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Social Determinants of Emergency 

Department Utilization in Utah

Disclaimer: Any opinions and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Census 

Bureau. The U.S. Census Bureau’s Disclosure Review Board (DRB) reviewed this data product for unauthorized disclosure of confidential 

information and approved the disclosure avoidance practices applied to this release, with authorization number CBDRB-FY20-362.

David Powers (presenter), Sara Robinson, Edward Berchick, J. Alex Branham, 

Lucinda Dalzell, Lorelle Dennis, Kristi Eckerson, Alfred Gottschalck, 

Joanna Motro, John Posey, Andrew Verdon, and Victoria Udalova

U.S. Census Bureau

November 3, 2021
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Background

In 2019, the U.S. Census Bureau entered into a partnership agreement 

with the Utah Department of Health (UDOH) with two aims:

• Aim 1: Examine social determinants of emergency department (ED) utilization 

in Utah in order to reduce preventable visits

• Aim 2: Evaluate the utility of ED encounter data for surveys for which the 

Census Bureau collects data, by making comparisons to the National Hospital 

Ambulatory Medical Care Survey (NHAMCS)

This presentation addresses Aim 1, examining social determinants of 

emergency department (ED) utilization in Utah
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• Understand person and household characteristics associated with 

preventable ED visits to inform policy, improve health outcomes, and 

increase cost-effectiveness of emergency care in Utah

• Increase utility of existing survey data, create new estimates related 

to social determinants of ED utilization, and validate survey content

• Determine which, if any, individual- and household-level Social 

Determinants of Health (SDOH) are significantly associated with 

preventable ED visits in Utah

• Compare our findings with existing literature

Goals
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• Utilizes existing survey and administrative records data and engages 

with new stakeholders to acquire health-related records

• Goal is to improve the quality and availability of statistical information 

to better understand and advance population health

• Potential to reduce respondent burden and data collection costs while 

increasing the quality and utility of existing data

• The COVID-19 pandemic has highlighted the relevance of statistics 

from these types of data partnerships to help answer crucial questions

Enhancing Health Data (EHealth) Program
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• 2013-2017 Emergency Encounters Data from Utah’s Department of 

Health (UDOH ED)

• Visit-level dataset

• 2013 through 2017 1-Year American Community Survey (ACS) 

restricted microdata from U.S. Census Bureau (not 5-year ACS product)

• Person- and household-level dataset

• Roughly 1-2% of Utah population sampled per year

• We link UDOH ED and ACS using internal person-level linkage keys, 

Protected Identification Keys (PIKs)

Source Data
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• UDOH ED visit file (2013-2017)

• 3.6 million UDOH visit records, from 1.4 million unique persons, i.e., 2.5 visits per person

• 3.5 million visits with matched PIK, i.e., 97 percent PIK rate 

• ACS Utah person file (2013 through 2017, not 5-year ACS product)

• 375,000 person records (about 75,000 person records per year)

• 353,000 persons with matched PIK, i.e., 94 percent PIK rate

• Linked UDOH-ACS file

• 230,000 matched visits, i.e., 7 percent of the PIKed UDOH visits

• 98,000 matched patients, i.e., 7 percent of the PIKed UDOH patients

• Many of the linked UDOH ED-ACS records borrow data from other years in the 

2013-2017 period (e.g., links between 2014 UDOH data and 2016 ACS data)

Linkage Summary
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• We use the New York University (NYU) ED Algorithm to classify visits

• Billings et al., 2000a, 2000b, 2000c

• The NYU ED Algorithm uses International Classification of Diseases (ICD) codes to 

classify ED visits into nine categories (four main categories and five others)

• To determine if a UDOH ED visit was preventable, we apply the Algorithm to the 

visit’s primary diagnosis code, including for the four main categories:

• Nonpreventable Emergency Care: Care Needed – Not Preventable (“true” emergency)

• Preventable Emergency Care: Care Needed – Preventable

Primary Care Treatable

Non-Emergent

• For ICD codes associated with multiple Algorithm categories, we assign the visits 

to the Algorithm’s highest probability category, and we randomize for ties of 50%

Classification of ED Visits
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• Theorizes that an individual’s health is impacted by conditions of the 

environments in which one works, lives, and plays (WHO, 2008)

• Consistent with the Healthy People 2020 framework (CDC, 2010), 

SDOH characteristics span five domains: 

• Economic Stability

• Education

• Social & Community Context

• Health & Healthcare

• Neighborhood & Built Environment

• We select ACS measures from each of the 5 SDOH dimensions: 

• 19 specific characteristics

Social Determinants of Health (SDOH) Framework
Economic 

Stability

Education Social & 

Community 

Context

Health & 

Healthcare

Neighborhood 

& Built 

Environment

• English 

Speaking Ability

• Educational 

Attainment

• Age

• Internet Access

• Marital Status

• Nativity

• Race/origin

• Sex

• Veteran Status

• Disability Status

• Health 

Insurance 

Coverage

• Public Coverage

• Vehicle Access

• Housing Tenure

• Employment

• Household 

Income Decile

• Household Size

• Poverty Status 

(family)

• SNAP 

Participation

Social Determinants of Health (SDOH) Variables

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• For each SDOH category and each of the 4 ED visit categories, we 

compute the following figures:

• Average number of ED visits per 1,000 people

• Percentage of ED visits across the 4 ED categories

• Study bivariate relationships between SDOH categories and ED use

• Study results from logistic regressions (stepwise, LASSO) to confirm 

observed relationships in the presence of control variables

• Study characteristics of Utah ED patients relative to those of the 

overall Utah population

Methodology
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• Confidential data cannot be disclosed or published in any way that permits identification of 

a particular individual or an entity

• Maintaining confidentiality of these data is guaranteed under Title 13 of the U.S. Code 

Section 9 and the Privacy Act of 1974

• This project was approved by UDOH Institutional Review Board (IRB) and executives, by 

Utah Health Data Committee at an open, public meeting, and by State of Utah executives

• Formal review and approval was received from the Census Bureau’s Disclosure Review 

Board (DRB) before release of this and any other results or products

• The released data contain no personally identifiable information, nor any information that 

can be made personally identifiable when combined with other publicly-available resources 

• The UDOH Data Suppression and Data Aggregation Guidelines, as well as additional Census 

Bureau DRB criteria, have been met

Data Confidentiality and Disclosure Avoidance
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Main Social Determinants of

Preventable Emergency Care Visits

• On average, Utah ED patients from more vulnerable populations tend to have more ED 

visits (many of which are preventable visits) than do other Utah ED patients
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Avg. # of Preventable Emergency Care Visits Per 1,000 People (1)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).

0

100

200

300

400

500

600

700

Lowest 2nd 3rd 4th 5th 6th 7th 8th 9th Highest

Average number of visits per 1,000 people

Household Income Deciles

Preventable Emergency Care Visits

All Ages

0

100

200

300

400

500

600

700

800

900

1000

Unemployed Not in Labor Force or In

Armed Forces

Employed

Average number of visits per 1,000 people

Employment Status

Preventable Emergency Care Visits

Ages 16+
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Avg. # of Preventable Emergency Care Visits Per 1,000 People (2)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).

0

100

200

300

400

500

600

700

800

Less than HS HS or GED Some College Bachelor's or

Higher

Average number of visits per 1,000 people

Educational Attainment

Preventable Emergency Care Visits

Ages 25+

0

200

400

600

800

1000

1200

No SNAP Any SNAP

Average number of visits per 1,000 people

SNAP Participation

Preventable Emergency Care Visits

All Ages
15

Avg. # of Preventable Emergency Care Visits Per 1,000 People (3)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).

0

100

200

300

400

500

600

700

800

Average number of visits per 1,000 people

Marital Status

Preventable Emergency Care Visits

Ages 15+

0

50

100

150

200

250

300

350

400

450

500

Male Female

Average number of visits per 1,000 people

Sex

Preventable Emergency Care Visits

All Ages
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Avg. # of Preventable Emergency Care Visits Per 1,000 People (4)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).

0

100

200

300

400

500

600

Renter-occupied Owner-occupied

Average number of visits per 1,000 people

Housing Tenure

Preventable Emergency Care Visits

All Ages

0

200

400

600

800

1000

1200

No Disability Any Disability

Average number of visits per 1,000 people

Disability Status

Preventable Emergency Care Visits

Ages 15+
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Estimates Among Four Populations

• United States (300+ million people)

• State of Utah (roughly 3 million people)

• People in Utah that had one or more ED visit during 2013-

2017 (estimate of roughly 1 million people)

• People in Utah that had one or more preventable ED visit 

during 2013-2017 (estimate of roughly 500,000 people)

Note: Not all observed differences are statistically significant
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Comparing Characteristics Among Populations

• On average, Utah ED patients (especially those with a preventable visit) tend to have 

vulnerable characteristics more often than does the overall Utah population
0

1

2

3

4

5

6

7

8

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Unemployment Rate

Ages 16+

0

2

4

6

8

10

12

14

16

18

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Poverty Rate

All Ages

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Percentage with Characteristic(s) in Each Population (1)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).
0

5

10

15

20

25

30

35

40

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Public Health Coverage Rate

All Ages

0

5

10

15

20

25

30

35

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Education - % with B.A. or Higher

Ages 25+

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Percentage with Characteristic(s) in Each Population (2)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).
0

5

10

15

20

25

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Disability Rate (Any Type)

Ages 15+

0

1

2

3

4

5

6

7

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Lack of Vehicle Access

All Ages

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Percentage with Characteristic(s) in Each Population (3)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).
0

10

20

30

40

50

60

70

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Sex - % Female

All Ages

0

2

4

6

8

10

12

14

16

United States Utah -

State

Utah -

People with ED

Visits

Utah -

People with

Preventable ED

Visits

Percent of people with the characteristic

Lack of Internet Access

All Ages

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Percentage with Characteristic(s) in Each Population (4)

Source: Utah Department of Health (UDOH) (2018), Utah Healthcare Facility Limited Use Data Sets, Emergency Department 

Encounter Data, 2013-2017 (2018). U.S. Census Bureau (2018), 2013, 2014, 2015, 2016, and 2017 American Community Survey 

(ACS), for Individual 1-Year Estimates (2018).
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• Examination by linkage year

• For example, 2013 UDOH visits linked only with 2013 ACS, 2014 with 2014, and so forth

• Results are very similar vs. all years, though with sample size reduced and MOEs raised

• Examination by age category

• Three age categories: Under 19, Ages 19-64, Ages 65+

• Results for Ages 19-64 are very similar vs. All Ages, though sample size is reduced

• Results for Under 19 and for Ages 65+ show some differences relative to All Ages

• Examination under logistic regression models

• Control for all 19 SDOH at once, with county effects, seasonality and day-of-week factors

• All of these SDOH covariates are highly statistically significant

• The original bivariate relationships between SDOH and ED visits hold up well

Results By Year, By Age Category

Note: MOE = margin of error
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Conclusion

• Strong associations within the combined ACS and UDOH data set

• We studied the number of preventable ED visits (per 1,000 people) by:

• Household income | Employment | Educational attainment | SNAP participation 

| Home ownership | Disability status | Marital status | Sex | and many others

• Among four populations (United States, Utah state, Utah ED patients, 

and Utah preventable-ED patients), we compared rates of:

• Poverty | Unemployment | B.A. degree | Public health coverage | Lack of 

vehicle access | Disability | Lack of Internet access | Female | and many others

• Strong associations among SDOH and preventable ED visits in Utah
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Data Partnership Made This Research Possible

• Creation and use of unique and valuable dataset

• Utah’s ED visit data linked, by patient, to Census Bureau’s ACS person-level data on SDOH

• Supports individual level analysis in contrast to aggregate geographic analysis

• Benefits to Data Partners

• Utah Department of Health

• Learn which SDOH are most important for preventable ED visit frequency

• Can inform new strategies and methods for reducing preventable emergency care, to 

potentially realize ED cost savings and reduce provider burden

• U.S. Census Bureau 

• Create new estimates leveraging existing data on SDOH, in ED setting, expanding research 

related to healthcare utilization and outcomes, contributing to mission

• Can help validate ACS content and seed ideas for health-related survey question(s)
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Next Steps

• Development and release of an interactive data dashboard

• Further study robustness, utilize additional approved variables, 

and compare more with benchmarks from related literature

• Discussion with UDOH to potentially extend the existing 

analysis using additional variables/years/datasets

• The EHealth Program seeks continued communication and 

partnership, to fulfill health-related data needs

• Please contact us!
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Dashboard Display – Work in Progress
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Paper Link and EHealth Web Site

• For more information about this project and to access the research paper:

• https://www.census.gov/programs-surveys/ehealth/information/evaluationemergency-udoh.html

• For more information about other EHealth projects and to explore 

partnership opportunities:

• https://www.census.gov/programs-surveys/ehealth.html

Contact Information

• David Powers, Economist, U.S. Census Bureau

• david.s.powers@census.gov | 301-763-5892

• Victoria Udalova, Senior Economist and EHealth Program Manager

• victoria.m.udalova@census.gov | 301-763-7101
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• ACS – American Community Survey

• ED – Emergency Department

• ICD – International Classification of Diseases

• MOE – Margin of error

• NYU – New York University

• SNAP – Supplemental Nutrition Assistance Program

• SDOH – Social Determinants of Health

• UDOH – Utah Department of Health

Acronyms Used
References

• Billings, J., Parikh, N., & Mijanovish, T. (2000a). Emergency Department Use in New York 

City: A Substitute for Primary Care? Available online at https://wagner.nyu.edu/files/admissions/Billings%20-

%20Emergency%20Department%20Use%20in%20NYC%20-%20A%20Substitute%20for%20Primary%20Care.pdf 

• Billings, J., Parikh, N., & Mijanovish, T. (2000b). Emergency Room Use: The New York Story. 

Available online at https://wagner.nyu.edu/files/admissions/Billings%20-%20Emergency%20Room%20Use%20-%20The%20New%20York%20Story.pdf

• Billings, J., Parikh, N., & Mijanovish, T. (2000c) Emergency Department Use in New York 

City: A Survey of Bronx Patients. Available online at https://wagner.nyu.edu/files/admissions/Billings%20-

%20Emergency%20Department%20Use%20in%20NYC%20-%20Survey%20of%20Bronx%20Patients.pdf

• Centers for Disease Control and Prevention (CDC). (2010). Healthy People 2020. Available 

online at https://www.cdc.gov/nchs/healthy_people/hp2020.htm

• World Health Organization (WHO), Commission on Social Determinants of Health (2008). 

Closing the Gap in a Generation: Health equity through action on the social determinants 

of health. Available online at https://www.who.int/publications/i/item/WHO-IER-CSDH-08.1

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