How do Medicaid, Medicare, and Commercial
Insurance Vary in Community-Level Performance?
Using Claims Data from the
Wisconsin Health Information Organization (WHIO)
to Assess Variation in Population Health Processes
Donna Friedsam, Daphne Kuo, and Kristen Voskuil
UW Population Health Institute
January 13, 2012
Background
 WHIO received Medicare data from the Dartmouth Atlas/Brookings
Institute collaboration, with support from the Markel Foundation, to
support its understanding of variation among various markets in payer
performance.
 UW Population Health Institute conducted exploratory analyses to
determine the utility of the Medicare data provided in aggregate at the
county level.
• Dartmouth (Medicare)
• Ingenix (Commercial and Medicaid)
Analyses Conducted
1. By County, along process measures for diabetes quality:
HbA1c, LDL annual, annual retinopathy exam.
2. For three service areas participating in pilot projects for
the Partnership for Health Care Payment Reform (PHPR):
Three process measures and the composite measure, by
payer and for all payers.
3. Factors Associated with county variation in diabetic care
measures: health care, socioeconomic status, and social
integration
1. Diabetes Process Measures by County
Percent of persons, by county, in each payer group receiving the
recommended tests – HbA1c and LDL tests – and the difference in
rates between the payers – Commercial, Medicaid, and Medicare.
Analysis of Variation from County Mean, by Payer
• Payer (COM, MCR, MCD) variation, by county, from the county
mean for HbA1c and LdL testing
• Counties performing outside the bounds of one standard deviation
above (better) or below (worse) than the overall mean of all
counties.
• Beyond the zone of standard deviation indicate performance either
significantly above or significantly below the mean for all counties
on that performance measure.
Summary of Findings
 For nearly all counties, Medicaid shows significantly lower performance than
Commercial and Medicare in these counties.
 Medicaid statewide performs approximately 35% lower than Commercial and
Medicare on LDL testing.
 Medicaid statewide performs approximately 30% lower than Commercial and
Medicare on HbA1c testing.
 The performance of Commercial and Medicare are statistically similar in most
counties, except
 In Jefferson, Juneau, Kenosha, Racine and Sauk Counties, Medicare performance
for LDL testing significantly outpaces Commercial payer performance.
 In Kenosha, Racine, and Sauk Counties, Medicare performance of HbA1c testing
significantly outpaces Commercial payer performance.
County Performance Relative to
Overall Mean for All Counties, Medicaid
Counties Performing Above Overall County Mean for Medicaid
HbA1c (County Mean = 59%)
LDL (County Mean = 47%)
Door
Door
Langlade
Langlade
Milwaukee
Richland
Oneida
Shawano
Polk
Portage
Price
Richland
Waushara
Counties Performing Below Overall County Mean for Medicaid
HbA1c (County Mean = 59%)
LDL (County Mean = 47%)
Green
Green
Iowa
Green Lake
Kenosha
Iowa
LaCrosse
Jackson
Monroe
LaCrosse
Sauk
Monroe
Sheboygan
Sauk
Trempeleau
Trempeleau
Vernon
Composite, All-Payer Variation by County
on Diabetes Testing Performance
• Diabetes tests – HbA1c, LDL, and retinopathy
• All-payer basis (Commercial, Medicare, and Medicaid)
• Weighted to adjust for varying composition of payer groups in
each county
2. Payment Reform Service Areas
Three service areas participating in the pilot
projects for the Partnership for Health Care
Payment Reform (PHPR).
Defined service areas in two levels:
1. Counties named by the providers participating in the
PHPR, and
2. As derived from the zip codes associated with the
Hospital Service Area within the Dartmouth Atlas.
Payer Performance in Each Service Area
Relative to Statewide Rates
Commercial:
 Both NEWHVN and Monroe exceed the all payer individual
test rates and composite rate.
 Milwaukee trails the statewide rate for each individual test
rate and for the composite rate.
Medicaid:
 Monroe substantial trails the statewide rate for HbA1c and
LDL testing and for the composite rate
All Payer:
 Only minor variations appear in the comparison of service
area all-payer rates to the statewide rates, particularly
once the service area rates are weighted to correct for
differing payer composition among the population.
Summary of Quality Measure Compliance for
Selected Diabetes Measures
by County and Product Category, Year Ending
9/30/2009, Patients within last 12 months
Table 2c: Commercial
HbA1c
PRODUCT
COUNTY
COM
Oconto
COM
Kewaunee
COM
NEWHVN
COM
Calumet
COM
DEN (N)
LDL
All Tests
Composite
Eye exam
NUM
Rate
NUM
Rate
NUM
Rate
Rate
199
181
91%
168
84%
70
35%
70%
123
119
97%
106
86%
46
37%
73%
1,454
1,322
91%
1,208
0.83
632
43%
72%
448
405
90%
379
85%
209
47%
74%
Outagamie
823
753
91%
713
87%
387
47%
75%
COM
Shawano
217
201
93%
192
88%
88
41%
74%
COM
Waupaca
382
358
94%
351
92%
199
52%
79%
COM
Waushara
140
134
96%
118
84%
57
41%
74%
COM
Winnebago
638
593
93%
572
90%
293
46%
76%
COM
NEWHVN-out
2,648
2,444
92%
2,325
0.88
1,233
47%
76%
COM
NEWHVN-TOTAL
4,102
3,766
92%
3,533
0.86
1,865
45%
74%
COM
Milwaukee
6,801
5,851
86%
5,387
79%
2,532
37%
67%
COM
Waukesha
2,839
2,475
87%
2,287
81%
1,161
41%
70%
COM
IPN
9,640
8,326
86%
7,674
0.80
3,693
38%
68%
COM
Kenosha
866
643
74%
618
71%
236
27%
58%
COM
Ozaukee
719
622
87%
577
80%
280
39%
69%
COM
Racine
1,246
912
73%
860
69%
363
29%
57%
COM
IPN-out
2,831
2,177
77%
2,055
0.73
879
31%
60%
COM
IPN-TOTAL
12,471
10,503
84%
9,729
0.78
4,572
37%
66%
COM
Green/Monroe
298
275
92%
258
87%
148
50%
76%
COM
Statewide
37,401
32,663
87%
30,093
80%
14,701
39%
69%
Table 2d: Medicaid
HbA1c
PRODUCT
COUNTY
LDL
All Tests
Composite
Eye exam
DEN (N)
NUM
Rate
NUM
Rate
NUM
Rate
Rate
184
114
62%
97
53%
76
41%
52%
80
45
56%
34
43%
33
41%
47%
MCD
Oconto
MCD
Kewaunee
MCD
NEWHVN
1,538
932
61%
797
52%
714
0.46
53%
MCD
Calumet
321
175
55%
156
49%
155
48%
50%
MCD
Outagamie
514
324
63%
272
53%
221
43%
53%
MCD
Shawano
215
142
66%
126
59%
95
44%
56%
MCD
Waupaca
270
147
54%
135
50%
132
49%
51%
MCD
Waushara
174
121
70%
91
52%
92
53%
58%
MCD
Winnebago
631
353
56%
301
48%
295
47%
50%
MCD
NEWHVN-out
2,125
1,262
59%
1,081
51%
990
0.47
52%
MCD
NEWHVN-TOTAL
3,663
2,194
60%
1,878
51%
1,704
0.47
53%
MCD
Milwaukee
10,891
7,332
67%
5,783
53%
4,364
40%
53%
MCD
Waukesha
756
423
56%
354
47%
338
45%
49%
MCD
IPN
11,647
7,755
67%
6,137
53%
4,702
40%
53%
MCD
Kenosha
884
421
48%
389
44%
345
39%
44%
MCD
Ozaukee
162
100
62%
80
49%
59
36%
49%
MCD
Racine
1,179
654
55%
554
47%
418
35%
46%
MCD
IPN-out
2,225
1,175
53%
1,023
46%
822
0.37
45%
MCD
IPN-TOTAL
13,872
8,930
64%
7,160
52%
5,524
0.40
52%
MCD
Green/Monroe
154
71
46%
61
40%
86
56%
47%
MCD
Statewide`
32,086
19,497
61%
15,731
49%
14,632
46%
52%
Table 2e: Medicare
HbA1c
Product
County
MCR
LDL
All Tests
Composite
Eye exam
DEN (N)
NUM
Rate
NUM
Rate
NUM
Rate
Rate
Brown
5,410
4,783
88.41
4,388
81.11
4,031
74.52
81%
MCR
Oconto
1,350
1,144
84.76
1,051
77.82
915
67.78
77%
MCR
Kewaunee
605
515
85.16
501
82.79
374
61.76
77%
MCR
NEWHVN
7,365
6,442
87%
5,940
81%
5,320
72%
80%
MCR
Calumet
530
458
86.37
450
84.90
382
71.99
81%
MCR
Outagamie
3,530
3,209
90.92
3,076
87.14
2,691
76.22
85%
MCR
Shawano
1,120
990
88.37
942
84.12
806
71.93
81%
MCR
Waupaca
1,770
1,551
87.64
1,580
89.24
1,368
77.27
85%
MCR
Waushara
1,225
1,030
84.09
923
75.34
788
64.36
75%
MCR
Winnebago
3,270
2,867
87.68
2,725
83.32
2,261
69.13
80%
MCR
NEWHVN-out
11,445
10,105
88%
9,695
85%
8,294
72%
82%
MCR
NEWHVN-TOTAL
18,810
16,548
88%
15,635
83%
13,614
72%
81%
MCR
Milwaukee
26,910
23,064
85.71
21,273
79.05
17,755
65.98
77%
MCR
Waukesha
9,270
8,150
87.92
7,784
83.97
6,875
74.16
82%
MCR
IPN
36,180
31,214
86%
29,057
80%
24,630
68%
78%
MCR
Kenosha
4,660
4,077
87.50
3,962
85.03
2,918
62.61
78%
MCR
Ozaukee
2,185
1,910
87.42
1,781
81.49
1,572
71.92
80%
MCR
Racine
6,310
5,468
86.65
5,107
80.93
4,088
64.79
77%
MCR
IPN-out
13,155
11,455
87%
10,850
82%
8,577
65%
78%
MCR
IPN-TOTAL
49,335
42,669
86%
39,907
81%
33,207
67%
78%
MCR
Green
1,240
1,131
91.21
1,091
87.95
806
64.97
81%
MCR
Statewide
146,815
129,231
88%
120,159
82%
104,398
71%
80%
Table 2f: All Payers Composite
All Tests
Composite
Weighted
NUM
Rate
Weighted
NUM
Rate
Weighted
Rate
Weighted
Brown
7,816
6,578
84%
86%
5,988
77%
78%
5,152
66%
68%
76%
76%
Oconto
1,733
1,439
83%
83%
1,316
76%
76%
1,061
61%
61%
73%
72%
808
679
84%
84%
641
79%
79%
453
56%
57%
73%
72%
NEWHVN
10,357
8,696
84%
85%
7,945
77%
78%
6,666
64%
66%
75%
75%
Calumet
1,299
1,038
80%
84%
985
76%
81%
746
57%
67%
71%
75%
Outagamie
4,867
4,286
88%
88%
4,061
83%
83%
3,299
68%
69%
80%
78%
Shawano
1,552
1,333
86%
87%
1,260
81%
82%
989
64%
65%
77%
76%
Waupaca
2,422
2,056
85%
85%
2,066
85%
85%
1,699
70%
71%
80%
79%
Waushara
1,539
1,285
84%
85%
1,132
74%
74%
937
61%
60%
73%
72%
Winnebago
4,539
3,813
84%
85%
3,598
79%
80%
2,849
63%
64%
75%
75%
NEWHVN-out
16,218
13,811
85%
86%
13,101
81%
81%
10,517
65%
67%
77%
76%
NEWHVN-TOTAL
26,575
22,508
85%
86%
21,046
79%
80%
17,183
65%
67%
76%
76%
Milwaukee
44,602
36,247
81%
84%
32,443
73%
76%
24,651
55%
60%
70%
72%
Waukesha
12,865
11,048
86%
84%
10,425
81%
79%
8,374
65%
67%
77%
75%
IPN
County
Rate
Eye exam
Num
LdL
Den (N)
HbA1c
Kewaunee
57,467
47,295
82%
84%
42,868
75%
77%
33,025
57%
62%
71%
73%
Kenosha
6,410
5,141
80%
81%
4,969
78%
78%
3,499
55%
56%
71%
70%
Ozaukee
3,066
2,632
86%
84%
2,438
80%
78%
1,911
62%
64%
76%
74%
Racine
8,735
7,034
81%
81%
6,521
75%
75%
4,869
56%
58%
70%
69%
IPN-out
18,211
14,807
81%
81%
13,928
76%
77%
10,278
56%
58%
71%
70%
IPN-TOTAL
75,678
62,102
82%
84%
56,796
75%
77%
43,303
57%
61%
71%
72%
WI, Green
1,692
1,477
87%
86%
1,410
83%
82%
1,040
61%
62%
77%
75%
Statewide
216,302
181,391
84%
85%
165,983
77%
78%
133,731
62%
65%
74%
74%
3. Factors Associated with County Variation in
Diabetic Care Measures
Health Care, Socioeconomic Status, and Social Integration
Daphne Kuo, PhD
Research Questions and Design
• Characteristics associated with compliance with
diabetic care measures
•
•
•
•
Economic resources
Health care
Healthy places
Social integration
• Analytical issues: structural equation models
• All characteristics correlated with one another
• A global view of diabetic cares: all three elements together
• Four different health care payers (commercial plans,
Medicaid, Medicare, or No Insurance)
Figure 1. County characteristics and variation in diabetes care measures
% Black
% Hispanic
% Male
% Age 45 & +
% single female hh
Commercial rate
HbA1c
Medicaid rate
Medicare rate
% public assistance
% family < poverty
% rural
% high school grad
% diabetics
% obesity
% smoking
Commercial rate
Blood
Lipid
Medicaid rate
Medicare rate
% heavy drinking
% English
% PCP
Segregation
Recreation
% teen birth
Healthy food
% violent crime
Commercial rate
EyeExam
Medicaid rate
Medicare rate
Results
% Black
% Hispanic
% Male
% Age 45 & +
% single female hh
Commercial rate
HbA1c
Medicare rate
% public assistance
% family income
% rural
% high school grad
% diabetics
% obesity
% smoking
% heavy drinking
% English
% PCP
degree segregation
Recreation
% teen birth
% Healthy food
% Crime
Medicaid rate
Commercial rate
Blood
Lipid
Medicaid rate
Medicare rate
Commercial rate
EyeExam
Medicaid rate
Medicare rate
Conclusions
 Proportion of minority is not the issue, but how
integrated into the community.
 Effective explanations for county variations in
diabetic care measures
 Primary care
 Social integration
 SES
 Additional data needs
 Analysis of role of personal responsibility requires
individual level data
 Characteristics of providers and medical facilities
Further Information
Donna Friedsam, MPH
Researcher and Health Policy Programs Director
UW Population Health Institute
608.263.4881
[email protected]
http://uwphi.pophealth.wisc.edu
http://www.evidencebasedhealthpolicy.org