Learning from Every Death · 100 death review – 2004 4th quarter review – 2005 Continuous...

©2013 MFMER | slide-1

Learning from Every Death: Moving From Counting to Improvement

Jeanne M Huddleston, MD, MSAssociate Professor of Medicine

Chair, Morbidity & Mortality CouncilMayo Clinic, MN, USA


Agenda

1. Mayo Clinic and US Healthcare Performance

2. Mortality Review System (MRS) History

3. MRS as a Safety Learning System

4. Case Study and Results

5. Possibilities for Denmark

St Marys Campus, Mayo Clinic Hospital

Total clinic patients:

1,260,000

Hospital admissions:

131,000

Hospital days:

608,000

Employees:

> 60,000

Annual Patient Encounters


21st century health care- Inefficient processes- Poor system integration- High levels of variation

- Care delivery - Outcomes

- Suboptimal value


11

12

What are you doing to learn from groups of

patients at high risk of harm?

What could you do to improve learning?


12 years in the making….


Iterative Learning: 12 year journey

M&M Tradition

100 death review –

2004

4th quarter review –

2005

Continuous review – 4th

quarter 2006

MCA (100% cases reviewed)

early 2009

MCF (targeted reviews)

later 2009

MCHS review roll-out

2012

Enterprise-wide

integration

M&M Tradition

100 death review –2003

4th quarter review –2005

Continuous review – 4th

quarter 2006


Original Charge from Hospital Leadership

1. To create a meaningful mechanism to review deaths at MCR hospitals:

• Thoroughly understandable

• Measurable

• Improvable

2. To identify and quantify unanticipated deaths

3. To identify rate of adverse events in patients who die in MCR hospitals

4. To classify and quantify system level changes which will improve mortality rate.


“No one should ever suffer or die as a result of failures in our systems or processes of healthcare delivery.”

MC Mortality Review Subcommittee, May 2007

16


Guiding Principles:Not Negotiable

1. System review (not peer review)

2. Every case is reviewed by a practicing nurse and physician

3. All findings are recorded in the central registry

4. Multidisciplinary, multispecialty sessions used to build consensus re: findings

5. Implementation is local


Aggregate learning

Aggregate learning

Is there anythingthat could mitigate

future events?

Is there anythingthat could mitigate

future events?

Prioritization of information

Prioritization of information

Identification of issues

Identification of issues

Raw InformationRaw Information case reviews

case reviews

ProblemProblem

Further reviewFurther review

YesYes

ReportReport

NoNo

No further review

No further review

No problem

No problem

Re

vie

we

r W

ork

Co

mm

itte

e W

ork

Clinical

PracticeQuality


Primary Reviewers (MD and RN)

Encompass the entire hospitalization

Include pre-hospitalization information as available

Identify possible system and process failures

Identify possible instances when standard of care was not followed

• Documentation, supervision, clinical guidelines, etc

Identify possible delays in treatment or diagnosis

Identify possible communication or documentation issues


Information Recorded into the Registry

Qualitative and quantitative

Qualitative: Patient’s story of healthcare experience

• Level of detail

• Describe timelines of issue identified

• Enough to remember for future presentation

• Enough for leadership to understand concern

Quantitative: Indicators

Case classification


Multidisciplinary Team Discussions

Many brains are better than one

Reviews are inherently subjective• Retrospective

• Rely on documentation

Clinical expertise

Cultural understanding

Consensus

Classification of death21


Overall Case Classification

Iterative learningIterative learningIterative learningIterative learning

NOT NOT NOT NOT related to to to to preventabilitypreventabilitypreventabilitypreventability

Consensus driven optionsConsensus driven optionsConsensus driven optionsConsensus driven options• Opportunity Opportunity Opportunity Opportunity for improvementfor improvementfor improvementfor improvement

• NO NO NO NO opportunity for improvementopportunity for improvementopportunity for improvementopportunity for improvement

22


Morbidity and Mortality Council: The Think Tank (of data geeks)

• Integration of safety and quality leadership with practicing providers and analysts

• Aggregate and reconcile all safety data

• Strategic data analysis

• Thoughtful interpretation

• Integrate recommendations to practice leadership


Omission vs. CommissionOmission vs. CommissionOmission vs. CommissionOmission vs. Commission

Mayo Clinic, Mortality Review System


Example: delayed diagnosis of sepsis & delayed recognition of a postoperative complication

59 year old female underwent TAH

POD #3 – AKI, urinary retention with new abdominal distension and pain

POD #4 – AKI worse, significant abdominal pain – narcotics stopped. Episode of PAF (130’s)

POD #5 – hypotensive (70/45) with diaphoresis and nausea

RRT called but no blood pressure on their arrival

Code called with > 1hr of resuscitation efforts

On autopsy, abdomen filled with pus and a knick in the small bowel.


82 year old male with severe COPD and pancreatic cancer was hospitalized for bowel obstruction.

Postoperative delirium

Postoperative respiratory failure

Pain meds held

Per nursing notes

- patient routinely called out in pain

- family members consistently asked that he be kept comfortable.

Average pain score was 8/10 in the 24 hours preceding death.

Patient was made comfort care only and died within hours.

Joshua Bright: A Good Death

Can patients

have a “good”

death?


P-chart of % of deaths with issues identified

Making a Difference through 2009

Nursing sepsis education

Wipe C-diff initiative

Sepsis order set

Admission office

Airway management protocol

Other localized efforts: official reads on outside films, consultant notification of patient condition change, NGT suction and chest tube in-services, DOM encouragement of RRT utilization

Avg=0.2262

LCL

UCL

Data source: MRS Mortality Registry


MRS System Findings (2010)

Narcotic-induced respiratory depression• postoperative

• OSA

Failure-to-Rescue

Failure-to-Recognize• Septic shock

• Hypovolemic shock

• Mesenteric ischemia

Triage of unstable patients

Supervision


SPC p-chart of MCR mortality rate

Data source: DSS and UHC

This information is confidential and protected from disclosure by Minnesota Statute 145.61 et seq.


P - chart of % of deaths with issues identified

Data source: MRS Mortality Registry

This information is confidential and protected from disclosure by Minnesota Statute 145.61 et seq.


Days Between Deaths (during 2007-2014 there were 669 deaths)


Slightly Deeper Dive

Data all from mortality review registry

2008 – 2014 (7 full years)

Inclusion criteria• Patients with either of two indicators:

1. Delayed diagnosis

2. Resuscitation

3. Only one event per patient per day per service


FTRR events by nursing unit


FTRR events for non-ICU nursing units by year


RRT called

Clear change in physiologic

state

Met RRT

Criteria

44 hours

27 hours

Labs:

Hb: 7.1, Leukocytes: 2.3

Creat (9/29): 3 (2-month baseline): 1.6

55-year-old male with CLL with MUD peripheral blood stem cell

transplant 7/10 (2 months before). Dismissed 9/14

Case Example


HSE Approach: Bedside Patient Rescue

• FMEA

• ID & understand stakeholder needs

• Classify/quantify user requirements

• Data mining: Identification of covariates predictive of deterioration

• Simulation modeling

• Integrate stakeholder needs, results of analytics and operational use specifications

• FEA

• Iterative sensitivity & specificity testing of predictive algorithms

•Simulation modeling

• Develop pilot

• Evaluate pilot

• Determine if & when implementation appropriate

• Develop implementation plan

• Develop monitoring plan

• Implement

Planning PhaseImplementation

Phase

Execution

Phase

BPR Project

Management Team

BPR Project

Management Team

Requirements

Team

Requirements

Team

Analytics

Team

Analytics

TeamSystems

Architecture

Team

Systems

Architecture

Team

Clinical

Verification &

Validation

Team

Clinical

Verification &

Validation

Team

Clinical

Pilot Team

Clinical

Pilot Team

Clinical

Integration

Team

Clinical

Integration

Team


Input from > 2,000 providers: Top 5 Failure Modes

1. The patient's clinical condition is not re-assessed at the bedside following new interventions (medication, fluid bolus, tests results).

2. Care providers of all types can feel that there are too many complex things to do in a short period of time.

3. A physician does NOT review nursing notes documented in the electronic medical record.

4. Care team attributes a patient's acute physiological deterioration to the wrong cause.

5. Some care providers (nurses or physicians) believe that a standard, or clear definition of acute patient deterioration does NOT exist.


Mortality Review taught us:

Our MAT was not being called.

Research supported by CSHCD

Our providers told us:

Criteria could not be trusted and it did not apply to all patients.


Research supported by CSHCD

Best performing score had a positive predictive value of < 1.8%....

98 of every 100 alarms would be wrong!!

How about a different Early Warning Score?


Traditional statistics failed to improve positive predictive value. Machine

learning methods to were much more successful (PPV from 2% to 20%).

AUC = 0.93


Adding nursing “worry” to the mathematical model drastically

improved the performance (300%).


Driving Principle, Locally OperationalizedTiered, time-limited escalation of

expertise at the bedside

RN Validation

Tier 1• First responder to

bedside & notifies senior member of team

Tier 2• Second responder to bedside

for eval of clinical condition, differential, goals of care, and plan for reassessment

Tier 3

• MAT

Evaluate/treat/resolve

or silence/snooze

Max 2-6 hours

Evaluate/treat/resolve

or silence/snooze

Max 2-3 hours

Concept derived from 7 RN focus groups & discussions with MERS, Sepsis MTR, CC-IMP &

HIM quality committee including their practice leadership. MANY details to sort through as

portion of Phase 2 BPR Charter. The practice must design the process and policies.

RN clinical

verification of

vital signs


How could you improve learning from mortality analysis (or other forms of

case review) in your hospital?

Name 3 suggestions


Why does MRS work?

• Move away from insular peer review

• Embrace concepts of process of care and system failure

• Culture change

• It’s not about adverse events • It’s about learning to identify process of

care failures• It’s about inspiring action

• Right size quality improvement initiatives


Multidisciplinary reviews identify opportunities for improvement.

• Ongoing culture shift with issue identification and open discussion

• Long gone are the days of “nurses’ jobs” or “physicians’ responsibilities”

• Increased physician involvement

• Integral part of how business is done• Leadership involvement

• Leadership accountability


“Mortality Review takes too much time and uses too many resources.”


Possibilities for “The Five”

• Work together• Common approach and registry

• Common definitions

• Standardized training

• Start small (100 consecutive patients)

• Reconcile findings with existing reporting mechanisms

• Meet monthly (at hospital level) to share learning

• Benchmark learnings amongst each other• Positive deviants?

“I have always thought a good deal of Lincoln’s Gettysburg address. There’s a line in it which

explains why we want to do this thing. It is ‘that

these dead shall not have died in vain.’ We

know how hard it is for those who have had the misfortune of deaths in their families, of deaths

that might have been avoided. What better could we do than take young men and help them become proficient in the profession so as to

prevent needless deaths?”

Foundation life goal, Dr. William J. Mayo, tells senators.

Minneapolis Morning Tribune, March 23, 1917.


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