Accepted and Presented in the Session of Injury Control and Emergency Health Services of American Public Health Association 2016 Annual Meeting and Expo Held in October 31.
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Chronic Conditions of as Predictors of Hospitalization Following an Emergency Department Visit in a Metropolitan Area
1. University ofTexas School of Public Health
Houston Health Services Research Collaborative
Shin Jeong, M.P.H., PhD
University ofTexas MD Anderson Cancer Center
Jane Hamilton, M.P.H., PhD
UTHealth McGovern Medical School
Charles Begley, PhD
UT School of Public Health
4. Chronic Conditions as Predictors of Hospitalization Following an Emergency DepartmentVisit
in a Metropolitan Area
Background
Primary Source of Hospitalization as
Emergency Department Use in U.S.
10 Percent ofTotal 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
5. Study Objectives
1. 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
7. 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
8. Chronic Conditions as Predictors of Hospitalization Following an Emergency DepartmentVisit
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.
9. Methods: Data Source
Emergency Department Use Data from following
hospitals
• Memorial Hermann Health Care System (Hermann
TMC, Southwest, Southeast, Northeast, Northwest,
TheWoodlands, Memorial City, Katy, and Sugar Land)
• Hospital Corporation of America (Bayshore, Clear
Lake Regional, andWest Houston)
• Texas Children’s Hospital Medical Center and West
Campus
10. Methods
Data Collection and Elements for EachVisit
•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
11. Measures
Dependent Variables: Hospitalization
Independent Variables
Age, Gender, Race
Insurance Coverage Type
Co-morbid Conditions
Primary Chronic Condition of Diagnosis
Hypertension
Cardiovascular Disease
Diabetes
Other Chronic Health Conditions
Primary Behavioral Condition
All Other Acute Primary Conditions of Diagnosis
Secondary Chronic Condition of Diagnosis
Hypertension
Cardiovascular Disease
Diabetes
Other Secondary Chronic Health Conditions
Secondary Behavioral Conditions of Diagnosis
Secondary All Other Acute Conditions
12. Chronic Conditions as Predictors of Hospitalization Following an Emergency DepartmentVisit
in a MetropolitanArea
Data Analysis
13. Model Building
Based 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
14. 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%)
16. Results 2 Descriptive Statistics :EDVisits 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
17. EDVisits 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
18. Results 3: Baseline Statistics EDVisits 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
Total
772,021
104.1****
*Acute conditions are defined as all visits beside Chronic and Behavioral Conditions.
**Other chronic conditions are defined as Hyperlipidemia, Stroke orTransient 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
19. Results 4
Significant Predictors of 2013 EDVisits
Resulting in a Hospital Admission
Predictors Odds Ratio 95% 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
20. 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
21. Acknowledgements
The 2012-2013 Harris County Emergency Department Use
Study was funded by the Memorial Hermann Healthcare
System, the Methodist Healthcare System, andTexas 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 (HermannTMC,
Southwest, Southeast, Northeast, Northwest,TheWoodlands,
Memorial City, Katy, and Sugar Land)
Hospital Corporation ofAmerica (Bayshore, Clear Lake Regional,
andWest Houston)
Texas Children’s Hospital Medical Center andWest Campus
Methodist Hospital System (Willowbrook, Sugar Land, andWest
Houston)
Editor's Notes
The model suggests that people's use of health services is a function of their predisposition to use services, factors which enable or impede use, and their need for care.
Among the predisposing characteristics, demographic factors such as age and gender represent biological imperatives suggesting the likelihood that people will need health services.
Enabling resources must be present for health care use to take place. First, health personnel and facilities must be available where people live and work. Then, people must have the means and know-how to get to those services and make use of them. Income, health insurance, a regular source of care, and waiting times are some of the measures that can be important here.