Chronic Conditions as Predictors of Hospitalization

Following an Emergency Department Visit

in a Metropolitan AreaUniversity of Texas School of Public Health

Houston Health Services Research Collaborative

Shin Jeong, M.P.H., PhD University of Texas MD Anderson Cancer Center

Jane Hamilton, M.P.H., PhD UTHealth McGovern Medical School

Charles Begley, PhD UT School of Public Health

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Presenter Disclosures

Shin Jeong, PhD, M.P.H.

No relationships to disclose

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AgendaI. Background II.Study ObjectivesIII.Method

Theoretical Framework Study Design Target Population Data Source Data Collection and Elements Data Analysis

V. ResultsVI.ConclusionVII.Question and Discussion

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Chronic Conditions as Predictors of Hospitalization Following an Emergency Department Visit in a Metropolitan Area

Background

Primary Source of Hospitalization as Emergency Department Use in U.S.

10 Percent of Total Healthcare Costs of Associated with Hospitalization of ED patients with Primary & Secondary Chronic Health Conditions

Chronic Conditions shown to increase the risk of hospitalization following and ED visit

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Study Objectives1. Determine the overall rate of ED visits that results in a hospital admission

2. Determine the diagnostic conditions, demographic, and geographic characteristics of patients with ED visits

3. Examine predictors of hospitalization following an ED visit

4. Examine the likelihood of hospitalization of patients with primary and secondary chronic conditions

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Methods Theoretical Framework: Behavioral Model of Health Services Utilization

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Chronic Conditions as Predictors of Hospitalization Following an Emergency Department Visit

in a Metropolitan Area

Methods: Study Design Retrospective Cohort Study

Secondary data analysis

Emergency Department visit data of 19 public and private hospitals in Harris County with EDs serving the general public (that accept walk-ins and 911 deliveries)

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Chronic Conditions as Predictors of Hospitalization Following an Emergency Department Visit

in a Metropolitan Area

Methods: Target Population

All individuals visited Emergency Department in 19 hospitals that

participates in the ED Use study from January 1, 2013 to December 31, 2013 in Harris County.

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Methods: Data Source

Emergency Department Use Data from following hospitals

• Memorial Hermann Health Care System (Hermann TMC, Southwest, Southeast, Northeast, Northwest, The Woodlands, Memorial City, Katy, and Sugar Land)

• Hospital Corporation of America (Bayshore, Clear Lake Regional, and West Houston)

• Texas Children’s Hospital Medical Center and West Campus

• Methodist Hospital System (Willowbrook, Sugar Land, and West Houston)

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MethodsData Collection and Elements for Each Visit

•Date and time of admission to the ED

•Primary and nine other diagnoses (ICD-9)

•Discharge date and time•Payment source •Patient age•Patient gender•Patient race/ethnicity•Patient ZIP code•Destination discharged •Method of transport•Emergency severity index

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Measures Dependent Variables: HospitalizationIndependent Variables

Age, Gender, RaceInsurance Coverage TypeCo-morbid ConditionsPrimary Chronic Condition of DiagnosisHypertensionCardiovascular DiseaseDiabetesOther Chronic Health ConditionsPrimary Behavioral Condition All Other Acute Primary Conditions of DiagnosisSecondary Chronic Condition of DiagnosisHypertensionCardiovascular DiseaseDiabetesOther Secondary Chronic Health ConditionsSecondary Behavioral Conditions of DiagnosisSecondary All Other Acute Conditions

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Chronic Conditions as Predictors of Hospitalization Following an Emergency Department Visit in a Metropolitan Area

Data Analysis

SAS 9.3 for all statistical analyses. For descriptive analyses of the sample, continuous and categorical variables summarized with means and percentages, respectively.

Multivariate logistic regression To identify the relative importance of patient age, gender, race/ethnicity, payer source (insurance status) and co-morbid diagnosis for predictors of Hospitalization

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Model BuildingBased on Anderson and Aday

Conceptual Framework

To examine the likelihood of hospitalization of ED visitors with comorbid conditions

<Generalized Logistic Model>•Logit [E (Admitted to Hospital)]

= β0 + β1Age+β2Gender+β3Coverage Type+β3Race+β4Non-primary Care Related Conditions + β5Primary Comorbid Conditions+β6 Secondary Comorbid Conditions + U

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Chronic Conditions as Predictors of Hospitalization Following an Emergency Department Visit in a Metropolitan Area

Results I

737,809 ED visits to participating hospitals in 2013

The overall rate of ED visits resulting in a hospital admission, 7.7% in a metropolitan area

Primary chronic physical conditions 5.6%9 out of 10 patients had an acute

condition( other than chronic and behavioral conditioned diagnosis)

92.4% in 2013

Most frequent secondary chronic conditions were hypertension (15.5% ) and behavioral health (10.8%)

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Geo-mapping of Admission to Hospitals

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Results 2 Descriptive Statistics :ED Visits by Primary Diagnosis

Condition 2013 Percent

Acute* 681,663   92.4

Chronic 41,128   5.6

Hypertension   6,592 0.9

Cardiovascular

Disease

  10,084 1.4

Diabetes   3,553 0.5

Other Chronic**   22,662 3.1

Behavioral

Condition***

15,018   2.0

Total 737,809   100

*Acute conditions are defined as all visits beside Chronic and Behavioral Conditions.**Other chronic conditions are defined as Hyperlipidemia, Stroke or Transient Ischemic Attack, Arthritis, Asthma, Cancer, Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease, Alzheimer’s and other senile Dementias and Osteoporosis*** Behavioral conditions include both mental health and substance use conditions.

See the appendix

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ED Visits by Primary Diagnosis

Acute 92.6%

Chronic 5.4%

Behavioral 2.0%

*Acute conditions are defined as all visits beside Chronic and Behavioral Conditions.**Other chronic conditions are defined as Hyperlipidemia, Stroke or Transient Ischemic Attack, Arthritis, Asthma, Cancer, Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease, Alzheimer’s and other senile Dementias and Osteoporosis*** Behavioral conditions include both mental health and substance use conditions.

See the appendix

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Results 3: Baseline Statistics ED Visits by Secondary Diagnosis

Secondary

Condition

2013 Percent

Acute* 533,125   72.3

Chronic 159248   21.6

Hypertension   114,145 15.5

Cardiovascular

  36,239 4.9

Diabetes   18,987 2.6

Other

Chronic**

  73,068 9.9

Behavioral*** 79,648   10.8

Total772,021

  104.1****

*Acute conditions are defined as all visits beside Chronic and Behavioral Conditions.**Other chronic conditions are defined as Hyperlipidemia, Stroke or Transient Ischemic Attack, Arthritis, Asthma, Cancer, Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease, Alzheimer’s and other senile Dementias and Osteoporosis*** Behavioral conditions include both mental health and substance use conditions.**** Doesn’t sum to 100% ED visit may contain a secondary diagnosis of more than one type

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Results 4Significant Predictors of 2013 ED Visits

Resulting in a Hospital Admission Predictors Odds

Ratio95% CI

Age 1.030** 1.029 - 1.030

Male Gender 1.136** 1.115 - 1.157

Non-Hispanic Black (Non-Hispanic White Reference)

0.853** 0.834 - 0.872

Hispanic (Non-Hispanic White Reference)

0.630** 0.614 - 0.646

Asian (Non-Hispanic White Reference) 1.248** 1.182 - 1.318

Other Race/Ethnicity (Non-Hispanic White Ref.)

1.537** 1.484 - 1.592

Uninsured (Commercial Insurance Reference)

1.147** 1.115 - 1.180

Medicare (Commercial Insurance Reference)

1.865** 1.810 - 1.922

Medicaid (Commercial Insurance Reference)

1.109** 1.074 - 1.145

Other Payment Source (Commercial Insurance Ref.)

1.023** 0.943 - 1.109

Behavioral Health Condition 0.655** 0.538 - 0.797

Hypertension 0.753** 0.683 - 0.831

Cardiovascular Disease 1.126** 0.997 - 1.271

Diabetes 2.003** 1.737 - 2.310

Other Chronic Condition 1.650** 1.464 - 1.860

Secondary Cardiovascular Disease 1.640** 1.602 - 1.680

Secondary Diabetes 1.114** 1.075 - 1.154

Secondary Other Chronic Condition 2.214** 2.168 - 2.261 Secondary Behavioral Condition 1.669** 1.633 - 1.707

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

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Conclusion Having a primary or secondary diagnosis of chronic health condition including cardiovascular disease, diabetes or other chronic conditions increased the likelihood of hospitalization

Medicare, Medicaid enrollees and uninsured, likelihood of hospitalization, compared to commercial insurance enrollees

Comorbid health conditions as need factors, insurance coverage type as enabling factors with several socio-demographic factors, strongest predictors

Implementation of quality improvement strategies in ED such as referral to medical homes and intensive care management may reduce the need of hospitalization for patients with chronic health conditions

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AcknowledgementsThe 2012-2013 Harris County Emergency

Department Use Study was funded by the Memorial Hermann Healthcare System, the Methodist Healthcare System, and Texas Children's Hospital in Houston, Texas.

We would like to express our gratitude to the hospitals that provided the funding and data for this project.

Memorial Hermann Health Care System (Hermann TMC, Southwest, Southeast, Northeast, Northwest, The Woodlands, Memorial City, Katy, and Sugar Land)

Hospital Corporation of America (Bayshore, Clear Lake Regional, and West Houston)

Texas Children’s Hospital Medical Center and West Campus

Methodist Hospital System (Willowbrook, Sugar Land, and West Houston)

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