Supplementary Online Content

Similar documents
Admissions with neutropenic sepsis in adult, general critical care units in England, Wales and Northern Ireland

SEPSIS RESEARCH WSHFT: THE IMPACT OF PREHOSPITAL SEPSIS SCREENING

Number of sepsis admissions to critical care and associated mortality, 1 April March 2013

Understanding Readmissions after Cancer Surgery in Vulnerable Hospitals

Sepsis Screening Tools

NUTRITION SCREENING SURVEYS IN HOSPITALS IN NORTHERN IRELAND,

SEPSIS Management in Scotland

Cause of death in intensive care patients within 2 years of discharge from hospital

Study Title: Optimal resuscitation in pediatric trauma an EAST multicenter study

IMPACT OF RN HYPERTENSION PROTOCOL

19th Annual. Challenges. in Critical Care

The Memphis Model: CHN as Community Investment

Sepsis/Septic Shock Pre-Hospital Care

Healthcare- Associated Infections in North Carolina

CNA SEPSIS EDUCATION 2017

OFF-HOURS ADMISSION AND MORTALITY IN THE PEDIATRIC INTENSIVE CARE UNIT MICHAEL CONOR MCCRORY, M.D. A Thesis Submitted to the Graduate Faculty of

Frequently Asked Questions (FAQ) Updated September 2007

SEPSIS RISK ASSESSMENT EVALUATION TOOL HEALTH QUALITY INNOVATORS

Pricing and funding for safety and quality: the Australian approach

Death and readmission after intensive care the ICU might allow these patients to be kept in ICU for a further period, to triage the patient to an appr

Supplementary Online Content

CLINICAL PREDICTORS OF DURATION OF MECHANICAL VENTILATION IN THE ICU. Jessica Spence, BMR(OT), BSc(Med), MD PGY2 Anesthesia

Technical Notes on the Standardized Hospitalization Ratio (SHR) For the Dialysis Facility Reports

Risk Factor Analysis for Postoperative Unplanned Intubation and Ventilator Dependence

DETAIL SPECIFICATION. Description. Numerator. Denominator. Exclusions. Minimum Data Reported to NHSN

Supplementary Online Content

MET CALLS IN A METROPOLITAN PRIVATE HOSPITAL: A CROSS SECTIONAL STUDY

Version 2 15/12/2013

Current Status: Active PolicyStat ID: Guideline: Sepsis Identification And Management in Adults GUIDELINE: COPY

Welcome and Instructions

Statistical Analysis Plan

2017 Quality Reporting: Claims and Administrative Data-Based Quality Measures For Medicare Shared Savings Program and Next Generation ACO Model ACOs

Inpatient Quality Reporting Program

Stopping the Chain of Infection: Strategies for Preventing Sepsis in Long Term Care September 20, 2016

Medicare Quality Based Payment Reform (QBPR) Program Reference Guide Fiscal Years

Healthcare- Associated Infections in North Carolina

HIMSS ASIAPAC 11 CONFERENCE & LEADERSHIP SUMMIT SEPTEMBER 2011 MELBOURNE, AUSTRALIA

HEDIS Ad-Hoc Public Comment: Table of Contents

Patients admitted to Australian intensive care units: impact of remoteness and distance travelled on patient outcome

Predictors of acute decompensation after admission in ED patients with sepsis

Infection Monitoring: National Healthcare Safety Network (NHSN) Bloodstream Infection in Hemodialysis Patients Clinical Measure

Minority Serving Hospitals and Cancer Surgery Readmissions: A Reason for Concern

Hip Hemi-Arthroplasty vs Total Hip Replacement for Displaced Intra-Capsular Hip Fractures: Retrospective Age and Sex Matched Cohort Study

The Role of Analytics in the Development of a Successful Readmissions Program

Type of intervention Treatment. Economic study type Cost-effectiveness analysis.

2018 Optional Special Interest Groups

June 25, Shamis Mohamoud, David Idala, Parker James, Laura Humber. AcademyHealth Annual Research Meeting

Chapter 39 Bed occupancy

FUNCTIONAL DISABILITY AND INFORMAL CARE FOR OLDER ADULTS IN MEXICO

NEW JERSEY HOSPITAL PERFORMANCE REPORT 2014 DATA PUBLISHED 2016 TECHNICAL REPORT: METHODOLOGY RECOMMENDED CARE (PROCESS OF CARE) MEASURES

Beth Israel Deaconess Medical Center Department of Anesthesia, Critical Care, and Pain Medicine Rotation: Post Anesthesia Care Unit (CA-1, CA-2, CA-3)

NEW JERSEY HOSPITAL PERFORMANCE REPORT 2012 DATA PUBLISHED 2015 TECHNICAL REPORT: METHODOLOGY RECOMMENDED CARE (PROCESS OF CARE) MEASURES

Scottish Hospital Standardised Mortality Ratio (HSMR)

Increased mortality associated with week-end hospital admission: a case for expanded seven-day services?

STRATIFICATION GUIDE 2018

Ambulatory Emergency Care in South Wales

Medicare Spending and Rehospitalization for Chronically Ill Medicare Beneficiaries: Home Health Use Compared to Other Post-Acute Care Settings

Epidemiological approach to nosocomial infection surveillance data: the Japanese Nosocomial Infection Surveillance System

Medicare Spending and Rehospitalization for Chronically Ill Medicare Beneficiaries: Home Health Use Compared to Other Post-Acute Care Settings

Rapid Response Team Building

Predictors of In-Hospital vs Postdischarge Mortality in Pneumonia

Metro South Health Intensive Care Services Strategy

Using the Trauma Quality Improvement Program (TQIP) Metrics Data to Change Clinical Practice Abigail R. Blackmore, MSN, RN Pamela W.

Family Integrated Care in the NICU

The impact of an ICU liaison nurse service on patient outcomes

*Your Name *Nursing Facility. radiation therapy. SECTION 2: Acute Change in Condition and Factors that Contributed to the Transfer

Gill Schierhout 2*, Veronica Matthews 1, Christine Connors 3, Sandra Thompson 4, Ru Kwedza 5, Catherine Kennedy 6 and Ross Bailie 7

Association between implementation of an intensivist-led medical emergency team and mortality

For Vanderbilt Medical Center Carolyn Buppert, NP, JD Law Office of Carolyn Buppert

Trends in Consultation Rates in General Practice 1995 to 2006: Analysis of the QRESEARCH database.

Objectives 2/23/2011. Crossing Paths Intersection of Risk Adjustment and Coding

THE DETERIORATING PATIENT IN THE SUB-ACUTE SETTING. Australasian Rehabilitation Nurses Association June 26 th 2015

A Randomized Trial of a Family-Support Intervention in Intensive Care Units

The deteriorating patient recognition and management Dave Story

2015 Executive Overview

Burnout in ICU caregivers: A multicenter study of factors associated to centers

TQIP and Risk Adjusted Benchmarking

Dan Bronson-Lowe, PhD, CIC

Knowledge about systemic inflammatory response syndrome and sepsis: a survey among Dutch emergency department nurses

Week 3: Ratios, Rates, and Proportions (Part I)

William B. Saunders, PhD, MPH Program Director, Health Informatics PSM & Certificate Programs. Laura J. Dunlap, RN

Comparison of New Zealand and Canterbury population level measures

Paediatric Critical Care and Specialised Surgery in Children Review. Paediatric critical care and ECMO: interim update

Rapid Response Team and Patient Safety Terrence Shenfield BS, RRT-RPFT-NPS Education Coordinator A & T respiratory Lectures LLC

NUTRITION SCREENING SURVEY IN THE UK AND REPUBLIC OF IRELAND IN 2010 A Report by the British Association for Parenteral and Enteral Nutrition (BAPEN)

Focus on hip fracture: Trends in emergency admissions for fractured neck of femur, 2001 to 2011

O U T C O M E. record-based. measures HOSPITAL RE-ADMISSION RATES: APPROACH TO DIAGNOSIS-BASED MEASURES FULL REPORT

NURSING COMPUTER SOFTWARE. Level 2- Semester 4. Advanced Medical Surgical Nursing/ Clinical Lab

Abstract Session G3: Hospital-Based Medicine

TRANSPLANT SURGERY ROTATION (PGY4) A. Medical Knowledge

Northern Ireland COPD Audit

Dialysis facility characteristics and services

Predicting Transitions in the Nursing Workforce: Professional Transitions from LPN to RN

Using Predictive Analytics to Improve Sepsis Outcomes 4/23/2014

E-BULLETIN Edition 11 UNINTENTIONAL (ACCIDENTAL) HOSPITAL-TREATED INJURY VICTORIA

National Provider Call: Hospital Value-Based Purchasing

Surviving Sepsis Campaign: Association Between Performance Metrics and Outcomes in a 7.5-Year Study

Protocol. This trial protocol has been provided by the authors to give readers additional information about their work.

The Power of the Pyramid:

Unplanned Readmissions to Acute Care From a Pediatric Postacute Care Hospital: Incidence, Clinical Reasons, and Predictive Factors

Transcription:

Supplementary Online Content Kaukonen KM, Bailey M, Suzuki S, Pilcher D, Bellomo R. Mortality related to severe sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-2012. JAMA. doi:10.1001/jama.2014.2637. emethods. APACHE admission diagnosis and detailed description of statistical analysis efigure 1. Availability of hospital and intensive care unit (ICU) beds efigure 2. All admissions, admissions with severe sepsis and proportion of ICU admissions with severe sepsis efigure 3. Mortality in severe sepsis/septic shock patients and in all other patients efigure 4. Hospital outcomes (death, home, to rehabilitation, to other hospital) in patients with severe sepsis from 2000 to 2012 with numbers indicating denominators efigure 5. Survival according to hospital length of stay efigure 6. Length of stay in deceased patients efigure 7. Stratified odds ratios for mortality in severe sepsis/septic shock referenced against the year 2000 efigure 8. Sensitivity analysis in the 63 ICUs that have contributed data each year from 2000 to 2012 etable 1. Multivariable analysis for risk of being septic etable 2. Characteristics of young patients with severe sepsis etable 3. Mortality in younger patients with severe sepsis/septic shock etable 4.Odds ratios for the annual change in risk in hospital outcomes for all patients with severe sepsis/septic shock in the 63 ICUs that contributed complete data This supplementary material has been provided by the authors to give readers additional information about their work.

emethods APACHE admission diagnosis with infection, SIRS criteria and organ failures. APACHE admission diagnosis consistent with infection: nonoperative: pneumonia, parasitic pneumonia, bacterial pneumonia, viral pneumonia, gastrointestinal tract perforation, gastrointestinal tract obstruction, neurologic infection, cellulitis or soft tissue infection; postoperative: respiratory infection, gastrointestinal tract perforation or rupture, cholecystitis or cholangitis, fistula or abscess surgery, peritonitis, cellulitis or soft tissue infection. Systemic inflammatory response syndrome (SIRS) criteria: Body temperature >38 C or <36 C Heart rate >90/minute Respiratory rate >20/minute or PaCO2 lower than 32 mmhg (4.3 kpa) White blood cell count >12 000 /µl (>12 x10 9 /L) or <4 000 /µl (<4 x10 9 /L) Organ failures: cardiovascular failure: lowest MAP <65 mmhg or lowest systolic pressure <90 mmhg, respiratory failure: intubation and ventilation, hepatic failure: Bilirubin 5.96 mg/dl (102 µmol/l), renal failure: highest creatinine 3.39 mg/dl (300 µmol/l) or urine output <410 ml/24h or acute renal failure. Acute renal failure was defined as: 1. urine output <410 ml/24h and 2. creatinine 1.50 mg/dl (133 µmol/l) and 3. no chronic dialysis lowest platelet count <50 x10 3 /µl (<50 x10 9 /L)

Detailed description of statistical analysis Logistic regression for risk of being septic at ICU admission: Model construction was made using a stepwise selection procedure (inclusion criteria p<0.001) with the following variables considered for inclusion: admission source for hospital and ICU, hospital level, location and care type, year and month of admission, age, gender and chronic comorbidities. The three stage multivariable modelling process to examine the change in hospital outcome over time specifically amongst the sepsis population: Firstly, a stepwise selection procedure was applied to a multinomial logistic model to identify factors that were significantly related to hospital outcome. The following variables were considered for model inclusion: admission source for hospital and ICU, hospital level, size, location, and care type, year and month of admission, age, gender, patient severity, comorbidities, risk of being septic, ventilation status, medical or surgical admission and principal diagnosis. Secondly, first order interaction terms between each significant main effect and year of admission (continuous variable) were created and a stepwise regression procedure was used to sequentially identify interactions that were found to have a statistically significant impact on the relationship between hospital outcome and year of admission. Finally, for increased interpretability, the 15 significant main effects and 5 significant first order interactions with year of admission, were individually fitted to each hospital outcome using ordinary logistic regression. All logistic regression results have been reported as odds ratios (95% CI). Given a large database (>1,000,000 ICU patients, >100,000 sepsis patients), in order to more closely align clinical and statistical significance, a twosided p-value of 0.001 was used for variable inclusion and to indicate statistical significance. Time to Death Time to death was analysed using Cox-proportional hazards regression accounting for year of admission(treated as continuous), Apache III risk of death, risk of being septic and centre, with results presented as hazard ratios (95% CI). To further clarify the change over time, the 13 year study period was divided into 3 cohorts (2000-2004, 2005-2008, 2009-2012) and presented as a Kaplan Meier curve with a log-rank test for equality across the 3 strata.

efigure 1. Availability of hospital and intensive care unit (ICU) beds Available ICU beds/100,000 inhabitants ICU Ventilator beds/100,000 inhabitants 10 9 8 7 6 5 4 3 2 1 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Hospital beds/100,000 inhabitants 250 200 150 100 50 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Annual number of intensive care unit (ICU) beds (available beds and ventilator beds, upper panel) and hospital beds (lower panel) per 100,000 inhabitants in Australia and New Zealand.

efigure 2. All admissions, admissions with severe sepsis and proportion of ICU admissions with severe sepsis. 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 ICU admissions/ 1,000 inhabitants ICU admissions with severe sepsis/ 1,000 inhabitants 12.0 Severe sepsis admissions/all admissions (%) 10.0 8.0 6.0 4.0 2.0 0.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Annual incidence of intensive care unit (ICU) admissions and ICU admissions with severe sepsis per 1,000 inhabitants in Australia and New Zealand (upper panel) and proportion of severe sepsis admissions as percentage of ICU admissions (lower panel).

efigure 3. Mortality in severe sepsis/septic shock patients and in all other patients. 40.0% Mortality from 2000 to 2012 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 All others 13.7% 13.0% 12.5% 12.0% 11.3% 10.8% 10.2% 10.0% 9.7% 9.4% 8.9% 8.7% 8.0% Sepsis 35.0% 33.6% 31.2% 30.1% 28.9% 26.2% 25.7% 24.5% 23.9% 22.0% 21.0% 19.8% 18.4% Crude mortality in severe sepsis/septic shock patients and in all other intensive care unit (ICU) patients.

efigure 4. Hospital outcomes (death, home, to rehabilitation, to other hospital) in patients with severe sepsis from 2000 to 2012 with numbers indicating denominators.

efigure 5. Survival according to hospital length of stay. 0.00 0.25 0.50 0.75 1.00 Hospital survival 0 50 100 150 200 days 250 300 350 Number at risk 2000-04 22755 2348 537 210 112 80 63 44 2005-08 31940 2989 653 247 120 83 61 43 2009-12 46369 3493 696 241 106 63 41 35 2000-04 2005-08 2009-12 logrank p<0.001 Kaplan Meier curves for survival in 2000-2004 (blue line), 2005-2008 (red line) and 2009-2012 (green line). Cox porportional hazard ratio for the declining risk in mortality per year (adjusting for APACHE III, risk of being septic and attending site) was 0.97 (95% CI, 0.97-0.97).

efigure 6. Length of stay in deceased patients Geometric Means (95% Confidence Intervals) for length of stay in deceased patients. Adjustments were performed for APACHE III risk of death and the risk of being septic with patients nested within sites and each site treated as a random effect. There was no significant linear trend for a change over time (P=0.74)

efigure 7. Stratified odds ratios for mortality in severe sepsis/septic shock referenced against the year 2000. 1 Metro Private Tertiary Rural Odds ratio 0.5 0.25 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 1 Small(<300) Med(300 500) Large(>500) Odds ratio 0.5 0.25 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 Hos LOS <5 Hos LOS 5 9 1 Hos LOS 9 17 Hos LOS >17 Odds ratio 0.5 0.25 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Adjustments were performed for APACHE III risk of death and the risk of being septic with patients nested within site and site treated as a random effect. There were statistically significant differences between stratified groups of hospital level (P<0.001) (uppermost panel), hospital size (P<0.001) (middle panel) and hospital length of stay (HOSLOS) (lowest panel). Confidence intervals have been omitted for clarity.

efigure 8. Sensitivity analysis in the 63 ICUs that have contributed data each year from 2000 to 2012. Odds ratios for hospital outcome referenced against the year 2000. P-values for the difference in trajectory for sepsis versus non-sepsis patients with year treated as a continuous variable are as follows; death 0.94 (0.94-0.95) vs. 0.94 (0.94-0.94) P=0.43, discharged Home 1.03 (1.02-1.03) vs. 1.01 (1.00-1.01) P<0.0001), discharge to other hospital 0.99 (0.98-1.00) vs. 0.99 (0.98-0.99) P=0.13 and discharge to rehabilitation 1.08 (1.07-1.09) vs. 1.10 (1.10-1.11) P<0.0001. Odds ratios have been generated adjusting for patient severity and the risk of being septic, with patients nested within hospital and hospital treated as a random effect.

etable 1. Multivariable analysis for risk of being septic The variables included in deriving each patient s risk of being septic. Odds ratios (95% confidence intervals, CI) Effect N OR (CI) Effect N OR (CI) ICU Source (ref=operating room) 543830 Month (ref=february) 82029 ICU Source: Emergency 269144 3.20 (3.14-3.26) January 76119 1.08 (1.04-1.12) ICU Source: Ward 139469 4.27 (4.18-4.35) March 89282 1.02 (0.98-1.05) ICU Source: Other ICU same hospital 3065 2.42 (2.16-2.70) April 81178 1.05 (1.01-1.09) ICU Source: Other hospital 73713 3.51 (3.41-3.61) May 89018 1.04 (1.01-1.08) ICU Source: Other hospital ICU 5674 3.92 (3.62-4.23) June 86603 1.08 (1.04-1.11) ICU Source: Unknown 2220 2.01 (1.69-2.38) July 91309 1.12 (1.09-1.16) Hospital Admission source (ref=home) 749256 August 92995 1.12 (1.08-1.16) Hospital Admission source: Other Hospital 165399 1.29 (1.26-1.31) September 86825 1.11 (1.07-1.15) Hospital Admission source: Chronic Care 13007 1.55 (1.48-1.63) October 88490 1.03 (0.99-1.06) Hospital Admission source: Other ICU 10411 1.41 (1.32-1.49) November 89645 1.03 (1.00-1.07) Hospital Admission source: Unknown 99042 0.75 (0.72-0.77) December 83622 1.08 (1.05-1.12) State or Country (ref=victoria) 251465 Year of admission 37722 (ref=2000) Australia capital territory 25755 1.36 (1.30-1.42) 2001 48783 1.10 (1.05-1.16) New South Wales 315741 1.16 (1.13-1.18) 2002 56640 1.19 (1.13-1.25) Northern Territory 15946 2.17 (2.08-2.27) 2003 63614 1.20 (1.14-1.26) New Zealand 58488 1.23 (1.19-1.27) 2004 71667 1.26 (1.20-1.33) Queensland 222760 1.07 (1.05-1.10) 2005 79207 1.24 (1.18-1.30) South Australia 74628 1.35 (1.32-1.39) 2006 83553 1.31 (1.25-1.38) Tasmania 18225 1.23 (1.17-1.29) 2007 86826 1.36 (1.29-1.42) Western Australia 54107 1.17 (1.13-1.22) 2008 86176 1.41 (1.34-1.48) Gender (ref=female) 425975 2009 95119 1.51 (1.44-1.58) Male 610791 1.18 (1.16-1.19) 2010 104752 1.50 (1.43-1.57) Unknown 349 0.98 (0.69-1.41) 2011 110258 1.55 (1.48-1.63) Hospital Level (ref=private) 253111 2012 112798 1.54 (1.47-1.61) Rural Hospitals 133428 2.22 (2.16-2.29) Age group (ref <=44) 206423 Metro Hospitals 174489 2.48 (2.42-2.55) Age group 45-64 308357 1.61 (1.58-1.65) Tertiary Hospitals 476087 1.86 (1.82-1.91) Age group 65-84 455125 2.06 (2.02-2.10) Care Type (ref=hdu) 168517 Age group >=85 67210 2.70 (2.62-2.78) ICU 766355 1.51 (1.48-1.54) Unknown 102243 1.06 (1.02-1.10) Chronic comorbidities (yes vs no) AUROC 0.753 Cardiovascular disease 116828 0.86 (0.84-0.88) Renal disease 31014 1.70 (1.64-1.75) Immune suppressive disease 19067 1.38 (1.32-1.44) Immune suppressive therapy 30866 1.71 (1.58-1.86) Aids 385 2.78 (2.20-3.50) Lymphoma 7093 2.42 (2.29-2.56) Metastastes 31983 1.27 (1.22-1.31) Leukemia 9022 2.69 (2.56-2.83) Immunosuppression 29476 1.46 (1.34-1.59) Cirrhosis 14809 1.46 (1.39-1.53)

etable 2. Characteristics of young patients with severe sepsis. Baseline characteristics and outcomes of young ( 44 years) patients with severe sepsis or septic shock stratified by the presence of co-morbidities in APACHE II or III chronic health evaluation co-morbidities. Variable All patients 44 years N=15,471 44 without comorbidities b N = 11,793 44 with comorbidities b N = 3,678 Age, years, mean (SD) 31.6 (9.6) 30.9 (9.8) 34.0 (8.4) a Male Gender, percent (number) 49% (7524) 48% (5662) 51% (1862) Surgical admission, percent (number) 16% (2450) 18% (2117) 9% (333) a APACHE III Score, mean (SD) 54.8 (29.8) 47.5 (20.7) 59.9 (20.4) a APACHE III risk of death, % median (IQR) 9.1 (3.5-24.4) 7.3 (2.9-17.3) 20.5 (8.1-48.1) a Intensive care unit length of stay, days, median (IQR) 3.0(1.5-6.9) 3.0 (1.5-6.9) 3.1 (1.5-7.2) Hospital length of stay, days, median (IQR) 10.8 (5.8-22.2) 10.0 (5.6-20.4) 14.4 (6.8-28.9) a Limitation of treatment, percent (number) 1% (190) 1% (77) 3% (113) a Intensive care unit mortality, percent (number) 9% (1434) 7% (776) 18% (658) a Hospital outcomes Mortality, percent (number) 12% (1784) 8% (902) 24% (882) a Discharge: Home, percent (number) 76% (11724) 79% (9318) 65% (2406) a Discharge: Rehabilitation, percent (number) 3% (514) 3% (411) 3% (103) Discharge: Other Hospital, percent (number) 9% (1449) 10% (1162) 8% (287) a Subgroups Severe Sepsis, percent (number) 54% (8363) 51% (1891) 55% (6472) a Septic Shock, percent (number) 46% (7108) 49% (1787) 45% (5321) a Medical admission, percent (number) 84% (13021) 91% (3345) 82% (9676) a Surgical admission, percent (number) 16% (2450) 9% (333) 18% (2117) a Respiratory failure c, percent (number) 48% (7410) 40% (1479) 50% (5931) a Acute Renal Failure d, percent (number) 10% (1613) 16% (606) 9% (1007) a APACHE II <25, percent (number) 86% (12783) 71% (2488) 91% (10295) a APACHE II 25, percent (number) 14% (2037) 29% (1018) 9% (1019) a APACHE III (<50), percent (number) 56% (6902) 35% (938) 61% (5964) a APACHE III (50-66), percent (number) 22% (2795) 29% (775) 21% (2020) a APACHE III (67-87), percent (number) 16% (1982) 25% (678) 13% (1304) a APACHE III (>87), percent (number) 5% (569) 9% (242) 3% (327) a Sepsis (not UTI e ), percent (number) 23% (3613) 27% (998) 22% (2615) a Sepsis with shock (not UTI e ), percent (number) 19% (3002) 27% (996) 17% (2006) a a Comparisons made between patients without and with co-morbidities (P<0.001), b Co-morbidity as defined by the APACHE II 23 or APACHE III 24 chronic health evaluation classification system c Respiratory failure is defined by mechanical ventilation and intubation. d Acute renal failure is defined by highest creatinine 3.39 mg/dl (300 µmol/l) or urine output <410 ml/24h or 1-3: 1. urine output <410 ml/24h and 2. creatinine 1.50 mg/dl (133 µmol/l) and 3. no chronic dialysis e Urinary Tract Infection

etable 3. Mortality in younger patients with severe sepsis/septic shock. Mortality in younger ( 44 years) patients with severe sepsis or septic shock, and subgroups of younger patients. n Mortality 2000 (95% CI) Mortality 2012 (95% CI) Absolute Risk Reduction (95% CI) Relative Risk Reduction (95% CI) All young patients 15471 22.1% (18.2%-26.0%) 7.3% (6.1%-8.5%) 14.8% (11.0%-19.1%) 66.9% (58.0%-74.0%) Without co-morbidities a 11793 16.2% (12.3%-20.1%) 4.6% (3.4%-5.8%) 11.6% (7.8%-16.0%) 71.6% (60.0%-79.8%) With co-morbidities a 3678 40.4% (31.2%-49.6%) 17.2% (13.5%-20.9%) 23.2% (13.5%-33.2%) 57.4% (41.6%-69.0%) Severe Sepsis 8363 14.9% (10.4%-19.4%) 5.1% (3.7%-6.5%) 9.9% (5.6%-15.1%) 66.0% (48.5%-77.5%) Septic Shock 7108 30.7% (24.2%-37.2%) 9.5% (7.5%-11.5%) 21.2% (14.9%-28.1%) 69.0% (58.5%-76.8%) Medical admissions 13021 23.7% (19.4%-28.0%) 8.3% (6.9%-9.7%) 15.4% (11.2%-20.1%) 65.0% (55.2%-72.6%) Surgical admissions 2450 9.8% (1.6%-18.0%) 3.0% (1.2%-4.8%) 6.8% (0.8%-18.1%) 69.5% (14.3%-89.1%) Respiratory failure b 7410 28.4% (23.1%-33.7%) 11.3% (8.9%-13.7%) 17.1% (11.5%-23.1%) 60.2% (47.6%-69.8%) Acute renal failure c 1613 44.8% (35.2%-54.4%) 19.6% (14.9%-24.3%) 25.2% (14.8%-35.6%) 56.3% (40.0%-68.1%) APACHE II <25 12783 12.0% (8.5%-15.5%) 3.7% (2.7%-4.7%) 8.3% (5.1%-12.4%) 69.2% (54.7%-79.1%) APACHE II 25 2037 58.8% (49.0%-68.6%) 38.7% (31.4%-46.0%) 20.0% (7.6%-31.6%) 34.1% (15.3%-48.7%) APACHE III (<50) 6902 6.2% (2.5%-9.9%) 1.1% (0.5%-1.7%) 5.2% (2.2%-10.0%) 83.0% (60.6%-92.7%) APACHE III (50-66) 2795 8.3% (2.4%-14.2%) 6.4% (3.9%-8.9%) 1.9% (-3.3%-10.1%) 23.0% (-74.1%-66.0%) APACHE III (67-87) 1982 23.5% (13.3%-33.7%) 11.1% (7.0%-15.2%) 12.5% (2.7%-24.3%) 53.0% (16.8%-73.4%) APACHE III (>87) 569 60.4% (50.6%-70.2%) 41.6% (34.2%-49%) 18.8% (6.3%-30.4%) 31.1% (12.5%-45.8%) Sepsis, (notuti d ) 3613 15.3% (7.7%-22.9%) 6.0% (3.6%-8.4%) 9.3% (2.6%-18.6%) 60.8% (26.5%-79.1%) Sepsis with shock (not UTI d ) 3002 38.2% (29.8%-46.6%) 16.7% (12.4%-21%) 21.4% (12.3%-30.8%) 56.2% (38.7%-68.7%) a co-morbidity as defined by the APACHE II 23 or APACHE III 24 chronic health evaluation classification system b Respiratory failure is defined by mechanical ventilation and intubation. c Acute renal failure is defined by highest creatinine 3.39 mg/dl (300 µmol/l) or urine output <410 ml/24h or 1-3: 1. urine output <410 ml/24h and 2. creatinine 1.50 mg/dl (133 µmol/l) and 3. no chronic dialysis d Urinary Tract Infection

etable 4.Odds ratios for the annual change in risk in hospital outcomes for all patients with severe sepsis/septic shock in the 63 ICUs that contributed complete data. Odds ratios (95%CI) for the annual change in risk in hospital outcomes for all patients with severe sepsis/septic shock in the 63 ICUs that contributed complete data from 2000 to 2012 (n=66050 (61%)) and for subgroups of these patients for which the change in risk was found to differ significantly (P<0.001). The annual decline in mortality for all severe sepsis/septic shock in the 63 ICUs that contributed complete data from 2000 to 2012 was given by an odds ratio of 0.94 (0.94 0.95). This decline in risk was significantly influenced by patient severity [lowest Apache III quartile 0.91 (0.88 0.94) vs. highest Apache III quartile 0.95 (0.92 0.97)], hospital level [Rural 0.92 (0.89 0.95) vs. Metropolitan 0.95 (0.93 0.98)], hospital admission source [Home 0.93 (0.91 0.96) vs. Other ICU 0.97 (0.93 1.02)] and state or country [Western Australia 0.87 (0.84 0.91) vs. Australian Capital Territory 0.98 (0.94 1.01)]. Effect modifier Outcome: death Outcome: home Outcome: other hospital Outcome: rehabilitation N Overall change per year OR (95%CI) 66050 0.94 (0.94 0.95) 1.03 (1.02 1.03) 0.99 (0.98 1.00) 1.08 (1.07 1.09) Patient severity Apache III 1st quartile (<50) 15407 0.91 (0.88-0.94) 1.02 (1.00-1.04) 0.99 (0.96-1.03) 1.08 (1.00-1.63) Apache III 2nd quartile (50-66) 16275 0.94 (0.92-0.97) 1.02 (1.00-1.04) 1.00 (0.97-1.03) 1.06 (1.00-1.46) Apache III 3rd quartile (67-87) 17197 0.94 (0.92-0.97) 1.03 (1.01-1.05) 1.01 (0.97-1.04) 1.07 (1.01-1.46) Apache III 4th quartile (>87) 16894 0.95 (0.92-0.97) 1.04 (1.01-1.06) 1.02 (0.99-1.06) 1.08 (1.02-1.49) Intensive Care type ICU 52550 0.93 (0.91-0.96) 1.03 (1.01-1.05) 1.01 (0.98-1.04) 1.06 (0.99-1.55) High-dependency unit 8781 0.95 (0.92-0.99) 1.01 (0.98-1.04) 1.01 (0.98-1.05) 1.00 (0.93-1.28) Hospital Type Rural 9581 0.92 (0.89-0.95) 1.03 (1.01-1.06) 1.02 (0.98-1.06) 1.06 (0.87-3.74) Metropolitan 17542 0.95 (0.93-0.98) 1.01 (0.99-1.04) 1.03 (1.00-1.06) 1.03 (0.98-1.08) Tertiary 33752 0.93 (0.91-0.96) 1.03 (1.01-1.06) 1.00 (0.97-1.03) 1.10 (1.05-1.15) Private 5175 0.94 (0.92-0.97) 1.01 (0.99-1.04) 0.95 (0.92-0.99) 1.10 (1.05-1.15) Hospital Admission source Home 42494 0.93 (0.91-0.96) 1.03 (1.01-1.05) 1.01 (0.98-1.04) 1.06 (0.99-1.61) Other Hospital 16138 0.94 (0.91-0.96) 1.04 (1.02-1.06) 0.99 (0.96-1.02) 1.06 (1.00-1.30) Chronic Care 1478 0.95 (0.91-0.99) 0.98 (0.94-1.02) 0.99 (0.93-1.06) 1.10 (1.02-1.51) Other ICU 1175 0.97 (0.93-1.02) 0.99 (0.95-1.03) 0.97 (0.92-1.01) 1.24 (1.12-1.78) Unknown 4765 0.93 (0.90-0.97) 0.98 (0.95-1.01) 1.03 (0.99-1.08) 1.21 (1.13-1.30) State or Country Australian Central Territory 1715 0.98 (0.94-1.01) 1.00 (0.97-1.04) 1.02 (0.97-1.06) 1.00 (0.93-1.08) New South Wales 24099 0.94 (0.92-0.96) 1.04 (1.02-1.06) 1.00 (0.97-1.03) 1.10 (1.05-1.15) Northern Territory 3375 0.95 (0.91-0.98) 1.03 (1.00-1.06) 1.03 (0.99-1.07) 0.82 (0.74-0.90) Queensland 11567 0.93 (0.90-0.95) 1.02 (1.00-1.04) 1.00 (0.97-1.03) 1.13 (1.08-1.18) South Australia 7667 0.94 (0.91-0.96) 1.06 (1.03-1.08) 1.00 (0.97-1.04) 0.98 (0.94-1.03) Tasmania 1160 0.92 (0.88-0.96) 1.10 (1.06-1.14) 0.92 (0.87-0.97) 1.10 (0.95-1.27) Victoria 13532 0.93 (0.91-0.96) 0.99 (0.97-1.01) 1.02 (0.99-1.06) 1.10 (1.05-1.14) Western Australia 1608 0.87 (0.84-0.91) 0.99 (0.96-1.02) 1.03 (0.99-1.08) 1.23 (1.16-1.30) New Zealand 1327 0.94 (0.90-0.99) 1.05 (1.00-1.09) 1.01 (0.94-1.09) 1.02 (0.05-20.01)