Quality Lowers Cost: The Cost Effectiveness of a Multicenter Treatment Bundle for Severe Sepsis and Septic Shock By: Lydia Dong MD, MS; Intermountain Healthcare - Intensive Medicine Clinical Programs
Presented at the 11th Annual HSR/ PCOR Conference: Partnering for Better Health: Bringing Utah's Patient Voices to Research 2016
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Quality Lowers Cost: The Cost Effectiveness of a Multicenter Treatment Bundle for Severe Sepsis and Septic Shock
1. Quality Lowers Cost:
The Cost Effectiveness of a Multicenter Treatment
Bundle for Severe Sepsis and Septic Shock
Intermountain Healthcare
Intensive Medicine Clinical Program
Healthcare Delivery Research, Institute for Healthcare Leadership
Lydia Dong MD, MS
2. Disclosures
There is no any conflicts of interest or relevant disclosures for
any of the authors
3. Introduction
• Sepsis occurs in 1% to 2% of all hospitalizations in the U.S.
• Severe sepsis and septic shock are leading cause of morbidity
and mortality in Intensive Care Unit
• Published in-hospital mortality rate ranges from 40-60%
• Sepsis resulted in an aggregate healthcare cost of $20.3
billion in 2011
• Requires early detection and treatment for survival
• Rapid identification, resuscitation and early evidence based
treatment is critical to best care and improved patient
outcomes
4. Introduction (Cont.)
• A longitudinal quality improvement study in severe sepsis and
septic shock patients was Initiated by Intensive Medicine
Clinical Program (IMCP) (2004-2010)
• Sepsis bundles and related quality improvement initiatives yield
improved bundle compliance and clinical outcomes (notably
mortality), but the relationship of bundle compliance to fixed
and variable healthcare costs is unclear
5. The Intermountain Bundle
Severe Sepsis & Septic Shock Bundles
Resuscitation Bundle
1. Serum Lactate measured within 3 hours of ED admit time.
2. Blood Cultures obtained prior to antibiotic administration.
3. Broad-Spectrum Antibiotics administered within 3 hours of ED admit time.
4. Fluid Resuscitation of Hypotension (SBP ≤ 90, or MAP ≤ 65) or lactate ≥ 4 mmol/L, with a minimum of 20-40
ml of crystalloid per estimated kg of predicted body weight (PBW).
5. Vasopressors employed for life threatening hypotension during resuscitation and after initial fluid
resuscitation if hypotension not responsive to fluids.
6. CVP and ScvO2 obtained at regular intervals via central catheter with tip in the SVC in the event of septic
shock 2 or lactate is ≥ 4 mmol/dl. CVP goal is ≥ 8 cm H2O and ScvO2 ≥ 70%
7. Inotropes and/or PRBC’s (if hematocrit < 30%) delivered for ScvO2 ≤70 % if CVP ≥ 8 mmHg.
Maintenance Bundle
1. Glucose Control maintained on average ≤ 180 mg/dl between 12-24 hours post-admission to ICU.
2. Steroids given if after adequate fluid resuscitation (CVP≥8) the patient was still on more than one
vasopressor, or a higher than normal recommended dose of a single vasopressor.
3. Drotrecogin Alfa Eligibility assessed for use employing hospital guidelines.
4. Use of a Lung Protective Strategy with Vt 6 ml/kg PBW and plateau pressures < 30 cmH20 for mechanically
ventilated patients.
6. Result and Conclusion from Our Previous
Study
1. Miller RR, 3rd, Dong L, Nelson NC, et al. Multicenter implementation of a severe sepsis and septic shock
treatment bundle. Am J Respir Crit Care Med. 2013;188(1):77-82.
7. Objectives
• To access the relationship between bundle compliance
and healthcare cost in severe sepsis and septic shock
patients
8. Study Design
• Observational study of a severe sepsis/septic bundle as
part of multi-year longitudinal quality improvement study
across multiple hospitals of an integrated healthcare
organization (IH)
• Fully compliant care was defined as success toward 11 of
11 bundle elements.
9. Study Population and Data Sources
• Inclusion criteria
• Patients 18 years or older
• Diagnosed with severe sepsis or septic shock
• Admitted to ICUs from the emergency department
(ED) or operating room
• 10 IH hospitals with 10 EDs and 13 ICUs
• Web-based sepsis bundle data collection application
and Intermountain Healthcare Enterprise Data
Warehouse
10. Intermountain Cost Accounting System
• Consolidated hospital case mix database which is sourced
from the corporate AS/400 production system.
• Total costs per patient were obtained through our enterprise
charge master. The charge master contains variable and
total costs for a standardized set of charge codes.
Hospitals conduct annual / biannual costing studies to
determine the variable and total cost for charge codes.
1. Roberts RR, Frutos PW, Ciavarella GG, et al. Distribution of variable vs fixed costs of hospital
care. JAMA. 1999;281(7):644-9.
11. Cost Outcomes
• Total costs = Fixed + Variable Costs
• Fixed Costs: Those costs that do not change due to volume
in a hospital or service. Examples include electricity, facility
maintenance, property and equipment.
• Variable Costs: Those costs that do change with volume
including salary, patient care supplies, medication and
diagnostic supplies etc.
12. Primary Outcome
•Standardized total and variable cost
A weighted adjustment method based on the
volume and inflation rate was applied to
standardize the costs and charge amounts for each
charge code across facilities and years
13. Statistical Method
• A Generalized Linear Mixed Model with Gamma
distribution and log link was independently performed to
assess the association between standardized costs (total
and variable) and treatment bundle compliance while
controlling for patient age and Charlson Comorbidity
Index Score (CCIS) stratified by severe sepsis and septic
shock sub-groups.
• Facilities were treated as random effects.
14. Results
• 3910/3997 eligible patients had all data available and were
enrolled from the 11 hospitals.
• Patients with bundle compliance had in-hospital mortality of
10.6% (n = 224 of 2118) versus 13.0% (n = 233 of 1792, p =
0.02) for those who did not receive fully compliant care.
• Patient characteristics, outcomes and standardized costs by
severity of sepsis are shown in Table 1-4.
16. Table 2: Cost Results by Severity of Sepsis
Cost variable
Severity of
sepsis
Total bundle compliant
p
Non-compliant Compliant
Standardized total cost
($)
Septic shock 32,498 ± 35,487 32,440 ± 35,445 0.9767
Severe sepsis 28,021 ± 40,301 24,589 ± 27,672 0.0096*
Non-Standardized total
cost ($)
Septic shock 26,868 ± 29,915 27,278 ± 29,453 0.7604
Severe sepsis 21,940 ± 31,737 20,858 ± 24,211 0.3211
Standardized variable
cost ($)
Septic shock 15,304 ± 17,475 15,375 ± 17,670 0.9426
Severe sepsis 13,134 ± 19,892 11,468 ± 13,619 0.0108*
Non-Standardized
variable cost ($)
Septic shock 14,236 ± 16,367 14,492 ± 16,551 0.7824
Severe sepsis 11,871 ± 18,212 10,515 ± 12,475 0.0234*
17. Table3. GLMM with Standardized Total Cost
Model with Total Cost in
Severe Sepsis
Model with Total Cost in
Septic Shock
Model Estimate p-value Estimate p-value
Intercept 9.7884 <0.0001 9.7960 <0.0001
Total bundle (not
compliant)
0.1092 0.0237* 0.0097 0.8667
Age
group
18-29 0.0233 0.8374 0.3075 0.0427
30-39 0.2967 0.0138 0.4017 0.0020
40-49 0.3693 <0.0001 0.2123 0.0516
50-59 0.1604 0.0385 0.3667 <0.0001
60-69 0.2464 0.0007 0.0885 0.0038
70-79 0.0879 0.2237 0.0888 0.0644
>80 Ref. Ref.
CCIS 0.0095 0.1502 0.0217 0.0066
Saving with bundle
per case
$2,557
(95% CI: $2,110, $3,096) (~11%
saving)
No saving
18. Table4. GLMM with Standardized Variable Cost
Model with Variable Cost in
Severe Sepsis
Model with Variable Cost in
Septic Shock
Model Estimate p-value Estimate p-value
Intercept 8.9873 <0.0001 9.0079 <0.0001
Total bundle (not
compliant)
0.1193 0.0182* 0.0082 0.8908
Age group 18-29 0.0163 0.8909 0.3381 0.0319
30-39 0.3179 0.0116 0.4144 0.0021
40-49 0.4002 <0.0001 0.2363 0.0369
50-59 0.1627 0.0448 0.3665 0.0001
60-69 0.2563 0.0007 0.2614 0.0045
70-79 0.0893 0.2377 0.1662 0.0716
>80 Ref. Ref.
CCIS 0.0125 0.0725 0.0233 0.0049
Saving with bundle per
case
$1,288
(95% CI: $1,055, $1,572)
~12%
No saving
19. Results (Cont.)
• Implementation of sepsis bundle in severe sepsis patients
saved 11% ($2,557, 95% CI: $2,110 - $3,096) in
standardized total cost and 12% ($1,288, 95% CI: $1,055 -
$1,572) in standardized variable cost after controlling
patient age and CCIS per case. Total $4.6 million saving
over the study period
• No savings in septic shock patients after implementing
sepsis bundle
20. Conclusions
• In this study, sepsis bundle compliance is associated with
improved mortality and lower costs (total and variable) in
hospitalized patients with severe sepsis but not in patients
with septic shock.
• While it remains unclear why the effect was only seen in
patients with severe sepsis, there appears to be an
important correlative relationship between clinical quality
and costs even in complex medical treatments.(1,2)
1. Chalupka AN, Talmor D. The economics of sepsis. Critical care clinics. 2012;28(1):57-76, vi.
2. Lagu T, Rothberg MB, Shieh MS, et al. Hospitalizations, costs, and outcomes of severe sepsis in
the United States 2003 to 2007. Critical care medicine. 2012;40(3):754-61.
21. Limitations
• Single system with unique TD-ABC capabilities
• Sub-optimal bundle compliance for the entire six years of
the study
• No QALY (Quality-adjusted Life-year) calculations
22. Acknowledgements
• Todd Allen, MD (ED Development Team Medical Chair )
• Terry Clemmer, MD (IMCP Medical Chair)
• Nancy Nelson (IMCP Operation Director)
• Danny Probst (IMCP Data Manager)
• Andrew Merrill (Statistician)
• Russell R. Miller III M((Critical Care Development Team
Medical Chair)
Sepsis is a serious medical condition caused by an overwhelming immune response to infection.
Sepsis occurs in 1% to 2% of all hospitalizations in the U.S. It affects at least 750,000 people each year.
It is a medical emergency that requires early detection and treatment for survival.
Severe sepsis is sepsis causing acute organ failure or insufficient blood flow. Insufficient blood flow may be evident by low blood pressure, high blood lactate, or low urine output. If sepsis patient with low blood pressure was not improved after reasonable amounts of intravenous fluids given, the patient would be at greater risk for developing septic shock
IH Clinical Program: The major vehicle to address the delivery and support of high quality, cost effective health care
Organization based on integration of medical providers and operational leadership
Goal – standardize clinical processes (reduce practice variance), improve clinical outcomes and reduce cost
Saving ~100 lives per year.
Charlson Comorbidity Index: The Charlson comorbidity index predicts the ten-year mortality for a patient who may have a range of comorbid conditions, such as heart disease, AIDS, or cancer (a total of 22 conditions). Each condition is assigned a score of 1, 2, 3, or 6, depending on the risk of dying associated with each one. Scores are summed to provide a total score to predict mortality.
Random Effects Modeling: In statistics, a random effect(s) model, also called a variance components model, is a kind of hierarchical linear model. It assumes that the dataset being analysed consists of a hierarchy of different populations whose differences relate to that hierarchy. In econometrics, random effects models are used in the analysis of hierarchical or panel data when one assumes no fixed effects (it allows for individual effects).
Leave ABC until later
Charlson Comorbidity Index: The Charlson comorbidity index predicts the ten-year mortality for a patient who may have a range of comorbid conditions, such as heart disease, AIDS, or cancer (a total of 22 conditions). Each condition is assigned a score of 1, 2, 3, or 6, depending on the risk of dying associated with each one. Scores are summed to provide a total score to predict mortality.
Random Effects Modeling: In statistics, a random effect(s) model, also called a variance components model, is a kind of hierarchical linear model. It assumes that the dataset being analysed consists of a hierarchy of different populations whose differences relate to that hierarchy. In econometrics, random effects models are used in the analysis of hierarchical or panel data when one assumes no fixed effects (it allows for individual effects).
Leave ABC until later
Compliance rates are different here than the paper because in the paper we reported the compliance rate in the final 2 year period. In this paper we are showing the compliance rate across all six years (2005-2010 inclusive) in order to compare costs between the two groups.
latter resuscitation elements including inotropes, red cell transfusions, glucocorticoids, and lung protective ventilation. As these latter resuscitation elements are expensive, it might naturally hold that this is where the cost savings might be achieved.
