Perinatal Collaborative July Coaching Call July 27 th , 2016 - - PowerPoint PPT Presentation

LHAREF HEN Perinatal Collaborative

July Coaching Call

July 27th, 2016

Agenda for Today’s Call

Welcome and introductions Update on Our Data: Taking action in light of variation & reliability Emerging Issues Office Hours (last 30 minutes)

– Please stay on the line to share what you are working on,

learn from other teams, and ask questions

Welcome and Introductions

Welcome from the IHI and LHA team Who’s on the call?

– Please chat in your name!

Emerging Issues?

Update on Our Data: Taking action in light of variation & reliability

Variation Reliability

VA VARIATI IATION ON exi xists sts

Common Cause

• Common cause variations are problems built right

into the system, such as defects, errors, mistakes, waste and rework. In a stable system, common cause variation will be predictable within certain limits

• Common cause variation is produced by the

aggregate of the variation in all the variables (random)

Special Cause

• Special cause variations represent a unique event

that is outside the system, such as a natural disaster, or an unexpected strike by public transportation workers

• Special cause is produced by a non-typical
• variable. (non-random)

Knowledge: Improvement Action

• 1. Random variation: Change the system
• 2. Non-random variation: Investigate

• 1. Most of the time in improvement we are trying to

introduce non-random variation into the system towards the direction of goodness. And then making it stable (random) at a new level or with less spread.

Median

Shift: the purpose of this test is to

identify a shift in the process. A run containing 6 or more consecutive data points all above or all below the median indicates a non-random pattern in your data which should be investigated. This non-random pattern may be a signal of improvement or of process degradation. (The IHI extranet)

Astronomical Point(s)

An astronomical point is one that is obviously and blatantly much higher or lower than all the

• ther points on the chart. On a run chart this rule is not determined statistically but rather by

judgment or consensus. (The IHI extranet definition)

Median

Trend: The purpose of this test is to

identify a low-probability trend in the data

• set. A trend is defined as 5 or more

consecutive points constantly increasing or 5 or more consecutive points decreasing. If a trend is detected it indicates a non-random pattern in your data which should be investigated. (The IHI extranet definition)

Rule 1 Rule 2 Rule 3

RUN CHART TOOL: Three (3) simple rules that indicate if something is not typical random variation. Only one rule needs to be present.

Median

Robust Testing and Reliability Tiers

Full, Sustained Implementation

A P S D A P S D Early tests are simple Designed to learn & succeed Test over a variety of conditions to identify weaknesses Later tests designed to Predict and prevent failures

Hunches Theories Ideas Prevent Initial Failure (80 – 90%) Using intent and standardization Segmentation Identify Failure and Mitigate (90 – 95%) Human factor changes Redundancy function Redesign from Failure Modes > 99% Identify critical failures & then redesign

@ V Crowe

Prevent Initial Failure

CRUD

• Complex
• Redundant (stupid

redundancy)

• Useless
• Delays

Unnatural Variation

@ V Crowe

Prevent Initial Failure (80 – 90%) Associated Changes

• Using intent and

standardization

• Segmentation
• Common equipment
• Standard orders
• Standard rooms
• Memory aids
• Personal check lists
• Awareness
• Training
• Compliance Feedback

Reference: IHI Reliability Presentation

@ V Crowe

intent and standardization Necessary not sufficient

Factors Affecting Human Vigilance :

• Reliance on memory
• Distractions / interruptions
• Fatigue
• Sleep deprivation
• Shift work
• Lack of training and

experience

• Overload
• Psychosocial factors

@ V Crowe

Reference: IHI Reliability Presentation

Identify Failure and Mitigate 90-95% Associated Changes

• Human Factor Changes
• Redundancy Function
• Decision aids & reminders built into

the system

• Differentiation e.g. color coding
• Constraints and Affordances
• Desired action the default
• Alarms
• Provide clear visual or other sensory

clues

• Schedule key tasks
• Take advantage of habits and patterns
• Continue standardization of processes
• Create intentional redundancy

(carefully) and process for mitigation

Reference: IHI Reliability Presentation

@ V Crowe

“This is a mop sink

www.mistakeproofing.com

@ V Crowe

unknown

Patients should experience healthcare processes that are more reliable than manufacturing processes.

www.mistakeproofing.com

@ V Crowe

Redesign from Failure Modes > 99% Associated Changes

Identify critical failures and then redesign

• There is a process to detect failure and

measure the failure.

• There is a clearly articulated process by

which the knowledge about the defects get back into the design

• FMEA – one method
• Failure modes
• What could go wrong?
• Failure causes
• Why would the failure happen?
• Failure effects
• What would be the consequences of

each failure?)

@ V Crowe

Reference: IHI Reliability Presentation

Redesign from Failures

@ V Crowe

Update on Our Data:

Not everything that can be counted counts, and not everything that counts can be counted. Albert Einstein, Physicist (attributed)

PC.01

Time Period min max average_team median n 10 - 2015 14.29 0.98 30 11-2015 20.0 1.78 29 12-2015 28.57 2.29 29 1 - 2016 16.67 0.82 30 2 - 2016 4.44 0.29 29 3 - 2016 9.09 0.52 29 4 - 2016 100 5.2 25 5 - 2016 50.0 4.56 19 6 - 2016 6

Hemorrhage

Time Period min max avg. median n 10-2015 41.67 2.87 24 11-2015 9.01 1.48 24 12-2015 13.79 1.42 24 1 - 2016 10.64 1.38 24 2 - 2016 13.14 1.35 22 3 - 2016 19.61 2.04 22 4 - 2016 13.70 1.68 20 5 - 2016 18.69 2.42 16 6 - 2016 11.24 2.25 5

HEN OB Hemorrhage

Zero events reported One or more events reported Population(D) < 100 month

Hospitals with population per month (D) less than 100 patients and had zero events reported. Hospitals with population per month (D) less than 100 patients and had one

• r more events

reported.)

Population (D) > 100 month

Hospitals with population per month (D) greater than 100 patients and had zero events reported Hospitals with population per month (D) greater than 100 patients and had one or more events reported

HEN OB Hemorrhage

Zero events reported (42% ) One or more events reported (58%) Population(D) < 100 month

8

( 4 < 50 and 4 > 50)

4

(3 had 1 event; 1 had 2 events) Population varied from 20 per month to 90+)

Population (D) > 100 month

3

( 3> 200) (1 had only 1 data point)

11

(3 > 200 and 1 > 600)

Pre-eclampsia

Time Period min max Avg. median n 10 - 2016 166.67 13.44 23 11 - 2016 34.48 1.64 21 12 - 2016 136.36 6.49 21 1 - 2016 142.86 19.53 22 2 - 2016 1000 54.11 21 3 - 2016 500 51.69 19 4 - 2016 86.96 5.44 16 5 - 2016 250.0 32.38 15 6 - 2016 4

Zero events reported 54% One

• r more events

reported 46% Population (D) in single digits

8

(0- 9)

5

(1 or 2 events) Population (D) in single/double digits

3

(0-20)

2

(1 or 2 events) Population (D) in double digits

2

(10 - 50)

4

1 – 3 events pop 17 – 36 19 events pop. 22 – 55

HEN Pre- ecla lampsia

OB Trauma with Instrument

Time Period min max Avg. team median n 10 - 2015 400 48.05 24 11 - 2015 500 82.77 25 12 - 2015 333.33 66.62 27 1 - 2016 1000 95.70 27 2 - 2016 250.00 37.40 25 3 - 2016 333.33 26.29 23 4 - 2016 1000 76.16 22 5 - 2016 428.57 39.92 17 6 - 2016 333.33 68.03 7

Zero events reported 24% One

• r more events

reported 76% Population (D) in single digits (0 – 9)

7 11

(1 – 8 events) Population (D) in single/double digits (1 – 25)

7

(1 - 6 events) Population (D) in double Digits (10 – 38)

4

(1 – 4 events)

HEN OB Trauma wit ith In Instrument

OB Trauma without instrument

Time Period min max Avg. median n 10 - 201 700 38.50 1.24 30 11 - 2015 1000 42.96 30 12 - 2015 769.23 31.15 30 1 - 2016 840.00 40.70 29 2 - 2016 944.44 47.02 29 3 - 2016 800.0 39.73 28 4 - 2016 55.56 10.08 25 5 - 2016 166.67 14.99 19 6 - 2016 34.78 7.01 7

Zero events reported 10% One

• r more events

reported 90% Population (D) in single digits (0 – 9)

3 6

(1 – 8 events) Population (D) in single/double digits (1 – 25)

14

(2 – 15 (101)) events) Population (D) in double Digits (10 – 38)

7

(1 – 22 events)

HEN OB Trauma wit ithout In Instrument

Summary Thoughts

We are seeing things we did not see ... We have improved our clinical processes ... We have much we can learn from each other ....

Emerging Issues

Pre-eclampsia categories ...

Survey Results

When administering labetalol and hydralazine on your OB Unit, do you require telemetry monitoring?

–

Yes: 2, No: 13

Do you require ACLS for your nurses caring for high risk patients with severe hypertension?

–

Yes: 7, No: 8

Do you have 24-hour in house anesthesia in your facility?

– Yes: 14, No: 1

Reminders

If you have not completed the survey, we would appreciate your responses by Thursday, July 28th: https://www.surveymonkey.com/r/6FFT895 Please complete your assessment worksheets if you have not done so already, and return them to Deborah (dbamel@ihi.org)

– Your worksheet can be found on the extranet on your team page,

• r a blank one can be found in the resources section

Upcoming Coaching Calls

Wednesday, August 24th, 12-1:30 pm CT Wednesday, September 21st, 12-1:30 pm CT

– Note: this deviates from our normal schedule due to

the dates of LHA’s agreement with IHI

Thanks for joining us!

Additional questions? Email Deborah at dbamel@ihi.org