The Massachusetts Health
Insurance Survey (MHIS)
Sharon K. Long
The Urban Institute
June 2010
State Health Research Policy Interest Group
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Why a State-specific Survey?
• Need larger state sample sizes
• Overall and for key population subgroups and
substate geographical areas
• Need information on state-specific insurance and health
care programs
• Need information on more than insurance coverage—
health care access and use, costs, quality, barriers to
care, etc.
• Need more timely access to data to inform policy and
program design
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The Challenge of the
Changing Telephone Environment
• States traditionally relied on random-digit-dial (RDD) surveys of
landline telephones to obtain a sample of state residents
• Rapid increase in cell-phone use and growth of cell-phone-only
households means RDD surveys are missing increasing shares
of state residents
– A recent study estimates 25% of households are now cell-phoneonly (Blumberg and Luke, 2010)
• Evidence that individuals in cell-phone-only households are
quite different from those in households with a landline
telephone
– For example, 29% of adults uninsured in cell-phone-only
households versus 14% in households with a landline telephone
(Blumberg and Luke 2010)
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Strategies for Including
Cell-Phone-Only Households
• Supplement RDD sample with sample of cell-phone
telephone numbers
– Limitations:
• Cell-phone exchanges are not necessarily linked to
geographic areas (numbers move with people)
• Combining the RDD and cell-phone samples is challenging
• Costs much more than RDD survey alone
• Rely on address-based sample frame
– Limitations:
• Accuracy of list of addresses (better in urban areas)
• Has implications for survey mode & questionnaire design
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Massachusetts Health
Insurance Survey (MHIS)
• Sponsored by Massachusetts Division of Health Care
Finance and Policy (DHCFP)
• Began in 1998 with RDD sample
– Small, in-person survey based on area sample conducted in
1998 yielded similar estimate of uninsurance as RDD sample
(7.8% vs. 8.2%)
• Re-evaluated sample frame as part of redesign in 2008
following 2006 health reform legislation
– At that time ~10% of Massachusetts households estimated to
be cell-phone-only, with expectation that the share would
continue to grow rapidly
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MHIS Re-design in 2008
• Combined an RDD-telephone sample and an addressbased (AB) sample
– AB sample based on United States Postal Service Delivery
Sequence File (DSF)
• Continued RDD sample to maintain continuity over time
• Choose not to use supplemental cell-phone sample
because of concerns about identifying cell-phone
numbers used by residents of Massachusetts
– With mobile population, especially younger adults, expect outof-state cell-phone numbers in Massachusetts and
Massachusetts cell-phone numbers in other states
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The New MHIS
• Includes both RDD and AB samples
• Obtain as much contact information as possible for both
samples by matching with external data sources
• Addresses for RDD sample & phone numbers for AB sample
• Offer multiple survey modes to as many as possible--mail,
telephone (call in and call out), and web
RDD Sample
With Known
Address (43%)
AB Sample
Without Known
Address (57%)
With Known Phone
Number (83%)
Without Known Phone
Number (17%)
Web
x
x
x
Mail
x
x
x
Call in to a toll-free
number
x
x
x
Outbound call by
the survey firm
x
x
x
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Characteristics of the 2009 MHIS Sample,
by Survey Mode and Household Telephone Status
Survey Mode
Household Telephone Status
Unknown, 8%
Landline-phone
Only, 13%
Web, 39%
Phone-Inbound, 7%
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Characteristics of the 2009 MHIS Sample,
by Sample Frame and Survey Mode
RDD Sample
AB Sample
Phone-Outbound, 40%
Phone-Inbound, 4%
Phone-Inbound, 8%
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Estimates of Cell-Phone-Only Households in
Massachusetts from the MHIS and the National
Health Interview Survey (NHIS)
20
14.4%
Percent
15
10
12.6%
9.6%
5
0
Estimate based on
2007 NHIS
2008 MHIS
2009 MHIS
Source: NHIS estimates from Blumberg et al. 2009.
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Trade-offs Between
RDD Sample and AB Sample in 2009 MHIS
• Cost per completed interview: $71 vs. $70
• Response rate: 48% vs. 36%
– Continuing to explore ways to increase the response rates
in both the AB- and RDD-samples
• Coverage: AB-sample looked more like the overall
Massachusetts population (based on Census data) than
did the RDD-sample (even without cell-phone-only
households), leading to smaller post-stratification
weights/design effects
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Estimates of the Uninsurance Rate in
Massachusetts from the 2009 MHIS,
by Sample Frame
10
9
8
Percent
7
6
5
4
3.1%
2.8%
2.7%
RDD Sample
AB Sample
Combined Samples
3
2
1
0
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Lessons from Massachusetts
• State survey essential for timely information in a
period of rapid state and national policy
development
• Address-based sample provides affordable strategy
for capturing cell-phone-only and non-telephone
households
• Need more research on effects of survey mode and
strategies to increase response rates
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Next slide is not for my presentation,
but maybe for discussion…
•
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Strategies to Increase the Value of National
Surveys for State-specific Studies
• Increase state and local area sample sizes
• Make state identifiers available outside of
Research Data Center settings
• More geocoding of state and local areas
• Add state program names to health insurance
questions
• Expand survey content
• Make data available in more timely manner and
user-friendly format
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