An alternative to Red-Yellow-GreenBoard ReportsDan Watson, MBA

Valerie Craig, RN, MSN, MAOM

Richard Scoville, PhD

Tuesday, December 12

Session A9/B9

Objectives

• Describe how MHS transitioned to a systems-based approach for selecting/prioritizing key metrics

• Describe our systems-based approach for selecting and prioritizing key metrics

• Walk through how MHS integrated systems-based data analysis to support their Board Committee

These presenters have nothing to disclose

Methodist Health System

10 Hospitals

31 Family Health Centers

6 Ambulatory Sites (imaging, urgent care)

1,500 beds

3

About Methodist Health System • Founded in 1927

• 8,500+ employees

• 1,500+ physicians on staff

• 290+ affiliated physicians

• 536,000 patient visits

• $140 million in unreimbursed charity care

• One of Dallas Business Journal’s Top 10 “Best Places to Work” (13 years running)

• First and only member of the Mayo Clinic Care Network in Texas

Fellowships– Gastroenterology

– Nephrology

– Surgical critical care

– Hepato-pancreato-biliary surgery

Residencies– General surgery

– Internal medicine

– Obstetrics-gynecology

– Family medicine

4

in 2014

THE SYSTEM QUALITY REVIEW COMMITTEE

…to best quartile…

Who’s Who & Does it Matter?

Change to report

as the cure to what ailed us

SYSTEMS-BASED MEASUREMENT

Goal-Driven View[with point-to-point coloration]

FY13 Q4 data includes

Jul-Aug data onlyPublic Measure

FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13

Goal ▲ 91.04% 97.44% 88.83% 93.81% 90.50% 94.49% 93.99% 96.59% 90.42% 93.79% 91.12% 98.00% 93.78% 90.53% 95.28% 90.83% 96.96% 88.55% 94.43% 96.20%

96.02% 95.47% 95.26% 96.38% 95.37% 98.85% 97.04% 91.44% 97.01% 93.86% 90.75% 94.12% 91.32% 89.99% 92.06% 93.53% 89.70% 95.88% 94.99% 92.01% 91.90% 97.53% 95.41% 94.16% 98.40% 1,2,3,4

Public Measure

Mortality

Hospital

Compare

Natl Avg (1)

FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13 FY13 Q1 FY13 Q2 FY13 Q3 FY13 Q4 FYTD13

Risk Adj Index

(All payors)▼ 0.43 0.49 0.97 0.63 0.60 1.73 1.02 0.79 0.00 0.92 1.14 1.24 0.98 0.45 1.04 0.98 0.97 1.34 2.48 1.32 0.88 0.83 0.95 0.65 0.90

All payors ▼ 4.65% 3.21% 6.34% 4.81% 4.87% 8.44% 8.62% 4.48% 0.00% 5.44% 5.29% 4.52% 5.07% 2.20% 4.66% 2.49% 6.66% 10.47% 9.95% 7.06% 5.53% 5.18% 6.01% 3.31% 5.05% 1,2,3,4,5,6

Risk Adj Index

(M'care only)▼ 0.45 0.42 1.41 0.81 0.75 3.14 1.04 1.16 0.00 1.24 0.53 0.00 1.35 0.00 0.64 0.00 1.14 1.32 3.21 1.59 0.83 0.74 1.28 0.85 0.92

M'care only 15.5% 5.52% 3.21% 13.64% 14.40% 8.99% 22.78% 12.89% 8.04% 0.00% 10.51% 3.42% 0.00% 8.27% 0.00% 3.54% 0.00% 6.02% 8.60% 16.72% 6.96% 6.25% 5.54% 10.32% 9.51% 8.17%

Risk Adj Index

(All payors)▼ 0.46 0.81 0.18 0.00 0.46 0.55 1.05 0.99 1.63 0.97 0.82 0.28 1.00 0.59 0.62 0.68 1.43 0.00 1.67 1.11 0.59 0.82 0.57 0.83 0.66

All payors ▼ 1.74% 2.61% 0.64% 0.00% 1.47% 1.87% 3.31% 2.89% 5.45% 3.18% 2.31% 0.91% 2.46% 1.44% 1.71% 2.26% 6.28% 0.00% 7.93% 3.89% 2.06% 2.82% 1.69% 2.77% 2.34% 1,2,3,4,5,6

Risk Adj Index

(M'care only)▼ 0.36 0.39 0.33 0.00 0.21 1.16 1.57 1.24 1.88 1.52 1.43 0.47 0.96 0.00 0.70 0.00 1.15 0.00 0.00 0.40 0.64 0.77 0.68 0.43 0.64

M'care only 11.6% 0.00% 1.45% 1.78% 0.00% 0.87% 4.50% 5.86% 4.22% 6.90% 5.57% 5.87% 2.37% 3.14% 0.00% 3.14% 0.00% 6.83% 0.00% 0.00% 1.57% 2.59% 3.41% 2.57% 1.87% 2.76%

Risk Adj Index

(All payors)▼ 1.18 1.02 1.20 0.52 1.06 0.35 0.36 0.56 0.52 0.48 1.36 0.53 0.46 1.19 0.85 1.38 0.74 0.00 0.00 0.58 1.10 0.66 0.58 0.59 0.71

All payors ▼ 3.73% 4.29% 3.69% 2.43% 3.88% 1.15% 1.38% 3.08% 2.24% 2.02% 3.10% 1.75% 1.51% 4.62% 2.37% 4.74% 1.82% 0.00% 0.00% 2.12% 3.21% 2.36% 2.35% 2.77% 2.57% 1,2,3,4,5,6

Risk Adj Index

(M'care only)▼ 1.65 1.25 1.63 0.00 1.16 0.00 0.00 0.51 0.00 0.17 1.95 0.91 0.00 1.93 1.03 1.88 1.08 0.00 0.00 0.84 1.39 0.86 0.45 0.66 0.87

M'care only 12.0% 8.29% 6.86% 7.61% 0.00% 6.71% 0.00% 0.00% 2.59% 0.00% 0.88% 5.69% 2.39% 0.00% 21.40% 4.35% 10.06% 3.41% 0.00% 0.00% 4.15% 6.03% 3.51% 2.55% 3.78% 3.96%

MCMC

Congestive Heart Failure

(CHF)

Goal ≤ 1.0

Acute Myocardial Infarction

(AMI)

Goal ≤ 1.0

Methodist Health System

Performance Improvement Dashboard, October 2013

Privileged and Confidential

Board Summary

Q1,Q2, Q3, Q4 FYTD13 (Oct-August13)

MDMC

Quality Process Domain

Score (Composite for VBP

indicators)

MHSMMMC MRMC

MMMC MRMC

Pneumonia (PN)

Goal ≤ 1.0

MCMC

MHSMDMC

Fails to provide actionable insight into overall performance, rather tends to overemphasize the significance of small, expected changes.

The Illusion of Change

Month Oct 2016 Nov 2016 Dec 2016 Jan 2017 Feb 2017 Mar 2017 Apr 2017 May 2017 Jun 2017 Jul 2017 Aug 2017 Sep 2017

KPI 0.20 0.04 0.06 0.06 0.06 0.13 0.04 0.16 0.04 0.12 0.12 0.12

Expected Variation is Not Difficult

Making decisions based on expected

variation can be intuitive

Our daily commute

• How long does it take you to get to

work?

15 minutes?

10 - 20 minutes?

• Would you change your route if it took 17 minutes one day?

• What about after an inclement weather day?

• How much time would you give yourself if you had a really important meeting?

Managing our daily commute

“No different” is an acceptable &

actionable conclusion

Math to the Rescue!

The “Swiss Army Knife”

of Control Charts

Ask not what your

chart can do for you,

but what you can do

with your chart

Don’t waste too much time

on tools and techniques. You

can learn the lot in 15

minutes

~Dr. Deming [from David Kerridge]

The value of the

data

doesn’t come

from the chart…

it comes from

how we use it.

patience, picked battles, and persistence on process

THE PATH TOWARDS OUR SOLUTION

A woodsman was once asked,

“What would you do if you had just five minutes to chop down a tree?”

“I would spend the first two and a half minutes sharpening my axe.”

Simple ≠ Summary

• Summarizing can obscure useful info

• But we can describe complexity simply

• We can differentiate performance to goal from system performance

Also, it’s 5*

Prioritize Performance

• Remove items we’re not working on

• Support System Performance over

Point-to-Point Comparison

• Define data well, but as reference

Consider Context Over Clarity

• Tone down designs that encourage knee-jerk conclusions

• Embrace and explain complexity

• Summarize AND analyze

Accentuate Action

• Prioritize key system initiatives

• Recognize hard work

• Avoid sharing effects without causes

First pass…

Current

Status“How did we do compared to last time?”

• Absolute change is a

coin flip

• Used Moving Range

Analysis from SPC

software

• Change is noted when

+/- 2 sigma & color

coded based on

favorable direction

Yes, I know. Not 3.

Sparkline*“What is our pattern of results?”

• Visual display of relative

performance

• Uses most recent running

data points

• Whole process is color-

coded based on system

stability

* Not a trend line. Because those are my enemy.

• Practical data definitions

• Replaces multiple in-line legends

• Available & scalable, but not intrusive

Parameters

Indicator Name

Unit of Measure

Calculation [if applicable]

Frequency

Time Periods• Current Value • Sparkline

Description• Summary statement• Key inclusion/exclusion• Aggregation methods• Benchmark Source

Data Source

Data Definitions“Where do these numbers come from?”

Entity Process Control Charts“How is each campus doing?”

The cutting room floor…

• You say ‘trend’, I say ‘shift.’ Let’s call the whole thing off

• Special cause is special causeYour fancy symbols don’t impress me

• Critical Values Managing KPI like lab values

was a bridge too far

Executive Summary“So what?”

• Unburdens each tool to focus on its strength

• Very effective treatment for footnote-philia

• Enables analysis & action to be shared

Lessons Learned

• Simple is hard

• Focus on your

stakeholders’ end goal

• Be patient and ready to compromise

Next Steps

• Center line assessment

• Routine re-assessment of content

• Bring Balance