1. Virtual Journal Club ACMQ
Pranavi Sreeramoju, MD, MPH
November 17, 2015

2. Sepsis
Systemic Inflammatory Response Syndrome (SIRS) requires the presence of two of the following four factors:
Temperature < 36.0 C or > 38.0 C
Heart rate > 90 beats per minute
Respiratory rate > 24 breaths per minute or PaCO2 <32
WBC <4K or > 12K or bandemia >10%
Sepsis is SIRS plus the suspected or known presence of infection.
Severe Sepsis is sepsis plus evidence of organ dysfunction
Septic Shock is sepsis plus hypotension (systolic blood pressure (SBP) <90 mmHg or mean arterial pressure (MAP) <70 mmHg or a SBP decrease >40 mmHg from baseline) that is unresponsive to adequate resuscitation.

3. Sepsis
Sepsis is the 11th cause of mortality in the US causing >38k deaths (more if you add pneumonia)
Many deaths preventable with proper care in the first six hours of detection
Less than what is cited in the paper – paper has older data
National Vital Statistics Report 2013

4. Sepsis Bundle TO BE COMPLETED WITHIN 3 HOURS OF TIME OF PRESENTATION*:
Measure lactate level
Obtain blood cultures prior to administration of antibiotics
Administer broad spectrum antibiotics
Administer 30ml/kg crystalloid for hypotension or lactate ≥4mmol/L ( included in 3-hr bundle per Surviving Sepsis Campaign)
* “Time of presentation” is defined as the time of triage in the emergency department or, if presenting from another care venue, from the earliest chart annotation consistent with all elements of severe sepsis or septic shock ascertained through chart review.

5. Sepsis Bundle TO BE COMPLETED WITHIN 6 HOURS OF TIME OF PRESENTATION:
Administer 30ml/kg crystalloid for hypotension or lactate ≥4mmol/L (NQF counts this in the 6-hr bundle)
Apply vasopressors (for hypotension that does not respond to initial fluid resuscitation) to maintain a mean arterial pressure (MAP) ≥65mmHg
In the event of persistent hypotension after initial fluid administration (MAP < 65 mm Hg) or if initial lactate was ≥4 mmol/L, re-assess volume status and tissue perfusion and document findings
Re-measure lactate if initial lactate elevated.

6. Sepsis: Early Goal-Directed Therapy
Rivers 2001: Severe sepsis and septic shock: Single center receiving EGDT vs. 133 receiving standard therapy – mortality was 30.5% vs. 46.5%.
PROCESS Trial 2014: Septic shock – 31 EDs – three groups - protocol-based EGDT (n=439), protocol-based standard therapy (n=446), or usual care (n=456). Mortality was 21%, 18.2% and 18.9% respectively.
ARISE Trial 2014: Early septic shock – 51 EDs – EGDT (n=796) vs usual care (n=804). Mortality was 18.6% and 18.8% respectively.
Mouncey et al 2015: Septic shock – 56 hospitals – EGDT (n=630) vs usual care (n=630). Mortality was 29.5% vs 29.2% respectively.

7. Sepsis
Surviving Sepsis Campaign collaborative: launched in 2002 – 7.5 year experience in 218 hospitals – severe sepsis and septic shock - hospitals with high compliance had 29.0% mortality vs. 38.6% in hospitals with low compliance with bundle (Levy MM et al. Crit Care Med Jan;43(1))
The UTSW/ Parkland experience
CMS initiative
University HealthSystem Consortium (UHC) data

8. The importance of accurate measurement!!
Stakes are getting higher and higher!
The importance of accurate measurement!!

9. Today’s Journal Club
Article

10. How much does sepsis mortality vary between hospitals?
Hospital Variations in Severe Sepsis Mortality
Henry E. Wang, MD, MS1, John P. Donnelly, MSPH1,
Nathan I. Shapiro, MD, MPH2, Samuel F. Hohmann, PhD, MS-HSM3,4 and Emily B. Levitan, ScD5
American Journal of Medical Quality 2015, Vol. 30(4) 328–336
University of Alabama School of Medicine, Birmingham, AL
Beth Israel Deaconess Medical Center, Boston, MA
University HealthSystem Consortium, Chicago, IL
Rush University, Chicago, IL
University of Alabama at Birmingham, Birmingham, AL

11. Setting and Context
UHC is a cooperative with 120 not-for-profit academic medical centers and 300 affiliated hospitals in 42 states
‘Collaboration that drives improvement’
Hospital discharge data set
Sepsis mortality and sepsis care are gaining increased attention
‘How much does sepsis mortality vary between hospitals?’

12. UHC Sepsis Mortality Data
Observed to Expected ratio to calculate mortality index
Aggregate of POA and non-POA (although UHC does sub-divide into each category)
45-60 day delay
Comparison with other UHC hospitals
Ranking within UHC drives friendly competition

13. UHC Sepsis Mortality Data
Inclusions for UHC sepsis mortality data in general:
Includes Postoperative sepsis
Includes Septicemia of Newborn
Exclusions for UHC sepsis mortality data in general:
Meningococcemia
“Bad Data”
Nonviable Neonate
Hospice
Additional exclusions for this study:
<18 years of age
Prisoners
Admitted to a psychiatric unit
Transferred from another acute care hospital
<5 expected deaths

14. Study Design Retrospective Observational January 2012- December 2012
Measures:
Hospital death in a patient with severe sepsis per coding/administrative data
Expected mortality calculated using UHC risk adjustment models
Mortality index calculated
Analysis – comparison of mortality index in different hospitals

15. UHC Risk Adjustment Model
Separate logistic regression models are developed for each base diagnosis group, leading to an estimated probability of hospital death.
Each base model uses inpatient death as the dependent variable, and patient demographics and comorbid conditions as the independent variables.
UHC incorporates additional variables into the model on an annual basis. The models are updated annually using at least 2 years of data from consortium medical centers.
Hospital characteristics – census, teaching status, etc.

16. Results Severe sepsis observed mortality (median = 8.6%;
IQR = 6.8%-10.3%; Range = 0.9%-18.2%)

17. Results
Severe sepsis observed-to-expected (O:E) mortality ratios (median = 0.91; IQR = ; Range = )

18. Conclusion
Variations in severe sepsis mortality were observed between UHC participating institutions

19. critique

20. Strengths of Study Robust data set
Established methodology for risk adjustment

21. Limitations of Study None per se General limitation
Coding data and consistency among institutions
Not a hypothesis testing study

22. What does the variation mean?
Is the variation a reflection of true differences in sepsis care at institutions?
What about other service delivery factors? E.g., availability of hospice service
What about other infrastructure characteristics? E.g., coding team
Need to explore this variation in follow-up studies
How would different hospitals at different points along the spectrum respond to QI interventions to improve sepsis mortality?

23. Thank You!
Comment? Question?