A Meta-Analysis of Interventions to Improve Chronic Illness Care Alexander Tsai

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A Meta-Analysis of
Interventions to Improve
Chronic Illness Care
Alexander Tsai1 (act2@case.edu),
S.C. Morton2, C.M. Mangione3,
E.B. Keeler2
AcademyHealth Annual Research
Meeting, June 7, 2004
1
Case School of Medicine; 2 RAND Health; 3 David Geffen School of Medicine at UCLA
The Chronic Care Model
Objective
• Lack of controlled studies of the CCM
– But there have been controlled studies of
interventions that incorporate one or more
CCM elements
• Using meta analysis, we sought to:
– Determine the extent to which CCM-style
interventions improve chronic illness care
– Determine whether any specific CCM
elements were essential to improved
outcomes
Table 1. Outcomes of Interest
Clinical Outcomes
(Continuous)
(Dichotomous)
Quality of Life
Processes
(Continuous)
(Dichotomous)
Asthma
# ED visits
% with at
least one ED
visit
Quality of life
% with longacting meds
CHF
# hospital
readmissions
% with at
least 1
readmission
Quality of life
% with ACE
inhibitor
Depression Depression
Scale
% depressed
/symptomatic
Quality of life
or SF-36 MCS
% with
antidepressant
Diabetes
% with HbA1c Quality of life
> 7%
HbA1c
% tested for
HbA1c level
Data Sources
1. Bibliographies of 23 recently published
systematic reviews and meta-analyses:
asthma (5), CHF (6), diabetes (7),
depression (2), general chronic care (2),
information systems (1)
2. MEDLINE 1998-2003
3. Chronic Care Bibliography
Inclusion/Exclusion Criteria
• Inclusion criteria
– 1993-2003
– Asthma, CHF, depression, diabetes
– Controlled (randomized or non-randomized)
– Outcomes of Interest
• Exclusion criteria
– Not written in English
– Non-adult patient population
– Insufficient statistics
Data Abstraction
• Data obtained from all relevant associated
articles and attributed to the primary
citation
• Only 12-month follow-up data recorded if
multiple follow-up times assessed
• If missing data, SD conservatively
assumed to be 1/4 of the theoretical range
for that measure
Statistical Analysis
• Comparisons at follow-up
• Pooled analysis by condition
– Hedges’ g (continuous), risk ratio (binary)
• Relative effectiveness of CCM elements
– Random-effects meta-regression model
• Funnel plots to detect publication bias
• Cochran’s Q to assess heterogeneity
• Sensitivity analysis for Jadad score ≥3
Table 2. Summary Statistics
(N=112)
Element Type DSD SMS DS
CIS
19
CR
4
HCO
6
N
60
80
38
# Elements
One
Two
Three Four
Five
Six
N
52
33
19
8
0
0
Jadad score
Zero
One
Two
Three Four Five
N
19
23
34
36
0
0
Table 3. By Condition
Clinical Outcomes
Quality of life
Processes
[continuous]
(lower=better)
[dichotomous]
(lower=better)
[continuous]
(higher=better)
[dichotomous]
(higher=better)
Effect Size
RR
Effect Size
RR
-0.23 *
0.84 *
0.11 *
1.19 *
Asthma
0.82 *
0.01
1.61
CHF
0.81 *
0.28 *
1.13 *
OVERALL
Depression
-0.25 *
0.83 *
0.18 *
1.28 *
Diabetes
-0.19 *
0.92
-0.02
1.10 *
* P<0.05
Table 4. By CCM Element
Clinical Outcomes
Quality of life
Processes
[continuous]
(lower=better)
[dichotomous]
(lower=better)
[continuous]
(higher=better)
[dichotomous]
(higher=better)
Effect Size
RR
Effect Size
RR
DSD
-0.21 *
0.77 *
0.33
1.16 *
SMS
-0.22 *
0.81 *
-0.03
1.31 *
DS
-0.14
0.87
0.04
1.29 *
CIS
-0.06
0.83
-0.28
1.08
* P<0.05
Conclusions
1. Interventions that contained one or more
CCM elements improved clinical
outcomes and processes of care for four
chronic illnesses
2. Effect on quality of life was mixed
3. The specific CCM elements most
responsible for the beneficial effects
could not be determined
Limitations
• Testing the CCM vs. testing CCM
elements
– Unable to assess intensity of implementation
• Unexplained heterogeneity in aggregating
across conditions and types of
interventions
• Conclusions limited to selected outcomes
and selected conditions
For additional information:
http://www.rand.org/health/ICICE
E-mail:
act2@case.edu
Fig 1. Clinical Outcomes (Continuous)
Depression
Diabetes
Banerjee (1996)
Barrett (2001)
Blanchard (1995)
Brown (2000)
Callahan (1994)
Coleman (1999)
Datto (2003)
Goldberg (1998)
Hunkeler (2000)
Katon (1995)
Katon (1996)
Katon (1999)
Katzelnick (2000)
Leveille (1998)
Llewellyn-Jones (1
Mann (1998)
Miranda (2003)
Mynors-Wallis (200
Rabins (2000)
Rollman (2002)
Rost (2001)
Rubenstein (2003)
Simon (2000)
Tutty (2000)
Unutzer (2002)
Whooley (2000)
Worrall (1999)
Benjamin (1999)
Brown (2002)
DICET (1994)
De Sonnaville (199
Glasgow (2000)
Glasgow (2003)
Hirsch (2002)
Hoskins (1993)
Hurwitz (1993)
Jaber (1996)
Keyserling (2002)
Kinmonth (1998)
Laffel (1998)
Meigs (2003)
O'Connor (1996)
Olivarius (2001)
Pieber (1995)
Piette (2000)
Piette (2001)
Ridgeway (1999)
Stroebel (2002)
Thompson (1999)
Tu (1993)
Weinberger (1995)
Whitlock (2000)
Combined
-2
-1
0
Standardized effect size
1
Q=230, df=51, P<0.001
Pooled Effect Size = -0.23 (-0.31, -0.15) favoring intervention
Fig 2. Clinical Outcomes (Binary)
Asthma
CHF
Depression
Diabetes
Bailey (1999)
Cowie (1997)
Garrett (1994)
Ghosh (1998)
Harish (2001)
Heard (1999)
Yoon (1993)
Capomolla (2002)
Cline (1998)
Ekman (1998)
Harrison (2002)
Hughes (2000)
Jaarsma (1999)
Kasper (2002)
Laramee (2003)
Naylor (1999)
Philbin (2000)
Rich (1993)
Rich (1995)
Riegel (2000)
Riegel (2002)
Schneider (1993)
Serxner (1998)
Stewart (1998)
Stewart (1999)
Weinberger (1996)
Banerjee (1996)
Katon (1999)
Katzelnick (2000)
Llewellyn-Jones (1
Mann (1998)
Mynors-Wallis (200
Rollman (2002)
Rubenstein (2003)
Simon (2000)
Tutty (2000)
Unutzer (2002)
Wells (2000)
Whooley (2000)
Williams (1999)
De Sonnaville (199
Meigs (2003)
Piette (2000)
Renders (2001)
Combined
.25
.5
Relative risk
1
2
4
Q=135, df=45, P<0.001
Pooled RR = 0.84 (0.78, 0.90) favoring intervention
Fig 3. Quality of Life
Asthma
Abdulwadud (1999)
Blixen (2001)
Cote (1997)
De Oliveira (1999)
Gallefoss (1999)
Kauppinen (1998)
Knoell (1998)
Kotses (1995)
Lahdensuo (1996)
Levy (2000)
Premaratne (1999)
Thoonen (2003)
Harrison (2002)
CHF
Jaarsma (1999)
Kasper (2002)
Philbin (2000)
Rich (1995)
Stewart (1999)
Depression
Rubenstein (2003)
Unutzer (2002)
Wells (2000)
Diabetes
Glasgow (2000)
Kinmonth (1998)
Piette (2000)
Combined
-2
-1
0
Standardized effect size
1
Q=93, df=23, P<0.001
Pooled Effect Size = 0.11 (0.02, 0.21) favoring intervention
Fig 4. Processes of Care
Asthma
Eccles (2002)
CHF
Gallefoss (1999)
Akosah (2002)
Cline (1998)
Gattis (1999)
Kasper (2002)
Philbin (2000)
Depression
Weinberger (1996)
Aubert (2003)
Bashir (2000)
Brown (2000)
Callahan (1994)
Coleman (1999)
Dowrick (1995)
Katon (1999)
Mann (1998)
Rollman (2002)
Rost (2001)
Rubenstein (2003)
Unutzer (2002)
Weatherall (2000)
Wells (2000)
Diabetes
Worrall (1999)
Branger (1999)
DICET (1994)
Davidson (2000)
Kiefe (2001)
McDermott (2001)
Meigs (2003)
O'Connor (1996)
Reed (2001)
Stroebel (2002)
Combined
.25
.5
1
2
4
Relative risk
Q=312, df=31, P<0.001
Pooled RR = 1.19 (1.10, 1.28) favoring intervention
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