Health Inclusive Poverty Measure Estimates 

in the United States: 2022

John Creamer

U.S Census Bureau

2023 FCSM Research and Policy Conference

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This paper is released to inform interested parties of ongoing research and to encourage discussion of work in progress. Any views expressed are those of the author 

and not those of the U.S. Census Bureau. Any errors or omissions are the sole responsibility of the author. All comparative statements have undergone statistical 

testing, and, unless otherwise noted, all comparisons are statistically significant at the 10 percent significance level. All data are subject to error arising from a variety 

of sources, including sampling error, non-sampling error, modeling error, and any other sources of error. For further information on data collection, standards, and 

accuracy, refer to https://www.census.gov/programs-surveys/cps/technical-documentation.html. The Census Bureau has reviewed this data product to ensure 

appropriate access, use, and disclosure avoidance protection of the confidential source data used to produce this product (Disclosure Review Board (DRB) approval 

number: CBDRB-FY24-SEHSD003-005.)
Background

• Current poverty measures (official and Supplemental Poverty Measure 

[SPM]) do not account for the resources individuals receive from the 

provision of Medicare and Medicaid and employer’s offsetting health 

insurance premiums.

• The SPM accounts for medical out-of-pocket expenses (MOOP) by deducting reported 

MOOP from resources.

• The Health Inclusive Poverty Measure (HIPM) adapts the SPM to capture 

these benefits and needs in poverty rates (Korenman and Remler 2016). 

• Creamer (2023) provides more information on implementation and 

historical time series. 

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Main Findings

• In 2022, the HIPM rate was 14.0 percent, 1.6 percentage points higher than the 

SPM. 

• HIPM and SPM poverty classification is the same for about 97 percent of the 

population in the 2023 ASEC.

• For those that change, about 80 percent of cases are in HIPM poverty and not SPM poverty (7.3 

million).

• The majority of individuals who are in HIPM poverty and not SPM poverty are uninsured.

• Results support feasibility of annual production under current timelines.

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Background

• The SPM MOOP deduction deducts premium MOOP (including Medicare premiums), 

non-premium MOOP, and over-the-counter expenses from resources.

• Captures implicit impact of health insurance through premium MOOP offsetting other costs. 

• Individuals who defer care may appear better off due to low reported MOOP. 

• Historically, estimating a value of health insurance has been complex. 

• Methodological challenges. 

• Data availability challenges with employer contributions to health insurance and Medicaid.

• Health needs are individual, and individuals value insurance differently. 

• In 2014, the implementation of the ACA set a benchmark plan that can be purchased 

across different geographical areas.

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SPM vs. HIPM: Needs

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SPM HIPM

Non-Health Component Based on recent food, clothing, shelter, utilities, telephone and 

internet expenses

Health Component none

Benchmark health plan: 

• Private Insurance and 

Medicaid: Second-lowest cost 

Silver plan

• Medicare: Avg. government 

contribution to Medicare 

($15,727 in 2022; Centers for 

Medicare and Medicaid 

Services 2023)
SPM vs. HIPM: Resources

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SPM HIPM

Non-Health Component Sum of cash and non-cash income minus taxes (plus tax credits), 

work expenses, child support paid

Health Component

• Subtracts MOOP from nonmedical resources

• Adds net health benefits 

(value of benchmark plan 

minus premium MOOP) 

• Zero value for uninsured 

and unsubsidized cov.

• Subtracts capped nonpremium MOOP
Data

• 2023 Current Population Survey Annual Social and Economic Supplement (CPS ASEC).

• 2022 Center for Medicare and Medicaid Services (CMS) Marketplace and State-Based

Marketplace Public Use Files and Medicare Prescription Drug Information Landscape

Files.

• Rating Areas.

• Second-lowest cost Silver plan premiums.

• Out-of-pocket maximums.

• Health plan data linked to the CPS ASEC at the county level where available, followed by

metropolitan area and then state level.

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Findings

• HIPM rates are higher than SPM rates for the overall population, but 

lower for those 65 and older.

• Differences vary by selected health insurance type.

• About 97 percent of the population had the same poverty status 

across the two measures.

• Majority of individuals who are HIPM poor and not SPM poor were uninsured.

• Those who are SPM poor and not HIPM poor were more likely to only have 

non-premium MOOP capped than those who are HIPM poor but not SPM 

poor or those whose poverty status did not change. 

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Next Steps

• Updating historical series to refine original method and implement 

uncompensated care intermediate fix. 

• Future research topics:

• Research on the impact of adding values of uncompensated care for the 

uninsured. 

• Focus on understanding geographic differences in SPM and HIPM rates. 

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Thanks!

John Creamer

SPM Team Lead, Poverty Statistics Branch

Social, Economic, and Housing Statistics Division

U.S. Census Bureau

Contact: john.creamer@census.gov

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