reducing preventable inpatient deaths in community hospitals€¦ · reducing preventable inpatient...

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Reducing Preventable Inpatient Deaths in Community Hospitals

Quality Symposium • February 19, 2007

Dr. Jeremy Theal MD FRCPC, CMIO

Ms. Linna Yang RN MHI, Clinical Informatics

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Introduction of Speakers

Jeremy Theal MD FRCPC

Chief Medical Information Officer

Linna Yang RN MHI

Manager, Clinical Informatics

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Photo Here

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Conflict of Interest

Jeremy Theal MD FRCPC

Linna Yang RN MHI

We have no real or apparent conflicts of interest to report.

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Agenda

• Overview of NYGH’s multi-year eCare project

• Methodology for engaging clinicians and integrating evidence into daily care

• Results from our study of CPOE outcomes

• Iterative quality improvement with eCare

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Learning Objectives• Explain how engagement of clinicians is crucial for system adoption and culture change

• Illustrate why integration of standardized evidence into daily clinician workflow

catalyzes improvement in quality and safety of patient care

• Enumerate the patient care benefits that can result when the goals of clinician adoption,

evidence integration, culture change, and system stewardship are achieved together

• Outline success factors required for meaningful improvements in quality and safety of

patient care when designing, implementing and maintaining CPOE systems

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Realizing Value of Health IT (STEPS)

T – Treatment/Clinical

• Integrated up-to-date evidence

into daily decision-making workflow of physicians

• Reduced mortality among inpatients in the Medical program,

specifically those with a diagnosis of pneumonia or COPD

exacerbation

E – Electronic Secure Data

• Business intelligence for tracking/reporting use of evidence-based care and patient outcomes

• Iterative quality improvement though corporate quality framework

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About North York General Hospital

• Community teaching hospital

affiliated with University of Toronto,

serving > 400,000 citizens

• Three Facilities

• Beds: 426 acute care

192 long-term care

• Volumes per year:

– 124,000 ED visits

– 31,000 inpatient cases

– 214,000 outpatient cases

– 5,800 births

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What is eCare?

Advanced Electronic Medical Record

+

Standardization on Evidence-Based Care

+

Safe Prescribing andMedication Administration

+

Clinical Decision Support (Order Sets, Rules, Alerts)

=

Multi-year hospital-wide clinical

transformation project utilizing health

information technology

Kickoff: 2007

Phased Implementation:

2008-2015

Hospital-wide: 2015

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Goals of the eCare Project

• Implement advanced EMR to improve patient outcomes:

Quality and safety of patient care

Enable Clinical & Business intelligence for better decisions

• Embrace culture of evidence-based care, best practices

Make it “easy to do the right thing”

Build evidence and best practice into optimized workflows

• SHARED VISION = “by clinicians, for clinicians”

100% clinician adoption via comprehensive engagement

Team-based interprofessional approach/workflows

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Phases of eCare

Phase Date Scope

1 Oct 2008 Med/Surg: Clinical Doc (Nsg, Allied)

2 Oct 2010 Med/Surg/CrCU: CPOE, eMAR, CDS, MedsRec

3 June 2012 Paediatrics: CPOE, eMAR, CDS, MedsRec

CrCU: Device Integration, Documentation

4 Oct 2013 L&D/PP: CPOE, eMAR, CDS, MedsRec, integrated

Fetal Monitoring

OR System – device integration

Anesthesia integration – Anesthesia doc

5 Oct 2014 Mental Health – CPOE, eMAR, CDS, MedsRec

6 Oct 2015 NICU – CPOE, eMAR, CDS, MedsRec

7 IN

PROGRESSEmergency Department – Tracking, triage, CPOE,

eMAR, CDS, MedsRec, Documentation

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How Physicians use Evidence in Daily Practice

• “Pull model”: almost 0% success rate

• “Push model”: 75% success rate

• Order sets: a key mechanism for building evidence into workflow

Predictor of Success Adjusted OR

Computer-based generation of decision support 6.3

Provision of recommendation rather than just an assessment 7.1

Provision of decision support

at the time and location of decision-making

15.4

Automatic provision of decision support as part of workflow 112.1

Kawamoto K et al. Systematic review of clinical decision support system success factors. BMJ 2005

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Change Management

Focus on Physicians for CPOE

and Order Set adoption:

• Gap analysis: 350 order sets to build

• 3 years of effort leading up to go-live

(2007-2010), direct MD involvement

• CMIO and physician champion network

• Goal: Communicate at least 7 times, 7 ways

• Change Management seminars for

project team, Physician Champions

• Standardization on evidence (no personal order sets!)

• Hired external firm: final go-live campaign

13Case #4: Reducing Inpatient Mortality

Involving Clinicians in CPOE Content Development

1• Order Set Prototyping (central build team)

2

• Order Set Interprofessional Review (ViewSpace):Nursing, Allied Health, Lab, Radiology, Medical Imaging

3

• Order Set MD Review (ViewSpace):online, one-on-one, group sessions

4

• Comment review and consolidation, evidence updates, consensus meetings as needed

5• Order Set Final Approval (MAC - monthly)

Evidence for care

discussed at each

step

Evidence was the

foundation for

consensus

NO personalized

order sets permitted

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Order Set Review


Pneumonia Admission Order Set:Integrated Evidence

Risk Stratification (home / ward / Critical Care):

Prophylaxis and Proactive Care:


Pneumonia Admission Order Set: Evidence-Based Empiric Antibiotic Selection


Pneumonia Admission Order Set: Integrated Reference Links


Pneumonia Admission Order Set: “Choosing Wisely”

Workflow-integrated

clinical decision

support to reduce

un-necessary

testing and

healthcare costs

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\Metro Edition Thursday Dec 13, 2012

In-Hospital Death Rates Down

Across Greater Toronto Area• Annual CIHI Report demonstrated that

preventable in-hospital deaths were

reduced

• NYGH – top performer in Greater Toronto

and second best in all of Canada

• CEO Tim Rutledge: “health information

technology has hard-wired quality and

safety into the hospital”

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HSMR Explained

• Reported from

hospitals to

CIHI annually

• Reported to

public by CIHI

annually

• GOAL:

Reduce

preventable

inpatient

deaths

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NYGH’s HSMR Performance – 2010

In 2010, the HSMR score at NYGH was worse than the

national average in several large clinical areas.

Inpatient

Population

Probability

of Death

Actual

Death

HSMR

Medicine Program

Overall

429.38 481 112.0

Pneumonia 46.82 56 119.6

COPD

Exacerbation

30.62 43 140.4


NYGH Medicine:Mortality (HSMR) Pre/Post CPOE

112

81

140.4

89.5

119.6

79.7

0

20

40

60

80

100

120

140

Pre-CPOE 2010 Post-CPOE 2011

Medicine Program

COPD

Pneumonia

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Study Methods

Retrospective chart review• All patients discharged with a most responsible diagnosis of

Pneumonia or COPD

• Population #1 (2010): Pre-CPOE (520 patients)

• Population #2 (2011): Post-CPOE (511 patients)

Why were Pneumonia and COPD selected?• High-volume diagnoses for inpatient care

• Plenty of evidence to guide treatment

• Clear clinical decision support available

• Diagnosis often made on admission

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Statistical Analysis

Baseline Population Characteristics:

• Wilcoxon rank-sum test for continuous variables

(e.g. probability of death, age, length of stay)

• Chi-squared test for other variables

Odds of death and readmission:

• Logistic regression

All statistical analyses performed using Stata 12

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Characteristics of Patient Groups were Similar

Paper Orders CPOE (eCare) p-value

Number of Patients 520 511 NS

Gender F=262, M=258 F=269, M=242 0.468

AgeMean: 78.13 yrs

Median: 81 yrs

Mean: 76.54 yrs

Median: 80 yrs0.152

CrCU Admission

Total: 61

Pneumonia: 16

COPD: 45

Total: 62

Pneumonia: 32

COPD: 30

0.351

Length of Stay

(days)

Mean: 9.85

Median: 6

Mean: 10.00

Median: 60.936

30 day Readmission 68 57 0.344

DiagnosisPneumonia = 248

COPD = 272

Pneumonia = 285

COPD = 2260.009

Probability of Death

- Pneumonia

- COPD

Mean / Median

0.128 / 0.103

0.155 / 0.130

0.104 / 0.087

Mean / Median

0.123 / 0.098

0.142 / 0.122

0.099 / 0.080

0.199

0.114

0.294

Death (unadjusted) 78 47 0.004

Statistical correction

applied for difference

in diagnosis-related

groups

Raw death rate

significantly lower

with eCare vs paper

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Outcome Odds RatioConfidence

Intervalp-value

Death 0.574 0.39 – 0.84 0.005

Death adj for

Probability of

Death

0.571 0.38 – 0.85 0.006

Death adj for

Probability of

Death and CrCU

Admission

0.547 0.36 – 0.83 0.005

30-Day

Readmission0.835 0.57 – 1.21 0.345

30-Day

Readmission adj

for Probability of

Death and CrCU

Admission

0.837 0.56 – 1.25 0.380

Results: CPOE vs Paper

Odds of dying in

hospital from

pneumonia or COPD

exacerbation

decreased by 45%

using CPOE vs.

paper processes

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Results: Evidence-Based Order Set Selection

Order Set OutcomeOdds

Ratio

Confidence

Interval

p-

value

Diagnosis-

appropriateDeath

.

0.48 0.26 – 0.90 0.022

Diagnosis-

appropriate

Death adj for


and CrCU Admission

0.44 0.21 – 0.90 0.024

Diagnosis-

appropriate30-Day Readmission

.

1.35 0.75 – 2.38 0.30

Close to diagnosis Death.

1.47 0.71 – 3.01 0.30

Close to diagnosis

Death adj for


and CrCU Admission

1.82 0.78 – 4.23 0.16

Any order set Death.

0.55 0.12 – 2.54 0.44

Any order set 30-Day Readmission .

1.53 0.19 – 11.92 0.69

Odds of dying in

hospital from

pneumonia or COPD

exacerbation

decreased by 56%

when the admitting

physician used the

correct evidence-

based order set

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Adoption and Culture Change

Overall proportion of

patients admitted to

hospital with a

standardized,

evidence-based

order set increased

from 36% to over

97% upon transition

to eCare / CPOE

Paper Orders CPOE (eCare)

Percentage of patients for

whom a diagnosis-

appropriate order set was used

Pneumonia 26.05% Pneumonia 60.43%

COPD 0.0% COPD 45.1%

Percentage of patients for

whom any admission

order set was used .

Pneumonia 37.90% Pneumonia 97.54%

COPD 35.11% COPD 97.35%

CULTURE CHANGE + TRUST = SYSTEM STEWARDSHIP


Inpatient Preventable Mortality: Medicine Program

E – C A R EP A P E R

1 – eCare Phase 2 Implementation (CPOE, order sets, electronic med management)

2 – Quality Based Procedure (QBP) implementation – phased, over 1 year

1 2

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Inpatient Preventable Mortality: Pneumonia



2 – Pneumonia QBP implementation, admission order sets in CPOE (April 1, 2015)

1 2


Inpatient Preventable Mortality: COPD



2 – COPD MRP care taken over by generalists (rather than specialist respirologists)

3 – COPD QBP integration with admission order sets in CPOE (May 26, 2014)

1 2 3

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Using our Hospital Information System to integrate the latest evidence into the

decision-making workflow,

we saved an estimated 120 lives from

pneumonia and COPD exacerbation between 2010 and 2015

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Iterative Quality Improvement

• Over 850 evidence-based order sets

in NYGH library

• Regular order set updates – many inputs

– Front-line clinician requests: system stewardship!

– Updated evidence, utilization reporting, policy

– Formulary, government, user requests

– “Choosing Wisely Canada” campaign

• Past 12 months:

– 379 new/updated electronic order sets – completed 5-step

interprofessional design and review process

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Integration of New Evidence

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Utilization Reporting

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Data Warehouse: Business/Clinical Intelligence

Finance System (SAP)

Coded Health Record (Med2020)

HR Database (Infinium_HR)

EHR System (Cerner)

Patient/Employee Survey (NRC Picker)

IPAC Database (Quality & Safety)

Transcription Services

Hand Hygiene Audit System

Critical Care Information System

ED System (Wellsoft)

Bed Tracking System (TeleTracking)

Wait Time Information System

Incident Reporting System (Parklane)

Other Sources (MRI, CIRT, etc)

Outcomes

Analysis

Patient

Safety

Research

PhysicianPerformance

Quality

Improvement

Compliance

Monitoring

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Quality-Based Procedure Tracking

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Evidence-based Resource Utilization

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Physician Scorecards

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IPAC Committee

eCare

Falls Committee

Never Event Action Team Committee

Medication Use Safety Committee

(MUSC)

Research and Ethics

Board

Program Quality

Committees

Emergency Preparedness

Committee

Access to Care (ATC) Committee

Hospital Quality of Care Committee

Senior Leadership Team

Quality Committee of the Board

Medical Advisory Committee

Board of Governors

Quality Governance at NYGH

Other Committees

Accreditation Standards

Other Committees

Other Committees

All Cases: Continuous Quality Improvement, BI, Education

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Team

Communication

Recognition

and Profiling

Rigorous

Delivery

Improvement

Methodology

Capacity

Building

Transparent

Reporting

• Lean

• Six Sigma

• Simulation modelling

and operations

research

• Define

• Measure

• Analyze

• Improve

• Control• Summary Poster

• Celebrating Success

• Award Applications

• Conference

Presentation

• Quality Improvement Plan

• QIO Dashboard

• Annual QIO Magazine

• QI Innovation Lab

• Knowledge Translation

• Program Quality

Committee Support

• Huddles

• Team Meetings

• Quality Circles

QIO

Core

Functions

QI Office: Core Functions

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QIO Dashboard identifies:

• Number of open projects

• High level progress and status of

each project

• Risks before they become an issue

• Impact of QIO project work on

outcomes

All Cases: Continuous Quality Improvement, BI, Education

QI Dashboard:Reporting to Our Leaders

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Education channel

running in a loop,

live data feed from

BI system

Folders with

trending

indicators

Calendar to

track daily

trends e.g.

falls

Kamishibai

cards to

sustain

process

changesWhiteboard for

documenting quick

action plans and

improvement ideas

Unit-Based Quality Boards

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If you remember 3 things from this presentation…

1. The key to meaningful outcomes from use of CPOE is

transformation of clinical practice and culture … this takes time, and

lots of hands-on clinician engagement … don’t rush!

2. Focus on redesigning and standardizing care, based on evidence.

Be strong, personalized order sets are not necessary for system adoption!

3. Quality improvement is an ongoing, iterative process. Success requires:

– Automated outcome measurement

– System stewardship with ongoing monitoring

– Effective corporate quality improvement governance structure and team

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Realizing Value of Health IT (STEPS)

T – Treatment/Clinical

• Integrated up-to-date evidence

into daily decision-making workflow of physicians

• Reduced mortality among inpatients in the Medical program,

specifically those with a diagnosis of pneumonia or COPD

exacerbation

E – Electronic Secure Data

• Business intelligence for tracking/reporting use of evidence-based care and patient outcomes

• Iterative quality improvement though corporate quality framework

46

Thank you for your attention! Questions?

Dr. Jeremy Theal MD FRCPC

[email protected]

Twitter: @drjeremytheal

Ms. Linna Yang RN MHI

[email protected]

Please complete an online evaluation of our session

mailto:[email protected]

mailto:[email protected]

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