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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.
OUR VISIONOUR VISIONPATIENT-INSPIRED HEALTH CARE WITHOUT BOUNDARIESPATIENT-INSPIRED HEALTH CARE WITHOUT BOUNDARIES
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