yyyyy yyyyy Report 13

Projecting National Medical

Expenditure Survey Data:

A Framework for MEPS Projections

Methodology Methodology 

U.S. Department of Health and Human Services

Public Health Service

Agency for Healthcare Research and Quality

Agency for Healthcare Research and Quality
  yyyy yyyy

Abstract

This report from the Agency for Healthcare

Research and Quality (AHRQ) describes the procedures

used to project data from the 1987 National Medical

Expenditure Survey (NMES) household survey to future

years. The 1987 NMES, sponsored by the National

Center for Health Services Research, AHRQ’s

predecessor agency, provided extensive information on

health expenditures by or on behalf of American families

and individuals, the financing of these expenditures, and

use of services. NMES data have been “aged” based on

more recent household population estimates from

government sources and data from the National Health

Accounts of the Centers for Medicare & Medicaid

Services. The NMES data were released in public use

data sets projected to the years 1996 and 2005. This

report describes the categories of expenditures and

payment sources in the projected data, the population

and expenditure reweighting procedures, and alignment

of the 1987 NMES to the 1987 National Health

Accounts.

Suggested citation

Moeller JF, Cohen SB, Hock E, et al. Projecting National Medical

Expenditure Survey data: a framework for MEPS projections.

Rockville (MD):Agency for Healthcare Research and Quality; 2002.

MEPS Methodology Report No. 13.AHRQ Pub. No. 02-0009.

Health Care Information and Electronic Ordering

Through the AHRQ Web Site

The Agency for Healthcare Research and Quality

Web site—http://www.ahrq.gov/—makes practical,

science-based health care information available in

one convenient place.

Buttons correspond to major categories of Web

site information, including funding opportunities,

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information, consumer health, and data.

The Web site features an Electronic Catalog to the

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working days.

http://www.ahrq.gov/ http://www.ahrq.gov/
  yyyyy yyyyy Report 13

Projecting National Medical

Expenditure Survey Data:

A Framework for MEPS Projections

Methodology Methodology 

AHRQ Pub. No. 02-0009

February 2002

U.S. Department of Health and Human Services

Public Health Service

Agency for Healthcare Research and Quality
The Medical Expenditure Panel

Survey (MEPS)

Background

The Medical Expenditure Panel Survey (MEPS) is

conducted to provide nationally representative estimates

of health care use, expenditures, sources of payment,

and insurance coverage for the U.S. civilian

noninstitutionalized population. MEPS also includes a

nationally representative survey of nursing homes and

their residents. MEPS is cosponsored by the Agency for

Healthcare Research and Quality (AHRQ), formerly the

Agency for Health Care Policy and Research, and the

National Center for Health Statistics (NCHS).

MEPS comprises four component surveys: the

Household Component (HC), the Medical Provider

Component (MPC), the Insurance Component (IC), and

the Nursing Home Component (NHC). The HC is the

core survey, and it forms the basis for the MPC sample

and part of the IC sample. The separate NHC sample

supplements the other MEPS components. Together

these surveys yield comprehensive data that provide

national estimates of the level and distribution of health

care use and expenditures, support health services

research, and can be used to assess health care policy

implications.

MEPS is the third in a series of national probability

surveys conducted by AHRQ on the financing and use

of medical care in the United States. The National

Medical Care Expenditure Survey (NMCES) was

conducted in 1977, the National Medical Expenditure

Survey (NMES) in 1987. Beginning in 1996, MEPS

continues this series with design enhancements and

efficiencies that provide a more current data resource to

capture the changing dynamics of the health care

delivery and insurance system.

The design efficiencies incorporated into MEPS are

in accordance with the Department of Health and

Human Services (DHHS) Survey Integration Plan of

June 1995, which focused on consolidating DHHS

surveys, achieving cost efficiencies, reducing respondent

burden, and enhancing analytical capacities. To

accommodate these goals, new MEPS design features

include linkage with the National Health Interview

Survey (NHIS), from which the sample for the MEPS

HC is drawn, and enhanced longitudinal data collection

for core survey components. The MEPS HC augments

NHIS by selecting a sample of NHIS respondents,

collecting additional data on their health care

expenditures, and linking these data with additional

information collected from the respondents’ medical

providers, employers, and insurance providers.

Household Component

The MEPS HC, a nationally representative survey

of the U.S. civilian noninstitutionalized population,

collects medical expenditure data at both the person and

household levels. The HC collects detailed data on

demographic characteristics, health conditions, health

status, use of medical care services, charges and

payments, access to care, satisfaction with care, health

insurance coverage, income, and employment.

The HC uses an overlapping panel design in which

data are collected through a preliminary contact

followed by a series of five rounds of interviews over a

21⁄

2-year period. Using computer-assisted personal

interviewing (CAPI) technology, data on medical

expenditures and use for 2 calendar years are collected

from each household. This series of data collection

rounds is launched each subsequent year on a new

sample of households to provide overlapping panels of

survey data and, when combined with other ongoing

panels, will provide continuous and current estimates of

health care expenditures.

The sampling frame for the MEPS HC is drawn

from respondents to NHIS, conducted by NCHS. NHIS

provides a nationally representative sample of the U.S.

civilian noninstitutionalized population, with

oversampling of Hispanics and blacks.

Medical Provider Component

The MEPS MPC supplements and validates

information on medical care events reported in the

MEPS HC by contacting medical providers and

pharmacies identified by household respondents. The

MPC sample includes all hospitals, hospital physicians,

home health agencies, and pharmacies reported in the

HC. Also included in the MPC are all office-based

physicians: 

• Providing care for HC respondents receiving

Medicaid.

ii
iii

• Associated with a 75-percent sample of households

receiving care through an HMO (health maintenance

organization) or managed care plan.

• Associated with a 25-percent sample of the

remaining households.

Data are collected on medical and financial

characteristics of medical and pharmacy events reported

by HC respondents, including:

• Diagnoses coded according to ICD-9 (9th Revision,

International Classification of Diseases) and DSMIV (Fourth Edition, Diagnostic and Statistical

Manual of Mental Disorders).

• Physician procedure codes classified by CPT-4

(Current Procedural Terminology, Version 4).

• Inpatient stay codes classified by DRG (diagnosisrelated group).

• Prescriptions coded by national drug code (NDC),

medication names, strength, and quantity dispensed.

• Charges, payments, and the reasons for any

difference between charges and payments.

The MPC is conducted through telephone

interviews and mailed survey materials.

Insurance Component

The MEPS IC collects data on health insurance

plans obtained through private and public-sector

employers. Data obtained in the IC include the number

and types of private insurance plans offered, benefits

associated with these plans, premiums, contributions by

employers and employees, and employer characteristics.

Establishments participating in the MEPS IC are

selected through three sampling frames:

• A list of employers or other insurance providers

identified by MEPS HC respondents who report

having private health insurance at the Round 1

interview.

• A Bureau of the Census list frame of private-sector

business establishments.

• The Census of Governments from the Bureau of the

Census.

To provide an integrated picture of health insurance,

data collected from the first sampling frame (employers

and other insurance providers) are linked back to data

provided by the MEPS HC respondents. Data from the

other three sampling frames are collected to provide

annual national and State estimates of the supply of

private health insurance available to American workers

and to evaluate policy issues pertaining to health

insurance. Beginning in 2000, national estimates of

employer contributions to group health insurance from

the MEPS IC are being used in the computation of

Gross Domestic Product (GDP) by the Bureau of

Economic Analysis.

The MEPS IC is an annual panel survey. Data are

collected from the selected organizations through a

prescreening telephone interview, a mailed

questionnaire, and a telephone followup for

nonrespondents.

Nursing Home Component

The 1996 MEPS NHC was a survey of nursing

homes and persons residing in or admitted to nursing

homes at any time during calendar year 1996. The NHC

gathered information on the demographic

characteristics, residence history, health and functional

status, use of services, use of prescription medications,

and health care expenditures of nursing home residents.

Nursing home administrators and designated staff also

provided information on facility size, ownership,

certification status, services provided, revenues and

expenses, and other facility characteristics. Data on the

income, assets, family relationships, and caregiving

services for sampled nursing home residents were

obtained from next-of-kin or other knowledgeable

persons in the community.

The 1996 MEPS NHC sample was selected using a

two-stage stratified probability design. In the first stage,

facilities were selected; in the second stage, facility

residents were sampled, selecting both persons in

residence on January 1, 1996, and those admitted during

the period January 1 through December 31.

The sampling frame for facilities was derived from

the National Health Provider Inventory, which is

updated periodically by NCHS. The MEPS NHC data

were collected in person in three rounds of data

collection over a 11⁄

2-year period using the CAPI system.

Community data were collected by telephone using

computer-assisted telephone interviewing (CATI)

technology. At the end of three rounds of data collection,

the sample consisted of 815 responding facilities, 3,209

residents in the facility on January 1, and 2,690 eligible

residents admitted during 1996.
iv

     yyyyy yyyyy yyyyy yyyyy yyyyy Public Health Service Act. They are edited and

published in accordance with the confidentiality

provisions of this act and the Privacy Act. NCHS

Survey Management

MEPS data are collected under the authority of the yyyyy

provides consultation and technical assistance.

As soon as data collection and editing are

completed, the MEPS survey data are released to the

public in staged releases of summary reports and

microdata files. Summary reports are released as printed

documents and electronic files. Microdata files are

released on CD-ROM and/or as electronic files.

Printed documents and CD-ROMs are available

through the AHRQ Publications Clearinghouse. Write or

call:

AHRQ Publications Clearinghouse

Attn: (publication number)

P.O. Box 8547

Silver Spring, MD 20907

800-358-9295

410-381-3150 (callers outside the United States only)

888-586-6340 (toll-free TDD service; hearing 

impaired only)

Be sure to specify the AHRQ number of the

document or CD-ROM you are requesting. Selected

electronic files are available through the Internet on the

AHRQ Web site: 

http://www.ahrq.gov/

On the AHRQ Web site, under Data and Surveys,

click the MEPS icon.

Additional information on MEPS is available from

the MEPS project manager or the MEPS public use data

manager at the Center for Cost and Financing Studies,

Agency for Healthcare Research and Quality, 2101 East

Jefferson Street, Suite 500, Rockville, MD 20852 

(301-594-1406).
v

Table of Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Medical Expenditure and Payment Source Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Household Population Aging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Aligning Health Service Type and Payment Source Categories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Reconciling 1996 NMES and NHA Expenditure Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

NMES-NHA Alignment for 1987. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Tables showing:

1. NMES and NHA expenditure categories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2. NMES and NHA payment source categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3. NMES expenditures–calibrated to NHA, uncalibrated, and ratio of calibrated to uncalibrated . . . . . . 8

Figure:

1. Reconciling NHA and NMES expenditure data for 1996 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Appendixes:

A. Control Variables for Population Aging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

B. Reconciling NHA and NMES Expenditure Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

1

Introduction

This report describes the procedure used to project

data from the 1987 National Medical Expenditure

Survey (NMES) household survey to future years. The

1987 NMES provided extensive information on health

expenditures by or on behalf of American families and

individuals, the financing of these expenditures, and use

of services. The 1987 NMES Household Survey was

based on a national probability sample of the civilian

noninstitutionalized population. The sample was

designed to provide a larger representation of population

groups of interest to the Federal Government than would

have been obtained from a random sample. These groups

included poor and low-income families, the elderly, the

functionally impaired, blacks, and Hispanics. The 1987

NMES was sponsored by the National Center for Health

Services Research, the predecessor to the Agency for

Healthcare Research and Quality (AHRQ). More

information on the 1987 NMES can be found in

Edwards and Berlin (1989).

NMES data were released in public use data sets

projected to the years 1996 and 2005. The projected data

files consisted of person-level records, each of which

included personal health expenditure variables by type of

service and payment source, as well as demographic and

insurance characteristics, and a weight that could be used

to produce national totals for the civilian

noninstitutionalized population.

Each projected data set was a person-level ASCII

data file. Each file was a sample of 34,175 people, had

one record for each person, and was designed to provide

estimates that were representative of the civilian

noninstitutionalized population of the United States in

the designated year. Projected data files cannot be linked

1Formerly with the Agency for Healthcare Research and

Quality.

2Formerly with Social and Scientific Systems, Inc.

to other NMES or MEPS data files that were not

projected. This prohibits analysts from making

projections for population groups that were not

statistically controlled for in the aging process.

Person-level records from NMES were reweighted

based on more recent household population estimates

from government sources to project the household

population. Household health expenditures by type of

service and payment source for the reweighted

population were then aligned to adjusted National Health

Accounts (NHA) data from the Centers for Medicare &

Medicaid Services (CMS), formerly called the Health

Care Financing Administration (HCFA), or to adjusted

NHA projections from the Congressional Budget Office

to complete the aging of the health expenditure data.

This report first describes the 16 categories of

expenditures and the 9 categories of payment sources in

the projected data. This section is followed by a

discussion of the reweighting procedure that projects the

household population to future years. The next two

sections describe the alignment of the reweighted

expenditure data to adjusted NHA data by type of

expenditure and payment source. This alignment

captured inflationary growth in expenditures, as well as

any real changes not otherwise accounted for by the

population aging, in addition to any remaining inherent

differences between NMES and the NHA after adjusting

the NHA data. The final section illustrates the alignment

of the 1987 NMES to the 1987 NHA using the method

described in the previous sections. By removing the

population reweighting step, this contemporaneous

alignment highlights the differences between NHA and

NMES estimates of National Health Expenditures in

1987 by service type and payment source.

Projecting National Medical Expenditure Survey Data:A Framework

for MEPS Projections

by John F. Moeller, Ph.D., and Steven B. Cohen, Ph.D.,Agency for Healthcare Research and Quality; Edward

Hock and Devi Katikineni, Social and Scientific Systems, Inc.; Patrick Purcell, M.A.,1 Congressional Research

Service; Brian Rowland,2 SAS Institute;Thomas Selden, Ph.D., and Marie N. Stagnitti, M.P.A.,Agency for

Healthcare Research and Quality; Daniel Zabinski, Ph.D.,1 Medicare Payment Advisory Commission
Medical Expenditure and

Payment Source Categories

Detailed expenditure data from NMES were

compiled and projected for 16 different medical service

categories plus a total expenditure category, as defined

below.

1. Hospital room and board expenditures: [hospital

facility expense]3 + [(0.7)hospital expense for

admissions without an overnight stay]4

2. Inpatient physician expenditures: [hospital physician

expense] + [(0.3)hospital expense for admissions

without an overnight stay]4

3. Emergency room expenditures: [expense for

emergency room visits not resulting in hospital

admissions] + [expense for emergency room visits

resulting in hospital admissions]

4. Physician office expenditures: [expense for

physician visits excluding hospital and home health]

+ [expense for home health visits by a physician] +

[expense for hospital outpatient visits by a

physician] + [expense for hospital outpatient visits

by a nurse] + [expense for hospital outpatient visits

by a technician] + [expense for outpatient visits by a

physician’s assistant] + [expense for phone visits

with a non-hospital-based physician] + [expense for

phone visits with a non-hospital-based

nonphysician] + [expense for other providers

working for physician (excluding hospital and home

health)] – [expense for visits for outpatient

psychiatric care by a physician]

5. Outpatient hospital expenditures (excluding mental

health and chiropractic services): [expense for

hospital outpatient visits to a physical therapist] +

[expense for hospital outpatient visits to a social

worker] + [expense for visits to other providers not

working for a physician (excluding visits in hospital

or in home)] + [expense for hospital outpatient

visits to other medical professionals]

3Includes physician expenses for services billed by the

facility.

4Hospital facility and physician expenses were not reported

separately for admissions without an overnight stay, so we

assumed the 0.7/0.3 allocation between categories 1 and 2

that approximates the split between the two categories without

this component.

6. Chiropractor expenditures (ambulatory plus

outpatient): [expense for chiropractor visits

(excluding visits in hospital or in home)] + [expense

for hospital outpatient visits by a chiropractor]

7. Podiatrist expenditures (ambulatory plus

outpatient): [expense for podiatrist visits (excluding

visits in hospital or in home)] + [expense for

hospital outpatient visits by a podiatrist] 

8. Optometrist expenditures (ambulatory plus

outpatient): [expense for optometrist visits

(excluding visits in hospital or in home)] + [expense

for hospital outpatient visits by an optometrist]

9. Outpatient mental health (ambulatory and hospital

outpatient): [expense for visits for outpatient

psychiatric care by a physician] + [expense for

psychologist visits (excluding visits in hospital or in

home)] + [expense for hospital outpatient visits by a

psychologist]

10. Prescription drug expenditures: [expense for

prescribed medicines (including refills)]

11. Orthodontia expenditures: [expense for orthodontic

dental visits]

12. Other dental expenditures: [expense for

nonorthodontic dental visits]

13. Glasses and contact lenses: [expense for vision

aids]

14. Durable medical equipment: [expense for durable

medical goods (excluding vision)]

15. Nondurable medical supplies: [expense for

nondurable medical goods]

16. Home health: [expense for home health visits by a

nonphysician medical professional] + [expense for

home health visits by a nonmedical professional]

• Total personal heath care expenditures: [the sum of

the 16 separate expenditure categories]

The expenditures in each of the expenditure

categories were divided into nine sources of payment

(and a total). These payment source categories are listed

below.

1. Self or family (out of pocket)

2. Private health insurance

3. Medicare

4. Medicaid

2
5. Other Federal sources: [includes CHAMPUS and

CHAMPVA (Armed-Forces-related coverage),

Supplemental Security Income (SSI), Indian Health

Service facility or contract, Intertribal Council,

Alaska Native Corporation, Department of Veterans

Affairs, and any other military or Federal program

(such as free government screening services and care

at the National Institutes of Health)]

6. Other State and local sources: [includes services

such as community health centers, but excludes local

and State employment-related insurance and meanstested programs]

7. Workers’ compensation

8. Other private sources: [includes automobile

insurance, other kinds of insurance not specified,

company (where company is not the respondent’s

insurer or employer), school (where school is not the

respondent’s insurer or employer), union (where

union is not the respondent’s insurer or employer),

friend, foreign government, and not otherwise

specified]

9. Free from provider

• Total personal health expenditures from all payment

sources

When using the expenditures reported under the

“free from provider” category, keep in mind that there is

a “double counting” issue. To the extent that “free care”

is financed through higher fees charged to patients

paying through insurance or out of pocket, including

imputed dollar values for “free from provider” as a

source of payment counts some health care spending

twice. However, some services rendered free from

provider are financed by philanthropy or sources of

nonpatient revenue (such as parking fees at a hospital).

Therefore, to obtain an accurate value, some “payments”

called “free from provider” should be included in total

expenditures. Unfortunately, the monies from

philanthropy and nonpatient sources could not be

separated from the other “free from provider”

expenditures. When projecting the data, the total

expenditure values in each of the service categories

include the imputed “free from provider” values, so

there is some double counting in the totals. Options

available to analysts are to use the total values or to

subtract the “free from provider” expenditures (or some

portion thereof) from the totals and use those results as

totals.

Household Population Aging

The person-level sample weight for each person

record in the projected data files is used to produce

national estimates for the civilian noninstitutionalized

population of the United States in a designated year. The

weight for the designated year was based on the original

NMES 1987 weight (which took into account survey

design and nonresponse) and was then adjusted in two

steps (Cohen, DiGaetano, and Waksberg, 1991). Both

steps employed a cell-based weighting-class procedure

to capture changes in the U.S. population from 1987 to

the designated year. The first step was a series of poststratifications designed to update the 1987 data to 1996

on a broad array of demographic, income, and health

care dimensions. In the second step, the 1996 data were

projected to later years based on Middle Series Census

Bureau estimates of growth in the population by age,

race/ethnicity, and sex (Bureau of the Census, 1992).

Both steps are detailed below.

The NMES weight was first adjusted to represent

the 1996 U.S. population by using the March 1997

Current Population Survey (CPS). In this process,

records from both NMES and the CPS were partitioned

into matrices defined by the following set of person

characteristics: (1) receipt of means-tested cash

assistance, (2) age, (3) race, (4) sex, (5) family income

relative to the poverty line, (6) primary source of health

insurance, (7) employment status of the family head, and

(8) region. Details for each of these and other stratifying

variables used in the population reweighting are

provided in Appendix A.

To assure that the minimum sample size was met in

each partitioned cell while maximizing the

disaggregation of the data, an automated cell collapsing

software product was developed for this purpose by a

contractor, Social and Scientific Systems, Inc. Each

NMES weight in a given cell was then multiplied by the

ratio of the sum of the CPS weights to the sum of the

NMES weights for that cell. This weight was then

adjusted so that the number of persons in each Census

region for the projected data (for 1996) reporting

participation in Aid to Families with Dependent

Children (AFDC), SSI, or other Medicaid (persons on

AFDC or SSI receive Medicaid coverage) on the

reweighted NMES matched the number of recipients of

these benefits according to an adjusted figure from 1996

administrative records. This was done to compensate for

the underreporting of these benefits in the CPS.

3
4

Increased enrollment in health maintenance

organizations (HMOs) since 1987 also needed to be

captured. To do so, the NMES population under age 65

with private coverage was reweighted within population

cells to the 1995 National Health Interview Survey

(NHIS) distribution of non-elderly persons with private

coverage enrolled in HMOs. NMES was first partitioned

into matrices using the automated cell collapsing

software and the same eight person-level characteristics

used in the first reweighting (described above) plus an

indicator of HMO participation. The weight for

individuals in each cell of these matrices was adjusted to

match HMO enrollment for the privately insured

population under age 65 as reported in the 1995 NHIS.

In both NMES and NHIS, an HMO was defined as

either a group or staff model prepaid health plan or an

independent practice association (IPA). The weights for

persons outside this targeted population were not

adjusted.

The proportions of the population with Medicare

who had no other insurance, who had other

employment-based insurance, and who had other

individually purchased insurance coverage on the

reweighted NMES file did not match data from the

Medicare Current Beneficiary Survey (MCBS) for

calendar year 1994. On the assumption that the MCBS

provides a more accurate representation of this

population than the CPS does, weights for these people

were adjusted so that the proportions with Medicare

only, Medicare and employer-provided insurance, and

Medicare and individually purchased insurance matched

the proportions found on the MCBS. No adjustment was

made to the weights for those outside this population.

An additional minor adjustment to the weight was

necessary because the population statistics used to

create the initial 1996 sample weight were based on the

March 1997 CPS. To account for population change that

occurred from 1996 to early 1997, Census data on age

and sex population characteristics for December 1996

were used. This last adjustment created the final version

of the 1996 sample weight.5

5The population contributing to annual health expenditures at

any time during 1996 is slightly underestimated by the crosssectional weighting of the population. A correction for this

was made in future revisions to the methodology as applied to

Medical Expenditure Panel Survey (MEPS) expenditure

projections.

The 1996 sample weight was projected to the years

1997-2005 by using population projections from the

Census Bureau based on age, race/ethnicity, and sex to

create the weights for those years.6 Initially, for each of

the 60 population cells defined by age (0-4, 5-14, 15-24,

25-34, 35-44, 45-54, 55-64, 65-74, 75-84, 85 and over),

race/ethnicity (Hispanic, black non-Hispanic, other), and

sex, population growth rates for each year from 1997

through 2005 were constructed as the ratio of the

Census projections for the specified year divided by the

Census data for 1996 for the same cell. Next, the 1996

sample weight for every person within each of the 60

age, race/ethnicity, and sex cells was multiplied by the

cell-specific population growth rate from the Census

projections for each year. This produced the weights for

each year from 1997 through 2005.

One caveat when using these projected data sets and

the weights included on each file concerns HMO

coverage. Only the population under age 65 with private

coverage was included in the post-stratification to

account for increased HMO coverage. There were too

few persons age 65 and over with HMO coverage in the

original 1987 data to post-stratify this population.

Therefore, it is possible to obtain an estimate only of the

total number of people under age 65 with private HMO

coverage.

A second caveat when using the weights on the

projected data files concerns obtaining totals for certain

populations with a particular set of characteristics. Some

of the cells in the reweighting matrices had a very small

number of observations, so estimates based on those

cells are unreliable. This is a particularly pertinent issue

for the population receiving means-tested cash

assistance (such as AFDC and SSI). The population was

split into two groups based on receipt of means-tested

cash assistance. However, the number of people with

cash assistance was too small to make estimates. To

remedy this problem, a minimum cell size of 20 records

for each cell was initially established, but it had to be

lowered to 10 records in some instances. As a result,

some cells were collapsed along one or more variables.

For example, 10 age categories were generally used in 

6The population reweighting technique was not updated with

more recent CPS files because the projection methodology

was revised after converting from a NMES to a MEPS

database. The projected MEPS data sets are now available on

the MEPS Web site at <http://www.meps.ahrq.gov/

MEPSDATA/Projected/mepsdata.htm>.
5

the creation of the weight for people without cash

assistance; however, the 10 age categories were

collapsed to 3 in a separate age variable for people with

cash assistance (Appendix A).

It is also important to note that the projected data

sets do not include demographic and insurance

characteristics other than those of the household

population used for the reweighting. Without controls

for these other variables in the population aging, there

would be no sound basis for projecting them to future

years.

Aligning Health Service Type

and Payment Source

Categories

To complete the aging of the NMES expenditure

values, the reweighted NMES expenditure data had to

be aligned to adjusted 1996 NHA data from CMS and

to projections of adjusted NHA data from the

Congressional Budget Office (CBO) for each year

from 1997 through 2005 (Congressional Budget

Office, 1995).7 This alignment was implemented by

type of health care service and, within service class, by

payment source. The first step in the alignment was to

construct health service and payment source categories

that were comparable between NMES and the NHA.

NMES identifies more categories of health

services than the NHA, so the alignment process

required combining several NMES health service types

into a smaller number of categories consistent with

those reported in NHA. To construct the alignment

factors, 16 NMES health service categories were

collapsed into 7 categories common to the NHA (Table

1). Two additional NHA health expenditure categories

7At the time the projected NMES data were developed, only

CBO projections beyond 1996 were available by type of

service and payment source. (Projected MEPS data are based

on more recent NHA estimates and projections from CMS.)

CBO projections for 1996 through 2005 were scaled

downward by the ratio of actual 1996 NHA data by service

type and payment source from CMS to CBO projections for

1996. More recently, CBO has updated its projections on the

basis of a lower growth assumption, but these projections do

not disaggregate NHA by type of medical service category

because of the difficulty in distinguishing types of services

in the present-day health care sector, which is dominated by

managed care.

Table 1. NMES Household Survey

expenditure catagories and corresponding NHA expenditure categories

Table 1. NMES Household Survey

expenditure categories and corresponding NHA expenditure

categori

Note: MEPS is the Medical Expenditure Panel Survey.

NMES is the National Medical Expenditure Survey. NHA is

the National Health Accounts of the Centers for Medicare

and Medicaid Services (formerly the Health Care Financing

Administration). The NMES expenditure categories are from

NMES expenditure data previously released on Public Use

Tape 18 (Agency for Health Care Policy and Research,

1993). This table represents a reconfiguration of the 16

expenditure categories described in the text. Numbers in

parentheses in the first column refer to numbers of the

expenditure variables in the list in the text.

Source: Center for Cost and Financing Studies, Agency for

Healthcare Research and Quality.

NMES expenditure NHA Collapsed

category and expenditure category

number(s) category number

Outpatient, facility (1) Hospital 1

Emergency room (3) Hospital 1

Inpatient, facility (1) Hospital 1

Outpatient, physician (4, 9) Physician 2

Physician office visits (4) Physician 2

Physician phone calls (4) Physician 2

Inpatient, physician (2) Physician 2

Physician home visits (4) Physician 2

Dental visits (11, 12) Dental 3

Outpatient, Other

nonphysician (5-9) professional 4

Nonphysician Other

office (5-9) professional 4

Nonphysician Other

phone (5-9) professional 4

Home health care (16) Home health 5

Prescribed drugs (10) Drugs and

nondurables 6

Nondurable medical Drugs and

goods (15) nondurables 6

Durable medical Durable

goods (14) medical goods 7

Eyeglasses, contact Durable

lenses (13) medical goods 7

No NMES equivalent Nursing home 8

No NMES equivalent Other personal

health 9

Total expenditures Total personal

health —
6

listed in Table 1 (nursing home and other personal

health) covered expenditures outside the scope of

NMES.

The 16 NMES expenditure categories in Table 1,

and a 17th category for total health expenditures, were

constructed directly from NMES Public Use Tape 18

(Agency for Health Care Policy and Research, 1993).

Analysts cannot replicate the creation of the alignment

factors for a given year from the projected data because

the projected data sets cannot be linked to Public Use

Tape 18.

As with type of service, there are different sources

of payment in NMES than in the NHA. NMES has nine

payment source categories, excluding the total category,

which were defined earlier and are listed in the first

column of Table 2. The NHA has 21 source of payment

categories, which are listed below:

Private funds

Out-of-pocket payments

Private health insurance

Other private funds

Industrial inplant

Nonpatient revenues

Public funds

Federal funds

Medicare

Workers’ compensation

Medicaid (Federal)

Department of Defense

Maternal and Child Health

Department of Veterans Affairs

Vocational rehabilitation

General hospital/medical, not elsewhere

classifiable

Alcohol, Drug Abuse, and Mental Health

Administration/Substance Abuse and Mental

Health Services Administration

Indian Health Service

State and local funds

Temporary disability

Workers’ compensation

Public assistance

Medicaid (State/local)

General Assistance

Maternal and Child Health

Vocational rehabilitation

State and local hospital and school health

Table 2. NMES Household Survey

payment source categories and

corresponding NHA payment source

categories

aCombines the NHA Federal and State/local Medicaid

payment source categories.

bHealth expenditures under workers’ compensation consist of

medical benefits paid under public law by private insurance

carriers and self-insured firms. They are treated as public

expenditures in the NHA.

cOther private expenditures from NMES were allocated

between self/family and private health insurance to construct

alignment factors in order to match their treatment in NHA. 

d“Free from provider” expenditures from NMES and “other

private” expenditures from the NHA were subtracted from

their respective totals to construct the alignment factors

because neither represents direct payment for patient services.

Note: MEPS is the Medical Expenditure Panel Survey. NMES

is the National Medical Expenditure Survey. NHA is the

National Health Accounts of the Centers for Medicare and

Medicaid Services (formerly the Health Care Financing

Administration). The NMES payment source categories are

from NMES data previously released on Public Use Tape 18

(Agency for Health Care Policy and Research, 1993). This

table represents a reconfiguration of the 9 payment source

categories described in the text. Numbers in parentheses in the

first column refer to numbers of the payment source variables

in the list in the text. 

Source: Center for Cost and Financing Studies, Agency for

Healthcare Research and Quality.

NMES payment source NHA payment Collapsed

category and source category

number category number

Self or family (1) Out of pocket 1

Private insurance (2) Private insurance 2

Medicare (3) Medicare 3

Medicaid (4) Medicaida 4

Other Federal (5) Other Federal 5

Other State (6) Other State 5

Workers’ No NHA

compensation (7) equivalentb 5

Other private (8) No NHA

equivalentc 1, 2

Free from provider (9) Other private

sourced —
Figure 1. Reconciling National Health Expenditures for 1996 from NHA and from

projected NMES household data [In billions of dollars]

1. National Health Accounts

National Health Expenditures = $1,035.1a

Minus:

Program administration, insurance loading, etc. = $60.9

Government public health activities = $35.5

Research and construction = $31.5

Nursing home care = $78.5

Other personal health care = $27.6

Subtotal = $234.0

Net National Health Expenditures = $801.1

2. Aged NMES data for 1996, aligned to adjusted NHA net National Health Expenditures

Aligned NMES National Expenditure total (excluding free from provider) = $649.8

Subtractions from NHA net National Health Expenditures = $151.3

3. Understanding the Subtractions from NHA net National Health Expenditures

Nursing home resident hospitalization, physician services, etc. (acute care) = $47.6 ($21,600 per person)

Noncommunity hospitals and nonpatient revenues in community hospitals = $53.6 (14.9 percent of NHA hospitalization)

Total other private nonpatient revenues from other services = $11.5

Physician = $4.2

Dental = $0.2

Other professional = $3.8

Home health = $3.3

Total nondurables = $29.4

Differences in populations (CPS is smaller) = $9.2

Subtotal of itemized subtractions = $151.3

aLevit, Lazenby, Braden, et al., 1998.

Note: CPS is the Current Population Survey, sponsored by the Census Bureau. NMES is the National Medical Expenditure

Survey. NHA is the National Health Accounts of the Centers for Medicare and Medicaid Services (formerly the Health Care

Financing Administration).

Source: Center for Cost and Financing Studies, Agency for Healthcare Research and Quality.

7

The NHA Medicaid category in the second column

of Table 2 was constructed by combining the Federal and

State/local Medicaid categories listed above. The “other

Federal” NHA category in the second column of Table 2

was constructed by combining all of the NHA Federal

funds sources listed above except Medicare and

Medicaid (Federal). The “other State” NHA category in

the second column of Table 2 contains all of the

components of the NHA State and local funds sources

listed above except for Medicaid (State/local). For the

alignment, the other Federal and other State/local

categories were combined into a single “other

government” category (third column of Table 2).

After the NMES expenditures were constructed by

collapsed service category, shown in Table 1, they were

further partitioned by collapsed payment source category

(within each service category), shown in Table 2. This

produced a matrix of six expenditure categories by five

payment source categories. (The categories for

physicians and for other health professionals shown in

Table 1 were combined into a single category to reduce

the number of service categories from seven to six.)
8

Table 3. 1987 NMES expenditures (in billions of dollars) calibrated to adjusted

NHA, uncalibrated, and ratio of calibrated to uncalibrated

Source of paymenta

Type of service and Out of Private Other

type of value pocket insurance Medicare Medicaid government Total

Billions of dollars

Hospital Cal 8.586 68.064 36.855 12.992 23.820 150.318

Uncal 15.301 68.129 44.350 15.249 18.860 161.889

Cal factor 0.561 0.999 0.831 0.852 1.263 0.929

Physicians Cal 38.608 48.732 17.959 4.611 5.990 115.899

and other Uncal 31.872 49.415 18.775 9.183 15.990 125.235

professionals Cal factor 1.211 0.986 0.957 0.502 0.375 0.925

Dental Cal 13.014 11.358 0.000 0.532 0.134 25.038

Uncal 16.858 10.430 0.025 0.543 0.503 28.359

Cal factor 0.772 1.089 0.000 0.980 0.266 0.883

Home health Cal 1.798 1.096 1.403 1.676 0.026 5.999

Uncal 4.898 1.272 2.178 2.813 0.131 11.292

Cal factor 0.367 0.862 0.644 0.596 0.201 0.531

Drugs and Cal 13.385 7.589 0.000 3.056 0.759 24.789

nondurables Uncal 13.372 6.698 0.289 2.257 1.291 23.907

Cal factor 1.001 1.133 0.000 1.354 0.588 1.037

Durables Cal 5.404 0.817 1.187 0.000 0.165 7.574

Uncal 5.509 0.775 0.341 0.215 0.079 6.919

Cal factor 0.981 1.054 3.477 0.000 2.095 1.095

Total Cal 81.489 136.953 57.400 22.845 30.894 329.583

Uncal 88.460 136.070 65.959 30.259 36.854 357.601

Cal factor 0.921 1.006 0.870 0.755 0.838 0.922

aExcludes services free from provider.

Note: NMES is the National Medical Expenditure Survey. NHA is the National Health Accounts of the Centers for Medicare

and Medicaid Services (CMS, formerly the Health Care Financing Administration). The NMES expenditure categories are

from NMES expenditure data previously released on Public Use Tape 18 (Agency for Health Care Policy and Research,

1993).

The calibrated amounts (cal) represent 1987 estimates of National Health Expenditures from CMS by service type and

payment source adjusted for a NMES population (Appendix B and Figure 1). The uncalibrated counterparts (uncal) are the

1987 NMES estimates. Calibration factors are defined as the ratio of the calibrated (adjusted NHA) amount to the

uncalibrated (NMES) amount.

For the projected NMES data, calibration factors are derived by comparing adjusted NHA expenditures by service type and

payment source for the future year to corresponding NMES estimates based on a reweighted NMES population for the same

year (see text).

Source: Center for Cost and Financing Studies, Agency for Healthcare Research and Quality.
9

After adjustments were made to the NHA data

(described in the next section, Appendix B, and

Figure 1), comparable NHA amounts for each

corresponding collapsed expenditure/payment source

category were constructed.8 Next, per capita NMES and

per capita NHA expenditure/payment source entries

were constructed for each cell of the matrix. Then, per

capita NHA amounts were divided by reweighted per

capita NMES amounts for each cell of the matrix to

produce the 30 alignment factors for a given projection

year. The 30 alignment factors for 1987 are shown in

Table 3.

A given expenditure/payment source variable

among the 144 such variables on the projected data sets

(16 expenditure categories by 9 payment source

categories) is “projected” to a future year by multiplying

the original variable by the appropriate alignment factor

and by the appropriate weight corresponding to the

projection year and the person’s demographic and

insurance coverage characteristics. The numbers in

parentheses in the first column of Table 1 provide the

linkage needed to determine which of the collapsed

expenditure categories (in the third column of Table 1)

in the alignment matrix is used to align any of the 16

types of health expenditure variables on the projected

data sets. There were seven collapsed categories from

the third column of Table 1 because Categories 8 and 9

from the NHA (nursing home and other personal health

expenditures) contain no NMES counterpart. For the

alignment, Categories 2 (physician) and 4 (other

professional) were combined to produce six final

collapsed categories for the alignment. Thus, the

alignment factor for the combined physician and other

professional category was used to age health care

expenditures for NMES expenditure Categories 2 and

4-9, as defined in the first column of Table 1.

As Table 2 makes clear, alignment within each

expenditure category by source of payment was

straightforward for the first seven NMES sources of

payment (with Categories 5, 6, and 7 sharing the same

“other government” factor). The last two categories,

“other private” and “free from provider,” were slightly 

8The blueprint for the adjustments to the NHA data was

established by HCFA, now CMS (Office of the Actuary,

1991). A MEPS version of these adjustments to the NHA data

was completed after the NMES version described in this

report. The MEPS adjustments are described in Selden, Levit,

Cohen, et al. (2000).

more complicated. The “other private” alignment factor

was calculated as the weighted sum of the alignment

factors for “self or family” and “private insurance,”

where the weights were their relative proportions for a

given expenditure item. The “free from provider” factor

used the average alignment factor across the five

payment source types for a given expenditure category.

Reconciling 1996 NMES and

NHA Expenditure Estimates

The health expenditure target for a national sample

of households in the civilian noninstitutionalized

population differs from National Health Expenditures

published in the National Health Accounts. Using 1996

as an example, Figure 1 shows the components of the

NHA estimate of National Health Expenditures that had

to be “backed out” to reach an appropriate alignment

target for a household survey such as NMES. This

section covers the rationale for the subtractions of

expenditure data from the NHA. A more detailed

discussion of this methodology appears in Appendix B.

In particular, Appendix B provides more detail on how

the expenditures removed from the NHA in section 3 of

Figure 1 were allocated across payment source

categories.

National Health Expenditures from the NHA in

1996 totaled $1,035.1 billion (Levit, Lazenby, Braden,

et al., 1998). Included in this total are $127.9 billion for

administration of health care services, insurance

loading, government public health activities, and

research and construction programs that are not

included in NMES or in the NHA personal health

expenditures. Subtracting these items reduces the NHA

total to $907.2 billion, which represents the NHA

estimate of personal health expenditures.9

A total of $106.1 billion in personal health

expenditures for nursing home care and other personal

health care services that were not covered by NMES

were also removed from the NHA. Examples of “other

personal health care services” not covered by NMES

include health screening services, case management

services, and home- and community-based waiver

services.

Total subtractions from the NHA to this point equal

$234.0 billion and reduce National Health Expenditures 

9The NHA estimates of National Health Expenditures were

revised after this analysis (Heffler, Levit, Smith, et al., 2001).
to $801.1 billion. The remaining $801.1 billion includes

expenditures for treating the acute care needs of

residents of nursing homes and intermediate care

facilities for the mentally retarded (ICF/MRs). These

services are not covered by a household survey of the

noninstitutionalized population. The estimate for the

hospital and physician services used to treat the acute

care needs of these institutionalized persons in 1996,

$47.6 billion, was backed out from the NHA estimate of

National Health Expenditures.

A total of $53.6 billion in expenditures for care in

noncommunity hospitals that were outside the scope of

the NMES hospital universe was also subtracted. This

figure also includes the nonpatient revenues in shortterm community hospitals that were in the NMES

universe.

In addition, expenditures paid by “other private”

sources were subtracted from each NHA service

category. In the NHA, “other private” sources of

payment represent primarily charity and philanthropy

not directly attributable to services for specific patient

events. There is no directly corresponding equivalent to

these sources in NMES, so $11.5 billion for this source

of payment had to be subtracted from NHA

expenditures to perform the alignment. Likewise, all

imputed expenditures from the “free from provider”

payment source category were subtracted from NMES

expenditures in each service category, because service

values for this category are not imputed for health care

services in the NHA.

The “other private” source of payment category in

NMES was allocated between two sources of payment,

“self or family” (out of pocket) and “private insurance,”

based on the relative proportion of each of these two

payment sources in each type of service category in the

NMES total health expenditure data. The “other private”

payment source in NMES consists of payments made by

automobile insurance, other unspecified types of

insurance, and miscellaneous private sources. In the

NHA, payments from these sources are allocated

between “out of pocket” and “private insurance.”

The portion of expenditures for nondurable medical

goods in the NHA not attributable to prescription drug

purchases primarily consists of over-the-counter

medication purchases. These expenditure data were not

collected in NMES. The entire NHA nondurable total

for nonprescription drug purchases, $29.4 billion, was

therefore subtracted from the NHA total.

It was not appropriate to align NMES to total

adjusted NHA health care expenditures because NMES

and the NHA are based on different populations. The

aged NMES sample (Household Survey) for 1996

represents the 265.4 million persons in the U.S. civilian

noninstitutionalized population. In contrast, the NHA

includes several groups not represented in NMES,

including residents of nursing homes, persons residing

in personal care homes and ICF/MRs, persons in the

Armed Forces, inmates of prisons and jails, persons in

psychiatric hospitals, and residents of U.S. territories

and possessions. CMS estimates that this non-NMES

population totaled 10.1 million persons in 1996, with

2.2 million of them represented by persons in nursing

homes and ICF/MRs. Health expenditures for these

groups of the population that were not covered in

NMES totaled $9.2 billion and were “implicitly”

removed from the NHA total of $1,035.1 billion.

The additional subtractions from the NHA estimate

of National Health Expenditures for 1996 totaled $151.3

billion. This produced a target National Health

Expenditures total for 1996 of $649.8 billion after

removing all non-NMES health expenditures from the

NHA total. A more detailed discussion of this back-out

procedure appears in Appendix B.

NMES-NHA Alignment for 1987

The 1987 alignment factors for the NMES data in

1987 (Table 3) illustrate the discrepancy between

estimates of national health expenditures by type of

service and payment source from a nationally

representative household survey and corresponding

estimates from the National Health Accounts adjusted to

a NMES population and data. Observed discrepancies

are attributable to the alignment methodology and to

sampling and nonsampling errors in both the NMES

data and the measures used to construct the NHA

estimates. For the overall population comparisons, an 8-

percent differential between NMES estimates and the

NHA (under the tenuous assumption that the NHA

estimate has no sampling error) would be a lower bound

of the margin of difference that could be detected at an

alpha level of 0.05. For cell-specific comparisons based

on smaller sample size constraints in NMES, only

substantially larger margins of difference in estimates

would be possible to detect as significant differences at

the 0.05 level. The calibrated value (cal) in each cell is

the adjusted NHA estimate, while the uncalibrated value

10
11

(uncal) is the corresponding NMES estimate. The

calibration factor (cal factor) is the adjusted NHA

estimate divided by the corresponding NMES estimate

in each cell. Calibration factors greater than 1 indicate

that the NMES estimate is less than the adjusted NHA

estimate for a given type of service and payment source,

while calibration factors less than 1 indicate that the

NMES estimate exceeds the corresponding adjusted

NHA estimate.

The ratio values referred to in the next paragraphs

are the reciprocals of the calibration factor values in

Table 3. Ratios are used here because the remaining text

in this section focuses on how much the NMES estimate

is above or below the corresponding NHA estimate. In

contrast, for calibration purposes, the focus is on how

much the NHA estimate is above or below the

corresponding NMES estimate.

Overall, total personal health expenditures estimated

from NMES exceed the corresponding adjusted NHA

estimate by just over 8 percent (ratio = 1.0850). Based

on the column totals for payment sources in Table 3,

private insurance payments from the NMES data are

only six-tenths of a percent lower than the corresponding

adjusted NHA estimate (ratio = 0.9936). Out-of-pocket

payments based on the NMES data exceed those from

the NHA by 8-9 percent (ratio = 1.0855). The public

payments estimated from NMES (for Medicare,

Medicaid, and other government) all exceed the

counterparts from the adjusted NHA data by

considerably more than 8 percent.

Turning to the row totals for the expenditure

categories in Table 3, hospital expenditures estimated

with the NMES data exceed the corresponding total

from the adjusted NHA data by slightly under 8 percent

(ratio = 1.0770). The NMES estimate for expenditures

on physician and other professional services exceeds the

adjusted NHA equivalent by slightly over 8 percent

(ratio = 1.0806). Prescription drugs and nondurables

estimated from the NMES data are 3.6 percent lower

than the adjusted NHA estimate (ratio = 0.9644). The

NMES estimate of durables is 8.6 percent smaller than

the adjusted NHA estimate (ratio = 0.9135), while the

NMES home health expenditure estimate is nearly

double that based on the NHA data (ratio = 1.883). A

substantial component of this discrepancy results from

the fact that only Medicare- and/or Medicaid-certified

home health agencies are recognized in the NHA data.

Also, hospital-based home health agencies are counted

in the NHA hospital services category rather than in the

separate NHA home health expenditure amount (Selden,

Levit, Cohen, et al., 2000).

Without discussing each of the cells in the interior of

Table 3, suffice it to say that there is considerable

variation within each row or column. This suggests that

the aggregate relationship between NMES and NHA

summarized by the marginal (row or column total)

comparisons is not necessarily representative of the

separate components in each row or column. The

sometimes extreme differences between the estimates

from the two sources call for further research into the

methodologies used to construct health expenditures and

payment sources in the National Health Accounts and in

household survey data.

References

Agency for Health Care Policy and Research. Household

Survey: expenditures, sources of payment and

population data. Rockville (MD); 1993. NMES Public

Use Tape 18. AHCPR 98-DP02.

Bureau of the Census (US). Population projections of the

United States, by age, sex, race, and Hispanic origin:

1992 to 2050. In Current Population Reports.

Washington: US Department of Commerce; 1992.

Cohen SB, DiGaetano R, Waksberg J. Sample design of

the 1987 Household Survey. Rockville (MD): Agency

for Health Care Policy and Research;1991. National

Medical Expenditure Survey Methods 3. AHCPR Pub.

No. 91-0037.

Congressional Budget Office (CBO). The economic and

budget outlook: an update, and unpublished spreadsheet

projections for 1996-2005 provided by CBO.

Washington; 1995. 

Edwards WS, Berlin M. Questionnaires and data

collection methods for the Household Survey and the

Survey of American Indians and Alaska Natives.

Rockville (MD): National Center for Health Services

Research and Health Care Technology Assessment;1989.

National Medical Expenditure Survey Methods 2.

DHHS Pub. No. (PHS) 89-3450.

Heffler S, Levit K, Smith S, et al. Health spending

growth up in 1999: faster growth expected in the future.

Health Affairs 2001 March/April; 20(2):193-203.
12

Levit KR, Lazenby HC, Braden BR, et al. National

health spending trends in 1996. Health Affairs 1998

Jan/Feb; 17(1):35-51.

Office of the Actuary. NMES comparisons to NHE and

other sources. Unpublished tables. Baltimore: Health

Care Financing Administration, Office of National

Health Statistics; Dec 1991.

Selden TM, Levit KA, Cohen JW, et al. Reconciling

medical expenditure estimates from the Medical

Expenditure Panel Survey and the National Health

Accounts, 1996. Paper presented at the Association for

Health Services Research Annual Meeting. 2000 June,

Los Angeles.
13

Appendix A. Control Variables

for Population Aging

The first step in projecting National Medical

Expenditure Survey (NMES) expenditure data was to

project the NMES population. This was accomplished by

reweighting the 1987 NMES sample so it represented

populations for years after 1987. The reweighting was

done in two stages. In the first stage, the NMES

population was projected from 1987 to 1996 using

population data from more recent household surveys. In

the second stage, the aged 1996 NMES population was

projected to each year after 1996 up to 2005 based on

Census projections of the population.

The technical definitions and construction of the

following person-level characteristics used to create the

initial 1996 sample weight are provided in this appendix:

age, race, sex, income relative to the poverty line,

primary source of health insurance, employment status

of the family head, region of residence, receipt of meanstested cash assistance, health maintenance organization

(HMO) participation status, and Medicare/private

insurance status. Variance estimates of the projected

expenditures are discussed briefly at the end of this

appendix.

After the 1996 sample weight was constructed, it

was aged (based on changes in age, race, and sex) to

create the final sample weight for the designated year

(yy = 96, 97, ..., 05). All of the variables described in this

appendix appeared on the publicly released projected

expenditure files.

In several instances, NMES definitions of these

population characteristics differed from their Current

Population Survey (CPS) counterparts. For example,

CPS insurance coverage variables reflect an annual time

period (coverage from a particular source at any time

during the year) rather than the time period covered by a

NMES “round” (which averages about 3 months).

Estimates of populations with these characteristics reflect

the CPS definitions, because the data were reweighted to

the CPS versions of these variables. For example,

population projections of the number of unemployed

persons should be interpreted as persons unemployed

using the “full year” definition of unemployment in

CPS, not the “part year” (or round) measure in NMES.

Similarly, additional reweighting of the projected NMES

data for Medicaid enrollees, HMO coverage, and

employer-sponsored retirement coverage with respective

Medicaid administrative data, NHIS data, and Medicare

Current Beneficiary Survey (MCBS) data “overrode”

NMES definitions of these populations (and their

counterparts, e.g., non-Medicaid coverage) with the way

these populations are defined in these secondary data

sources.

Definitions of Control Variables

The partitioning of NMES records during the first

step of the aging process (described in the Household

Population Aging section) was defined by the following

person-level variables.

CASHASST: Indicates participation in cashassistance means-tested programs. It was created with

NMES data concerning income from participation in

Supplemental Security Income (SSI), Aid to Families

with Dependent Children (AFDC), and other public

assistance programs. This variable was formatted as:

1 = SSI

2 = AFDC or other public assistance

3 = Neither

NUHNSCOV: Indicates primary source of health

insurance. Private insurance coverage categories were

constructed from NMES data collected from employers

and insurance companies in the Health Insurance Plans

Survey (HIPS). The HIPS data were imputed to persons

who were eligible for HIPS but for whom data were not

collected. Coverage from CHAMPUS (Armed-Forcesrelated coverage) and public health insurance was

constructed by using data collected in the NMES

Household Survey. Data on age, private insurance

coverage, CHAMPUS coverage, Medicare participation,

and Medicaid participation were based on the last round

a person participated in NMES. Persons under age 65

were hierarchically coded into one of the first four

categories unless they had both CHAMPUS and private

coverage that was not employment related, in which case

they were in Category 2. All persons age 65 and over

were coded into Category 5. This variable was formatted

as:

1 = Private, employment-related or CHAMPUS

2 = Private, not employment-related

3 = Public (Medicare or Medicaid)

4 = Uninsured

5 = Age 65 or older
14

POVSTALB: Indicates family income relative to the

poverty line. It was based on a NMES variable that

classifies people as living in poor, near-poor, low

income, middle income, high income, or negative

income families. This NMES variable was based on the

income of all related persons residing in the same

household. This variable was formatted as:

1 = Less than 1.00 times poverty line

2 = 1.01 to 1.24 times poverty line

3 = 1.25 to 1.99 times poverty line

4 = 2.00 to 3.99 times poverty line

5 = 4.00 or more times poverty line

The families with negative income were included in

Category 1.

AGE3: A three-category age variable based on age

data from the last round a person participated in NMES.

All records have a value of this variable, but it was used

to post-stratify on age for persons identified as being on

cash assistance (CASHASST = 1 or 2). This variable

was formatted as:

1 = 0-17

2 = 18-64

3 = 65 or older

AGE10: A 10-category age variable based on age

data from the last round a person participated in NMES.

All records have a value of this variable, but it was used

to post-stratify on age for persons not getting any cash

assistance (CASHASST = 3). This variable was

formatted as:

1 = 0-4

2 = 5-14

3 = 15-24

4 = 25-34

5 = 35-44

6 = 45-54

7 = 55-64

8 = 65-74

9 = 75-84

10 = 85 or older

SEX: Indicates sex as reported in NMES. This

variable was formatted as:

1 = Male

2 = Female

NEWRACE: A person-level variable constructed to

facilitate the post-stratification of the sampling weight

by race and ethnicity considering three mutually

exclusive classifications: Hispanic, black non-Hispanic,

and other. This variable was formatted as:

1 = Hispanic

2 = Black non-Hispanic

3 = Other

EMPFAMHD: A constructed variable based solely

on NMES Household Survey data which cross-classifies

household-reported data on employer insurance

premium contributions and employment status for the

head (eldest person) in each family. Employment status

was based on the survey week of the last round a person

designated as the family head participated in NMES. In

coding this variable, all family members were assigned

the same category as the family head. This variable was

formatted as:

1 = No job (last week)

2 = Has job and employer makes health insurance 

contributions

3 = Other

REGION: Indicates the Census region (Northeast,

Midwest, South, or West) that persons resided in as of

the last round they participated in NMES. This variable

was formatted as:

1 = Northeast

2 = Midwest

3 = South

4 = West

The NMES variables used in the adjustment of the

1996 sample weight for the underreporting of AFDC,

SSI, and Medicaid participation on the March 1997 CPS

were REGION and the following.

CASHAS36: A hierarchical variable that indicates if

a person participated in SSI, AFDC, or other Medicaid

(noncash) at any point in NMES. It was created with

NMES data on income from participation in SSI,

income from participation in AFDC, other Medicaid
15

participation (noncash), age, and region of persons in the

last round they participated in the survey. This variable

was formatted as:

1 = Cash, AFDC, <18, Northeast

2 = Cash, AFDC, 18+, Northeast

3 = Cash, SSI, <65, Northeast

4 = Cash, SSI, 65+, Northeast

5 = Noncash, <21, Northeast

6 = Noncash, 21-64, Northeast

7 = Noncash, 65+, Northeast

8 = Other, <65, Northeast

9 = Other, 65+, Northeast

10 = Cash, AFDC, <18, Midwest

11 = Cash, AFDC, 18+, Midwest

12 = Cash, SSI, <65, Midwest

13 = Cash, SSI, 65+, Midwest

14 = Noncash, <21, Midwest

15 = Noncash, 21-64, Midwest

16 = Noncash, 65+, Midwest

17 = Other, <65, Midwest

18 = Other, 65+, Midwest

19 = Cash, AFDC, <18, South

20 = Cash, AFDC, 18+, South

21 = Cash, SSI, <65, South

22 = Cash, SSI, 65+, South

23 = Noncash, <21, South

24 = Noncash, 21-64, South

25 = Noncash, 65+, South

26 = Other, <65, South

27 = Other, 65+, South

28 = Cash, AFDC, <18, West

29 = Cash, AFDC, 18+, West

30 = Cash, SSI, <65, West

31 = Cash, SSI, 65+, West

32 = Noncash, <21, West

33 = Noncash, 21-64, West

34 = Noncash, 65+, West

35 = Other, <65, West

36 = Other, 65+, West

An interim 1996 sample weight was created by

partitioning the population on the file into the 36

categories in CASHAS36. The sum of the initial 1996

sample weight for the people in these categories was

calculated. The total number of people in each category

as reported on administrative records was divided by the

sum in that category. Each person’s initial 1996 sample

weight was multiplied by the ratio from this CASHAS36

category to create the interim 1996 sample weight.

Next, this interim 1996 sample weight was adjusted

to match HMO enrollment of persons under age 65 with

private insurance as reported in the 1995 National Health

Interview Survey (NHIS). In both NMES and NHIS, an

HMO was defined as either a group or staff model

prepaid health plan or an independent practice

association. The population under 65 with private

insurance was partitioned by the same personal

characteristics used in the creation of the initial 1996

sample weight plus the following.

LASTHMOX: Indicates if people were covered in

their last round of NMES eligibility by a private health

insurance plan that was classified as an HMO based on

health insurance plan abstraction (HIPA) data. The

NMES HIPA data consisted of detailed coverage

parameters such as deductibles, copayments, and

coinsurance rates that were abstracted from private

health insurance plan booklets of NMES policyholders.

The LASTHMOX variable was imputed to persons

eligible for HIPA but for whom data were not collected

due to sampling nonresponse. This variable was

formatted as:

0 = No

1 = Yes

The people under age 65 with private insurance had

their weight values adjusted according to these partitions.

The people outside this population did not. Charges

imputed to health services consumed by the HMO

population based on charges by the fee-for-service

population in the 1987 NMES were carried forward in

the aged NMES database.

Ultimately, the weights for the Medicare population,

age 65 and over were adjusted so that the proportions of

people with no insurance other than Medicare, other

employment-based insurance, and other individually
16

purchased insurance coverage matched the same

proportions from MCBS. The Medicare population was

partitioned by the following characteristics.

ANYMCARE: Indicates whether people age 65 and

over had Medicare coverage only, Medicare and

Medicaid coverage, Medicare coverage with

employment-sponsored private insurance, Medicare

coverage with other private insurance, or no Medicare

coverage. Only NMES Household Survey data were

used to construct this variable. A person was considered

to be covered by Medicare if the NMES Medicare

participation variable indicates Medicare coverage in any

round of the survey. 

If people were not 65 years of age or over during the

last round they participated in the survey, they were

assigned to Category – 1. If people were classified as

having Medicare coverage and had Medicaid or other

public coverage on the interview date in any round they

participated in NMES, regardless of any other coverage,

they were assigned to Category 1. If they were classified

as being covered by Medicare and reported having group

coverage through their employer or union in any round

of NMES, they were assigned to Category 2. If they

were classified as being covered by Medicare and, in any

round of NMES, had group coverage that was not

through their employer or union or had nongroup

coverage, they were assigned to Category 3. If they were

classified as being covered by Medicare and had no

other coverage, they were assigned to Category 4. If they

were not classified as being covered by Medicare, they

were assigned to Category 5. This hierarchical variable

was formatted as:

– 1 = Inapplicable (under age 65)

1 = Medicare and Medicaid

2 = Medicare and employer or union group

insurance

3 = Medicare and individually purchased insurance

4 = Medicare only

5 = No Medicare

Finally, the weight was adjusted to represent the

1996 population rather than the March 1997 population

from CPS to create the final version of the 1996 sample

weight. The entire population was partitioned into one of

60 categories defined by SEX, NEWRACE, and AGE15. 

AGE15: A 15-category age variable based on age

data from the last round a person participated in NMES.

This variable was formatted as:

1 = 0

2 = 1-4

3 = 5-9

4 = 10-14

5 = 15-19

6 = 20-24

7 = 25-29

8 = 30-34

9 = 35-44

10 = 45-54

11 = 55-59

12 = 60-64

13 = 65-69

14 = 70-74

15 = 75 or older

Variance Estimation

It is possible to estimate the variances associated

with projected estimates that are a consequence of the

underlying sample design of NMES data. Variance

estimates of descriptive statistics derived from these data

that are made using conventional procedures that focus

on measuring sampling variability generally understate

the overall variance. This is a consequence of the

influence of additional sources of error introduced to

NMES data through aging and alignment to external

data sources. The variance estimates attributable to

NMES sample design can be used instead as lower

bound guideposts in the absence of more complex

variance expressions that account for additional sources

of uncertainty introduced by the projection methodology.
17

Appendix B. Reconciling NHA

and NMES Expenditure Data

The material in this appendix supplements the

material in the body of this report on the National Health

Accounts (NHA) alignment procedure. The “back-out”

of health expenditures from the NHA was implemented

for each year from 1996 through 2005 with spreadsheet

software. A description of the methodology for the

subtractions from NHA, totaling $151.3 billion in 1996

(Section 3 of Figure 1), follows. A description of how

these subtracted amounts were allocated across the

various payment sources in the spreadsheet software is

included as well. 

The general approach adopted was to first remove

from the NHA the expenditures of the population groups

not covered in the National Medical Expenditure Survey

(NMES) that were assumed to be atypical compared to

the average expenditures of the NMES population. The

health care expenditures of persons not sampled in

NMES because they were in nursing homes or

intermediate care facilities for the mentally retarded

(ICF/MRs) were assumed to be atypical and were thus

removed by a series of steps outlined below. It was

unnecessary to remove expenditures of the non-NMES

population groups assumed not to be atypical because

the alignment of NMES to adjusted NHA expenditures

was done on a per capita basis. Figure 1 shows that the

alignment implicitly removed $9.2 billion from the NHA

for non-NMES populations, although this removal was

not explicitly carried out in the spreadsheet software

except for the nursing home and ICF/MR populations. It

was assumed that the expenditures of all other

populations excluded from NMES had average

expenditures the same as those of the sampled NMES

population. Thus by inflating per capita expenditures to a

NMES population, rather than an NHA population, the

expenditures of these other excluded populations were

implicitly excluded.

Adjustments to NHA Hospital

Expenditures

First, a series of steps was implemented to remove

from total NHA hospital expenditures (1) the acute care

hospital expenditures of the nursing home and ICF/MR

population, (2) the hospital expenditures of non-shortterm noncommunity hospitals outside the NMES

sampling frame, and (3) the nonpatient revenues of

short-term community hospitals within the NMES

sampling frame. The estimation procedure for the

amounts backed out from total NHA hospital

expenditures and payment sources is described in the

following four steps.

Step 1: Estimating privately paid acute care

hospital expenditures for the nursing home

and ICF/MR population

Acute care hospital expenditures for the NHA

population in nursing homes or ICF/MR facilities that

were paid from private sources, either from private

health insurance or by self or family (out-of-pocket)

payments, were estimated to be $0.4 billion in 1987. It

was assumed that the remaining non-NMES population

in the NHA had no hospital expenditures paid from these

private sources. The $0.4 billion represents the product

of the estimated number of hospital admissions for this

population and estimated private payments per

admission. It was inflated to $0.7 billion in 1996 by

using the Medical Care component of the Consumer

Price Index (CPI-M). It was then inflated to years 1997

through 2005 by using the 1987-96 annual average value

of the CPI-M for the appropriate number of years.

The fraction of these expenditures paid by private

health insurance (or paid out of pocket) was estimated by

the ratio of NHA hospital expenditures paid by private

insurance (or paid out of pocket) to NHA hospital

expenditures paid from private sources (combined

private health insurance and out of pocket) for a given

year.

To obtain an estimate of NHA hospital expenditures

for the NMES population that were paid by private

health insurance, the above ratio was multiplied by $0.7

billion and the result subtracted from the total NHA

hospital expenditures paid by private insurance. A

similar procedure was used to estimate out-of-pocket

hospital expenses for the NMES population. To

summarize:

NHA hospital out of pocket (net of the nursing

home and ICF/MR population) =

Total NHA hospital out of pocket –

estimated hospital out of pocket of the nursing home

and ICF/MR population
18

NHA hospital private health insurance (net of the

nursing home and ICF/MR population) = 

Total NHA hospital private health insurance –

estimated hospital private health insurance of the

nursing home and ICF/MR population

Step 2: Estimating total acute care hospital

expenditures for the nursing home and

ICF/MR population 

Before adjusting NHA Medicare, Medicaid, and

other government hospital expenditures for the nursing

home and ICF/MR populations, total acute care hospital

expenditures for the nursing home and ICF/MR

populations were first estimated. Spending per capita on

acute care hospital and physician services by the nursing

home population was estimated by using NMES mean

hospital and physician expenditures of

noninstitutionalized persons who were age 65 and over,

and who had limitations in three or more activities of

daily living. This value of $11,000 was aged from 1987

to years 1996 through 2005 by using the 1987-96

average annual CPI-M.

A per capita value for acute care hospital and

physician services for the ICF/MR population was

estimated by using NMES mean total health care

expenditures for the entire civilian community

population that had any medical expenditures. This value

of $1,800 in 1987 was also inflated by the 1987-96

average annual CPI-M to estimate expenditures in the

years 1996 through 2005. (Using the overall mean for

persons with any medical expenditures may

underestimate acute care expenses for the ICF/MR

population, but it is not likely to affect the results

significantly because this population accounted for only

about 15 percent of the combined nursing home and

ICF/MR population in 1996.)

Total acute care hospital and physician expenditures

for the nursing home and ICF/MR population in a given

year were obtained by multiplying the nursing home

estimate from NMES by the nursing home population,

multiplying the ICF/MR estimate from NMES by the

ICF/MR population, and then taking the sum of the two

products. The populations for these two groups were

estimated by applying recent growth rates to reported

levels. The portion of the total acute care hospital and

physician expenditures for this combined population

allocated to hospital expenditures was estimated by

multiplying the total by the fraction of total NHA

hospital and physician expenditures that were attributed

to hospitals only. However, about 15 percent of NHA

hospital expenditures were from hospitals outside the

scope of NMES and revenue sources not included in

NMES. (See Step 3 of this section.) Therefore, the total

NHA hospital expenditures used in both the numerator

and denominator of this adjustment factor were reduced

by 15 percent.

Step 3: Estimating hospital expenditures

of non-short-term noncommunity hospitals

and nonpatient revenue of short-term

community hospitals

The NMES universe of hospitals includes only

short-term community hospitals, and NMES

expenditures include only patient revenues in these

hospitals. Data on nonpatient revenues, such as parking

fees or State and local subsidy payments, were not

included in NMES. The NHA, in contrast, include

Federal hospitals, psychiatric hospitals, and other longterm hospitals and include all sources of revenue

received by these and other hospitals. These non-NMES

hospital expenditures were estimated to represent $29.1

billion of the $194.1 billion in total NHA hospital

expenditures in 1987. For years after 1987, these

expenditures were assumed to represent the same

proportion of total NHA hospital expenditures as in

1987. 

Neither expenditures for noncommunity hospitals

excluded from the NMES universe nor nonpatient

revenues of community hospitals were assumed to be

financed from private sources (either by private health

insurance or family/self payments). These expenditures

were instead assumed to be financed solely by public

sources (Medicare, Medicaid, and other government).

Step 4: Removing publicly financed nonNMES hospital expenditures and

nonpatient revenues from NHA Medicare,

Medicaid, and other public sources 

Subtracting the total private acute care expenditures

of the nursing home and ICF/MR population in Step 1

of this section from the total acute care hospital
expenditures for this population in Step 2 of this section

produces the publicly financed portion of acute care

hospital expenditures for this population. Combining this

with Step 3 of this section, the publicly financed

estimated hospital expenditures of non-NMES hospitals

and the nonpatient revenues of NMES hospitals,

produces a total publicly paid hospital back-out amount

(PHBACK). Subtracting this amount from the NHA

total public payments to hospitals (PHNHA) adjusts this

total for PHBACK. The ratio of (PHNHA – PHBACK)

to PHNHA produces an adjustment factor PHADJUST.

Medicare, Medicaid, and other public payments to

hospitals in the NHA (which sum to PHNHA) are each

multiplied by PHADJUST to produce estimates of each

payment source after removing the corresponding public

payments for each source attributed to the acute hospital

care of the nursing home and ICF/MR population, the

expenditures of non-NMES hospitals, and the nonpatient

revenues of NMES hospitals.

Adjustments to NHA Physician

Expenditures

Adjustments made to the NHA physician service

category to remove physician payments for the acute

care of the nursing home and ICF/MR population were

similar to those described for the hospital service

category, with the following exceptions.

Step 1: Estimating privately paid acute

care physician expenditures for the nursing

home and ICF/MR population 

Physician expenditures for the nursing home and

ICF/MR population paid from private sources (out of

pocket or by private health insurance) were estimated by

multiplying the previously estimated value for hospitals

from Step 1 of the preceding section (Adjustments to

NHA Hospital Expenditures) by the ratio of total NHA

physician expenditures to total NHA hospital

expenditures in a given year. The fraction of these

expenditures paid by each separate private source was

estimated by the ratio of NHA physician expenditures

paid by each source (private health insurance or out of

pocket) to NHA physician expenditures paid from

private sources for a given year.

Step 2: Estimating total acute care

physician expenditures for the nursing

home and ICF/MR population 

The physician expenditure value for the nursing

home and ICF/MR population was estimated by

multiplying estimated hospital and physician

expenditures for this population from Step 2 of the

hospital section, above, by the fraction of total NHA

hospital and physician expenditures dedicated to

physicians only.

Step 3: Removing NHA physician

expenditures paid by other private sources

Physician expenditures paid by other private sources

in the NHA were also subtracted from NHA physician

expenditures. In the NHA, other private sources of

payment represent primarily charity and philanthropy not

directly attributable to services for specific patient and

other nonpatient revenues. There is no directly

corresponding equivalent to these sources in NMES, so

this source of payment had to be subtracted from NHA

expenditures to perform the alignment.

Step 4: Removing publicly financed acute

care physician expenditures from NHA

Medicare, Medicaid, and other public

sources

This adjustment was similar to Step 4 in the hospital

section, above. Each of the public sources (Medicare,

Medicaid, and other public) was multiplied by an

adjustment factor (PPADJUST) that was the ratio of

[NHA physician expenditures paid by public sources

(PPNHA) minus acute care physician expenditures of

the nursing home and ICF/MR population paid by public

sources (PPBACK)] to PPNHA.

Adjustments to NHA Dental

Expenditures

The procedure for estimating dental expenditures of

the nursing home and ICF/MR population, and for

allocating these expenditures across payment sources,

differed from the procedures for hospital and physician

expenditures. Dental expenditures in NHA categorized

19
as paid by other private sources were also removed from

the NHA total.

Step 1: Estimating total dental

expenditures for the nursing home and

ICF/MR populations

The total dental expenditures of the nursing home

and ICF/MR populations were estimated by multiplying

total NHA dental expenditures by the fraction of the

NHA population that was in nursing homes and

ICF/MRs. These values were then subtracted from NHA

total dental expenditures to obtain a net value. The

reported NHA value of dental expenditures for each of

the five sources of payment was multiplied by the ratio

of the value of NHA dental expenditures (net of the

nursing home and ICF/MR populations) to the NHA

total value of dental expenditures.

Step 2: Removing NHA dental

expenditures paid by other private sources

Dental expenditures paid by other private sources

were also subtracted from NHA dental expenditures.

Adjustments to NHA Other

Professional Health Care

Expenditures

Adjustments to NHA other professional

expenditures were similar to the NHA physician

expenditure adjustments documented previously, with

the following exceptions.

Step 1: Estimating privately paid acute

care other professional expenditures for

the nursing home and ICF/MR population

Other professional health care expenditures for the

nursing home and ICF/MR population paid by private

sources (private health insurance or out of pocket) were

estimated by multiplying the aged NMES hospital

private-pay estimate for this population from Step 1 of

the Adjustments to NHA Hospital Expenditures section

by the ratio of total NHA other professional health care

expenditures to total NHA hospital expenditures in a

given year. It is assumed that the ratio of other

professional expenditures to hospital expenditures is the

same in the aged NMES population as in the excluded

population. The fraction of these expenditures paid by

each separate private source was estimated by the ratio

of NHA other professional expenditures paid by each

respective source (private health insurance or out of

pocket) to NHA other professional expenditures paid

from private sources for a given year.

Step 2: Estimating total acute care other

professional expenditures for the nursing

home and ICF/MR population

The other professional expenditure value for the

nursing home and ICF/MR population was estimated by

multiplying the total NHA other professional health care

value by the fraction of NHA total hospital and

physician expenditures attributed to the nursing home

and ICF/MR population.

Step 3: Removing NHA other professional

expenditures paid by other private sources

Other professional expenditures paid by other

private sources were also subtracted from NHA other

professional expenditures. The rationale for this

adjustment is explained in Step 3 of the Adjustments to

NHA Physician Expenditures section.

Step 4: Removing publicly financed acute

care other professional expenditures from

NHA Medicare, Medicaid, and other public

sources

This adjustment was similar to Step 4 in the

sections on adjustments to hospital expenditures and

adjustments to physician expenditures. Each of the

public sources (Medicare, Medicaid, and other public)

was multiplied by an adjustment factor (POPADJUST)

that was the ratio of [NHA other professional

expenditures paid by public sources (POPNHA) minus

other professional acute care expenditures of the nursing

home and ICF/MR population paid by public sources

(POPBACK)] to POPNHA.

20
Adjustments to NHA Home

Health Expenditures

Home health expenditures paid by other private

sources in the NHA were subtracted from NHA home

health expenditures. No other adjustments were made to

home health expenditures in the NHA prior to the

alignment of reweighted NMES expenditures to NHA

targets.

Adjustments to NHA Drugs and

Nondurables Expenditures

The NHA nondurable expenditures include

expenditures for prescription drugs, nonprescription

drugs, and other nondurables. The portion of NHA

nondurable expenditures not covering prescription drugs

was completely removed from NHA nondurable

expenditures. NMES did not collect data on over-thecounter medications, and most other nonprescription

nondurables were out of scope for NMES. The NHA

prescription drug expenditures were, however, adjusted

for estimated purchases by the nursing home and

ICF/MR populations.10

Step 1: Estimating total prescription

expenditures for the nursing home and

ICF/MR populations

The total expenditures on prescription drugs for the

nursing home and ICF/MR population were estimated

by multiplying total NHA prescription drug

expenditures by the ratio of nursing home and ICF/MR

hospital and physician expenditures to total NHA

hospital and physician expenditures. This result was

subtracted from total prescription drug expenditures to

obtain a net NHA prescription expenditure value.

10It is likely that this adjustment overcorrects for the

prescription purchases of the nursing home and ICF/MR

population. Many residents may have purchased their

prescription drugs from the institution in which they resided

rather than directly from retail pharmacy outlets. If so, then

some portion of these expenditures had already been removed

from National Health Expenditures with the removal of

nursing home expenditures and non-NMES hospital

expenditures. 

Step 2: Removing prescription drug

expenditures of the nursing home and

ICF/MR populations from each private

and public payment source

The reported NHA value of prescription drug

expenditures for each of the five sources of payment

was multiplied by the ratio of the value of NHA

prescription drug expenditures (net of the nursing home

and ICF/MR populations, from Step 1 of this section) to

the NHA total value of prescription drug expenditures. 

Adjustments to NHA Durable

Medical Goods Expenditures

Adjustments to NHA durable medical goods

expenditures were similar to the NHA physician

expenditure adjustments documented above, with the

following exceptions.

Step 1: Estimating privately paid durable

medical goods expenditures of the nursing

home and ICF/MR populations.

The durable medical goods expenditures for the

nursing home and ICF/MR population paid by private

sources (private health insurance or out of pocket) were

estimated by multiplying the privately paid hospital

expenditures for this population (from Step 1 of the

Adjustments to NHA Hospital Expenditures section) by

the ratio of total NHA durable medical goods

expenditures to total NHA hospital expenditures.

The fraction of these expenditures paid by each

separate private source was estimated by the ratio of

NHA durable goods expenditures paid by each source

(private health insurance or out of pocket) to NHA

durable goods expenditures paid from private sources

for a given year.

Step 2: Estimating total durable medical

goods expenditures for the nursing home

and ICF/MR populations

Total expenditures on durable medical goods for the

nursing home and ICF/MR populations were estimated

by multiplying total NHA durable medical goods

expenditures by the fraction of total hospital and

physician expenditures applicable to the nursing home

21
and ICF/MR population. (The numerator of this fraction

is produced in Step 2 of the Adjustments to NHA

Hospital Expenditures section.)

Step 3: Removing NHA durable medical

goods expenditures paid by other private

sources

There were no other private source payments for

durable medical goods expenditures in the National

Health Accounts.

Step 4: Removing publicly financed durable

medical goods expenditures for the nursing

home and ICF/MR populations

This adjustment was similar to Step 4 in the

sections on adjustments to hospital, physician, and other

professional expenditures. Each public source

(Medicare, Medicaid, and other public) was multiplied

by an adjustment factor that was the ratio of [NHA

durable medical goods expenditures paid by public

sources (PDNHA) minus durable medical goods

expenditures of the nursing home and ICF/MR

population paid by public sources (PDBACK)] to

PDNHA.

Per Capita Values

Per capita expenditure values were calculated for

each source of payment in each service category using

the following guidelines for the per capita values based

on NHA data.

The population used to calculate per capita values

for each source of payment was the same across all

service categories but typically differed between the per

capita values based on NMES and NHA data and

differed across payment source categories. 

A low percentage of the medical services utilized

by the non-NMES population was assumed to be paid

by private health insurance or out of pocket. Therefore,

the entire non-NMES population was excluded from the

calculation of per capita expenditures in the out-ofpocket and private health insurance sources of payment.

The nursing home and ICF/MR populations were

assumed to have a high rate of utilization of services,

and a relatively high percentage of these services was

assumed to be paid by Medicare and Medicaid. The rate

of utilization for the remaining non-NMES population

was presumed to be about equal to the rate for the

NMES population. Therefore, only the individuals in

nursing homes and ICF/MRs were excluded from NHA

per capita calculations in the Medicare and Medicaid

sources of payment. The population used in the other

government payment source category was the average of

these two per capita adjustments. This is because the

expenditures for the non-NMES population were

assumed to be paid by other government sources, but

the rate at which the non-NMES population received

assistance from other government sources was assumed

to be lower than the rate for the NMES population.11

11The aging process employed was relatively insensitive to

alternative assumptions underlying the method utilized for

obtaining per capita amounts.

22
U.S. Department of Health and Human Services

Public Health Service

Agency for Healthcare Research and Quality

2101 East Jefferson Street, Suite 501

Rockville, MD 20852

Official Business

Penalty for Private Use $300

AHRQ Pub. No. 02-0009

February 2002

ISBN 1-58763-070-2

ISSN 1531-5673

BULK RATE

POSTAGE & FEES PAID

PHS/AHCPR

Permit No. G-282