niatx –how do we know a change is an improvement? a.k.a. “data is your friend”
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NIATx –How Do We Know A Change Is An Improvement? a.k.a. “Data Is Your Friend” -REMIX- Graphs and Graphing Thomas R Zastowny, PhD NIATx Coach & Healthcare Consultant. Reduce Waiting & No-Shows Increase Admissions & Continuation All authors share equally in this presentation. - PowerPoint PPT PresentationTRANSCRIPT
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NIATx –How Do We Know A Change Is An Improvement? a.k.a. “Data Is Your Friend”-REMIX-Graphs and Graphing
Thomas R Zastowny, PhDNIATx Coach & Healthcare Consultant
Reduce Waiting & No-Shows Increase Admissions & Continuation All authors share equally in this presentation
![Page 2: NIATx –How Do We Know A Change Is An Improvement? a.k.a. “Data Is Your Friend”](https://reader036.vdocuments.mx/reader036/viewer/2022070408/56814408550346895db09d73/html5/thumbnails/2.jpg)
“To put it simply: tell your story clearly and communicate the data accurately. Do that, and you'll be
alright….”
Basic Rules for Making Charts Right « graphs-of-the-day.com. Pingback: Curious Cat Management Improvement Blogflowingdata.com/2010/.../7-basic-rules-for-making-charts-and-graphs/ -
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1. Check the data2. Label axes3. Include units4. Keep your geometry in
check5. Include your sources6. Explain encodings7. Consider your audience
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Model for Improvement
Act Plan
Study Do
• What are we trying to accomplish?• How will we know that a change is an improvement?• What changes can we make that will result in an improvement?
Reference: Langley, Nolan, Nolan, Norman, & Provost. The Improvement Guide
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Hunches Theories
Ideas
Changes That
Result in Improveme
nt
A P
S D
APS
D
A P
S DD S
P ADATA
Change Cycles
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Three common pictures:
■Pie Charts
■Bar Graphs
■Pictograms
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SAMPLE BAR
Leadership Characteristics
0% 10% 20% 30% 40% 50%
Focuses team on objectives.
Is respected
Is persistent
Results verifiable by data
Challenges status quo
Top Five Mentions - Overall
Change Leader Characteristic Survey29 Categories, 99 responses - Change leaders (n = 40)/Executive sponsors (n=20)/Change teams members (n=39)
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STAR-SI Results: Improvements on a Single Measure
RMHA: Decreased average days from 1st request to admission by 47% (on average) for 12 months
FACTS: Almost doubled the % of first appointments kept on average (38% to 71%)
HHC: Reduced the average # of days from 1st Assess to Admission by 39% (on average) for 15 months
SE Nassau: Increased the number of assessments per month by 30% (on average)
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29
23
39
29
0
5
10
15
20
25
30
35
40
45
Average Assessments permonth
Average Admissions permonth
Baseline
April/May 2008
STAR-SI providers* increase monthly assessments by 34 % and monthly admissions by 26%
*n = 8 STAR-SI Providers (Year I and II)
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Sample STAR-QI ReportAS4: # Days from 1st request for service to 1stclinical service
This provider was able to reduce the # days from the time of 1st contact to first service by almost 4 days.
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Example ChartTime from First Contact to First Treatment
0.00
2.00
4.00
6.00
8.00
10.00
12.00
Jun-03
Jul-03
Aug-03
Sep-03
Oct-03
Nov-03
Dec-03
Jan-04
Feb-04
Mar-04
Apr-04
May-04
Jun-04
Jul-04
Aug-04
Sep-04
Oct-04
Nov-04
Changes Implemented ChangesSustained
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PI TEA –Use of Data (NIATx Workbook, 2007)
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Summary-10 Questions1. Does the message of interest stand out clearly?
2. Is the purpose or title of the picture evident?
3. Is a source given for the data, either with the
picture or in an accompanying article?
4. Did the information in the picture come from a
reliable, believable source?
5. Is everything clearly labeled, leaving no
ambiguity?
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Summary-10 Questions6. Do the axes start at zero or not?
7. Do the axes maintain a constant scale?
8. Are there any breaks in the numbers on the
axes that may be easy to miss?
9. For financial data, have the numbers been
adjusted?
10. Is there information cluttering the picture or
misleading the eye?
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