HEALTH CARE EXPENDITURES

ASSOCIATED WITH PERSISTENT

EMERGENCY DEPARTMENT USE:

A MULTI-STATE ANALYSIS OF

MEDICAID BENEFICIARIES

Presented by –

Parul Agarwal, PhD MPH1,2

Thomas K Bias, PhD3

Usha Sambamoorthi, PhD1

1 West Virginia University School of Pharmacy, Morgantown, WV 2 Institute of Healthcare Delivery Science, Mount Sinai Health Systems, NY 3 West Virginia University School of Public Health, Morgantown, WV

BACKGROUND

• Emergency Medical Treatment and Labor Act

• Changing role of Emergency Department (ED)

• ED use by

- Uninsured

- Insured

• Used for emergent and non-emergent conditions1,2

• ED use results in3

- Fragmented care

- Higher healthcare expenditures

- Reduced quality of care

2

Background

▶ Increased ED visits in past two decades - 32% increase from 1997 to 20074

- More than 130 million ED visits in 20115

▶ Out of 354 million visits for acute care conditions that could have

been managed by primary care providers one-third treated in EDs6

▶ Many individuals visit ED repeatedly7

▶ Provision of treatment in EDs is expensive as compared to other

settings8

3

Date of download: 12/12/2014 Copyright © 2014 American Medical

Association. All rights reserved.

From: Trends and Characteristics of US Emergency Department Visits, 1997-2007

JAMA. 2010;304(6):664-670. doi:10.1001/jama.2010.1112

ED indicates emergency department. Error bars indicate 95% confidence intervals.

Figure Legend:

ED visits increased

from 9.6 million to

17.7 million among

Medicaid enrollees

4

Background

▶ Patient- and county-level factors are associated with increased ED

visits9,10

▶ ED use by Medicaid beneficiaries received policy attention11

▶ Post Affordable Care Act more individuals enrolled in the Medicaid

program12

▶ Expanded health insurance coverage without corresponding

increase in the number of primary care providers may impact ED use

▶ Previous expansion of health insurance coverage revealed mixed findings

5

Study Rationale

▶ Frequent ED use for non-urgent and preventable conditions1,2 ▶ Frequent ED use may be persistent with some individuals visiting

EDs frequently every year7

▶ Understanding persistent ED use important for Medicaid ▶ Comprehensive research on subgroup differences in persistent ED

users is lacking ▶ No study has examined the association between persistent ED use

and healthcare expenditures excluding costs of ED visits

6

Objective

Examine the patient- and county-level factors associated with

persistent ED use and its impact on healthcare expenditures among

adult fee-for-service (FFS) Medicaid beneficiaries.

7

Methods

Study Design

▶ Retrospective observational study design

▶ Data from MD, OH, and WV for year 2009 & 2010

▶ Index (calendar year 2009) and follow-up period (calendar year 2010)

▶ Persistent ED use was based on ED visits measured in both years

8

Index (2009) Follow-up (2010)

Independent variables Dependent variable: Total

healthcare expenditures

Persistent ED use

Methods

Study Population

▶ 22-64 years old

▶ Alive

▶ Men and non-pregnant women

▶ Not Medicare eligible

▶ FFS continuous enrollees

Data Sources

▶ Medicaid Analytic eXtract files

▶ Area health resource file

▶ County health rankings data

9

Methods

10

Medicaid

Analytic

eXtract (MAX)

Files

Examples of patient-level information

Personal

Summary File

Demographics, Medicaid eligibility, county federal

information processing standard (FIPS) codes,

Medicaid managed care enrollment, and Medicare

eligibility status

Inpatient

Claims File

Hospital stays, dates of service, Medicaid payment,

and the ICD-9-CM diagnosis and procedure codes

Other Therapy

Claims File

Dates of service, types of service, Medicaid

payment, ICD-9-CM, and CPT codes

Prescription

Drugs Claims

File

Date of prescription filled, days supplied, and

national drug code (NDC), Medicaid payment

Methods

11

Other Data

Sources

Examples of county-level information

Area Health

Resource File

(AHRF)

Percent with college education, health

professional shortage area, federally qualified

health centers per 100,000 population and urgent

care centers per 100,000 population, FIPS codes

County Health

Ranking

Obesity rate

All datasets linked together using Federal Information Processing Standard (FIPS)

codes.

Methods Dependent Variable 1) Persistent ED users versus Non-users

– No consensus on the number of ED visits that define frequent ED

users

– Commonly used definition (i.e. 4 or more ED visits annually)

2) Total healthcare expenditures

– Payments made by Medicaid for outpatient, inpatient, and

prescription drugs utilization

– ED expenditures were excluded

– Expenditures expressed in 2010 US dollars

12

Methods

Independent Variables: Patient-level

13

Variables Categories

Age 22-34, 35-44, 45-54, 55-64 years

Gender Female, male

Race/Ethnicity Whites, African Americans, Hispanics, Other Races

Medicaid

Eligibility

Cash eligibility, No cash eligibility, Medical eligibility,

No medical eligibility

Primary care use None, fragmented, continuous

Poly-pharmacy Yes, No

Complex chronic

illness

Presence of physical health conditions, presence of

mental health conditions, presence of both physical

and mental health conditions, none

Tobacco use Yes tobacco use, No tobacco use

Metro Metro, non-metro

Methods

Independent Variables: County-level

14

Variables Categories

Education County-level education rate

Unemployment County-level unemployment rate

Obesity County-level obesity rate

Health Professional

Shortage Area

None, partial, complete shortage

Hospitals with EDs Number of hospitals with EDs/100,000 population

Hospitals with

psychiatric emergency

services

Number of hospitals with psychiatric emergency

services/100,000 population

Rural health clinics Number of rural health clinics/100,000 population

Federally qualified

health centers

Number of federally qualified health centers/100,000

population

Community mental

health centers

Number of community mental health centers/100,000

population

Urgent care centers Number of urgent care centers/100,000 population

Methods

Statistical Analyses

15

Define Methods

Characteristics of the study

population

Frequencies and percentages

Unadjusted differences between

persistent ED users vs non-users

Chi-square tests of association

Patient- and county-level factors

associated with persistent ED use

Logistic regression

Association between healthcare

expenditures and persistent ED

use

Unadjusted and adjusted

generalized linear models (GLM)

with log link function and gamma

distribution

Characteristics of persistent ED users

and inpatient use (N = 22,252)

16

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Persistent EDusers

Non-users

55.60%

2%

Co

lum

n p

erc

en

tage

s

0102030405060708090

100

Prim

ary

Ca

re u

se

Fra

gem

en

ted

Contin

uou

s

Com

ple

x c

hro

nic

illn

ess

PH

C

MH

C

PH

C &

MH

C

None

Poly

-ph

arm

acy

Yes

No

Toba

cco

Use

Yes

No

28.7

13.2 20.1 17.6

41.7

6.7

53.4

17.2

55.1

21.2

Row

pe

rcen

tage

s

Patient-level Factors

Factors associated with persistent ED

use

17

1.67

7.65

4.36 3.97

1.08 1.2 0.9

0

1

2

3

4

5

6

7

8

9

10

Ad

juste

d O

dd

s R

ati

os

Patient- and County-level Factors

Mean Expenditures and Ratio of Means

by Type of Healthcare Expenditures

Non-users

(N = 17,107)

Persistent ED users

(N = 5,145)

Type of

Expenditures Mean ($) SE Mean ($) SE

Ratio of

means

Total*** 17,731.1 218.6 42,229.2 758.1 2.4

Outpatient*** 13,205.8 209.0 21,277.9 455.9 1.6

Prescription

Drugs*** 4,314.4 46.6 7,952.6 184.4 1.8

In Users

Prescription

Drugs*** 4,582.8 48.8 7,993.0 185.2 1.7

Inpatient*** 10,368.4 764.5 22,747.9 700.2 2.2

ED expenditures excluded from total and outpatient 18

Note: Asterisks represent significant group differences between persistent ED users and non-users based on IPTW

adjusted t-tests. SE = standard errors

*** p< .001; ** .001 < p < .01; * .01 < p < .05

Generalized Linear Models with Log Link Function

By Type of Expenditures

Type of

Expenditures

Intercept

(SE)

Persistent ED

Use -Beta

(SE) Change ($)

Total

(without ED)

8.68***

(0.62)

0.78***

(0.06) 6,951.84

Outpatient

(without ED)

7.59***

(0.72)

0.77***

(0.06) 2.294.38

Prescription Drugs

7.61***

(0.35)

0.13***

(0.15) 280.19

19

Note: SE = standard errors

*** p< .001; ** .001 < p < .01; * .01 < p < .05

Policy Implications

▶ Critical to explore ways to triage patients to other settings such as urgent care centers

▶ Need for policies, programs, and interventions that can meet the healthcare needs of persistent ED users

▶ One can speculate that coordinated care models may reduce persistent ED use and healthcare expenditures

20

Limitations & Strengths

Limitations

▶ Administrative claims data are for billing purposes

▶ Could not measure some patient-level factors such as obesity or reasons for using ED

Strengths

▶ Track repeated ED visits by an individual

▶ Differentiate between persistent ED users and non-users

▶ Information available on clinical diagnosis

▶ Availability of payment amount

▶ Use of county-level factors

21

Acknowledgements

22

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THANK YOU !

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