Cardiovascular Disease (CVD)
Risk Factors
Cardiovascular Risk
Factors, Type 2 Diabetes &
Primary Care Clinic Structure
„
Hemoglobin
Goal:
1University
Blood Pressure
„
Lipids
Goal:
LDL
<= 130/80
Cholesterol
<= 100 mg/dl (if no CAD)
Goal:
of Texas Health Science Center, San Antonio, Texas
2Trinity
A1c
<= 7.0%
„
MD1
Michael L. Parchman,
Amer Kassai, PhD2
Jacqueline A. Pugh, MD1
Raquel L. Romero, MD1
Glucose Control
University, San Antonio, Texas
Self-Care Activities
The Chronic Care Model (CCM)
Diet, Exercise, Glucose Monitoring,
Medication Adherence
„ 5 Stages of Change:
„
Pre
-
contemplation
Contemplation
Preparation
Action
Maintenance:
adherence for 6 months or
more
Purpose
„ Examine
the relationship between
control of CVD risk factors, patient
self-care behaviors, and the presence
of the CCM model elements across a
diverse group of primary care clinic
settings.
Methods
„
20 small autonomous primary care clinics
Solo
practice physicians (n=11)
group practices (n=3)
Community Health Clinic (n=1)
VHA Primary Care OPC (n=2)
City/County Indigent Health Clinics (n=3)
Small
„
Recruited from a Primary Care Practice
Based Research Network (PBRN)
1
Subjects and Data Collection
„
Patients
Organizational Leadership
Community Linkages
„ Self-Management Support
„ Decision Support
„ Delivery System Design
„ Clinical Information Systems
„
30
consecutive presenting pts with an established dx
of type 2 DM
Exit survey: demographics, stage of change for selfcare behaviors, health status (excellent, v. good,
good, fair, poor)
Chart Abstraction: most recent values of A1c, BP and
LDL-cholesterol
„
ACIC Survey: Sub-Scales
Clinicians
„
Assessment
of Chronic Illness Care (ACIC) Survey.
(Bonomi, Wagner et al 2002) (25 items)
Analysis
„
Outcome: All 3 risk factors well controlled (Y/N)
Hierarchical Logistic Model (Random Effects Model)
„
Predictors:
„
Patients
clustered within clinic
Patient:
„
„
„
„
Age (years)
Hispanic ethnicity (Y/N)
Female gender
Maintenance Stage of Change for all 4 behaviors (Y/N)
Results: Patient Characteristics
Age
58.6 (12.93)
Female
51%
Hispanic
57%
Maintenance Stage of change
for all 4 self- care behaviors?
25%
Clinic
„
Sub-scale scores from ACIC survey
Results: CVD Risk Factors
Risk Factor
A1c <= 7.0%
Percent of total (range
by clinic)
43% (20 to 69.7)
BP <= 130/80
49% (0 to 72.7)
LDL <= 100
50% (0 to 73.3)
All 3 well controlled
ACIC Sub-scale Scores
Mean (S.D.)
Orgnzn Leadership
Range*
6.5 (2.3)
2.5 – 10.0
Comm Linkage
7.1 (1.7)
4.3 – 10.7
Self-
6.9 (1.9)
2.8 – 10.3
6.0 (1.8)
2.7 – 9.0
Delivery System
6.7 (2.2)
3.4 – 11.0
Clinical Info System
5.2 (2.4)
0.6 – 10.2
Care Support
Decision Support
13% (0 to 31.3)
*Potential Range of each sub-scale: 0 to 11
2
HLM Model: No Clinic-level Predictors
Patient
Characteristic
HLM: No Patient-level predictors
CCM component
O.R.
95% C.I.
Odds Ratio
1.01
95% C.I.
1.00, 1.02
Org Leader
0.89
0.72, 1.11
Comm Linkage
1.65*
1.31, 2.09
Female
0.66*
0.48, 0.92
Self-
0.97
0.78, 1.21
Hispanic
0.86
0.62, 1.19
Decision Support
1.10
0.75, 1.63
All Maintenance
1.55*
1.09, 2.21
Delivery System
1.38*
1.40, 1.67
Clin Info System
0.58*
0.42, 0.81
Age
HLM Final Model
Predictor
O.R.
95%C.I.
Female
0.59
0.36, 0.98
All Maintenance
1.82
1.08, 4.07
Comm Linkages
1.56
1.23, 1.98
Delivery System
1.47
1.17, 1.86
Clin Info System
0.58
0.44, 0.73
Conclusions
„
Linking clinicians to diabetes specialists
and educators
„ Patient diabetes education resources
„ Coordinates implementation of diabetes
care guidelines with assessment/treatment
by specialists
Control of CVD risk factors among patients
with T2DM is associated with structural
characteristics of primary care clinic:
Community
Linkages
Delivery System Design
Clinical Information Systems
Community Linkages
„
Care Support
Delivery System Design
Practice Team Functioning
„ Practice Team Leadership
„ Appointment System
„ Follow-up
„ Planned Visits for diabetes care
„ Continuity and Coordination of Care
„
3
Clinical Information Systems
„
Inversely associated with CVD risk factor:
Diabetes
registry
to providers
Feedback on performance
Identification of patients needing attention
Patient treatment plans
Reminders
Limitations
Small number of primary care clinics
Cross-sectional data
„ Selection bias of consecutive patients
„
„
Bias
toward worse control of CVD risks
burden of illness
Worse overall health status
Greater
CIS may improve measurement of risk
factors but not efforts to control
„ Implementation of CIS may distract from
risk factor control
„
Current/Future Research*
„
Organizational Intervention in Primary
Care Clinics to improve risk factor control
Primary
care clinics are complex adaptive
systems with non
- linear dynamic behavior
No “one
- size
- fits
- all” approach to improving
risk factors
Facilitation of organizational change with a
focus on inter- d
ependence among agents
See Poster by Leykum et al this afternoon
Acknowledgements
„
Supported by:
Agency
for Healthcare Research and Quality
(Grant #K08 HS013008)
South Texas Health Research Center
Office of Research and Development, Health
Services Research and Development Service,
Department of Veterans Affairs.
The views expressed are those of the authors
and do not necessarily represent the views of
the Department of Veterans Affairs
*Funded by NIH/NIDDK 1 R34 DK067300-01
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