevention and
management. Arch Intern Med 2007; 167: 551–61.
11 Lacasse Y, Brosseau L, Milne S, Martin S, Wong E, Guyatt
GH et al. Pulmonary rehabilitation for chronic obstructive
pulmonary disease. Cochrane Database Syst Rev 2001; (4): Art.
No.: CD 003793. doi: 10.1002/14651858.CD 003793.
12 Sin DD, McAlister FA, Man SF, Anthonisen NR.
Contemporary management of chronic obstructive
pulmonary disease: scientific review. JAMA 2003; 290:
2301–12.
13 Clark AM, Hartling L, Vandermeer B, McAlister FA.
Meta-analysis: secondary prevention programs for patients
with coronary artery disease. Ann Intern Med 2005; 143:
659–72.
14 McAlister FA, Stewart S, Ferrua S, McMurray JV.
Multidisciplinary strategies for the management of heart
failure patients at high risk for admission. J Am Coll Cardiol
2004; 44: 810–19.
15 Rees K, Taylor RS, Singh S, Coats AJS, Ebrahim S. Exercise
based rehabilitation for heart failure. Cochrane Database Syst
10
16
17
18
19
20
21
22
23
24
25
26
27
28
Rev 2004; (3): Art. No.: CD 003331. doi: 10.1002/14651858.
CD 003331.pub2.
Shojania KG, Ranji SR, McDonald KM, Grimshaw JM,
Sundaram V, Rushakoff RJ et al. Effects of quality
improvement strategies for type 2 diabetes on glycemic
control. A meta-regression analysis. JAMA 2006; 296:
427–40.
Knight K, Badamgarav E, Henning JM, Hasselblad V,
Gano AD Jr, Ofman JJ et al. A systematic review of diabetes
disease management programs. Am J Manag Care 2005; 11:
242–50.
Deakin T, McShane CE, Cade JE, Williams RDRR.
Group-based training for self-management strategies in
people with type 2 diabetes mellitus. Cochrane Database Syst
Rev 2005; (2): Art. No.: CD 003417.doi: 10.1002/
14651858.CD 003417.pub2.
Renders CM, Valk GD, Griffin S, Wagner EH, Eijk JT,
Assendelft WJ. Interventions to improve the management
of diabetes mellitus in primary care, outpatient and
community settings. Cochrane Database Syst Rev 2001; (4):
Art. No.:CD 001481.doi: 10.1002/14651858.CD 001481.
Loveman E, Royle P, Waugh N. Specialist nurses in diabetes
mellitus. Cochrane Database Syst Rev 2003; (2): Art. No.: CD
003286. doi: 10.1002/14651858.CD 003286.
Valk GD, Kriegsman DMW, Assendelft WJJ. Patient
education for preventing diabetic foot ulceration. Cochrane
Database Syst Rev 2001; (4): Art. No.: CD 001488.
doi: 10.1002/14651858.CD 001488.pub2.
Norris SL, Engelgau MM, Narayan KM. Effectiveness of
self-management training in type 2 diabetes: a systematic
review of randomized controlled trials. Diabetes Care 2001;
24: 561–87.
Chodosh J, Morton SC, Mojica W, Maglione M, Suttorp MJ,
Hilton L et al. Meta-analysis: chronic disease
self-management programs for older adults. Ann Intern Med
2005; 143: 427–38.
Tsai AC, Morton SC, Mangione CM, Keeler EB. A
meta-analysis of interventions to improve care for chronic
illness. Am J Manag Care 2005; 11: 478–88.
Kim Y-J, Soeken KL. A meta-analysis of the effect of
hospital-based case management on hospital length of stay
and readmission. Nurs Res 2005; 4: 255–64.
Ofman JJ, Badamgarav E, Henning JM, Knight K, Gano AD
Jr, Levan RK et al. Does disease management improve
clinical and economic outcomes in patients with chronic
diseases? A systematic review. Am J Med 2004; 117: 182–92.
Warsi A, Wang PS, LaValley MP, Avorn J, Solomon DH.
Self-management education programs in chronic diseases:
a systematic review and methodological critique of the
literature. Arch Intern Med 2004; 164: 1641–9.
Weingarten SR, Henning JM, Badamgarav E, Knight K,
Hasselblad V, Gano A et al. Interventions used in chronic
disease management programmes for patients with chronic
illness–which ones work? Meta-analysis of published
reports. BMJ 2002; 325: 925–32.
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
Chronic disease management
29 KreinSL,KlamerusML,VijanS,LeeJL,FitzgeraldJT,PawlowA
et al. Case management for patients with poorly controlled
diabetes: a randomized trial. Am J Med 2004; 116: 732–9.
30 Gaede P, Vedel P, Larsen N, Jensen GVH, Parving H-H,
Pedersen O. Multifactorial intervention and cardiovascular
disease in patients with type 2 diabetes. N Engl J Med 2003;
348: 383–93.
31 Harris LE, Luft FC, Rudy DW, Kesterson JG, Tierney WM.
Effects of multidisciplinary case management in patients with
chronic renal insufficiency. Am J Med 1998; 105: 464–71.
32 Cohen J. Statistical Power Analysis for the Behavioural Sciences.
New York: Academic Press; 1977.
33 Roccaforte R, Demers C, Baldassarre F, Teo KK, Yusuf S.
Effectiveness of comprehensive disease management
programmes in improving clinical outcomes in heart failure
patients. A meta-analysis. Eur J Heart Fail 2005; 7: 1133–44.
34 Gonseth J, Guallar-Castillon P, Banegas JR,
Rodriguez-Artalejo F. The effectiveness of disease
management programmes in reducing hospital
re-admission in older patients with heart failure:
a systematic review and meta-analysis of published reports.
Eur Heart J 2004; 25: 1570–95.
35 Rothman AA, Wagner EH. Chronic illness management:
what is the role of primary care? Ann Intern Med 2003; 138:
256–61.
36 Celler BG, Lovell NH, Basilakis J. Using information
technology to improve the management of chronic disease.
Med J Aust 2003; 179: 242–6.
37 Clark RA, Inglis SC, McAlister FA, Cleland JGF, Stewart S.
Telemonitoring or structured telephone support programmes
for patients with chronic heart failure: systematic review and
meta-analysis. BMJ 2007; 334: 942–50.
38 Linden A. What will it take for disease management to
demonstrate a return on investment? New perspectives
on an old theme. Am J Manag Care 2006; 12: 217–22.
39 Goetzel RZ, Ozminkowski RJ, Villagra VG, Duffy J. Return
on investment in disease management: a review.
Health Care Financ Rev 2005; 26: 1–19.
40 Partnership for Solutions. Medicare: Cost and Prevalence of
Chronic Conditions. Baltimore, MD: John Hopkins University
Press; 2002.
41 Zwar N, Harris M, Griffiths R, Roland M, Dennis S, Davies GP
et al. A Systematic Review of Chronic Disease Management. Sydney:
Research Centre for Primary Health Care and Equity, School
of Public Health and Community Medicine UNSW; 2006.
42 Harris MF, Zwar NA. Care of patients with chronic disease: the
challenge for general practice. Med J Aust 2007; 187: 104–7.
43 O’Halloran J, Ng A, Britt H, Charles J. EPC encounters in
Australian general practice. Aust Fam Physician 2006; 35: 8–10.
44 Zwar NA, Hermiz O, Comino EJ, Shortus T, Burns J, Harris M.
Do multidisciplinary care plans result in better care for patients
with type 2 diabetes? Aust Fam Physician 2007; 36: 85–9.
45 Farmer L, Knight A, Ford D. Systems change in Australian
general practice: early impact of the National Primary Care
Collaboratives. Aust Fam Physician 2005; 34: 44–6.
ª 2008 The Author
Journal compilation ª 2008 Royal Australasian College of Physicians
46 Jordan JE, Osbourne RH. Chronic disease self-management
education programs: challenges ahead. Med J Aust 2007;
186: 84–7.
47 Australian Government Department of Health and Ageing.
Sharing Health Care Initiative. Executive summary and discussion,
Canberra: Commonwealth Government, 2005 [cited 30
April 2007]. Available from URL: www.health.gov.
au/internet/wcms/publishing.nsf/Content/
chronicdisease-nateval
48 Australian Government Budget, 2007–2008. Budget Paper
No. 2. Chronic and complex conditions – supporting patient
care. [cited 2007 May 20]. Available from URL:
www.budget.gov.au/2007-08/bp2/html/expense-20.htm
49 Kennedy A, Gately C, Rogers A. National Evaluation of the
Expert Patients Programme. Manchester, UK: National
Primary Care Research and Development Centre, 2004
[cited 2007 April 30]. Available from URL:
www.npcrdc.ac.uk/PublicationDetail.cfm?ID=105
50 Lorig KR, Hurwicz ML, Sobel DS, Hobbs M, Ritter PL.
A national dissemination of an evidence-based
self-management program: a process evaluation study.
Patient Educ Couns 2005; 59: 69–79.
51 Paasche-Orlow MK, Schillinger D, Greene SM, Wagner EH.
How health care systems can begin to address the
challenge of limited literacy. J Gen Intern Med 2006; 21:
884–7.
52 Casalino L, Gillies RR, Shortell SM, Schmittdiel JA,
Bodenheimer T, Robinson JC et al. External incentives,
information technology and organised processes to improve
health care quality for patients with chronic diseases. JAMA
2003; 289: 434–41.
53 Fitzner K, Sidorov J, Fetterolf D, Wennberg D, Eisenberg E,
Cousins M et al. Quality and Research Committee, Disease
Management Association of America. Principles for
assessing disease management outcomes. Dis Manag 2004;
7: 191–201.
54 Rundall TG, Shortell SM, Wang MC, Casalino L,
Bodenheimer T, Gillies RR et al. As good as it gets? Chronic
care management in nine leading US physician
organisations. BMJ 2002; 325: 958–61.
55 National Health Priority Action Council (NHPAC). National
Chronic Disease Strategy. Canberra: Australian Government
Department of Health and Ageing; 2006.
56 Vale MJ, Jelinek MV, Best JD, Dart AM, Grigg LE, Hare DL
et al. COACH Study Group. Coaching patients On Achieving
Cardiovascular Health (COACH): a multicenter randomized
trial in patients
with coronary heart disease. Arch Intern Med 2003; 163:
2775–83.
57 Brand CM, Scott IA, Greenberg PB, Sargious P. Chronic
disease management: time for consultant physicians to take
more leadership in system redesign. Intern Med J 2007; 37:
653–59.
58 Porter ME, Teisberg EO. How physicians can change the
future of health care. JAMA 2007; 297: 1103–11.
11