ccc - ‘ids after epc’ epoch a project of the canadian ... · christopher s parshuram staff...

a cluster-randomised trial of a documentation-based system of care

CCCF 9:10-9:30 ‘Kids after EPOCH’

EPOCHEvaluating Processes of care and Outcomes of Children in Hospital

a project of the Canadian Critical Care Trials Group

Christopher S Parshuramstaff physician Department of Critical Care Medicine senior scientist Child Health Evaluative Sciences Program. The Research Institute.Hospital for Sick Children. director Centre for Safety Research. professor Interdepartmental Division of Critical Care Medicine & Departments of Pediatrics & Health Policy, Management and Evaluation. faculty Patient Safety Centre, Faculty of Medicine, Univeristy of Toronto, Canada.

and the EPOCH Investigators for the Canadian Critical Care Trials Group

NCT01260831

Christopher S Parshuram MB.ChB. D.Phil.Physician: Critical Care Medicine Scientist: Child Health Evaluative Sciences Hospital for Sick Children Professor: University of Toronto

Ontario, Canada. EPOCH

disclosures

Named inventor: Patent Bedside Paediatric Early Warning System. Owner the Hospital for Sick Children.

Shareholder: Bedside Clinical Systems - a clinical decision support company in part owned by the Hospital for Sick Children.



clinical deterioration GAPIll

ness

Sev

erity

Qua

ntifi

catio

n (S

core

)

Discharge

Death

IntervenePrevent

Routine Care Needs

Increased Care Needs

Critical Illness

Cardiac Arrest

Ward

ICU



1 cardiac arrest 25-40% survival2 morbidity of ‘late prevention’ reduced QoL3 excess mortality & morbidity 14 vs 28%4 low frequency 5-20/1000 pt-days5 well children & clinician optimism 6 reconceptualized as a system failure

potentially preventable

the GAP



RESEARCH Open Access

Multicentre validation of the bedside paediatricearly warning system score: a severity of illnessscore to detect evolving critical illness inhospitalised childrenChristopher S Parshuram1,2,3,4,5,6,7,8,9*, Heather P Duncan9, Ari R Joffe10,11, Catherine A Farrell12, Jacques R Lacroix12,Kristen L Middaugh2,3, James S Hutchison1,3,4,6,7,13, David Wensley14, Nadeene Blanchard2,3, Joseph Beyene2,15,16

and Patricia C Parkin2,3,4,5

Abstract

Introduction: The timely provision of critical care to hospitalised patients at risk for cardiopulmonary arrest iscontingent upon identification and referral by frontline providers. Current approaches require improvement. In asingle-centre study, we developed the Bedside Paediatric Early Warning System (Bedside PEWS) score to identifypatients at risk. The objective of this study was to validate the Bedside PEWS score in a large patient population atmultiple hospitals.

Methods: We performed an international, multicentre, case-control study of children admitted to hospital inpatientunits with no limitations on care. Case patients had experienced a clinical deterioration event involving either animmediate call to a resuscitation team or urgent admission to a paediatric intensive care unit. Control patients hadno events. The scores ranged from 0 to 26 and were assessed in the 24 hours prior to the clinical deteriorationevent. Score performance was assessed using the area under the receiver operating characteristic (AUCROC) curveby comparison with the retrospective rating of nurses and the temporal progression of scores in case patients.

Results: A total of 2,074 patients were evaluated at 4 participating hospitals. The median (interquartile range)maximum Bedside PEWS scores for the 12 hours ending 1 hour before the clinical deterioration event were 8 (5 to12) in case patients and 2 (1 to 4) in control patients (P < 0.0001). The AUCROC curve (95% confidence interval)was 0.87 (0.85 to 0.89). In case patients, mean scores were 5.3 at 20 to 24 hours and 8.4 at 0 to 4 hours before theevent (P < 0.0001). The AUCROC curve (95% CI) of the retrospective nurse ratings was 0.83 (0.81 to 0.86). This wassignificantly lower than that of the Bedside PEWS score (P < 0.0001).

Conclusions: The Bedside PEWS score identified children at risk for cardiopulmonary arrest. Scores were elevatedand continued to increase in the 24 hours before the clinical deterioration event. Prospective clinical evaluation isneeded to determine whether this score will improve the quality of care and patient outcomes.

IntroductionTimely application of critical care improves patient out-comes [1-4] but depends upon early identification ofpatients at risk [5,6]. Late recognition resulting in cardi-opulmonary arrest occurs in 0.1 to 20 of 1,000 children

admitted to hospital inpatient units [7-9] and is asso-ciated with poor survival [10] and significant morbidityin survivors [8,11-15].Systems that distinguish patients at risk for near and

actual cardiac arrest from other low-risk, ‘well’ hospita-lised patients will minimise false-alarm calls to criticalcare teams while identifying patients at risk. To date,few identification systems have undergone methodologi-cally rigorous development and evaluation [6,16-18].

* Correspondence: [email protected] of Critical Care Medicine, Hospital for Sick Children, 555University Avenue, Toronto, ON, M5G 1X8, CanadaFull list of author information is available at the end of the article

Parshuram et al. Critical Care 2011, 15:R184http://ccforum.com/content/15/4/R184

© 2011 Parshuram et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly cited.

EPOCH



rapid ‘response’

initial mortality benefit ‘resolved’‘positive’ B&A paediatric studies questionable benefit



Does the BedsidePEWS... improve early detection of critical illness reduce mortality & improve processes of care without increasing healthcare utilization ?

research questions



BedsidePEWSBedside Paediatric Early Warning System

1

validated score to quantify severity of illness & risk of deterioration

2 documentation record representation, score calculation & decision support

3 score matched recommendationsa safety-net that describes reasonable care

4 implementation programeducator-designed, frontline expert tested

enthusiasm but no MET-RRT required

RESEARCH Open Access

Multicentre validation of the bedside paediatricearly warning system score: a severity of illnessscore to detect evolving critical illness inhospitalised childrenChristopher S Parshuram1,2,3,4,5,6,7,8,9*, Heather P Duncan9, Ari R Joffe10,11, Catherine A Farrell12, Jacques R Lacroix12,Kristen L Middaugh2,3, James S Hutchison1,3,4,6,7,13, David Wensley14, Nadeene Blanchard2,3, Joseph Beyene2,15,16

and Patricia C Parkin2,3,4,5

Abstract

Introduction: The timely provision of critical care to hospitalised patients at risk for cardiopulmonary arrest iscontingent upon identification and referral by frontline providers. Current approaches require improvement. In asingle-centre study, we developed the Bedside Paediatric Early Warning System (Bedside PEWS) score to identifypatients at risk. The objective of this study was to validate the Bedside PEWS score in a large patient population atmultiple hospitals.

Methods: We performed an international, multicentre, case-control study of children admitted to hospital inpatientunits with no limitations on care. Case patients had experienced a clinical deterioration event involving either animmediate call to a resuscitation team or urgent admission to a paediatric intensive care unit. Control patients hadno events. The scores ranged from 0 to 26 and were assessed in the 24 hours prior to the clinical deteriorationevent. Score performance was assessed using the area under the receiver operating characteristic (AUCROC) curveby comparison with the retrospective rating of nurses and the temporal progression of scores in case patients.

Results: A total of 2,074 patients were evaluated at 4 participating hospitals. The median (interquartile range)maximum Bedside PEWS scores for the 12 hours ending 1 hour before the clinical deterioration event were 8 (5 to12) in case patients and 2 (1 to 4) in control patients (P < 0.0001). The AUCROC curve (95% confidence interval)was 0.87 (0.85 to 0.89). In case patients, mean scores were 5.3 at 20 to 24 hours and 8.4 at 0 to 4 hours before theevent (P < 0.0001). The AUCROC curve (95% CI) of the retrospective nurse ratings was 0.83 (0.81 to 0.86). This wassignificantly lower than that of the Bedside PEWS score (P < 0.0001).

Conclusions: The Bedside PEWS score identified children at risk for cardiopulmonary arrest. Scores were elevatedand continued to increase in the 24 hours before the clinical deterioration event. Prospective clinical evaluation isneeded to determine whether this score will improve the quality of care and patient outcomes.

IntroductionTimely application of critical care improves patient out-comes [1-4] but depends upon early identification ofpatients at risk [5,6]. Late recognition resulting in cardi-opulmonary arrest occurs in 0.1 to 20 of 1,000 children

admitted to hospital inpatient units [7-9] and is asso-ciated with poor survival [10] and significant morbidityin survivors [8,11-15].Systems that distinguish patients at risk for near and

actual cardiac arrest from other low-risk, ‘well’ hospita-lised patients will minimise false-alarm calls to criticalcare teams while identifying patients at risk. To date,few identification systems have undergone methodologi-cally rigorous development and evaluation [6,16-18].

* Correspondence: [email protected] of Critical Care Medicine, Hospital for Sick Children, 555University Avenue, Toronto, ON, M5G 1X8, CanadaFull list of author information is available at the end of the article

Parshuram et al. Critical Care 2011, 15:R184http://ccforum.com/content/15/4/R184

© 2011 Parshuram et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly cited.

Care RecommendationsBedside PEWS Score® Recommendationsvalue

or

other

charting in ‘value section” of BPEWS record

or

other significant deterioration

immediate consider CPR Monitoring ICU consult

if patient stays on ward formalize a customized plan

1 Initial recommendations are intended to be applied when a patient either has their initial Bedside PEWS score calculated on admission to the hospital ward, or when the patients condition is changing as indicated by an increase or decrease in the category of their Bedside PEWS score.

2 Subsequent recommendations are intended to assist level of care decision-making for children who after review have a BPEWS score remaining in the same category and who are continue to be cared in a hospital ward.

3 ICU Consultation includes referral to a Medical Emergency Team or other “ICU Outreach” service. These items are recommendations to be applied at the discretion of the frontline health care professionals providing patient care. They are intended to augment clinical judgement, not replace it.



design

RUsual CareUsual Care

BedsidePEWS Usual Care

run

in

Control

Intervention26 weeks 52 weeks

eligible: Hospital with PICU + willing to be randomised

hospitals randomized 1 : 1 ratioconcealment until week oneanalyses account for clustering, baseline rates, volumesub-group anlayses: ECMO, MET-RRTrationale : best available system to compare vs. control



primary outcome

all-cause hospital mortality

objective in an inherently unblinded study is independent of care limitations (DNR)

estimated 5/1000 patient discharges >>> power 80% alpha 0.05 for ARR 0.1%



No major interventionnone of the below

Non-Invasive Ventilationunplanned BMV, CPAP, BIPAP

Late

ICU

Invasive Respiratoryendotracheal intubation

Circulatory>60 ml/kg, inotropes, pressors

Circ.+Invasive Resp.Circulatory and Intubation

CPR / ECMOcardiac massage or ECMO

Death irrespective of above

reveiwed for face validity at CCCTG and PALISI meetings, validated versus ICU mortality

late ICU admissionmain secondary outcome



resuscitation intensity

9

ICU

Mor

tality

%50

40

30

20

10

0

1 2 3 4 65 5Late ICU admissionEarly

CPR

369 patients urgent ICU transfer from inpatient ward5 deaths before transfer

15% overall mortality 22% ‘Late’ ICU admission



1 late detection of critical illness 2 cardiac arrest 3 potentially preventable cardiac arrest 4 unplanned hospital readmission 5 unplanned PICU readmission& in urgent PICU admission 6 PIM score (predicted mortality) 7 PICU mortality 8 PELOD score day1 & all PICU 9 Ventilator Free Days + ICU resource utilization

secondary outcomes



oversight processes1 dual study oversight: Executive Steering Committee Canadian Critical Care Trials Group

2 delegated randomisation 3 data safety & monitoring board4 site data confirmation & sign off

5 ESC writing committee6 independent statistician review7 independent pre-submission review



21 hospitals, 3 continents, 3 languages Jan 2011 -2015 Sept. 144,539 patients

results (preliminary)



all usual care BedsidePEWSHospitals

Sites 21 11 10

Staffed Paediatric Beds 2085 1148 937

>200 Beds 3 1 2

Rapid Response Team 9 4 5

ECMO 13 8 5

Patients*Hospital Discharges 144,539 94,366 50,173

*Ward Patient Days 559,443 307,584 251,859

*ICU Days 15,961 9,293 6,668

* post-randomization period only

the participants



1 880 hours meetings + local 2 education planned & delivered3 changed vital sign documentation4 run-in requiring >80% adherence5 ongoing local audit and feedback6 site-visit interactions/ observations 7 preliminary qualitative data

... (yes)

intervention fidelity



increased documentationprocess outcome usual care BedsidePEWS Rate Ratio (95%CI) p

adjusted mean differenceheart rate

measurements /24 hours 6.45 7.40 0.49 (0.09-0.89) 0.027

systolic blood pressuremeasurements /24 hours 3.58 5.05 0.96 (0.62-1.29) <0.0001

capillary refill time measurements /24 hours 1.66 6.66 4.55 (4.28-4.82) <0.0001

respiratory ratemeasurements /24 hours 5.53 7.38 0.48 (0.09-0.90) <0.0001

saturationmeasurements /24 hours 5.21 7.30 0.77 (0.33-1.21) 0.003

oxygen therapymeasurements /24 hours 3.00 7.16 4.99 (4.68-5.30) <0.0001

Odds Ratio most recent >5 vital signs

sets -- -- 12.9 (11.2-13.2) <0.0001

greater documentation with BedsidePEWS



main outcomesmain outcome usual care BedsidePEWS Odds or Rate

Ratio (95% CI) p

all-cause hospitalN (/1000 hospital discharges) 147 (1.56) 97 (1.93) 1.003 (0.77-1.32) 0.98

late ICU admissionN (/1000 hospital days) 257 (0.836) 121 (0.480) 0.763 (0.61-0.95) 0.016

similar all-cause hospital mortality mortality 60% lower than anticipated

less late ICU admission with BedsidePEWS 16% vs 24% of urgent ICU admission component clinical outcomes NS



timeliness of ICU

0102030405060708090

100

BedsidePEWS

Usual Care

_7_6_5_4_3_2_1

Patie

nts

with

clin

ical d

etio

ratio

n %

No m

ajor

Pos.

Pre

ss. V

Intu

batio

n

Circ

ulat

ory

Circ

.& R

esp.

CPR/

ECMO

Deat

h

1076

776 clinical deterioration events recieving interventions

no major pre-ICU intervention:65% control 77% BedsidePEWS

65%

77%

7.0days8.1days

ICU LoS

|--------Late ICU Admission--------| 16% BedsidePEWS 24% Usual Care



process outcomesmortality outcome usual care BedsidePEWS Odds or Rate

Ratio (95% CI) p

Resuscitation Team N (/1000 hospital days) 179 (0.582) 126 (0.50) 0.97 (0.77-1.23) 0.82

‘Stat’ calls for PhysicianN (/1000 hospital days) 1157 (3.762) 1727 (6.857) 1.17(1.09-1.26) < 0.0001

ICU / MET-RRT consult N (/1000 hospital days)) 1694 (5.507) 1015 (4.03) 1.05 (0.97-1..14) 0.26

similar ‘code-blue’ & ICU consult callsmore ‘we need the Dr. now’ with BedsidePEWS



ICU resource utilizationresource outcome usual care BedsidePEWS Odds Ratio Mean

Difference (95% CI) p

UICU Length of Stay mean 7.28 7.85 1.31 (-0.619-3.234) 0.20

ventilation days/1000 UICU days 273.93 273.5 -7.67 (-66.23-50.90) 0.80

technology-days/1000 ICU days 308.2 315.5 -17.8 (-89.0-53.5) 0.63

ECMO use% urgent ICU admit 16 (1.67%) 9 (1.31%) 0.33 (0.09-1.19) 0.09

HFOV use % urgent ICU admit 30 (3.13%) 25 (3.65%) 0.57 (0.25-1.27) 0.17

Dialysis use % urgent ICU admit 27 (2.82%) 27 (3.94%) 1.40 (0.50-3.92) 0.53

similar ICU resource utilization



BedsidePEWS vs usual care:1 similar hospital mortality 40% initially anticipated rate ->power vs. no difference zero assymptote...

2 decreased late ICU admission main secondary, prev. original main outcome 16% vs. 24% of urgent ICU admissions were late 78% vs. 91% CPA judged potentially preventable

3 changed processes of care more vital signs documented, more ‘Dr. now’

4 similar ICU resource utilization

interpretation



larger academic hospital focus unclear generalizablity to community hospitals no US hospitals, few EU.

major events were infrequent smaller regional hospitals had zero mortality ‘only’ 59 cardiac arrests

culture change challenging adherence needs review - physican & nurse actions 12m may be too short for complex healthcare intervention

more sub-study analyses to complete death, non-escalation, factors associated adoption,

limitations



questions addressed

Does BedsidePEWS ...Yes improve processes of care & Yes improve early detection of critical illnessYes not increase healthcare resourcesNo reduce mortality



many planned

sub studies



MET-RRT subgroupsAll Cause Mortality

Late ICU Admission

Hospital Mortality with DNR

ICU Mortality, Urgent ICU Admission as Denominator

ICU Mortality, Patient Discharges as Denominator

Clinical Deterioration Events

Cardiac Arrests (CA)

Potentially Preventable Cardiac Arrests

Unplanned ICU Readmissions

Unplan. Hospital Readmission

Resuscitation Team Calls

Stat Calls

Urgent ICU Consultations

Urgent ICU Admissions

MET-RRT interaction p

0.617

0.24

0.10

0.25

0.72

0.037

0.34

0.50

0.15

0.0256

0.61

< 0.0001

0.0096

0.0139

No MET-RRT

MET-RRT avaiable0.25 0.5 1 2

Favours intervention Favours usual care0.25 0.5 1 2



5 outcomes with significant interactions=different effect of BedsidePEWS in hospitals with/without MET

BedsidePEWS implementation ... in hospitals with no MET... >less clinical deterioration/ urgent ICU >more stat calls & urgent consults

Hypothesis generating ... increased use of ICU expertise with BedsidePEWS in non-MET

MET-RRT



additions & next

severity of illness quantificationdecision support (GUI/SMCR)real-time situational awareness

case-based team training

explicit event reviewSQUARE Severity Quantification clinical Assessments & Responses before Events

4RESPECT

video educational reference

safety method effect mechanism


Ontario, Canada.

heading onerecorded sessions

locally selected case

session form

library & additional materials

case variationsHC-FMEA what & how?

question responsesvideo, other documents

structured, patient-basedlow fidelity, team focussed conduct

Remote Expert Facilitator

Inter-professionalEducation

TIARA checklistBedsidePEWS

paediatric experts prepare & conduct sessions

identify -> real-time reviewinteractive, team-based

4RESPECT

localremote

on-s

ite e

duca

tion

inpa

tient

car

e



thank you

team EPOCHArianne Willems

Malika HazimBernard Wenderickx

Paul MourlhouAfrothite Kotsakis

Sarah GanderWendy HarrisJoanne Holland

Julie MacLeanDarlene Boliver

Stephanie CajolaisSamara ZavalkoffMaryse Dagenais

Sarah SheaMarc-Andre Dugas

Josee GaudreaultLouise Gosselin

Catherine FarrellCaroline Cler-ProulxLaurence Bertout

Isabelle GrisoniJonathan Duff

Jodie PughDenise Capito

Amanda BarclayFiona Auld

Laurie Robson

Jonathan GillelandLois Saunders

Douglas FraserPaige Bechard

Colleen MartinLindsay Spear

Kathleen ToblerKimberly Kulbaba

Nicola RobertsonDermot Doherty

Emma LadewigSuja Somanadhan

Louise GreensmithCormac Breatnach

Cathal O’RourkeCorrado Cecchetti

Orsola GawronskiAryanna Rusucitto

Ester Pagaduan CabillonGabrielle Nutall

Gregory D. WilliamsClaire Sherring

Tracey BushellMiriam ReaLouise ArmridingGreta Olykan

Cynthia Van der StarreAngelique Hogeboom

Andrea De Oude-LubbersMartin MartinNargis HematSimon BroughtonSarah Harris Emily DowningDavid InwaldRuchi Sinha

Sophie RaghunananMamta VaidyaLeanne Reardon

Margarita BurmesterKanwarjit KailayLoredana Haidu

Susan FerriJessica GrilloNida ShahidSarah Ashley

Simran SinghKate Byrne

Aarthi KamathKristen Middaugh

Michael-Alice MogaNelly Thwaites

Critical Care Collegues@SickkIds



[email protected] you

ccc - ‘ids after epc’ epoch a project of the canadian ... · christopher s parshuram staff...

Documents