AEGIS

Automated Early warning Generation Information System

A Quality Improvement Journey

ONIG Presentation October 2015

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The Problem – Current ICU Admission State

25% of all patients admitted to the ICU are from the in patient wards

80% of these patients had vital abnormalities that included 3 or more SIRS criteria

Ward admissions to ICU had a mortality rate of 30-40% vs ED admission mortality rate of 15% and post-op mortality rate of 5%

Results of an internal retrospective chart review of 365 patients admitted to Osler’s ICUs & data retrieved through the CCSO CCIS database

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The Problem - Delayed Response & Failure to Rescue

50% of ward patients admitted to Osler’s ICU had not had a prior CCRT consult

Delayed CCRT notification of greater than 8 hours from onset of calling criteria

In-hospital cardiac arrest 80% non-shockable rhythms 13% hospital survival rate 6% 1 year survival rate

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Finding the Right Solution

Literature Review

“What has been done”

“ What has been proven to be beneficial”Environmental survey

“What is being done”

“Where it is being done”

Decision Point # 1 – is it the right solution ???

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Literature Review

“Physiological track and trigger warning systems” (EWS) have been developed for use outside critical care areas

These system have been found to assist in the timely recognition of deteriorating patients.

Use periodic observation of basic vital signs together with pre-determined criteria.

They should be used as an adjunct to clinical judgment.

They have been found to be supportive to novice and beginner level nurses and to assist in assessment skill building.

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Environmental Survey

The NEWS score is the largest national EWS effort to date.

still remains problematic in the UK due to its lack of universal implementation ability (it has exclusion criteria) and it has yet to have its retrospective validation study published.

Despite, poor validation there are now many expensive “out of the box” software applications developed that utilize either a “MEWS” or “NEWS” scoring system.

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“Out of the Box” Scoring Systems

Scoring systems have been found to have poor discriminatory value as a score requires interpretation

The MEWs Scoring System

Decision Point # 2 – could we design a more specific set of triggers??

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Project Feasibility – Right Time & Right Resources

Completed a supportive project infrastructure review1. Organizational aptitude

Business case Stakeholder commitment

2. Organizational capacity Fiscal health Human resource abilities & capacity Technical systems abilities & capacity

Decision Point # 3 – is it the right time ??Decision Point # 4 – do we have the right resources ???

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Project Aim

To reduce the time to early recognition of patient deterioration and thereby increase the response time to prevent failure to rescue on the inpatient wards through the implementation of a home grown “track & trigger” system.

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Project Sponsors & Project Teams

Leadership Sponsorship

Executive Director of Clinical Operations

Regional Chief Technology Officer Program Director of Critical Care Services

Project Technical Design Team CW Critical Care LHIN Lead (Physician Lead) Clinical Analyst(s,) Information Services Information Services Telecommunications & Devices Lead

Project Clinical Design & Pilot CW Critical Care LHIN Lead (Physician Lead)

Clinical Quality Critical Care Lead Clinical Analyst(s,) Information Services Pilot Inpatient Ward Clinical Resource Nurses

Corporate Project Implementation CW Critical Care LHIN Lead (Physician Lead) Clinical Quality Critical Care Lead (Clinical Lead) Clinical Champion (Clinical Co Lead) Corporate Project Manager Clinical Analyst(s,) Information Services

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Project Measurements

Process Measures Frequency of alertsTime to CCRT call from 1st calling criteria met

Balancing Measures Frequency of CCRT New Consults

Inpatient Ward Staff Satisfaction with new processes

Outcome Measures Inpatient ward Code Blue events rate (# of CODE Blue events/1000 inpatient ward admits) Inpatient ward unplanned transfers to ICU rate ( # of ICU transfer/1000 inpatient ward admits) Inpatient ward mortality rates ( # of inpatient ward deaths/1000 inpatient ward admits)

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Technical Design

Vital Signs & Laboratory Values in Meditech (EMR)

Meditech Version 5.67

AEGIS algorithms programmed in

IATRICS a middle ware

product.When algorithms

are identified IATRICS sends a preprogrammed alert message.

Alert Message sent to wireless handheld

device

iPOD ®

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Clinical Algorithm Design

Original algorithms designed with SIRS & Sepsis in mind

All Inpatient Wards•SIRS Criteria (HR, Temp., WBC)•Shock Index (HR/SBP)

Additional Added Inpatient Ward Specific Algorithms Respirology

High & Low Respiratory RateNeurology

Elevated Systolic Blood Pressure AVPU

Cardiology High & Low HR

Surgical (Post Op) Low RR

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Operational Feasibility Trial - PDSA Cycle #1

3 month (2) inpatient ward trial1 inpatient unit at each organizational site

Technical Concept •I site - new facility with new technical and structural infrastructure•1 site 50 year old facility with a fragmented technical infrastructure and significant structural limitations•wireless transmission & point of care equipment

Clinical Concept •differing case mix patient groups to test algorithmic specificity & clinical response•testing clinical operational concept and required processes to ensure clinical success & sustainability•preliminary data collection for concept confirmation

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Feasibility Outcomes

Technical resource requirements identified •Wireless improvements •additional portable wheeled computers •refresh of stationary desktops

Clinical requirements identified•Algorithm adjustments required to provide optimal clinical recognition for differing case mix groups•Clinical operational processes will need more fulsome review in a longer term pilot

Technical

Decision Point # 5 - technical & clinical concepts confirmed as feasible !!!

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Clinical Pilot – Continuous PDSA Cycles

SIX (6) Month Pilot SIX (6) inpatient medical wards, 3 at each siteFOUR (4) medical clinical disciplines

Tested: clinical algorithm specificity, clinical processes & practices Measured: clinical performance Defined: additional Resources

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• competing clinical projects (CMAR implementation)• competing clinical priorities (bedside reporting & bedside rounding ) • clinical educational needs re: SIRS & Sepsis• time to vital signs documentation • non structured response communication between frontline nursing & physician

team

• wireless device management• Meditech documentation limitations

• end of life clinical technical tools• point of care resources limited for point of care documentation

• manual data collection processes

Clinical Pilot – Challenges

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Pilot Outcomes

Average CODE Blue rate decreased by 35% 8.3 to 5.4 CODE Blue events/1000 ward

admissions

Average unplanned ICU transfer rate decreased by 17.5% 31.5 to 26 unplanned ICU admissions/1000 ward admissions

Average inpatient ward mortality rate decreased by 2-4 lives/month 38 to 36 deaths/1000 ward admissions

Despite an expected low positive predictive value of 15% for the outcomes the alert frequency was manageable, 3-6 per day per ward

Charge nurses felt the system facilitated improved communication with bedside and CCRT nurses as well as with attending physicians

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Corporate Implementation

Decision Point # 6 - Spread…WHY NOT !!! Increased Patient Safety, Effective, and Efficient Scope Additional 13 inpatient units including Surgical Program

Additional Resources Required 1. Project Manager 2. Clinical Champion

Continued Focus on Process ImprovementsTime to documentation Meditech Documentation & Optimization Performance Metrics & Performance follow up

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Addition of a Champion – BIG Benefits!!!Addition of a Champion – BIG Benefits!!!

1. Strong communication skills

2. Experienced and knowledgeable in current ward processes and skilled in day to day clinical care & documentation

3. Have a positive attitude

4. Clinical frontline role model

5. Demonstrate the potential to be a successful leader

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Benefits of Adding of a Project Manager

Keeping the project….

1. within scope

2. on time 3. and within budget

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Time to Documentation

Time to documentation continues to improve

on the 19 AEGIS units

Average Time was 4.7 hours …NOW 1.27 hours

90th Percentile was 6.85 hours ...NOW 2.8 hours

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Meditech Vital Signs Documentation & AEGIS

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Meditech Optimization for AEGIS

Pre-set data fields for each vital sign allowed for the data entry of extra digits within the boxes.

A keystroke error created false AEGIS alerts.

QI # 1: Each pre-set data field was set for the exact number of digits required.

QI # 2:Pop-up messages were created to alert the nurse if the entries were outside of normal limits.

Reduction of Keystroke

Errors

from10% to 0.5% !!

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Hardwiring Excellence & Building Clinical Performance

Set & Communicate Expectations

Audit & Review

Communicate Performance

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Accountability Documentation

Multiple Alerts from same vital signs

Multiple Alerts from same vital signs

Nursing actionNursing action

Orders from MDOrders from MD

The nurse is required to document the intervention called AEGIS alert after each alert received for his/her patient.The nurse is required to document the intervention called AEGIS alert after each alert received for his/her patient.

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Compliance Audit

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Monthly Metrics

Available Accessible Visible Meaningful

Time to DocumentationICU Transfer RateCODE Blue RateMortality Rate

CCRT New Consult Rate Time to CCRT Notification

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Staff Communication & Training

Market your project wellPrepare your marketing toolbox Hit the road and hold hands with the stakeholders

Remember the 5 Rights Right information Right people Right time to get the right attention and get the right results !

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Address Challenges

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3 months, 6 months, 12 months, 18 months

Sustainability & Outcomes

Measure…Measure …Measure

Shout out and spread the good news Corporate CODE Blue Rate

3.88 3.33

Another 15% reduction !!!

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Review unexpected outcomes

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Address Interdependencies

ICU Transfer Email Notification

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Next steps…

1. Point of Care Vital Sign data collection and wireless transmission to the EMR through the capital purchase of new vital signs devices

2. More spread …into the Emergency department3. Scale up to include LHIN partners at Headwaters Healthcare

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References

Cretikos, M., Bellomo, r., Hillman, K., Chen, J., Finfer, S., & Flabouris, A. (2008). Respiratory rate: The neglected vital sign. Medicine Journal,

188, (11). 657-659.Cooksley, T., Kitlowski, E., Haji-Michael, P. (2012). Effectiveness of Modified Early Warning Score in predicting outcomes in oncology patients. Quality Journal of Medicine, doi:10.1093/qjmed/hcs138Fullerton, J., Price, C., Silvey,N., Brace, S., & Perkins, G. (2012). Is the modified early warning system (MEWS) superior to

clinician judgement in detecting critical illness in the pre-hospital environment? Resuscitation, 83, 557-562. doi:10.1016/j.resuscitation.2012.01.004Ghanem-Zoubi, N., Vardi, M., Laor, A., Weber, G., & Bitterman, H., (2011). Assessment of disease severity scoring systems for patients with sepsis in general internal medicine department. Critical Care 2011, 15:R95

http://ccforum.com/content/15/2/R95Higgins Y et al. (2008). Promoting patient safety using an early warning scoring system. Nursing Standard. 22(44), 35-40. Ludikhizen, J., Smorenburg, S., de Rooij, S. E., de Jong, E. (2012). Identification of deteriorating patients on general wards;

measurement of vital parameters and potential effectiveness of the Modified Early Warning Score. Journal of Critical Care 27, 424e7-424e13.Nursing Executive Center (2009), The critical thinking toolkit. The Advisory Board Company. https://www.advisory.com/international/research/global-centre-for-nursing-executives/studies/2009/the-critical-thinking-toolkitRoyal college of Physicians (2013). The Medical patient at risk: Recognition and care of the seriously ill or deteriorating

medical patient. Acute Care Toolkit 6. Subbe. C., Kruger, M., Rutherfornd, P., & Gemmel, L. (2001). Validation of a modified early warning score in medical

admissions. Quality journal of Medicine, 94, 521-526.

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