driving quality inpatient outcomes with cpoe and ...atrius health non-profit alliance of six leading...

06-Mar-2014

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1 © 2014 North York General Hospital and Zynx Health Incorporated

Unauthorized review, use, disclosure or distribution is strictly prohibited. All rights reserved.

Driving Quality Inpatient Outcomes with CPOE and Integrated Evidence-Based Clinical Decision Support

The eCare Story

North York General Hospital, Toronto, Canada

Jeremy Theal MD FRCPC • CMIO and Gastroenterologist



Community teaching hospital affiliated with the University of Toronto

Catchment area: > 400,000

Three Sites: General, Branson, Seniors’ Health

Beds: 418 acute care

192 long-term care

Volume per year: 113,000 ED visits

29,500 inpatient cases 5,800 births

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• Implement advanced electronic medical record

technology to improve patient outcomes:

Quality and safety of patient care

• Embrace culture of evidence-based care, best practices

Make it “easy to do the right thing”

Build evidence into clinical workflow

• SHARED VISION = “by clinicians, for clinicians”

100% clinician adoption

Team-based interprofessional approach/workflows

Goals of the eCare Project



• Computerized Provider Order Entry (CPOE)

• Evidence-Based Order Sets & Clinical Workflows

• Closed-Loop Medication Administration

• eMAR, Medication Reconciliation, Depart Process

• Advanced Clinical Decision Support

System Components

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Integrating Evidence and Professions: eCare Order Set Team

• Goal – 350 evidence-based Order Sets (gap analysis)

• Order Set Build Team: – 1.0 FTE physician (spread amongst 4 MD’s)

– 1.0 FTE pharmacist (spread amongst 2 pharmacists)

– 1.5 FTE application analysts (from clinical informatics)

• Sources of Evidence: – Zynx Health Evidence-Based Order Sets

– Canadian/International Guidelines/key articles

– NYGH paper order sets, protocols, directives

• Directly involved front-line clinicians in design: – > 80 MD’s (interdepartmental input)

– > 150 clinical staff (interprofessional input)



• Insert eCare picture here

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System Adoption by Physicians: One Year post-“Go-Live”

• User adoption of the system – 100%

• Percentage of physician orders entered by MD’s – 92%

• Number of orders entered by physicians - > 1,700,000

• Evidence-based PowerPlans created - > 350

• Evidence-based PowerPlans activated - > 42,000

• Orders entered through PowerPlans – > 830,000

• Percentage orders from evidence-based PowerPlans: 49%



\ 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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Study – CPOE and Evidence-Based OS:

Impact on Mortality, Readmission, LOS

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

Pneumonia or COPD

• Population #1: Pre-CPOE (Jan-Sep 2010)

• Population #2: Post-CPOE (Jan-Sep 2011) (CPOE go-live was October 26, 2010)

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





Primary Hypothesis:

• Use of CPOE with evidence-based order sets is associated

with a reduction in age and comorbidity-adjusted inpatient

mortality, 30-day readmission and/or length of stay from

pneumonia and COPD, compared with traditional paper-

based processes

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Secondary Hypothesis:

• The use of CPOE with an evidence-based admission order

set that is the same as, or closely matching, the final most

responsible discharge diagnosis is associated with a

reduction in age and comorbidity-adjusted inpatient

mortality, 30-day readmission and/or length of stay in

patients hospitalized for pneumonia or COPD, compared

with use of any order set



Pre vs Post-CPOE Population (Table 1)

• 520 patients (paper orders) vs 511 patients (CPOE)

• No statistically significant difference in sample size, gender distribution, age, Critical Care admission rate

• More patients with COPD in the paper orders group, vs more patients with pneumonia in the CPOE group (p=0.009)

• Correction applied: Probability of Death (adjusts for age, sex, length of stay, comorbidities, admission type and diagnosis group)

• Additional correction applied for critical care admission

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Primary hypothesis – proven correct

• Mortality:

Strongly significant reduction in risk of death from

pneumonia or COPD when using CPOE with

evidence-based order sets versus traditional paper

processes, even after adjusting for age, comorbidity,

diagnosis and CrCU admission

45% reduction, statistically significant

• 30-day readmission / LOS – no significant change

Summary of Results



Summary of Results

Secondary Hypothesis – proven correct

• Mortality: Use of CPOE with an evidence-based

admission order set that matches the

most responsible discharge diagnosis results in

significant reduction in death from COPD or pneumonia,

adjusted for age, comorbidity, diagnosis,

CrCU admission

56% reduction, statistically significant

• Mortality:

Admission OS close match or no match: no sig. change

• 30-day readmission / LOS: no significant change

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Summary of eCare Clinical Benefits

• 100% clinician adoption

• Medication turnaround improved by 83% (291 to 50 mins)

• Order set usage for patient admission to hospital increased from 37% (using paper) to >97% (using CPOE)

• Appropriate prophylaxis against VTE increased from 50% of inpatients to >96% of inpatients

• Mortality from pneumonia and COPD exacerbation was reduced by 45% using CPOE vs paper orders

• Mortality from pneumonia and COPD exacerbation was reduced by 56% in patients admitted using CPOE with a correctly-matched evidence-based order set



In Closing

• Implementation of CPOE with integrated evidence-based real-time CDSS can result in significant improvement in multiple patient outcomes, such as mortality

• Keys to success:

– Close partnership with evidence provider that has regular content updates and effective suite of software tools (ZynxHealth)

– Engagement of front-line clinicians in design and build of content, workflows

– High rates of system adoption

– Culture change to focus on the importance and power of evidence-based medicine and standardization of care

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A Measured Approach to Alerting

The Path to Drug-Disease Interaction Alerts

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Atrius Health

• Non-profit alliance of six leading independent medical groups and home health/hospice

– Granite Medical

– Dedham Medical Associates

– Harvard Vanguard Medical Associates

– Reliant Medical Group

– Southboro Medical Group

– South Shore Medical Center

– VNA Care Network & Hospice

• Providing care for ~ 1,000,000 adult and pediatric patients with 1000 physicians, 1450 other healthcare professionals across 35 specialties from over 50 sites

.

© 2013 Atrius Health, Inc. All rights reserved.

Atrius Health

Non-profit alliance of six leading independent

medical groups in Eastern

Massachusetts and one home health

agency and hospice

Granite Medical

Dedham Medical

Associates

Harvard Vanguard Medical

Associates

Reliant Medical Group

Southboro Medical Group

South Shore

Medical Center

VNA Care Network

and Hospice

.

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Providing care for ~ 1,000,000 adult and pediatric

patients with 1000 physicians, 2100 other healthcare

professionals across 35 specialties

© 2013 Atrius Health, Inc. All rights reserved.

Atrius Health

• 100% on EMR combined with corporate data warehouse,

used for managing quality and cost. Patient portal.

• Long history with global payments, currently about 50%

risk across commercial, Medicare and Medicaid

populations.

• Pioneer ACO

• HIMSS Stage 7

• Strong infrastructure to manage risk

The Triple Aim

Experience

Of Care Per Capita

Cost

Population Health

Source: IHI.org

The root of the problem in health care is that the business models

of almost all US health care organizations depend on keeping

these aims separate. Society on the other hand needs these three

aims optimized (given appropriate weightings on the components)

simultaneously. Tom Nolan, PhD.

5 © 2013 Atrius Health, Inc. All rights reserved.

Atrius Health Goal: “Triple Aim + 1”

Improve

Experience

Of Care

Reduce

Per Capita

Cost of

Care

Improve

Population Health

. +1 = Improve Provider and Staff

Satisfaction

6 © 2013 Atrius Health, Inc. All rights reserved.

The Problem

• 3,000,000 ambulatory visits/yr

• 3.2 million RX/yr

• 95% cancel or over-ride

• Over-ride reason not required (soft-stop)

• Cannot always tell what changes made

relative to alert

• Coumadin tells the tale

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Coumadin Stealth Alert

• Any time patient followed in anti-coag and

has med RX sent for medication

interfering with INR a 2nd alert is sent to

anti-coag team without prescriber’s

knowledge

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Interaction Severity Drug-Drug

• Contraindicated

• Severe

• Moderate

• Undetermined (filtered)

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Baseline Reporting

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Approach to Solution

• Clinical Pharmacy Team

• Clinical Decision Support Workgroup

• Me

• Initial effort to voluntarily submit alerts that

were annoying

• Review by team

• Suppress 1 level of interaction

• Removed Drug-Food

• Change alert severity-removed 10-20

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The Dreaded Allergy File

• Issue related to being “Old” EMR user

• Many free-text allergens and unusual

synonyms created in file

• Standards document created

• Manual conversion of free-text meds to

discrete med allergies

• Allergy to phone # and “mother’s sister”

• However-also high frequency allergy to

G6PD and Long QT

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G6PD and Long QT

• Hundreds of entries-most of time also on

prob list

• Prob list NOT viewable at time of placing

order

• MD’s using allergy file as a sensible

trigger

• No real appreciation for future effect or

the lack of actual alert “illusion of alert”

• Have noticed similar in other EHR

(Centricity) as well

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Drug-Disease Alerting

• Turned on full file and then shut it off 3

weeks later

• Overwhelming volume

• Wanted to target specific subset of areas

of concern to providers

• Alert Space

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Alert Space

• Allowed for search by disease condition

and then specific interaction

• Also offered Drug-Drug modifications to

have a much better way to monitor

changes over time and preserve

documentation

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Selective Alerting

• Used system setting in EHR to turn ON all

alerts

• Then use Alert Space to turn OFF all

alerts

• Then selectively turn on ONLY the ones

you want to display

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Long QT and G6PD

• Need to make sure understand clinically

similar terms

• Does take some practice with the system

but re-design has already improved

• Went into prod for these 2 conditions 8

weeks prior to this conference

• Took 4-6 months to get a handle on drug-

drug and drug-disease and do 2-3 rounds

of testing.

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Future

• Need to share the information across

organizations-collective knowledge

• Need to change pattern of alerting to

make it easier to do the right thing rather

than tell provider they did the wrong thing

• Better emphasis on important and

dangerous conditions and make other info

less distracting

• BEERS alerts now in test system

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Michael A. Lee MD, MBA

Director, Clinical Informatics

Atrius Health

[email protected]

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