lean process improvements for quality reporting aug tasc 90 mli… · tasc 90 webinar august 13,...

Lean Process Improvements for Quality Reporting

TASC 90 Webinar

August 13, 2012

Melissa P. Lin, MS, LSSBB, CPHQ

2

No Shortage of Quality Reporting Requirements

• Medicare Beneficiary Quality Improvement Project (MBQIP)

• Partnership for Patients (P4P) Hospital Engagement Networks (HENs)

• 10th Scope of Work (SOW) - Integrating Care for Populations and Communities

• Healthcare-associated Infections (HAIs) via CDC

• Meaningful Use of Electronic Health Records Clinical Quality Measures

• Other state quality reporting initiatives

• Third-party reporting group initiatives

• Individual organization’s quality reporting initiatives

3

Data, data everywhere…

• How do we keep track of it all?

• How do we know we’re collecting it…

– Correctly?

– Timely?

• What does it tell us?

• How do we act based on the results?

4

What is Lean?

• “Lean” coined by Massachusetts Institute of Technology

– Originated from Toyota

• A philosophy that is focused on:

– Defining value in the eyes of the patients

– Eliminating wasteful steps that add no value to the organization

– Creating flexibility and agility to meet the changing needs of the patient and the industry

– Empowering frontline by incorporating easy problem-solving tools to use daily

– Do more with less

This entire philosophy is driven by data!

5

Data drives Lean.

6

Best Safety

Highest Quality

Shortest Lead Time

Lowest Cost

Highest Employee

Morale

LEAN

6

How can Lean improve your hospital?

7

Data, information and facts

Measurements used for reasoning, calculations or discussion

Gathering and analyzing data leads to information

Data Knowledge obtained from the investigation, study or analysis of data

Information leads to the identification of facts

Information A piece of information presented as having objective reality

Fact

8

Continue improving

measurement consistency

Begin data collection

Plan for data consistency &

stability

Develop operational definitions & procedures

Clarify data collection

goals

What Data Should I Get?

• What questions are you trying to answer? • Who on the team is collecting data? • What data does the team need to answer the questions? • How will the data help

answer these questions? Meet customer needs? Improve operations?

• Is the needed data already available? If not, what data must be collected?

• How much data does the team need? Collected over what time period?

9

Who Owns the Data?

• The people living and breathing the process

– E.g. The person(s) responsible for discharging AMI patients with statin prescribed

• Data stewardship

– Being responsible for data that’s worth caring for and preserving

• Data quality is a team sport

– So is process improvement

• Process owners are responsible and accountable for the quality and simplicity of data that represents and enables their processes

• Data measurements can be both formal metrics from reporting indicators and informal measures the team finds vital to the improvement process that supports a formal reporting indicator

10

Formal example

• Central line-associated bloodstream infection rate

Informal examples

• Percentage of ICU patients with central lines who receive all 5 elements of the central line bundle

What Data do We Want Measured?

11

Clarify Data Collection Goals

• What is the concept the team is trying to evaluate?

– Examples: length of time, volume, ease of use, uniformity, completeness, defects

• What data will allow the team to attach a value to this concept?

Continue improving




stability



goals

12

Clarify Data Collection Goals

• Is the operational definition clear?

– Examples: Does “on-time” mean within five minutes? Two hours? Three days?

• What is your plan for collecting the data? − What procedures will be used to make the collection

precise and consistent? − How will the data be recorded?

Continue improving




stability



goals

13

• Data is consistent if any two people who measure the same things arrive at essentially the same answer

• Data is stable when the results do not show signs of special causes of variation over time

– Will my data show whether the process is stable or unstable?

Collecting Meaningful Data

Continue improving




stability



goals

Continue improving




stability



goals

14

• Explain the procedures to all data collectors • Practice makes perfect!

− Have everyone practice using the forms and/or the procedures before “real” data collection begins

• Have someone who knows what to do watch and instruct beginning data collectors

− Daily huddles to review a test of change is a perfect time to check in with data collectors

Begin Data Collection

Continue improving




stability



goals

15

• Are measurements stable? • Are measurements consistent? • Analyze the data

− What was the answer to our question(s)? − Does it show us what we need to improve?

Continue Improving Measurement Consistency

Continue improving




stability



goals

16

Presenting Data for Analysis

Adapted from NHS Improvement Network

Number of Patients Treated per Week

1 2 3 4 5 6 7 8 9 10

216 239 233 226 288 227 238 228 287 229

11 12 13 14 15 16 17 18 19 20

242 233 286 228 239 232 237 285 232 235

17


200

210

220

230

240

250

260

270

280

290

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Pat

ien

ts T

reat

ed

Weeks

Adapted from NHS Improvement Network

18


Source: Carey, RG. Improving Healthcare with Control Charts. Milwaukee, WI: ASQ Quality Press, 2003.

• Average CABG mortality before and after implementation of new protocol. Did the improvement reduce mortality rate?

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

2008 2009

Intervention begins in Jan 2009

19

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

Jan

-98

Feb

Mar

apr

May Jun

Jul

Au

g

Sep

Oct

No

v

Dec

Jan

-99

Feb

Mar

Ap

r

May Jun

Jul

Au

g

Sep

Oct

No

v

Dec


• Average CABG mortality before and after implementation of new protocol.

• Decreased mortality was not due to the new protocol which may have had an unintended negative effect

Intervention begins in Jan 2009

2008 Avg. = 5%

2009 Avg. = 4%

Median 4.5%

Source: Carey, RG. Improving Healthcare with Control Charts. Milwaukee, WI: ASQ Quality Press, 2003.

20

Displaying Data: The Run Chart

• Line graphs that plot any type of data over time

• Help you see trends

• Help you determine when a change might have occurred

– Common cause vs. special cause variation

• Requires paper and pencil, no statistics!

Me

asu

red

Ou

ptu

t

Time

Run Forrest RUN!

21

• Monitor progress and display data for staff members

– Data Wall

– Keep it simple – one graph, one message

– Report regularly to Improvement Team

• We are what we repeatedly do, make improvement a regular do!

• Check in from time to time to ensure that the metric is still useful or the benchmark is still ambitious enough

– Do we need to 5S our metrics?

Excellence is not one act, it is a habit. - Aristotle

22

5S – A Lean Tool

22

SUSTAIN

• Discipline

• Established procedures become habit

SORT

• Organize

• Eliminate waste

STRAIGHTEN

• Everything has a place

• Keep everything in its place

SHINE

• Cleanliness

• Keep clean and tidy

STANDARDIZE

• Adherence

• Maintain the first three pillars

23

The Results of 5S

24

Value

Value Stream Map

Eliminate Waste

Flow

Strive for Perfection

24

Five Principles of Lean

25

Final Thoughts

• The five major steps of data collection can lead you to useful information and decision-making

• Good data collection can be ruined by bad data analysis

• Data doesn’t belong to just one person, it belongs to everyone involved in the process it measures

• Without baseline data analysis, how do we know that a change is an improvement?

– Improvement of the process (Lean) and the underlying data must go hand-in-hand

• A useful metric today can become a useless metric tomorrow

– Check metrics from time to time

“Data are like garbage. We need to know what we are going to do with the data before we actually collect them.” – M. Twain

26

Melissa P. Lin, MS, LSSBB, CPHQ

Consultant

207-221-8273 (O)

[email protected]

Any Questions?

mailto:[email protected]

lean process improvements for quality reporting aug tasc 90 mli… · tasc 90 webinar august 13,...

Documents