risk informed evaluation of patient safety training anthony d. slonim, md, drph vice president...

Risk Informed Evaluation of Patient Safety Training

Anthony D. Slonim, MD, DrPH

Vice President Medical AffairsCarilion Medical Center

Senior Staff, Departments of Medicine and PediatricsCarilion Clinic

Professor, Medicine and PediatricsVirginia Tech-Carilion School of Medicine

Objectives

• Decision-making science How do we normally make decisions?

• Picking up on Level 4…Can we train to improve our decision making results?

Decision Making Science

Bayes Theorem

P (A/B)=P(B/A) * P(A)

P(B)

Pattern Recognition

How many squares do you see?

Jumping to

conclusions too quickly.

Is there flashing in the

squares?Your

mind will play

tricks on you!

Decision-Making

Medical Decision-Making Process1. Perception/Data gathering (training-H and P, Labs, Rads)

• “Amber light” is showing

2. Interpretation (training-pattern recognition and probability)• “Amber light” means prepare to stop, maybe

3. Decision making (based on probability + experience)• Stop or go

4. Action taking (reflex/“gut level response”/programming)• Hit the brake or accelerator

Marx, D

Marx D and Slonim AD: Assessing patient safety risk before the injury occurs: An Introduction to Socio-Technical Probabilistic Risk Assessment. Quality and Safety in Healthcare 2003; 12 Suppl 2: 33-38.

Medical Decision-Making

Perception/Data GatheringInterpretatio

n

Decision-Making

Act

ion

Triage Nurse

ED Nurse

Physician

XGet Help:

Cardiology Consultation

Make a Dx and Treat

Do more testing-which

test?

(Pre-test probabilities)

Medical Decision-Making

Perception/Data GatheringInterpretatio

n

Decision-Making

Act

ion

Triage Nurse

ED Nurse

Physician

XGet Help:

Cardiology Consultation

Make a Dx and Treat

Do more testing-which

test?

(Pre-test probabilities)

Expert Decision Making:Practice, Practice, Practice

* Expert – pattern matching against large mental library, quick, accurate if confirm correct answer

* Novice – library is empty – slow, error prone process

* Certain Diagnoses are Favored- Frequent, Recent, Serious

* Heuristics – fixating on the wrong pattern

Pattern Recognition

Picking up on Level 4:Can we train for results?

Kirkpatrick’s Levels• Level I Reactions

• How well trainees liked training

• Level II Learning• The extent to which trainees understand and retain

principles, facts, and techniques

• Level III Behavior• The extent to which behavior changes as a result

of training

• Level IV Results• Impact of training on organizational criteria

Data AnalyticsData AnalyticsProcess Process

ImprovementsImprovementsChange Management

Improved Outcomes

Program Identification &

Prioritization

Elements of Quality Programs

Quality Functions

Research Education / Training

Why is there a safety problem ?

• Considerable variation in practice • Based on opinion or consensus • Evidence-based guidelines-unsupported• Failure to create fail-safe processes• Our providers may not know their work

• Policies and procedures

• We’re learning to work together• We’re not sure of the results we’re looking for

Process Analysis• Processes:

• A series of sequential steps governing interactions

• Between patients and providers• Between providers and providers

• Examples of process analysis techniques:• Root cause analysis-retrospective• HAACP (hazard analysis and crit control points)• FMEA (failure mode effects)• PI methodology

Low-frequency, High Impact Events

• Low frequency, high-impact events • Variable processes and practices

• Wrong site surgery • The abduction of children from hospitals• Deaths or major harm

• Process analysis helps to identify risk and prioritize interventions

• Decision support helps to guide decision making

Probabilistic Risk Assessment

• A hybrid between process analysis and decision support

• Identifies risk points and directs to interventions• Is hierarchical and probabilistic

• Allows disentanglement of patient level risks, provider level risks, and system level risks

• Assigns probabilities for prioritization of risk reduction strategies

• Includes sociotechnical components into the models

Conceptual Framework

Probabilistic Risk Assessment

The Institution

The Providers

The Patient

Quantitative Methods:

Qualitative Methods:

The Prospective Risk Model

Gate1

Patient Harm

Q:0.000146343

Gate2

Patient Harm - Type 1 - Failure

to Detect Initial Severity

Q:8.1143e-005

Gate20

Patient injury prior to

assessment - 1 event

Q:1.94e-008

Gate70

Type 1 harm for those at

risk of harm

Q:8.11236e-005

Gate23

Simulatanous patient, nurse, and

physician failures lead to harm

Q:4.68636e-005

Gate26

Patient escalation, but

patient harmed

Q:2e-006

Gate53

Nurse escalation, but

patient harmed

Q:3.016e-005

Gate57

Physician request for help

fails - 3 events

Q:2.1e-006

Gate71

Patient Harm - Type 2 - Failure to

Detect Critical Change in Condition

Q:6.52e-005

Gate12

Simulatanous patient, nurse, and

physician failures lead to harm

Q:3.4e-005

Gate14

Patient escalation, but

patient harmed

Q:1.48e-005

Gate46

Nurse escalation, but

patient harmed

Q:1.54e-005

Gate50

Physician request for help

fails - 2 events

Q:1e-006

The Top Three Risks

Training Evaluation

• Definition• The systematic collection of descriptive and

judgmental information necessary to make decisions related to instructional activities

• Ensures training• Meets its stated objectives• Changes trainee attitudes• Increases trainee knowledge• Develops trainee skills• Transfers results to the job

Training Evaluation

• Important variables to consider:• Organizational Factors• Individual Factors• Trainee Knowledge, Skills, and Attitudes• Training Transfer• Organizational Outcomes

Merging Kirkpatrick and ST PRA

• Socio-Technical Probabilistic Risk Assessment• Good for examining low base rate events (Six Sigma)• Models contributing causes

• Procedural tasks• Team tasks

• Identifies the impact of an intervention• Evidence base• Empirically based

• Adjust and test the model• Monte Carlo• Changes in the likelihood of outcomes

Traditional ApproachesTraditional Approaches

•Quick Wins•“Fire-fighting”•Burn-out / Fatigue•Difficult-to-Sustain, Short-Term Results

Typical Results

Imp

act

Time

Quality Fusion ApproachQuality Fusion Approach

Time

Imp

act

Quality Fusion Results

Typical Results

Example

What is Escalation?

• Failure to rescue associated with• Interpretation problems• Throughput problems

Put another way…

• When you do not realize the patient is in trouble OR you know the patient is in trouble, but you don’t respond as needed.

Common Course

Ideally, we track the illness. As the patient gets worse (line goes up), we respond. As the patient improves we adjust.

The patient conditionThe provider team response

==

Going Off Course

The defect rate in our modelis caused by failures to properly trackthe course of the illness.

The patient conditionThe provider team response

==

Never On Course

The provider team responseThe patient condition=

=

Sometimes, we’re off course right from the beginning and it’s difficult to get back on course.

The Prospective Risk Model

Gate1

Patient Harm

Q:0.000146343

Gate2

Patient Harm - Type 1 - Failure

to Detect Initial Severity

Q:8.1143e-005

Gate20

Patient injury prior to

assessment - 1 event

Q:1.94e-008

Gate70

Type 1 harm for those at

risk of harm

Q:8.11236e-005

Gate23

Simulatanous patient, nurse, and

physician failures lead to harm

Q:4.68636e-005

Gate26

Patient escalation, but

patient harmed

Q:2e-006

Gate53

Nurse escalation, but

patient harmed

Q:3.016e-005

Gate57

Physician request for help

fails - 3 events

Q:2.1e-006

Gate71

Patient Harm - Type 2 - Failure to

Detect Critical Change in Condition

Q:6.52e-005

Gate12

Simulatanous patient, nurse, and

physician failures lead to harm

Q:3.4e-005

Gate14

Patient escalation, but

patient harmed

Q:1.48e-005

Gate46

Nurse escalation, but

patient harmed

Q:1.54e-005

Gate50

Physician request for help

fails - 2 events

Q:1e-006

The Top Three Risks

Conclusions

• A focus on results helps providers and patients• Training on risk points can improve performance

• Leads to better results• Requires alterations in decision making• Enhances empiric data for better understanding training