This document summarizes a study that used patient data to analyze treatments for Post Traumatic Stress Disorder (PTSD). It finds that: 1) Demographic factors like gender, age, and location are associated with higher rates of PTSD diagnosis. Females in the Midwest and Northeast have significantly higher rates. 2) Anxiety, drug/alcohol abuse, and suicidal thoughts decreased over time for patients, but depression and PTSD-related encounters did not improve. 3) While antidepressants and therapy did not significantly reduce PTSD symptom severity over time, other treatments should be investigated, as the efficacy of antidepressants is questionable. Tracking individual patients longitudinally could provide better insight.

1. PTSD: A Data Driven Approach
Team HIMAT
6th March 2018
COPYRIGHT © CENTER FOR HEALTH SYSTEMS INNOVATION
ALL RIGHTS RESERVED

2. IntroductionGeneral Background
● PTSD, also known as shell shock or combat stress, tends to occur after an individual experiences severe
trauma or a life-threatening event
● 70% of adults in the U.S. have experienced some type of traumatic event at least once in their lives. This
equates to approximately 223.4 million people
● Although common treatments for PTSD include medications and different types of psychological
interventions, there is a growing body of research questioning the effectiveness of these treatments
Gap
Problem Statement
The key question to be answered is how patient data such as demographics factors, encounter details, record of anti-
depressants etc, can be used to improve the quality of treatment for Post Traumatic Stress Disorder

3. Methods
Data Cleaning
● Both datasets combined, PTSD_FLAG variable created to note which dataset used
● BMI column added using the height and weight variables
● Some outlier rows were removed by impossible heart rate. We removed all patients with a heart
rate less than 40 or greater than 250.
● All NULL values in binary columns were changed to 0 for ease of future analysis
● Created a new dataset with ID, PTSD_AGE and number of encounters for each symptom type
(anxiety, depression, suicide, drug abuse and PTSD)
■ For example a patient diagnosed with PTSD in 2013 will have 3 rows, since YEAR_PTSD and
encounters are known for 2013, 2014 and 2015
● Finally a flag is added for each symptom type to represent whether a patient never experienced any
of a symptom type

4. Methods
Data Analysis
● In SAS EM trees, neural nets and regression were used to predict the target variable PTSD_FLAG,
using imputation and variable selection
● In Tableau demographic variables were plotted as a percentage of the total using the PTSD_FLAG to
see patterns in PTSD patients
● In Tableau PTSD_AGE was graphed overtime in comparison to each type of symptom encounters in
order to see the trend of PTSD symptoms overtime
● In SAS EM each total of systoms encounters from 2011-2015 was regressed with the antidepressant
flags and # psychology procedures as the explanatory variables
● Since the data is oversampled, a decision node in SAS EM is used to adjust for the estimated of PTSD
in the population (3.6%)

5. Association of Individual Factors with PTSD

6. Association of Individual Factors with PTSD

7. Anxiety Encounters

8. Discussion
• When trying to predict PTSD, only demographic variables can be used
• The best model was decision tree
• The positive response was 52% after running a model as opposed to 50% (best guess). The model did not
do any better than chance
• Sensitivity is 4.8%, better than chance
• Potentially the problem is too many missing values, imputation does improve the neural net, but leads to
bias
• However, when looking at the individual factors in Tableau, it is clear that demographic factors related to
stress are associated with PTSD

9. Discussion
• The project mined previously unknown patterns from large-size datasets, which would be useful
predicting the possibility of illness based on patients’ symptoms. If one assumes the number of
encounters is an operationalization of severity of symptoms one can see that anxiety, suicidal thoughts
and drug and alcohol abuse decrease overtime
• The implication of this finding is that doctors can expect that and tell their PTSD patients that even though
they are feeling bad right now some symptoms will naturally get better overtime
• Depression doesn’t appear to improve overtime and PTSD related encounters do not either
• There are two limitations to this finding, first being that the time PTSD was diagnosed may long after its
onset. Second is that specific patients are not tracked overtime, a max of five years is possible

10. Discussion
• Regression Structure: Symptom Target Encounters = Intercept + Antidepressant flag(1) + … Antidepressant flag(9)
+ # Psychological treatments
• When statistically significant anti-depressants and the number of psychological treatments lead to an increase in
the number encounters relating to each symptom
• There could be selection bias and no way to conduct temporal analysis
• This suggests though that other drugs may need to be investigated as the efficacy of these drugs is questionable
• Target users could be individuals who are experiencing life stressors such as poor financial condition or a bad
relationship. It is necessary to negate the connotation that PTSD can affect mostly war victims
• It is also observed to be significantly higher for females mainly in Midwest and NorthEast

11. Recommendations
● PTSD should be rebranded to better represent those who suffer from it
● Doctors should track patients PTSD symptoms severity overtime
○ There appears to be a natural pattern of decreasing symptoms. If this is true, doctors conveying this
information to their patients may give the patients hope of improvement which could in turn lead to a
lessening of symptoms
○ It may also mean that doctors could focus more on the symptoms like depression that don’t seem to
naturally improve overtime
○ Finally it may help better advise the use of hospital resources as doctors spend more time on symtoms that
will be less likely to improve without intervention
○ Treatments other than antidepressants and psychological procedures should be further investigated
temporally. Also separating out which psychological treatment a patient receives would be useful since
research shows that Eye movement desensitization and reprocessing might be more useful than other
methods for treating PTSD

12. APPENDIX

13. Depression Encounters

14. Drug and Alcohol Encounters

15. Suicide Encounters

16. PTSD Encounters

17. Key Business Questions
• Can PTSD be predicted based on demographic factors?
• Does PTSD symptoms have a pattern over-time?
• Does anti-depressants or therapy reduce the severity of the symptoms?
• How is PTSD linked with Charleston?

18. Association of Individual Factors with PTSD

19. Association of Individual Factors with PTSD