Quality and Use in Managed Care Sarah Hudson Scholle

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Quality and Use
in Managed Care
Sarah Hudson Scholle
Academy Health Annual Research Meeting
Seattle June 26, 2006
Background
• Health care costs continue to increase
• Greater emphasis on demonstrating value in
health care.
• Evidence about the relationship between
utilization/ costs of care and quality is limited.
– Studies in ambulatory settings show no relationship
– A recent Medicare study found higher spending was
correlated with poorer quality of care.
Purpose
• To examine the relationship between quality
and utilization of health care among
commercial health plan
– correlation of HEDIS® 3.0 effectiveness measures
with outpatient and inpatient utilization
– regression analyses controlling for patient and
plan covariates
Data Sources
• NCQA’s Commercial HEDIS/CAHPS data
set
• Includes plans that do not allow public
reporting of data
• Reporting year 2003 (Measurement year
2002)
Study Group
316 Commercial Plans submit data in 2003
62 (excluded: 20%)
29 No data on any of the Dependent variables
10 No data on the patient characteristics
23 Missing 4 or more of the 11 quality measures
254 included in analysis
Represents 83% of
commercial
managed care enrollees
Utilization Measures
• Limited to adults age 20-64
• Excluded behavioral health, maternity, &
surgical care
• Measures
–
–
–
–
Outpatient visits per 1,000 members per year
Emergency visits per 1,000 members per year
Medical discharges per 1,000 members per year
Inpatient days per 1,000 members per year
Quality Indicators and Composite
Measure
Mean, SD
Advising Smokers to Quit
67.8%, 5.1%
Asthma medication management
68.8%, 5.6%
Beta Blocker After Heart Attack
93.8%, 7.6%
Blood Pressure control
59.1%, 7.7%
Breast Cancer Screening
75.9%, 5.2%
LDL-C control
62.6%, 12.0%
Diabetic HbA1c control
67.8%, 11.5%
Acute phase antidepressant treatment
59.9%, 7.8%
Flu Shots
44.5%, 7.5%
Follow-up after Hosp for Mental Illness
73.6%, 9.8%
QUALITY COMPOSITE
67.4%, 5.0%
Covariates
• Plan Characteristics
– Public reporting, Profit status, type of plan (HMO
vs POS vs both), Geographic location
• Member Characteristics
– Age and gender distribution
– CAHPS data on race, education and health status
Quality Composite
Correlation: Quality Composite
and Outpatient Visits
0.85
0.75
0.65
0.55
0.45
1000
3000
5000
Outpatient Visits
Quality Composite
Correlation: Quality Composite
and Hospital Discharges
0.85
0.75
0.65
0.55
0.45
0
10
20
30
Hospital Discharges
40
Correlations between Quality and Utilization
Smoking Cessation
Outpt
Visits
ER
visits
Medical
Discharges
Hospital
Days
0.22***
-0.12
-0.26***
-0.22**
-0.24***
-0.26***
-0.30***
Asthma Medication Mgmt 0.19**
Beta Blocker after MI
0.09
0.00
-0.21***
-0.20**
Blood Pressure Control
0.08
0.01
-0.06
-0.04
Breast Cancer Screening
0.20**
-0.07
-0.28***
-0.30***
Cholesterol LDL Control
0.12
-0.20**
-0.17**
-0.18**
Diabetic HbA1c Control
0.10
-0.10
-0.20**
-0.23***
Acute Phase
Antidepressant Tx
0.01
0.22***
-0.46***
-0.42***
Flu Shots
0.09
-0.23***
-0.29***
-0.30***
MH Inpt Follow-up(30)
0.15*
-0.06
-0.17**
-0.16*
Quality Composite
0.19*
-0.18**
-0.36***
-0.35***
Regression Results:
Relationship of Quality to Utilization
Dependent Measure
Estimate P-value
Emergency visits
-0.4735
0.3677
Outpatient Visits
0.5702
0.1275
Hospital Admissions
-0.6900
0.0365
Hospital Days
-0.7781
0.0207
Based on loglinear regressions using Poisson distributions.
Covariates include plan region and profit status as well as plan
rates of patient covariates from CAHPS data - age, gender,
minority status and health status.
Summary of Findings
• Positive Correlation between Quality and
Access: Plans with higher quality score have a
higher proportion of members with at least one
visit.
• Negative Correlation between Quality and
Hospital Use: Plans with higher quality score
have lower average admissions and hospital
days.
• There is no correlation between quality and the
outpatient visit rate.
Discussion
• Findings are consistent with prior
research focusing on the Medicare
population.
• Impact is important:
– A 5% improvement in quality is related to a 4%
decrease in hospital days.
– This translates to $12 per member per month
(based on a conservative estimate of hospital
costs of $3,000 per inpatient day).
Limitations
• This cross-sectional study cannot address
causality.
• Measurement of quality is limited to available
measures.
• Using CAHPS data as a proxy for population
socioeconomic and health status is an indirect
method of adjustment.
• Controlling for health plan region may not be
sufficient for disentangling impact of supply on
utilization.
What mechanism links quality to
utilization and costs?
• Quality reduces unnecessary
hospitalization.
• Quality reflects better data collection.
• Quality is a marker of better organization
for managing hospitalization days and
HEDIS quality efforts.
Implications
• The IOM envisioned restructuring the health
care system to address both quality and costs
simultaneously.
• These data give hope that improvements in
effectiveness of care may reduce both the
human costs of poor care and their financial
implications as well.
• More research is needed on the relationship
between quality and utilization and potential
mechanisms affecting that relationship.
For More Information…
Sarah Hudson Scholle
[email protected] ncqa.org
202-955-1726
www.ncqa.org
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