Treatment Intensity and Health Care
Spending Growth among the Elderly
Melinda Beeuwkes Buntin (RAND)
Dana Goldman (RAND)
Baoping Shang (The Urban Institute)
1
Background
•
Rapid growth in overall health care spending and
Medicare spending
•
Factors that might have contributed to health care
spending growth
− Population aging, health insurance and income
− Risk factors such as obesity and smoking, and
chronic conditions and disabilities
− Technologies
− Changes in treatment patterns:
•
Increase in treated disease prevalence (Thorpe
et al. 2005)
2
Research Questions
•
How treatment intensity has contributed to health care
spending growth
− More conditions getting treated
− Each condition getting treated more intensively
3
Data
•
Data: The Medicare Current Beneficiary Survey (MCBS)
1993-2003 and associated Medicare claims
•
Study sample: Medicare (Fee-For-Service) FFS
beneficiaries; 65 years of age or older; Community
dwelling
4
Measurements
•
Health care spending: including Medicare spending,
beneficiary OOP spending and spending by other health
insurance
•
Treatment intensity:
− Number of treated conditions: 0 CCSs; 1-5 CCSs; 5-10
CCSs; 11+ CCSs
− Per capita RVUs
•
Demographics: age, gender, race, education, income,
supplemental coverage, et al.
•
Health status: self-reported disease conditions, functional
status and risk factors
5
Methods
•
Health care spending growth
− Regress per capita health care spending on demographics and
self-reported health status
− Regress per capita health care spending on demographics, selfreported health status and number of treated conditions
− Regress per capita health care spending on demographics, selfreported health status, number of treated conditions and per
capita RVUs
•
Decomposition of change in per capita RVUs
− New services: CPT codes that were not included in 1993 physician
payment schedule
− Existing services:
•
Number of treated beneficiaries receiving services
•
Number of services per treated beneficiaries
•
RVU value updates
6
Descriptive Statistics
Mean (1993) Mean (2003) Difference
Per capita spending (in 2003 $)
6,432
10,142
3,710
Per capita utilization (RVUs)
39.94
72.29
32.35
Age
74.37
75.20
0.83
Male
0.410
0.430
0.019
Self-reported health measures
Heart disease
0.382
0.433
0.051
Diabetes
0.168
0.202
0.034
Cancer
0.191
0.187
-0.004
Lung disease
0.140
0.147
0.007
Stroke
0.100
0.122
0.022
HBP
0.539
0.618
0.079
1 or more ADLs
0.293
0.283
-0.009
3 or more ADLs
0.099
0.093
-0.006
Obesity
0.156
0.225
0.069
Ever smoked
0.605
0.603
-0.002
Died
0.036
0.035
-0.001
Number of CCSs
0 CCSs
0.117
0.070
-0.047
1-5 CCSs
0.273
0.131
-0.142
6-10 CCSs
0.281
0.210
-0.071
11 or more CCSs
0.328
0.589
0.261
N
7894
7485
7
Determinants of Health Care Spending Growth
•
Actual increase in health care spending from 1993-2003:
$3,710
•
Demographics and self-reported health status: $639 or 17%
•
Demographics, self-reported health status and number of
treated conditions: $2,542 or 69%
•
Demographics, self-reported health status, number of treated
conditions and per capita RVUs: $3,448 or 93%
When per capita RVUs are included in the model, the coefficients
on demographics, self-reported health and number of treated
conditions are reduced to close to zero, indicating that
treatment intensity (per capita RVUs) is the direct determinant
of health care spending growth.
8
Per Capita RVU growth
75
70
Per Capita Relative Value Unit
65
60
55
50
45
Actual
40
Using 1993 Schedule with value update
35
30
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
Year
9
Decomposition of Existing Services
Year
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
Total Change
Per Capita RVU for
Relative to 1993
Existing Codes
39.9
0.0
41.2
1.3
42.1
2.1
44.5
4.5
45.9
6.0
46.6
6.7
49.4
9.5
55.3
15.3
57.6
17.6
61.6
21.6
62.8
22.9
Decomposition of Total Change
Percent
# of Services RVU Value
Treated*
Per Treated† Update‡
0.0
0.0
0.0
2.2
0.8
-1.8
4.0
0.7
-2.5
6.1
1.4
-3.0
7.5
0.0
-1.6
7.4
0.7
-1.5
9.3
0.0
0.2
12.5
2.2
0.6
13.6
3.4
0.6
16.4
4.0
1.2
17.6
4.0
1.3
10
Top 25 Codes Contributing to Per Capita RVU Growth
HCPCS % of Total Increase Description
99213
99214
97110
99232
78465
70553
93510
45378
92014
99244
99233
43239
76092
99285
77418
88305
92015
98941
45385
93307
97140
72193
45380
76075
99243
7.63%
6.65%
2.23%
2.18%
2.16%
1.84%
1.73%
1.66%
1.49%
1.38%
1.27%
1.27%
1.25%
1.19%
1.12%
1.08%
1.07%
1.06%
1.00%
0.99%
0.98%
0.91%
0.91%
0.90%
0.86%
Office/Outpatient Visit, Established Patients
Office/Outpatient Visit, Established Patients
Therapeutic Exercises
Subsequent Hospital Care
Heart Image (3D), M ultiple
M agnetic Resonance Imaging of Brain without & with Dye
Left Heart Catheterization
Diagnostic Colonoscopy
Eye Exam & Treatment
Office Consultation
Subsequent Hospital Care
Upper Gastrointestinal Endoscopy, Biopsy
M ammogram, Screening
Emergency Department Visit
Radiation Therapy Delivery, Intensity-M odulated Radiation Therapy
Tissue Exam by Pathologist
Refraction
Chiropractic M anipulation
Lesion Removal Colonoscopy
Echo Exam of Heart
M anual Therapy
Computed Tomography Pelvis with Dye
Colonoscopy and Biopsy
Dual Energy X-ray Absorptiometry, Axial Skeleton Study
Office Consultation
11
Conclusion
•
Demographics and health status only contribute to 17% of the
health care spending growth between 1993 and 2003
•
Treatment intensity is the primary and direct driver of health
care spending growth
•
−
New services
−
Existing services
A limited number of treatments account for a large portion of
the increase in treatment intensity
12