1. Not What the
Doctor Ordered:
RACIAL DIFFERENCES IN
HOSPITAL DISCHARGES
AGAINST MEDICAL ADVICE
TREVOR HUNT

2. Acknowledgements
Dr. Simon – 1st reader and primary mentor
Dr. Harnois – 2nd reader and statistics help
Dr. Harris – idea, inspiration, and encouragement

3. Outline
Introduction to topic and dataset used
Background and major findings in the literature
Hypotheses about race and discharges against medical
advice, insurance status, and hospital ownership
Tables and a discussion of the results
Limitations
Conclusions: is race really the cause?

4. Key Term – AMA
AMA against medical advice
 A very small subset of all hospital discharges
 Increased rates of readmission and mortality
 One study found being black to be a
significant predictor of discharges AMA

5. Data – 2008 National Hospital Discharge Survey
2008 – most recent year available
▪ N=165,530, 207 hospitals
▪ Unit of observation: discharges
▪ Not patients!
After processing – N=44,647
▪ 18+, removed dead discharges,
removed all missing data

6. Why would anyone leave AMA?

7. Background
Other racial health disparities
Institutionalized racism and access to healthcare facilities
SES and health insurance coverage
Trust and communication
Health risks associated with discharges AMA

8. Hypotheses
I. Black patients will be significantly more likely to discharge
AMA compared to white patients
II. Black patients will be significantly more likely to utilize
government insurance (Medicare/Medicaid) or be uninsured
III. Black patients will be significantly more likely to be treated
at nonprofit and government owned hospitals
IV. Racial disparities in discharges AMA will be explained by
insurance status and hospital type in the final regression
model

9. Table 1
Sociodemographic
Characteristics

10. Table 2 – Binary Logistic Regression Models

11. Summary of Results
Hypotheses I, II, and IV are supported but III is not
Demographic variables make the largest contribution
Including all three sets of predicting variables causes race to
no longer be a significant predictor of discharging AMA
Private insurance has a very strong negative association
with discharging AMA
Private hospitals have the fewest discharges AMA

12. Limitations
Insurance status groupings created from a NHDS variable
called “Expected Source of Payment”
Many variables not present in NHDS
▪ Income
▪ Education
▪ Employment
▪ Occupation
▪ Trust
Other race variable too diverse, not all that useful
Data may not be 100% accurate due to how it is collected

13. Conclusions
Provides clues about the
mechanisms behind the observed
racial disparities in discharges
against medical advice
The explanation is not simple! This
thesis barely scratches the surface
Future directions
▪ Examine age, gender, marital status
▪ Incorporate missing social variables
▪ Expand to examine more races

14. That’s it! Questions?
THANKS FOR LISTENING!