A recent study, for instance, finds that many veterans lack health insurance.  As summarized in the National Journal:

“About 10 percent of U.S. veterans under the age of 65 lack health insurance and are not being cared for by the Veterans Affairs Department, either, according to a study published on Thursday.

The study estimated that 1.3 million veterans and nearly 950,000 members of their families lack health insurance. These uninsured military families account for 4.8 percent of the 47.3 million uninsured Americans, the Urban Institute and Robert Wood Johnson Foundation reported.”

The share of veterans without health insurance varies widely across states.  According to the study,

“Just four states have uninsurance rates below six percent—Massachusetts, Hawaii,Vermont and North Dakota.  Meanwhile,four states—Louisiana,Oregon,Idaho, and Montana—have uninsurance rates above 14 percent.”

But doesn’t the Department of Veterans Affairs (VA) provide health insurance to all veterans?

It is true that the VA is “the nation’s largest health system and provides health care for many veterans through a system of medical centers, clinics, and other facilities…However, some veterans do not use VA health care services. Eligibility is based on veteran status, service-related disabilities, income level, and other factors, and even within the groups eligible for VA care, other factors, such as their proximity to VA facilities and the cost-sharing requirements, may affect the likelihood
that they seek care in the VA system.”

Source:

• Haley J and Kenney GM. Uninsured Veterans and Family Members: Who Are They and Where Do They Live? Urban Institute, May 2012.

Sources:

• John Bakija, Williams College ”Jobs and Income Growth of Top Earners and the Causes of Changing Income Inequality: Evidence from U.S. Tax Return Data.” November 2010, Working Paper.
• Hat tip: Mother Jones.

Between 2010 and 2011, some things have remained the same.  Healthcare premiums are far outpacing inflation over the medium run and California premiums remain higher than average. Workers at small California firms have to cover a large share of premiums and receive less generous insurance coverage (i.e., deductibles more than $1000).

High-wage firms (66% vs. 42%), firms with few part-time workers (70% vs. 41%) and firms with at least some unionized staff (84% vs. 61%) are more likely to offer health insurance to their workers.

Growth in California health insurance premiums (9.1%) in 2011 fell below the growth rate of the U.S. overall (9.5%). In 2010, the opposite was true. California health insurance premiums rose by 7.5%, but overall U.S. premium growth rose by only 3.0%.

The stereotype that California is the land of managed care holds true. Whereas the national proportion of covered workers enrolled in an HMO declined from 20% to 17% between 2009 and 2011, in California the proportion of covered workers enrolled in an HMO held steady at 54%. Also, although the U.S. overall has seen significant growth in high-deductible health plans (HDHPs) so that 17% of covered workers are enrolled in these plans, in California, only 6% of workers have enrolled in this plan type.

Is the ACA working? The answer is probably no. “Just 32% of small California firms not currently offering health benefits were aware of the small firm tax credit that is part of the Affordable Care Act.”

CHCF 2011 Employer Health Benefits Talking Points

• Since 2002, family premiums rose 153%, more than five times the 29% increase in California’s inflation rate.  In 2010 family premiums also rose by five times inflation since 2002.
• The proportion of California employers offering coverage declined from 73% to 63% in the last two years.
• Annual premiums were higher in California than nationally for individual coverage ($5,970 versus $5,429) and family coverage ($15,724 versus $15,073).
• However, the employer contribution in California is significantly higher than the national average. Employers in California contributed $5,213 annually for single coverage and $11,921 for family coverage.
• Workers at small firms were much more likely to cover at least half of the premium for family coverage than workers at large firms.
• Workers at small firms with a deductible of $1,000 or more increased to 27% from just 7% in 2006.
• Twenty-five percent of California firms either reduced benefits or increased cost sharing for employees in thepast year, while 22% increased employees’ share of the premium (compared to 15% in 2010).
• thirty-six percent of California firms say they are “very” or “somewhat” likely to increase the amount workerspay for premiums in the coming year.

Source: CHCF “California Employer Health Benefits Survey.” December 2011.

The California Health Care Foundation examines the uninsured in California in more detail.  Although Texas has the highest share of individuals uninsured (27.3%), California has the largest number of uninsured individuals in the country (6.9 million) and one of the largest share of (21%).  One of the reasons for this decline is a decrease in the share of firms offering insurance.  The share of non-elderly Californians who obtain their insurance through their job has  declined from 65% in 1987 to 53% in 2010. Part of this decrease has been offset by a rise in the share of Californians covered by Medicaid.

Some other highlights from the CHCF report include:

• Employees in businesses of all sizes are more likely to be uninsured in California than in the United States.
• Nearly one-third of the uninsured in California and the nation have family incomes of $50,000 or more.
• Fifty-three percent of California’s uninsured children are in families where the head of household worked full-time during calendar year 2010, down from 61% in 2008.
• About 60% of the uninsured population are Latino.

Below are two charts displaying the insurance source for Californians in 2010 and 2000.

For more facts and figures, see the CHCF Snapshot, California’s Uninsured, Dec 2011.

Although not discussed in this post, another portion of the Health Care Almanac looks at quality by site of service.  Much of this data comes from Hospital Compare, CMS OASIS data, AHRQ’s National Healthcare Quality Report, and the Dartmouth Atlas.

Today I highlight 3 topics related to clinical quality:

• Cesarean Deliveries
• Infant Mortality
• Cancer Incidence.

More detail is below.

Cesarean Deliveries

Whereas less than one in four live births were delivered via Cesarean in 1999, in 2009, about one in three live births were delivered via Cesarean. The difference between California (33.0%) and the nation (32.9%) is tiny. Both California and the nation as a whole experienced a growth in Cesareans of over 45 percent.

Not surprisingly, two Kaiser Permanente hospitals (Redwood City, South Sacramento) have among lowest rates of Cesareans. However, Sutter David Hospital and San Francisco General (located in my neighborhood) actually have the two lowest Cesarean Delivery rates. The hospital with the worst rate of Cesareans is Los Angeles Community Hospital.

Infant Mortality

Over the past ten years, infant mortality is persistently lower in California than the U.S. Both the U.S. and California have seen an encouraging trend towards lower infant mortality rates over time.

Infant Deaths Per 1,000 Live Births

Cancer Incidence

California generally has lower cancer incidence compared to the U.S. as a whole.  Most notably is the lower incidence of lung cancer.  This observation may be due in part to more strict smoking laws.

Cancer Incidence per 100,000 Population

Source: California Health Care Almanac, “Quality of Care facts and Figures: Clinical Areas.,” October 2011.

Despite the fact that millions of children are uninsured, children’s participation rates in Medicaid/CHIP are increasing. Today I will review the results of an Urban Institute study examining trends in Medicaid participation rates for children.

Data

The authors use data from the 2008 and 2009 American Community Survey (ACS). This large survey data set has replaced the Census long form. The authors use the Integrated Public Use Microdata Series (IPUMS) version of the ACS.

Determining Eligibility

Three main characteristics determine a child’s eligibility: family composition, income, and immigration status.  Medicaid eligibility depends on the family’s income as a share of the federal poverty level (FPL).  The FPL threshold changes based on how many individuals are in the household.  Further, many States restrict Medicaid and CHIP access to citizens or legal residents.  Although survey data often indicate whether the individual is foreign born, the data do not contain information on whether the individual is a citizen, legal resident, temporary resident, or lives in the U.S. illegally.  This paper describes one methodology to impute immigration status from these survey data.

Results

• The share of children without health insurance coverage fell between 2008 and 2009,despite the ongoing economic downturn;
• Nationally, the rate of Medicaid/CHIP participation among children rose by 2.7 percentage points to 84.8 percent and cross-state variation in Medicaid/CHIP participation rates narrowed, as larger improvements occurred on average for states that had the lowest participation rates in 2008;
• Six states (DC, Hawaii, Maine,Massachusetts, Michigan and Vermont) had participation at or above 90.0 percent in 2008 and 2009
• Six states (Florida, Montana, Nevada, North Dakota, Texas and Utah) had participation rates below 80.0 percent in both 2008 and 2009
• Participation gains occurred between 2008 and 2009 for children in each race/ethnicity, language, income and age group examined;

Source: Kenney GM, Lynch V, Haley J, Huntress M, Resnick D and Coyer C. “Coverage Gains for Children,” Urban Institute, RWJF Report, Aug 16, 2011.

• Employer-sponsored group plan: 156.1 million (59.0 percent)
• Insurance bought directly from insurer on individual market: 16.7 million (6.3 percent)
• Medicaid: 44.1 million (16.7 percent)
• Medicare: 7.3 million (2.8 percent)
• Tricare/CHAMPVA: 8.3 million (3.1 percent)
• No Health Insurance: 50.0 (18.9 percent)

Employer-based coverage has dropped from 65.9 percent in 2000 to 55.8 percent in 2009 for children and from 69.3 percent to 60.2 percent for adults under 65.  The advent of CHIP has meant that many more children are now covered by Medicaid (33.8 percent today versus 20.9 percent in 2000) and the uninsurance rate has dropped over the last 10 years from 11.3 percent to 10.0 percent. Medicaid enrollment for adults has also increased, from 6.4 percent of adults to 9.9 percent of adults today. Uninsurance rates, however, have also grown for adults: from 17.2 percent in 2000 to 22.4 in 2009.

Source:

•  Employee Benefit Research Institute “Sources of Health Insurance and Characteristics of the Uninsured: Analysis of the March 2010 Current Population Survey” EBRI Issue Brief #347, September 2010.

• Personal Health Care Expenditures
• Medicare Enrollment
• Medicare Program Payments
• Medicare Cost Sharing
• Medicare Short Stay Hospitals
• Medicare Skilled Nursing Facilities
• Medicare Home Health Agencies
• Medicare Hospices
• Medicare Physician Services
• Medicare Hospital Outpatient Services
• End Stage Renal Disease
• Medicare Managed Care
• Medicaid
• Medicare Part D

There is data available from 2001 to 2010.

“…simple extrapolations of trends observed in the years before Medicare and Medicaid are surprisingly accurate. For example, if one extrapolates the relationship between 1950 and 1960 to the per capita GDP in 2008, the error in predicted per capita NHE in 2008 is 8.6%. Or if one extrapolates the trends defined by the relationship between per capita NHE and per capita GDP in 1929 and 1965 to the per capita GDP in 2008, the error in predicted NHE in 2008 is 11.8%.”

Source:

• Woodward, R. S. and Wang, L. (2011), The Oh-so Straight and Narrow Path: Can the Health Care Expenditure Curve be Bent?. Health Economics. doi: 10.1002/hec.1765

According to Gorina and Kramarow (2011) the results are mixed.  The authors examine the strengths and limitations of using CMS’s CCW algorithm with Medicare claims data to identify chronic conditions in older persons.  Their methodology is as follows:

“Records from the NHANES I Epidemiologic Follow-up Study (NHEFS), including data from questionnaires, physical examinations, medical facility records, and death certificates, have been linked to Medicare claims records. We selected five conditions common among older persons: diabetes, ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), dementia, and arthritis. We compared diagnoses for these five conditions derived from the two data sources (NHEFS and Medicare claims using the CCW algorithm).”

The authors identified the person as having the chronic disease if either i) the patient self-reported having the chronic disease or ii) the ICD code was listed in the patient’s medical records.

The percent of preexisting NHEFS cases identified during the CCW reference period for each of the 5 diseases was:

• Diabetes: 68.6%
• IHD: 62.9%
• Dementia: 39.3%
• COPD: 24.4%
• Arthritis: 17.0%

The references period the CCW uses to identify these diseases were 3 years for dementia, 1 year for COPD, and 2 years for the other three illnesses.

The authors find that the CCW is good at detecting chronic illnesses when these illnesses require frequent visits to the doctor.  This is why CCW performs well in identifying IHD, but not identifying arthritis, a disease where patients may visit the doctor infrequently for this illness.

The paper does have some drawbacks.  First, the authors do not examine the CCW’s specificity (the share of patients without the chronic condition diagnosis that the CCW correctly identifies as not having the disease.  Second, patient self-reported disease may be unreliable.  Patients with sore hands may report having arthritis when this may not in fact be the true cause of their ailment.  The authors could have considered how well the CCW performed in the case where the NHEFS requirement was both a self-report and an ICD code in the patient’s records.  Finally, the NHEFS sample that is linked to Medicare records is fairly small.

Nevertheless, the article does make a good point: researchers should not blindly use the CCW without fully understanding how the disease cohorts are created.

• Gorina, Y. and Kramarow, E. A. (2011), Identifying Chronic Conditions in Medicare Claims Data: Evaluating the Chronic Condition Data Warehouse Algorithm. Health Services Research, 46: no. doi: 10.1111/j.1475-6773.2011.01277.x