Series 13, Number 155 May 2004

Characteristics of

Emergency Departments

Serving HighVolumes

of Safety-net Patients:

United States, 2000
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Burt CW, Arispe IE. Characteristics of emergency departments serving high

volumes of safety-net patients: United States, 2000. National Center for Health

Statistics. Vital Health Stat 13(155). 2004.

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Series 13, Number 155

Characteristics of Emergency

Departments Serving High

Volumes of Safety-net Patients:

United States, 2000

Data From the National Health Care

Survey

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

Hyattsville, Maryland

May 2004

DHHS Publication No. (PHS) 2004-1726
National Center for Health Statistics

Edward J. Sondik, Ph.D., Director

Jack R. Anderson, Deputy Director

Jennifer H. Madans, Ph.D., Associate Director for Science

Lawrence H. Cox, Ph.D., Associate Director for Research

and Methodology

Edward L. Hunter, Associate Director for Planning, Budget,

and Legislation

Michael H. Sadagursky, Associate Director for

Management and Operations

Margot A. Palmer, Director for Information Technology

Phillip R. Beattie, Director for Information Services

Diane M. Makuc, Dr.P.H., Associate Director for Analysis

and Epidemiology

Charles J. Rothwell, Director for Vital Statistics

Thomas McLemore, Acting Director for Health Care

Statistics

Jane F. Gentleman, Ph.D., Director for Health Interview

Statistics

Clifford L. Johnson, Director for Health and Nutrition

Examination Surveys

Division of Health Care Statistics

Thomas McLemore, Acting Director

Thomas McLemore, Deputy Director

Irma Arispe, Ph.D., Associate Director for Science

Catharine W. Burt, Ed.D., Chief, Ambulatory Care Statistics

Branch
Contents

Abstract .................................................................................................. 1

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

Plight of Safety-net Hospitals............................................................................... 1

Identifying High Safety-net Burden EDs ...................................................................... 2

Methods .................................................................................................. 2

Evaluating Safety-net Burden ............................................................................... 3

Emergency Department Characteristics ....................................................................... 3

Analysis ................................................................................................ 4

Results ................................................................................................... 5

Safety-net Burden Hospital ED Characteristics ................................................................. 5

Differences Among Safety-net Hospitals ...................................................................... 6

Relationship Between Safety-net Burden and Receipt of DSH Payments ............................................ 7

Discussion ................................................................................................ 7

Safety-net Characteristics .................................................................................. 7

Role of DSH Payments in ED Safety-net Status............................................................... 10

Limitations............................................................................................. 10

Conclusions .............................................................................................. 11

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

Figures

1. Distribution of hospital emergency departments by percent of visits made by Medicaid or uninsured patients grouped

by safety-net criteria: United States, 2000 ................................................................ 5

2. Percent distribution of hospital emergency departments by safety-net criteria: United States, 2000................... 6

3. Probability that an emergency department has high safety-net burden by geographic region: United States, 2000 ....... 7

4. Probability that a hospital received a Medicaid DSH payment by emergency department safety-net status and

geographic region: United States, 2000................................................................... 9

Tables

1. Number of sample and estimated hospital emergency departments, percent classified as high safety net and 95%

confidence intervals by selected hospital characteristics: United States, 2000 ................................... 13

2. Comparison of characteristics of high and low safety-net burden emergency departments: United States, 2000........ 14

3. Bivariate correlation coefficients between emergency department characteristics and continuous safety-net burden

estimates and amount of Medicaid Disproportionate Share Hospital Program payment received ................... 15

4. Medicaid Disproportionate Share Hospital Program estimates for 2000 by State with geographic region designation,

ranked by State generosity index....................................................................... 16

iii
Objective

This report describes hospital, Characteristics of Emergency

community, and patient factors

associated with emergency Departments Serving High departments (EDs) whose case loads

are driven by ‘‘safety-net’’ populations.

The study also explores the relationship Volumes of Safety-net Patients:

between safety-net burden and receipt

of Medicaid Disproportionate Share United States, 2000

Hospital (DSH) Program funds.

Methods Catharine W. Burt, Ed.D., and Irma E. Arispe, Ph.D., Division of

Linked data were analyzed from the Health Care Statistics

2000 National Hospital Ambulatory

Medical Care Survey (NHAMCS), Area Introduction hospital EDs vary widely in the

Resource File, and reports of Medicaid proportion of visits covered by Medicaid

DSH payments to hospitals. NHAMCS with the 25th percentile at 9 percent and

ED visit data were aggregated to the n Institute of Medicine (IOM) the 75th percentile at 24 percent (5).

hospital ED level (n=376). Hospital study notes that increased Understanding differential safety-net

sampling weights were used to produce Anumbers of uninsured Americans burden among EDs is important for two

national estimates of hospital EDs.

Hospitals were classified into high vs. in a highly price-driven health care reasons. First, because the uninsured are

low safety-net burden based on the market have led to a subset of health more likely to lack a usual source of

percent of ED visits where the expected care providers whose case load includes care, delay seeking care, and not receive

source of payment was Medicaid or large proportions of low-income and needed care, their visits to the ED may

uninsured (self-pay or no charge). High- uninsured patients (1). These high- represent more severe or complicated

and low-burden EDs were compared burden safety-net providers include cases requiring more intensive treatment,

along five domains: hospital public hospital systems, community placing more demand on an already

characteristics; community factors; health centers, and clinics. However, the overburdened system. Second, research

patient mix; diagnosis mix using most likely source of health care for has shown that much of the care

Billings’ profiling algorithm; and vulnerable populations is the Nation’s provided in EDs is uncompensated care

condition severity, visit content, and

emergency departments (EDs). The ED (1,4,6) so that in addition to treating

outcome. is open to all segments of the more complex cases, hospital EDs may

Results population, serving as a primary source not be fully compensated for the care

Approximately one-third of health care for many vulnerable they provide.

(36.1 percent) of U.S. EDs were subgroups including the uninsured, low- This study quantifies the number of

classified as high safety-net burden income underinsured, Medicaid hospital EDs at high risk for serving

providers. Hospitals located in the beneficiaries, patients with special vulnerable populations and describes

South were more likely to have a high needs, individuals in geographically factors associated with high safety-net

ED safety-net burden (61.3%). remote or economically disadvantaged providers. The distribution of Medicaid

High-burden EDs saw a higher communities, race and ethnic minorities, Disproportinate Share Hospital (DSH)

percentage of cases that were either and immigrants. Program payments to high-burden

nonurgent or emergent, but primary The term ‘‘safety-net burden’’ is safety-net providers was examined to

care treatable. EDs high in uninsured used to describe the amount of care explore the extent to which the demands

burden were not necessarily high in provided to Medicaid, uninsured, and of treating high safety-net cases are

Medicaid burden. Fewer than half of

high-burden

payments. Researchers often use the percent of compensate these EDs.

Medicaid and uninsured patients as an

Conclusions indicator of safety-net burden (2–4). Plight of Safety-net

High safety-net burden is not

necessarily offset by public funding.

Because vulnerable populations are

often clustered within communities, Hospitals

The vast majority of EDs that serve

high proportions of uninsured patients

some hospital EDs will be more likely

to have a greater caseload of such

Hospitals with high Medicaid and/or

uninsured caseloads are at higher risk

EDs received DSH other vulnerable populations. offset by publicly funded efforts to

do not receive such compensation. patients. For example, data from the than other hospitals for not being

National Hospital Ambulatory Medical adequately compensated for the care Keywords: Medicaid DSH payments Care Survey (NHAMCS) show that they provide. Medicaid has generally c NHAMCS c health policy

Page 1
Page 2 [ Series 13, No. 155

provided low reimbursement rates while,

at the same time, Medicaid beneficiaries

tend to have more diverse needs and

less access to primary care and specialty

physicians (1). The emergence of

Medicaid managed care compounded the

financial pressures of these hospitals.

During the 1990s, States moved to

managed care to control costs, expand

coverage, and make providers more

accountable for performance and quality

(7). By 1998, over one-half of all

Medicaid enrollees were in managed

care (8). With more Medicaid

beneficiaries moving toward managed

care, safety-net hospital revenues are

less certain. Increased Medicaid

managed care risk plans negatively

affect high safety-net hospitals by

redistributing Medicaid patients to low

safety-net hospitals (2). The effect is to

further reduce revenues available to

high-burden safety-net providers. At the

same time, private payers have become

more aggressive in controlling payment

rates, which puts greater pressure on

hospital revenues (9).

Hospitals serving large proportions

of Medicaid inpatients are eligible to

receive funds from the Medicaid DSH

Program. The Medicaid DSH program

was initiated in 1981 as part of the

Omnibus Budget Reconciliation Act to

establish payment rates that consider

hospitals serving a disproportionate

share of low-income patients (10). In

1997, Medicaid DSH payments from

States and the Federal government

totaled about $16 billion, or 10 percent

of total Medicaid spending (11). In

1998, Medicaid DSH payments totaled

$15 billion, or 7% of total Medicaid

spending (4). Although offsetting some

of the burden faced by these hospitals,

DSH subsidies are not guaranteed. For

example, to help curb Medicaid

spending, the 1997 Balanced Budget Act

(BBA) required a reduction in Medicaid

DSH payments by more than $10 billion

by 2002. In response to the plight of

public hospitals that are dependent on

DSH payments for survival, Congress

passed the Benefits Improvement and

Protection Act (BIPA) of 2002 and

eliminated the biggest Medicaid DSH

cuts planned for 2001 and 2002. BIPA

also raised allotments in States with

very low spending and increased

allotments to public hospitals (2).

Even when DSH payments are

available, not all hospitals receive the

same amount relative to the safety-net

care they provide. States vary widely in

the Medicaid DSH payments provided

to hospitals. In 1997, four States made

no DSH payments, and five States made

an average DSH payment of over $500

per Medicaid or uninsured person in

their State. Research has shown that

with the shrinking base of paying

patients, high safety-net hospitals

increasingly rely on subsidies to cover

operating deficits (12). To survive,

high-burden safety-net hospitals must

increase revenues or reduce costs. This

is not easy when there are an increasing

number of uninsured patients and a

downturn in the economy that limits

revenue from State and local

government subsidies.

During the 1990s in an effort to

reduce costs and increase revenue, many

safety-net hospitals were merged or

closed (2). For those that remained

open, American Hospital Association

data show that many dropped services,

although nonsafety-net hospitals were

more likely to drop services than were

safety-net hospitals. Eliminated services

include Acquired Immunodeficiency

Syndrome (AIDS) services, psychiatric

emergency units, outpatient substance

abuse services, and EDs (2). The closing

of EDs has the effect of shifting patients

to other EDs in the area that are still

open, contributing to increases observed

in both ED crowding and temporarily

diverting ambulances from EDs to other

hospitals in the area (13).

Identifying High Safety-net

Burden EDs

Researchers have identified

safety-net hospitals based on a variety

of factors including ownership

(not-for-profit status), status as a

teaching hospital, geographic location,

hospital revenue share from Medicaid,

or level of uncompensated care.

Zuckerman et al. (2) note that others

have focused on how dependent the

community is on a provider for caring

for the indigent. Together these

definitions suggest that safety-net

provider status is composed of both

hospital and community components (2).

The IOM report defined the health care

safety net as those providers who

organize and deliver a significant level

of health care to uninsured, Medicaid,

and other vulnerable populations and

further defined ‘‘core safety-net’’

providers as those with a legal mandate

to have an ‘‘open door’’ policy

regarding care regardless of ability to

pay (1). For these reasons, this study

focuses on EDs, defines high safety-net

burden based on the compensation of

caseload from Medicaid and the

uninsured, and considers a range of

hospital and community factors in

understanding characteristics associated

with safety-net burden.

Methods

Asecondary analysis of data from

the 2000 NHAMCS ED visit file

was performed to identify

hospital EDs whose caseloads include

large proportions of safety-net patients.

The NHAMCS is a national probability

sample survey of hospital emergency

and outpatient departments conducted by

the Centers for Disease Control and

Prevention (CDC), National Center for

Health Statistics (NCHS) and is aimed

at describing the utilization of

ambulatory care services as well as

characteristics of patients seeking care

and the providers who serve them.

The target universe of the

NHAMCS includes visits made in the

United States to EDs of non-Federal,

short-stay hospitals (hospitals with an

average stay of less than 30 days) or

those whose specialty is general

(medical or surgical) or children’s

general care. A four-stage probability

sample design is used in NHAMCS

(14). The design involves samples of

primary sampling units (PSUs),

hospitals within PSUs, emergency

service areas within hospitals and/or

clinics within outpatient departments,

and patient visits within EDs and/or

clinics. The first-stage sample contains

112 PSUs (geographic units consisting

of counties, county equivalents, or

townships), which are sampled from
Series 13, No. 155 [ Page 3

PSUs in all 50 States and the District of

Columbia. Within the sampled PSUs, a

sample of 600 hospitals was selected

and divided into 16 panels. In any 1

year, only 13 panels are used for data

collection (486 hospitals). In 2000,

94 percent of the sampled hospitals with

EDs participated (a total of 376

responding EDs from 398 hospitals with

24-hour EDs) (15). In hospitals with an

operating ED, hospital staffs were asked

to complete patient record forms for a

systematic random sample of patient

visits occurring during a randomly

assigned 4-week reporting period. Using

the ED patient arrival log, a random

start was made on the first day of the

reporting period with the selection of

every kth log entry thereafter, where k is

the inverse of the sampling fraction such

that a sample of approximately 50 visits

would be obtained. Encounter data

included patient characteristics such as

age, sex, and race, and visit

characteristics such as medical

diagnosis, disposition, expected source

of payment, and diagnostic and

therapeutic services ordered or provided.

The NHAMCS has been approved by

the NCHS Institutional Review Board as

incurring little risk to patients’ rights

because the data are abstracted from

existing medical records and no

identifying information such as patient’s

name or address is collected.

Out of a total of 25,611 sample ED

encounter records abstracted, there were

4,449 records where the expected source

of payment was Medicaid. These cases

include visits covered by the State

Children’s Health Insurance Program

(SCHIP). There were 4,359 records with

the expected pay source recorded as

‘‘self-pay’’ and 71 records with ‘‘no

charge,’’ and these cases are treated as

uninsured within this study. Visit data

were aggregated by hospital to provide

estimates of facility characteristics such

as the percentage of each sampled ED’s

visits with Medicaid and percentage of

visits by uninsured patients.

Sample hospital weights were

applied to provide annual national

estimates. The weights include factors

representing the selection of the PSU

and the hospital within the PSU.

Adjustment factors for hospital

nonresponse and inclusion of hospital

panels each year are also included (15).

Because the estimates presented in this

report are based on a sample rather than

on the entire universe of EDs, they are

subject to sampling variability. Estimates

of sampling error were made using a

Taylor Series approximation as

computed by SUDAAN software (16),

which takes the complex sampling

design into account. In addition to

sampling error, the NHAMCS data are

also subject to nonsampling error such

as omissions, mistakes in reporting, and

processing error. In the 2000 NHAMCS,

the quality control error rate for

diagnosis coding was 1.1 percent.

Evaluating Safety-net

Burden

Two approaches were used for

evaluating hospital ED safety-net

burden.

High vs. low burden—Hospital EDs

were dichotomized into high vs.

low safety-net burden. EDs were

classified as high burden if their

caseload met any one of the

following three criteria: more than

30% of visits with Medicaid as

expected source of payment, more

than 30% of visits with self-pay or

no charge as the expected pay

source (considered uninsured), or a

combined Medicaid and uninsured

patient pool greater than 40% of the

visits.

Of the 376 sample hospitals, 147

were classified as high burden: 53

had greater than 30% of their ED

visits with Medicaid, 45 had greater

than 30% of their visits by

uninsured patients, and 49 had a

combined Medicaid and uninsured

patient pool representing greater

than 40% of their caseload.

Uninsured and Medicaid case

mix—Because high and low

safety-net EDs were found to vary

in terms of their uninsured and

Medicaid burden, the second phase

of analysis analyzed the following

three continuous variables:

percentage of ED visits that were

uninsured, percentage of ED visits

that were covered by Medicaid, and

the total percentage of Medicaid

and uninsured ED visits. Because

the majority of high-burden EDs

were so designated due to a

combined Medicaid and uninsured

burden, continuous variables were

used to examine correlates of these

factors. Dichotomizing the

continuous variables into high- and

low-burden groups masks the

intensity of linear relationships

among the variables.

Emergency Department

Characteristics

Facility characteristics were

measured in five categories: hospital

characteristics; community factors;

patient mix; diagnosis mix using

Billings’ algorithm; and condition

severity, visit content, and outcome.

Hospital characteristics—Hospital

size and location variables included

annual ED visit volume, whether

the hospital was a public hospital

operated by a local or State

government, whether the hospital

was located in a nonmetropolitan

statistical area (non-MSA), whether

the hospital was located in the

southern region of the United States

(South), whether the hospital was

affiliated with a medical school, and

whether the hospital received any

Medicaid DSH payment and amount

received as reported from the most

recent State report located on the

Centers for Medicare and Medicaid

Services (CMS) Web site (17). The

DSH payment was merged with the

NHAMCS data file based on State

and hospital name.

Community factors—Community

factors analyzed included

geographic contextual variables,

which were mostly taken from the

Health Resources and Services

Administration’s (HRSA) Area

Resource File (ARF) (18) and

matched via State and county

Federal Information Processing

Standards (FIPS) codes to the

NHAMCS hospitals. Contextual

variables have been shown to be

related to ED visit characteristics
Page 4 [ Series 13, No. 155

(19). The ARF variables included

income per capita, percent of

population in poverty,

unemployment rate, percent of

population aged 65 years and over,

the number of primary care doctors

practicing per county population,

ED visit rate per 100 population,

and health maintenance organization

(HMO) penetration rate per 100

population.

In addition to community factors

from the ARF, an additional

contextual variable related to the

generosity of the State’s Medicaid

DSH payment policy was analyzed.

This generosity measure was based

on the ratio of the most recently

reported total DSH payments to

hospitals in the State to the total

numbers of uninsured persons and

Medicaid and SCHIP enrollees in

the State. The estimates for the

denominator for the ratio came from

the total of uninsured individuals

based on the 2000 Current

Population Survey (20) and the

number of Medicaid and SCHIP

enrollees from the CMS (21). The

DSH program payment per

Medicaid/SCHIP enrollee or

uninsured person in the State where

the hospital was located was

merged to each hospital record by

State FIPS code.

Patient mix—Patient mix variables

included patient demographics

aggregated from the NHAMCS ED

visit records, such as percentages of

visits by children (under 15 years),

seniors (65 years and over), and

black or African Americans, and

payment sources such as percentage

of visits by Medicare patients. The

percentage of Medicaid visits for

each ED where the patient was in a

risk-based plan as opposed to a

fee-for-service plan was also

included. Risk-based was

determined by whether the visit had

both Medicaid and HMO indicated

on the patient record form.

Diagnosis mix—NHAMCS

diagnosis data for each sampled

visit, coded to the International

Classification of Diseases, 9th

revision, Clinical Modification (22),

were used to classify cases

according to profiling algorithms

developed by John Billings et al.

and based on the concept of

‘‘ambulatory care sensitive’’ (ACS)

conditions (23–26). The original

Billings algorithm, based on expert

physician review of clinical

information from patient records in

New York City, classifies cases in

terms of urgency with which the

case should be seen in the ED and

avoidability (the extent to which the

visit could have been avoided with

adequate primary care). Aggregated

across all visits to the ED, the

algorithm parses the caseload of

visits into several different

categories. The algorithm used in

this study consists of the following

eight categories:

+ Nonemergent (NE) (e.g., toothache,

back pain, ingrown toenail, eczema,

and attention to dressings)

+ Emergent-primary care treatable

(EPCT) (e.g., nosebleed, abdominal

pain/cramps, acute bronchitis, and

painful breathing)

+ Emergent but possibly preventable

with good primary care (EDCNPA)

(e.g., asthma, cellulitis, emphysema,

epilepsy, and pelvic inflammatory

disease)

+ Emergent and not avoidable with

good primary care (EDCNNPA)

(e.g., heart attack, appendicitis,

occlusions, kidney stone, and chest

pain)

+ Injury related (INJURY) (e.g.,

fractures, sprains, poisoning, and

contusions)

+ Mental health related (PSYCH)

(e.g., depression, anxiety, and

bipolar disorder)

+ Alcohol-related diagnoses

(ALCOHOL) (e.g., elevated blood

alcohol, alcohol abuse, alcoholic

cardiomyopathy, and blood alcohol

tests)

+ Unclassified (UNCLASSIFIED)

diagnoses not falling into one of the

other categories (e.g., abnormal

blood chemistry, enlarged heart, and

wheezing)

The drug-related diagnoses category

in the algorithm was not used because

the NHAMCS sample size is too small

to reliably estimate such rare conditions.

Condition severity, visit content, and

outcome—Visit characteristics

included percentage of patients

arriving by ambulance; percentage

triaged as emergent or urgent; mean

waiting time to see a physician;

percentage of visits where the

patient was seen by a resident or

intern; percentage of cases with

intravenous (IV) fluids

administered; average number of

drugs prescribed per visit (drug

mention rate); and percentage of

visits with each of the following

disposition options: admitted to

inpatient status, left before being

seen, transfer to another facility, and

no followup planned.

Data on the inpatient payer mix are

not collected in the NHAMCS.

Because a hospital’s inpatient payer

composition is critical to the

determination of DSH payments,

proxy variables were needed for the

analysis. Although not entirely

reflective of the inpatient

composition, the percentages

admitted from the ED that were

Medicaid or uninsured were used as

proxy measures for the hospital’s

inpatient safety-net burden.

Analysis

Analysis included SUDAAN

chi-square tests of association between

the safety-net status of hospital EDs and

hospital facility characteristics such as

geographic region, MSA status,

ownership, and ED annual volume. One

hospital was excluded from further

analysis because the majority of visits

were for mental health, drug, and

alcohol conditions and appeared to be

an outlier for the analysis. Student

t-tests were used to evaluate the

observed differences between prevalence

of characteristics describing high and

low safety-net hospitals. Bivariate

correlations were computed for each of

the variables studied with the combined

percentage of ED visits that were made

by Medicaid enrollees and persons with

no insurance (combined burden), with

percentage of ED visits by Medicaid
patients (Medicaid burden), and

percentage of ED visits by uninsured

patients (uninsured burden) using

SUDAAN.

Results

Safety-net Burden Hospital

ED Characteristics

Hospital EDs vary widely in the

proportion of cases that are by

uninsured and Medicaid patients with

13 percent of EDs having over half their

caseload comprised of these vulnerable

populations. Approximately one-third

(36.1 percent) of U.S. EDs had a high

safety-net burden. This corresponds to

approximately 1,770 hospital EDs with

high safety-net burden (95% confidence

interval: 1,344–2,197). The distribution

of safety-net burden is positively

skewed with most hospitals having a

relatively small burden, but a few

hospitals having a high burden whether

it is for Medicaid or for uninsured

patients. The distribution of hospital

EDs by their percentage of combined

Medicaid and uninsured cases shows

great variability across EDs (figure 1).

Figure 2 shows the distribution of

hospital EDs by high and low burden.

High-burden EDs are further

subclassified by their composition of

Medicaid and uninsured cases. EDs that

were high in percentage of Medicaid

cases were not necessarily high in

percentage of uninsured (χ2 =.96, df=1,

p=.333). In total, 9.4% of hospitals were

classified as high burden because more

than 30% of their ED cases were

covered by Medicaid, and 7.7% had

more than 30% of their cases from

uninsured patients. The largest category

of high safety-net hospitals had more

than 40% of visits from the combination

of Medicaid or uninsured cases. Two

percent of hospitals in the sample had

both a high Medicaid and a high

uninsured burden, where each

population comprised more than 30% of

visits.

Table 1 shows sampled EDs and the

percentage of EDs that fell into the high

safety-net status by selected hospital

characteristics. The majority of hospital

characteristics were not associated with

safety-net burden status. Geographic

region was associated with burden status

with 61.3 percent of EDs located in the

South classified as high burden (χ2

= 20.0, df=3, p<.001). Figure 3 depicts

this graphically, showing the States in

each region with the corresponding

probability that an ED in each region is

part of the high safety-net group.

High safety-net burden designation

was also associated with whether the

hospital received DSH payments in

2000 (χ2 =5.2, df=1, p=.028). About

half of hospitals receiving Medicaid

DSH payments fell into the category of

high burden (47.7%). However, of those

hospitals not receiving payments, about

a third had high safety-net burden EDs

(29.7%).

Table 2 contrasts high and low

safety-net burden hospital EDs.

Consistent with the hospital domain

findings presented in table 1, the

majority of EDs with high burden were

located in the South (65.2 compared

with 23.3 percent among low-burden

EDs). Less than one-half of all high

safety-net EDs received some DSH

payment (41.0 percent). One-quarter of

low-burden EDs also received DSH

payments. However, the median

Medicaid DSH amount was significantly

higher for high-burden hospitals (43%

higher).

Several of the community factors

were associated with high safety-net

burden, most notably the percentage of

population in poverty and the

unemployment rate. As was the case

with median Medicaid DSH payment,

the State’s ratio of total DSH payment

per Medicaid/SCHIP enrollee or

Figure 1. Distribution of hospital emergency departments by percent of visits made by

Medicaid or uninsured patients grouped by safety-net criteria: United States, 2000

Series 13, No. 155 [ Page 5
uninsured person was significantly

higher in high-burden EDs compared

with low-burden EDs ($204 versus $148

per uninsured or Medicaid/SCHIP

individual, or about 30% higher).

High safety-net EDs have a higher

proportion of visits made by children

and black or African American patients,

but a smaller proportion of visits by

persons 65 years and over and,

therefore, fewer Medicare cases. The

average high safety-net ED has a

combined Medicaid and uninsured

patient burden of 51.0 percent compared

with 23.5 percent in low safety-net EDs.

There was no association between

safety-net burden and the percentage of

Medicaid visits from patients with

risk-based Medicaid coverage.

Of the eight Billings algorithm

categories used to determine the urgency

and avoidability of ED visits, only a few

were associated with safety-net burden

status. High-burden EDs had higher

percentages of nonurgent and urgent, but

primary care treatable cases. Visit

characteristics studied include variables

related to severity, treatment, and case

disposition. High-burden EDs had a

higher percentage of cases seen by

residents/interns, cases that left without

being seen, and a higher share of cases

admitted from the ED that were

Medicaid. Low-burden EDs had a higher

percentage of cases where IV fluids

were administered and where the patient

was either admitted or transferred.

Differences Among

Safety-net Hospitals

Analyzing high versus low

safety-net hospitals revealed that the

composition of Medicaid and uninsured

case mix varied by hospital for the high

safety-net burden EDs. To better

understand these ‘‘within group

differences,’’ the second phase of this

study involved three continuous

variables: percentage of ED visits

covered by Medicaid, percentage of ED

visits by uninsured, and percentage of

ED visits by either Medicaid or

uninsured. The bivariate correlation

between the percentage of ED visits by

Medicaid patients and the percentage by

uninsured patients was not significant

(r=.10) supporting the independence

observed with the dichotomized

safety-net variable. However, the

correlation between each of these

continuous variables and the percentage

of visits made by either Medicaid or

uninsured patients in the ED was .74

(table 3).

The bivariate correlations for the 40

ED characteristics studied and the

continuous variables of Medicaid

burden, uninsured burden, and combined

Medicaid and uninsured burden are in

table 3. Significant correlations (p<.01)

are in bold type.

Four study variables were positively

related to higher percentages for both

Medicaid and uninsured: being located

in the South, generosity index for the

State’s DSH payment, percentage of

cases that were nonurgent, and

percentage of ED visits by black or

African American patients. Six other

variables were negatively associated

with both percentage of Medicaid and

uninsured burden: percentage of county

population that were seniors, rate of

primary care physicians per population,

percentage of visits made by seniors,

percentage of visits by patients on

Medicare, percentage of ED visits that

were emergent but not avoidable, and

percentage of ED cases admitted to the

hospital.

Hospital EDs with higher

concentrations of uninsured patients

differed from those with higher

concentrations of Medicaid patients in

several ways. Those with a higher

uninsured burden had a larger

percentage of uninsured admissions, a

longer mean waiting time, and a higher

percentage of cases that left without

being seen. They also had a lower

percentage of emergent cases that were

avoidable with good primary care. In

contrast, those with higher Medicaid

concentrations were more likely to be in

impoverished communities with higher

unemployment rates, lower income, and

a higher ED utilization rate. Higher

Medicaid-burden EDs also had more

visits by children, had more Medicaid

admissions, and were more likely to

receive a DSH payment. They also had

Figure 2. Percent distribution of hospital emergency departments by safety-net criteria:

United States, 2000

Page 6 [ Series 13, No. 155
Series 13, No. 155 [ Page 7

Figure 3. Probability that an emergency department has high safety-net burden by geographic region: United States, 2000

a higher percentage of emergent,

primary care treatable cases and a lower

percentage of injury cases.

Relationship Between

Safety-net Burden and

Receipt of DSH Payments

The last column in table 3 shows

the bivariate correlations between each

of the characteristics studied and the

State’s 2000 or recent Medicaid DSH

payment to the hospital. The largest

bivariate correlation is with annual ED

volume (r=.32). Examining the other

correlations in table 3 with ED volume

shows that it is not related to Medicaid,

uninsured, or combined burden in the

ED. However, there is a slight positive

relation found between amount of DSH

payment received by the hospital and

the percent of patients admitted from the

ED that are Medicaid enrollees (r=.12).

This characteristic is the only variable in

this study that approaches the criteria

upon which Medicaid DSH payments

are based (i.e., inpatient Medicaid

burden).

Discussion

Safety-net Characteristics

Approximately one-third of our

Nation’s EDs serve high relative

proportions of uninsured and Medicaid

patients. Although scattered over the 50

States and the District of Columbia, they

are most likely to be located in southern

States. The South accounts for about

one-third of all non-Federal, general,

and short-stay hospital EDs in the

United States, but accounts for

two-thirds of the EDs with heavy

combined Medicaid and uninsured

patient burden. High-burden EDs are

located in areas with high poverty and

unemployment and treat a higher mean

percentage of visits by children and

African Americans. Their diagnosis mix

includes higher mean percentages of

cases that are nonurgent or urgent, but

primary care treatable. High-burden EDs

have higher mean percentages of visits

where patients leave without being seen.

They also have a higher mean

percentage of patients seen by residents

or interns and more Medicaid cases

admitted to the hospital.

In contrast, low safety-net burden

EDs have a higher percentage of seniors

and a higher mean percentage of visits

covered by Medicare. Their case mix

appears to reflect a higher severity,

including higher percentages of

emergent unavoidable conditions,

injuries, and cases where IV fluids are

administered. These EDs also have a

higher mean percentage of ED cases

admitted to the hospital.

The diagnosis mix studied here

using the Billings algorithm showed that

high-burden EDs were more likely to

have higher percentages of visits for

nonurgent conditions and primary care

treatable conditions, but less likely to

have higher percentages of unavoidable

emergent conditions and injury

conditions (table 2). Other studies have

shown that Medicaid and uninsured
Page 8 [ Series 13, No. 155

Characteristics of high safety-net burden emergency departments:

+ Comprised mostly of Medicaid or uninsured cases, but rarely high in both. Often has a moderate amount of

each.

+ Has a 40% chance of receiving some Medicaid DSH payments. If received, the average payment is $1.5

million.

+ Located in a State with a more generous DSH payment policy.

+ Three times more likely to be located in the South.

+ Community is likely to have:

o lower income per capita

o higher percentage below poverty level

o higher unemployment rate

o lower percentage of seniors

o fewer primary doctors per capita

+ Emergency department patient mix has:

o more children

o fewer seniors

o more black or African American patients

+ Emergency department payer mix has:

o 31% fewer Medicare patients

o average of 26% Medicaid patients

o average of 25% uninsured patients

+ Inpatient payer mix has:

o 22% Medicaid recipients

o 10% uninsured patients

+ Emergency department diagnosis mix has:

o 25% more nonurgent cases presenting

o 10% more emergent conditions presenting that are primary care treatable

o 14% fewer unavoidable emergent conditions presenting

o 14% fewer injury conditions presenting

+ Treatment in emergency department indicates:

o more likely to utilize residents or interns

o less likely to need the use of intravenous fluids

+ Emergency department disposition indicates:

o 50% more likely to have patients leave without being seen

o less likely to transfer or admit patients

patients comprise a disproportionate patients comprise a higher proportion of conditions that were avoidable with

share of ED visits for avoidable ED care ACS conditions (28). It seems preventive care were not different

such as chronic ACS conditions (asthma, reasonable that hospital EDs with high between high and low safety-net

chronic obstructive lung disease, proportions of Medicaid and uninsured hospitals.

congestive heart failure, diabetes patients would have higher percentages Analysis shows that there is some

mellitus, and hypertension), which is not of visits by patients with these kinds of variability among high safety-net burden

explained by a higher prevalence or conditions. However, table 2 showed hospitals with respect to their

disease severity (27) and that Medicaid that the mean percentages of emergent composition of Medicaid and uninsured
Series 13, No. 155 [ Page 9

Figure 4. Probability that a hospital received a Medicaid DSH payment by emergency department safety-net status and geographic region:

United States, 2000

Characteristics not related to safety-net burden in the

emergency department:

+ Annual volume of visits

+ Public ownership

+ Whether located in a metropolitan statistical area

+ Being affiliated with a medical school

+ Annual emergency department utilization rate in the community

+ Health maintenance organization penetration rate in the community

+ Emergency department mix of Medicaid patients in a risk-based plan

+ Inpatient mix of uninsured patients

+ Emergency department diagnosis mix:

o Percentage of visits with emergent, but avoidable, conditions

o Percentage of mental health or alcohol-related visits

+ Percentage arriving by ambulance

+ Percentage triaged as urgent or emergent

+ Length of waiting time to see physician

+ Number of drugs prescribed

+ Percentage of cases with no followup planned

cases. Most of the high safety-net

hospitals were classified as high burden

because the sum of the uninsured and

Medicaid percentages exceeds 40% and

not because the ED was high (>30%) in

both Medicaid and uninsured patients.

The hospitals with high numbers of

Medicaid visits are also more likely to

be high in visits by children (r=.42).

CMS reports that children under age 18

represent about half of Medicaid

enrollees. As expected, high Medicaid

EDs were likely to have a higher

percentage of Medicaid admissions

leading, in turn, to higher DSH

payments.

Almost 8% of hospitals were

classified as high safety-net because

their ED case mix consisted of more

than 30% of uninsured cases. These

hospitals had a higher percentage of

admissions by the uninsured, a longer

mean waiting time, and a higher
Page 10 [ Series 13, No. 155

percentage of patients who left without

being seen. Because of the structure of

the DSH program, these hospitals are

less likely to receive public

compensation for safety-net burden.

Role of DSH Payments in

ED Safety-net Status

Analysis shows that fewer than half

of high-burden EDs received any recent

DSH payment, yet almost one-third of

low-burden EDs also received such

payments. However, the median amount

received by hospitals with high-burden

EDs was almost $1.5 million, an amount

42% higher than the $850,000 received

by the average low-burden ED. Most at

risk are those high safety-net burden

hospitals which, because their EDs serve

high concentrations of uninsured, are

largely unable to benefit from the

Medicaid DSH program. Results showed

that among EDs with high uninsured

burden, only 36% received a Medicaid

DSH payment, whereas about half of the

EDs with high Medicaid burden

received a payment (47%).

Medicaid DSH payments are

formulated on several factors related to

hospital inpatient care such as Medicaid

Inpatient Utilization Rate (MIUR),

percentage of revenue from MIUR, and

hospitals with low income utilization.

Section 701(b) from BIPA requires

States to provide DSH payment for

some criteria and allows States to

provide payment for other criteria. But

whether the ED serves a high proportion

of Medicaid and uninsured patients is

not one of the criteria for either

mandated or optional DSH payment.

There is great regional variability in

payments received by those hospitals

that benefit from DSH payments.

Table 4 presents the 2000 or most recent

State DSH payments reported and ratios

used in this analysis in descending order

of the State’s generosity as indicated by

the ratio of the DSH payment to the

numbers of uninsured and Medicaid/

SCHIP enrollees. The 2000 reports were

only available for about half of the

States so 1998–99 reports were used

assuming that the 2000 payments were

similar. The majority of States in the

Northeast have DSH ratios greater than

Characteristics of emergency departments whose hospitals

receive Medicaid DSH payments:

+ More likely to be located in a State with a generous Medicaid DSH policy

+ 10% more likely to be affiliated with a medical school

+ Emergency department mix:

o 22% more children

o 23% fewer seniors

o Twice the percent of black or African American patients

+ Emergency department payer mix:

o 20% Medicaid patients (represents a 32% higher Medicaid burden

compared with hospitals that did not receive a DSH payment)

o 18% uninsured patients (not different from hospitals that did not

receive DSH payments)

+ Emergency department disposition indicates:

o 37% less likely to transfer cases

o 57% more likely to have patients leave without being seen

$300 compared with other regions. In

contrast, approximately 20 percent of the

States in the South have DSH payment

ratios over $300. The majority of States

in the Midwest and the West have ratios

less than $100. The southern States have

made strides to increase their DSH

payments so that the majority of them

had DSH ratios between $100 and $300

based on the most recent reports.

Table 4 also shows the variation across

States in the percentage of Medicaid

expenditures spent on DSH payments to

hospitals.

Figure 4 shows the probability of

hospitals receiving any DSH payment

broken down by geographic region and

whether the hospital is in the high or

low safety-net group. Hospitals in the

West have the greatest difference in that

probability based on safety-net status.

The distinction in the South is the

smallest in the Nation where low

safety-net hospitals have a probability

almost equivalent to the hospitals in the

high safety-net group. However, the

southern hospitals in the high safety-net

group (which is the majority in the

Nation), have the lowest probability of

receiving any DSH payment (PR=.33).

Hospitals located in the South and West

are also at risk of serving a higher

proportion of uninsured patients than

Medicaid patients. Studies have shown

that the southern and western regions of

the country have twice the rate of

uninsured persons to Medicaid enrollees

under age 65 (4). The rate of Medicaid

enrollees is fairly equivalent across all

four census regions (4).

Limitations

Limitations of this study include

that the variability surrounding the

aggregated hospital estimates was not

taken into account, only the variability

among sampled hospitals. Because ED

visits are sampled for a 4-week

reporting period, the estimates for any

given hospital may be affected by

seasonality of conditions seen.

Notwithstanding, a sensitivity analysis

on the number of visits used in each

hospital to produce the aggregated

statistics was robust to sample size of

the visits. Nonsampling error may be

related to the expected source of

payment item where some self-pay

patients may have some kind of

insurance, but it was incorrectly entered

into the hospital computer at the time of

arrival. Another limitation of the

NHAMCS for studying factors

associated with high safety-net use is

that it does not collect any financial

information from the hospital. Because

the sample was drawn from the 1991
Series 13, No. 155 [ Page 11

SMG, its results do not generalize to

new hospitals that were not existent in

1991, but were in 2000. The DSH

payments came from the CMS reports

and may include some error in

reporting. Similarly, the actual DSH

payments for 2000 may be different for

those States where the 1998 or 1999

report was used. Finally, to define

uninsured, the expected source of

payment categories of ‘‘self-pay’’

(N=4,359 visit records) and ‘‘no

charge’’ (71 visit records) were used.

Visit data were aggregated by hospital

to provide estimates of facility

characteristics such as the percent of

each sampled ED’s visits by the

uninsured. Some proportion of the

self-pay records are probably for

patients who do have health insurance,

but who pay out of pocket.

Conclusions

This study examined the

distribution of hospital EDs by

their likelihood of having a large

caseload of patients from vulnerable

populations. The fact that one-third of

hospital EDs rely heavily on uninsured

and/or Medicaid patients places these

institutions at risk for financial viability.

With evermore restrictions on Medicaid

payments (29), such hospitals are less

able to shift costs to cover

uncompensated care that the Emergency

Medical Treatment and Active Labor

Act legislation demands (30). Reliance

on subsidy income from the Medicaid

DSH program helps less than half of

high safety-net hospitals, and the

amount of help varies greatly by State.

High-burden EDs tend to be located in

areas of poverty and relatively higher

unemployment making local resources

scarce for helping these hospitals stay

open.

References

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Table 1. Number of sample and estimated hospital emergency departments, percent classified as high safety net and 95% confidence

intervals by selected hospital characteristics: United States, 2000

Hospital characteristic

Emergency departments

Raw

sample number

Estimated

number

Percent with

high safetynet burden1

95%

confidence

interval

All hospital emergency departments . . . . . . . . . . . . . 376 4,904 36.1 27.4, 44.8

Geographic region2

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 702 24.9 13.8, 36.0

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 1,428 15.9 7.2, 24.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 1,884 61.3 47.9, 74.7

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 890 24.0 5.6, 42.4

MSA status3

MSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 2,756 38.5 30.2, 46.8

Non-MSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 2,148 33.1 17.2, 49.0

Ownership

Not for profit . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 2,890 30.0 21.6, 38.4

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 1,401 47.4 18.6, 76.2

Proprietary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 613 39.3 18.5, 60.1

Emergency department volume

Small (less than 15,000) . . . . . . . . . . . . . . . . . . . . 70 2,169 37.4 21.1, 53.7

Medium (15,000–50,000) . . . . . . . . . . . . . . . . . . . 216 2,288 32.7 25.3, 40.1

Large (more than 50,000) . . . . . . . . . . . . . . . . . . . 90 447 47.2 35.7, 58.7

Medical school affiliation4

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 1,120 39.6 31.1, 48.0

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 3,619 35.4 24.6, 46.1

Any Medicaid DSH payment4,5,6

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 1,398 47.7 36.6, 58.8

No . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 3,250 29.7 19.5, 39.9

1High safety-net burden is defined as an emergency department (ED) with more than 30% of visits by Medicaid patients, more than 30% of visits by uninsured patients, or combined Medicaid and

uninsured percentages of more than 40%.

2Significant chi-square (p=.001).

3MSA is metropolitan statistical area.

4Medical school affiliation and Medicaid Disproportionate Share Hospital Program payment information was missing for a few hospital EDs.

5DSH is Disproportionate Share Hospital Program.

6Significant chi-square (p < .05).

Series 13, No. 155 [ Page 13
Page 14 [ Series 13, No. 155

Table 2. Comparison of characteristics of high and low safety-net burden emergency departments: United States, 2000

Ratio of

High safety- Low safety- HSN/LSN1

Emergency department characteristic net burden1 net burden burden Significance

Raw number of sample emergency departments ........ 146 229 . . . . . .

Hospital factors

Annual emergency department volume .............. 23,950 21,440 1.12 NS

Percent:

Public ownership .......................... 37.6 23.5 1.60 NS

Located in a non-MSA area2 ................... 40.2 45.9 0.87 NS

Located in the South ........................ 65.3 23.3 2.80 ‡‡

Medical school affiliation ..................... 25.7 22.5 1.14 NS

Any Medicaid DSH payment received3 ............. 41.0 25.2 1.63 ‡

Median Medicaid DSH amount3,4 ................. $1,474,897 $844,842 1.75 ‡

Community factors5

Income per capita ........................... $ 23,980 $ 25,970 0.92 ‡

Mean percentage:

Poverty ................................ 16.5 12.5 1.33 ‡‡

Unemployed ............................. 5.2 4.1 1.27 ‡‡

65 years and over ......................... 12.4 14.5 0.86 ‡

Primary care physicians per population .............. 52.5 67.0 0.78 ‡

Emergency department visit rate .................. 43.6 40.2 1.08 NS

HMO penetration rate6 ........................ 18.2 22.2 0.82 NS

State’s DSH payment ratio3,7 .................... 203.9 148.1 1.38 ‡

Patient and payer mix

Mean percentage visits by:

Children ............................... 25.2 18.7 1.35 ‡‡

Seniors ................................ 12.4 19.8 0.63 ‡‡

Black or African Americans .................... 26.4 10.9 2.42 ‡‡

Medicare patients .......................... 13.1 19.0 0.69 ‡‡

Medicaid ............................... 26.3 11.8 2.23 ‡‡‡

Uninsured .............................. 24.7 11.7 2.11 ‡‡‡

Combined Medicaid and uninsured ............... 51.0 23.5 2.17 ‡‡‡

Mean percentage of Medicaid visits with a risk plan ...... 15.1 10.5 1.44 NS

Diagnosis mix

Mean percentage visits for various conditions:

Nonurgent .............................. 21.2 16.9 1.25 ‡‡

Emergent, primary care treatable ................ 21.3 19.3 1.10 ‡‡

Emergent, but possible avoidable ................ 7.3 8.1 0.90 NS

Emergent, but unavoidable .................... 10.7 12.4 0.86 ‡

Injury ................................. 28.1 32.8 0.86 ‡‡

Mental health ............................ 1.9 2.0 0.95 NS

Alcohol related ........................... 0.6 0.7 0.86 NS

Unclassified ............................. 9.0 7.8 1.15 NS

Condition severity, visit content, and outcome

Mean percentage visits:

Arrival by ambulance ....................... 12.1 14.1 0.86 NS

Triaged as emergent or urgent ................. 51.1 54.9 0.93 NS

Seen by a resident or intern ................... 8.1 3.7 2.21 ‡‡

Intravenous fluids administered ................. 13.2 18.7 0.70 ‡‡

Left before being seen ...................... 1.8 1.2 1.50 ‡

Transfered to another facility ................... 2.2 3.2 0.68 ‡

No followup planned ........................ 11.3 10.0 1.14 NS

Admitted to hospital ........................ 9.2 13.9 0.66 ‡‡

Medicaid admittance ........................ 22.2 6.7 3.31 ‡‡

Uninsured admittance ....................... 10.2 7.1 1.44 NS

Mean waiting time (in minutes) to see physician ........ 39.1 34.2 1.14 NS

Mean drug mention rate ....................... 1.5 1.6 0.94 NS

. . . Category not applicable.

‡ p <.05.

‡‡ p < .01.

‡‡‡ Variable used in the definition of safety-net burden status.

1High safety-net hospitals defined as those whose emergency department case load is more than 30% Medicaid, more than 30% uninsured, or more than 40% combined Medicaid and uninsured.

2MSA is metropolitan statistical area.

3DSH is Medicaid Disproportionate Share Hospital Program.

4Median DSH payment received by hospitals that received any DSH payment.

5Contextual variables are from the HRSA’s Area Resource File (1999) matched by county location of hospital with the exception of State’s DSH payment ratio which is calculated from the State reports

to CMS.

6HMO is health maintenance organization.

7This is also referred to as State generosity index.

NOTE: HSN is high safety-net, LSN is low safety-net, and NS is not significant.
Series 13, No. 155 [ Page 15

Table 3. Bivariate correlation coefficients between emergency department characteristics and continuous safety-net burden estimates and

amount of Medicaid Disproportionate Share Hospital Program payment received

State’s 2000 or recent

Combined Medicaid Medicaid Uninsured Medicaid DSH2

Emergency department characteristic and uninsured burden burden burden payment to hospital

Raw number of sample emergency departments ........ 375 375 375 359

Hospital factors Correlation coefficient

Annual emergency department volume .............. 0.12 0.00 0.18 0.32

Percent:

Public ownership .......................... 0.10 0.04 0.10 0.08

Located in a non-MSA area1 ................... -0.09 0.02 -0.16 -0.14

Located in the South ........................ 0.44 0.23 0.42 -0.04

Medical school affiliation ..................... -0.04 -0.05 -0.01 -0.23

Any Medicaid DSH payment received2 ............. 0.20 0.20 0.10 0.30

Medicaid DSH amount2 ....................... 0.15 0.12 0.10 1.00

Community factors3

Income per capita ........................... -0.14 -0.21 0.00 0.15

Percent:

Poverty ................................ 0.44 0.46 0.20 0.03

Unemployed ............................. 0.31 0.40 0.07 0.00

65 years and over ......................... -0.34 -0.20 -0.30 -0.06

Primary care physicians per population .............. -0.25 -0.20 -0.16 -0.06

Emergency department visit rate .................. 0.13 0.18 0.02 0.07

HMO penetration rate4 ........................ -0.08 -0.11 -0.02 0.13

State’s DSH payment ratio2,5 .................... 0.27 0.25 0.15 0.15

Patient and payer mix

Percentage of visits by:

Children ............................... 0.29 0.42 0.01 0.03

Seniors ................................ -0.53 -0.41 -0.38 -0.17

Black or African Americans .................... 0.43 0.29 0.36 0.17

Medicare patients .......................... -0.43 -0.31 -0.32 -0.12

Medicaid ............................... 0.74 1.00 0.10 0.12

Uninsured .............................. 0.74 0.10 1.00 0.10

Combined Medicaid and uninsured ............... 1.00 0.74 0.74 0.15

Percentage of Medicaid visits with risk plan ........... 0.09 0.07 0.07 0.05

Diagnosis mix

Percentage of visits for various conditions:

Nonurgent .............................. 0.36 0.22 0.31 0.02

Emergent, primary care treatable ................ 0.18 0.22 0.05 0.01

Emergent, avoidable ........................ -0.20 -0.05 -0.25 0.01

Emergent, not avoidable ..................... -0.22 -0.17 -0.16 -0.06

Injury ................................. -0.19 -0.19 -0.09 -0.14

Mental health ............................ 0.03 0.08 -0.04 0.21

Alcohol ................................ -0.01 -0.05 0.04 0.12

Unclassified ............................. 0.03 0.02 0.02 0.13

Condition severity, visit content, and outcome

Percentage of visits:

Arrive via ambulance ....................... -0.15 -0.18 -0.04 0.05

Triaged as emergent or urgent ................. 0.02 0.00 0.03 -0.07

Resident/intern seen ........................ 0.13 0.18 0.01 0.27

Intravenous fluids administered ................. -0.24 -0.22 -0.13 -0.03

Left before being seen ...................... 0.19 0.05 0.24 0.09

Transfer to another facility .................... -0.12 -0.05 -0.13 -0.04

No followup planned ........................ 0.02 0.01 -0.01 -0.02

Admitted to hospital ........................ -0.39 -0.30 -0.28 -0.01

Medicaid admittances ....................... 0.38 0.58 -0.01 0.13

Uninsured admittances ...................... 0.18 -0.09 0.35 0.04

Mean waiting time to see physician ................ 0.15 0.02 0.19 0.14

Mean drug mention rate ....................... -0.03 0.05 -0.11 -0.07

1MSA is metropolitan statistical area.

2DSH is Disproportionate Share Hospital Program.

3Contextual variables placed on the State and county where the hospital is located.

4HMO is health maintenance organization.

5This is also referred to as State generosity index.

NOTES: Correlations in bold type are significantly different from zero (p< .01) Safety-net burden is the percent of visits made by Medicaid patients and/or uninsured patients in each emergency

department.
Page 16 [ Series 13, No. 155

Table 4. Medicaid Disproportionate Share Hospital Program estimates for 2000 by State with geographic region designation, ranked by

State generosity index

State Percent of Medicaid

generosity expenditures Geographic

State Total DSH payment1 index2 for DSH3 region

New Hampshire ............................ $ 156,569,068 $ 846 29.7 Northeast

New Jersey ............................... 983,158,288 580 22.4 Northeast

Connecticut ............................... 313,746,334 476 11.7 Northeast

Louisiana ................................ 734,339,152 454 29.0 South

South Carolina ............................. 433,786,686 402 17.6 South

Massachusetts ............................. 552,619,933 354 11.2 Northeast

Rhode Island .............................. 83,064,805 353 9.4 Northeast

Missouri ................................. 455,431,517 338 16.3 Midwest

Alabama ................................. 4

394,719,037 337 23.3 South

Ohio ................................... 4

636,464,508 257 10.1 Midwest

Delaware ................................ 4

35,345,000 207 7.7 South

Texas .................................. 1,290,660,599 198 15.9 South

Colorado ................................ 4

174,755,257 194 10.6 West

Mississippi ............................... 182,571,620 190 11.4 South

Washington ............................... 276,767,506 175 10.7 West

Nevada ................................. 4

73,560,000 171 16.0 West

District of Columbia .......................... 4

32,857,143 170 4.3 South

New York ................................ 1,093,003,870 169 4.3 Northeast

North Carolina ............................. 4

338,800,136 168 7.9 South

California ................................ 1,908,263,981 163 12.4 West

Kentucky ................................ 184,266,454 156 7.1 South

Maine .................................. 48,053,303 149 4.0 Northeast

West Virginia .............................. 79,582,331 147 5.9 South

Vermont ................................. 24,500,001 140 5.8 Northeast

Illinois .................................. 433,484,493 140 6.8 Midwest

Maryland ................................ 144,651,150 131 4.8 South

Virginia ................................. 4

163,724,595 124 7.4 South

Michigan ................................ 4

215,041,384 107 4.6 Midwest

Indiana ................................. 4

116,439,213 91 4.2 Midwest

Arizona ................................. 4

122,347,000 90 6.5 West

Kansas ................................. 4

43,549,804 86 4.0 Midwest

Florida .................................. 4

370,754,045 80 5.8 South

Minnesota ................................ 4

56,382,060 66 1.9 Midwest

Alaska .................................. 13,800,518 66 3.5 West

Oregon ................................. 25,165,448 30 1.6 West

Iowa ................................... 13,658,858 29 1.0 Midwest

Pennsylvania .............................. 4

51,883,327 21 0.8 Northeast

Oklahoma ................................ 22,490,264 20 1.6 South

New Mexico .............................. 12,274,960 17 1.1 West

Wisconsin ................................ 4

11,177,730 12 0.5 Midwest

Nebraska ................................ 4

3,970,516 12 0.5 Midwest

Utah ................................... 4,141,404 10 0.5 West

North Dakota .............................. 1,055,485 9 0.3 Midwest

South Dakota ............................. 4

1,075,557 7 0.3 Midwest

Idaho ................................... 1,425,518 4 0.3 Midwest

Arkansas ................................ 4

2,172,917 3 0.2 South

Wyoming ................................ 4

148,252 1 0.1 West

Montana ................................. 218,637 1 0.1 West

Hawaii5 ................................. – – – – – – – – – West

Tennessee5 ............................... – – – – – – – – – South

Georgia5 ................................ – – – – – – – – – South

– – – Data not available.

1Latest reports available on the Centers for Medicare & Medicaid Services (CMS) Web site. Most are for 2000, but some are for 1998 or 1999.

2State generosity index is the total Medicaid DSH payment per Medicaid, State Children’s Health Insurance Program, or uninsured person residing in the State. Numerator is total DSH payment, and

denominator is based on Current Population Survey and Centers for Medicare & Medicaid Services (CMS) data from Statistical Census Abstracts of the United States, 2002. Also referred to as the

State’s DSH payment ratio.

3Numerator is total DSH payment, and denominator is based on total 1999 Medicaid payments from Statistical Census Abstracts of the United States, 2002.

4DSH reports for 2000 were unavailable so 1998 or 1999 reports were used with exception of Ohio where a 2001 report was used and Minnesota where a 1997 report was used.

5No DSH payment reports available between 1998 and 2001.

NOTE: DSH is Disproportionate Share Hospital Program.
Vital and Health Statistics

series descriptions

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