lab finance peerwani 162016 final
TRANSCRIPT
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Critical considerations and best practices in managing finances and the lab bottom line
Ziad Peerwani M.D.Tawam Hospital
June 1, 2016
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What We Are Not Discussing (In Detail):
• Quality Management: Lean, Six
Sigma, Lean Six Sigma
• PDCA Cycles
• Work Flow and Process Mapping
• Economies of Scale
• And More….
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What We Are Not Discussing (In Detail):
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Our Mission: Critical Considerations and Best Practices
• Big Picture: Macro-allocation and Health Care
• Culture and Leadership: Effectively Leveraging Vision and Mission
• Cost of Poor Communication• The Age of Human Capital • Baylor Health Care System Case
Study
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What is Value?
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What is Value?
Value70% of Decisions
2-4% of Net Revenue
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Allocation of Resource: Multi-tiered
Total Resources Available to a Country
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Allocation of Resource: Multi-tiered
HealthCareMilitary
Education
Infrastructure
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Allocation of Resource: Opportunity Cost
Healthcare
Military
Education
Infrastructure
Other
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HealthCare
Military
Education
Infrastructure
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Allocation of Resource: Multi-tiered
ResearchPatient Care
Infrastructure
Public Health
Healthcare
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Allocation of Resource: Multi-tiered
Eventually…
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Allocation of Resource: Multi-tiered
Laboratory Medicine
Hospital
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Allocation of Resource: Scarcity
HealthcareDemand
HealthcareResources>
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Perspective
• Laboratory services = Value• Scarcity: Demand for health severely exceeds
resources • Leaders within health care have a
fiduciary responsibility to ensure responsible and efficient resource utilization at all levels of Healthcare
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Vision and Mission: Aligning Strategy
Organizations that have clearly defined Vision and Mission statements that are aligned with a strategic plan, outperform those who do not.
Evans, J; “Vision and Mission - What's the difference and why does it matter?” Psychology Today, April 24, 2010
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Vision and Mission: Creating Culture and Aligning Strategy
Vision: • Understanding who you are and defining what you
hope to be.• Provides Guidance and Inspiration• Succinct and Clear
Baylor Scott and White: To be the most trusted name in giving and receiving safe, quality, compassionate health care.
Cleveland Clinic:World's leader in patient experience, clinical outcomes, research and education
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Vision and Mission: Creating Culture and Aligning Strategy
Mission Statement: • What do we do?• How do we do it?• Whom do we do it for?• What value are we bringing?
Cleveland Clinic:Provide better care of the sick, investigation into their problems, and further education of those who serve.
Erie Insurance: To provide our policyholders with as near perfect protection, as near perfect service as is humanly possible and to do so at the lowest possible cost.
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“I think that the good and the great are only separated by the willingness to sacrifice.”
Kareem Abdul-Jabbar
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Vision and Mission: Creating Culture and Aligning Strategy
Radiology
Nursing
Laboratory
Clinical
Pharmacy
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Vision and Mission: Creating Culture and Aligning Strategy
Radiology
Nursing
Laboratory
Clinical
Pharmacy
VisionMission Alignment
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• Engagement• Payroll efficiency• Communication Barriers• Downtime• Safety• Employee Retention • Turnover• Managers’ Performance• Corporate Change• Etc
Cost of Poor Communication
Cost
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Cost of Poor Communication
System/Hospital Admin
Laboratory Admin
Pathologist & Technologists
• Strategic planning and resource allocation requires robust multi-tiered communication
• Misalignment results in decreased efficacy of cost reduction tools.
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Cost of Poor Communication
System/Hospital Admin
Laboratory Admin
Pathologist & Technologists
• Robust synergistic relationships and communication aligns strategic planning and resource allocation
• Decreased waste and improved operational efficiency
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Cost of Poor Communication
System/Hospital Admin
Laboratory Admin
Pathologist & Technologists
• Robust synergistic relationships and communication aligns strategic planning and resource allocation
• Decreased waste and improved operational efficiency
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Age of Human Capital
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…refers to the knowledge, information, ideas, skills, and health of individuals. This is the “age of human capital” in the sense that human capital is by far the most important form of capital in modern economies.
Gary S. Becker, Nobel Laureate in Economics
Age of Human Capital
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Age of Human Capital
Time
Valu
e to
Com
pany
Training Status Quo
Employee Start
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Time
Valu
e to
Com
pany
Training Status Quo
Employee engagement, recognition,
development, and great
management
Effective Human Capital
Management
Age of Human Capital
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Time
Valu
e to
Com
pany
Age of Human Capital
Value
Quality + Service
Cost
Cost of Poor Human Capital Management
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Time
Valu
e to
Com
pany
Age of Human Capital
Recruitment: matching skills with workflow
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Time
Valu
e to
Com
pany
Age of Human Capital Starting point does not reflect potential
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BHCS Case Study
Healthcare System Leadership: Reduce Costs
Independent Consulting Agency
Reduce cost within Automated Hematology by Adjusting Flag Settings to
Reduce Manual Review Rates by 2-4%
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Literature was less instructive due to wide variety of recommended flagging parameters
Neut #<
Neut %<
Neut#>
Neut%>
Lymp#<
Lymph%<
Lymp#>
Lymph%>
Mono#>
Mono%>
Parameter
Eos#>
Eos%>
Baso#>
Baso%>
WBC#<
WBC#>
IG#>
IG%>
NRBC%>
At Sysmex recommended setting
Average of all data points; BUMC’s current setting
Range between average and Sysmex recommended
Wide variation, keep BUMC setting
BUMC is at average, keep BUMC setting
This is a strong lever of flags, recommend a wide range
At Sysmex recommended setting
Most sources use this value
At Sysmex recommended setting
Most sources use this value
Rationale
At Sysmex recommended setting
Most sources use this value
At Sysmex recommended setting
This setting is a very weak lever, no change between this range
Wide variation & weak lever, use average
Wide variation & weak lever, use average
Limited sources, keep BUMC setting
Most sources use this value
Weak lever, keep BUMC setting
1.5
–
15
–
0.8
–
5
–
1.5
–
Sysmex 100 average
2
–
0.5
–
2.5
20
–
2
1
1.5
10
9
80
1
7
3.5
50
0.8
10
Sachse
0.5
7
–
–
–
–
0.1
2
2
1
20
18
95
0
0
4
60
1
15
Lin
0.7
20
0.2
5
2
25
–
–
2
1
–
20
–
–
–
5
–
1.5
–
Int’l Cons. Group1
2
–
0.5
–
–
–
–
–
–
–
30
–
85.5
–
10
–
70
–
15.5
Hur
–
20
–
2
–
–
–
–
2
–
–
–
80
–
–
–
–
–
–
Stam-minger
–
–
–
–
–
–
–
2
–
–
–
–
–
–
–
–
–
–
–
Field
–
–
–
–
–
–
0.5
5
–
–
–
7.5
80
–
–
6
60
1
15
Hyun
1
15
0.3
4
4
50
–
–
3
–
–
–
–
–
–
8
–
2
–
Lantis
1.5
–
–
–
1
50
–
–
–
1
20
12
85
0.8
10
4.8
60
1.2
15
BUMC
1.6
20
0.2
3
3
18
0.5
1
1
1
20
15
85
0.8
10
5
60
1.5
15
More sen-sitive
2
20
0.5
3
2.5
20
0.5
2
1
1
20
20
85
0.8
7
5
60
1.5
15
Less sen-sitive
2
20
0.5
5
2.5
25
0.5
2
1
Our recommended settings and rationale
1 Sysmex advises clients to follow the recommendations of the International Consensus Group
-
–
-
–
–
–
4.99
100
1.69
100
Cleve-landClinic
1.99
100
0.2
100
2.01
19.99
0.1
100
–
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Concerning when Baylor’s scan and differential count rate is higher than 75% of the 263 studied institutions1
Rates of manual differential count in participating institutions1
Rate; n=263 institutions, 95,141 CBCs
Percentile of performance
0%
5%
10%
15%
20%
25%
10th%Median 25th%90th% 75th%
Rates of manual blood scan in participating institutions1
Rate; n=263 institutions, 95,141 CBCs
Percentile of performance
BHCS’s average
0%
5%
10%
15%
20%
25%
30%
35%
40%
10th%Median 25th%90th% 75th%
BHCS’s average
1. Arch Pathol Lab Med – Vol. 130, May 2006
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BHCS Case Study
Leadership
We should attempt to shift our rates to the national average or to values comparative to other large institutions
2-4% reduction is sufficient and reduces the risk of impacting patient care. We are unique and the status quo reflects our steady state.
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Flagging study accumulated specimens from each type of facility in BHCS to ensure applicability to our portfolio of hospitals’ types of patients
100110200
400
933
1,500
SW WAXGRPIrvingBASBUMC
Specimens collected from 6 facilitiesNumber of samples per facility, n=3,243
Study designSample and data collection
• Randomly collected, three times per day
• Automated CBC with diff• 100 cell manual diff counts
Analysis • Collected and analyzed in Excel
• Consensus amongst 4 hematopathologists
• Validation of excel model with comparison to Sysmex’s analysis
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Literature was less instructive due to wide variety of recommended flagging parameters
Neut #<
Neut %<
Neut#>
Neut%>
Lymp#<
Lymph%<
Lymp#>
Lymph%>
Mono#>
Mono%>
Parameter
Eos#>
Eos%>
Baso#>
Baso%>
WBC#<
WBC#>
IG#>
IG%>
NRBC%>
At Sysmex recommended setting
Average of all data points; BUMC’s current setting
Range between average and Sysmex recommended
Wide variation, keep BUMC setting
BUMC is at average, keep BUMC setting
This is a strong lever of flags, recommend a wide range
At Sysmex recommended setting
Most sources use this value
At Sysmex recommended setting
Most sources use this value
Rationale
At Sysmex recommended setting
Most sources use this value
At Sysmex recommended setting
This setting is a very weak lever, no change between this range
Wide variation & weak lever, use average
Wide variation & weak lever, use average
Limited sources, keep BUMC setting
Most sources use this value
Weak lever, keep BUMC setting
1.5
–
15
–
0.8
–
5
–
1.5
–
Sysmex 100 average
2
–
0.5
–
2.5
20
–
2
1
1.5
10
9
80
1
7
3.5
50
0.8
10
Sachse
0.5
7
–
–
–
–
0.1
2
2
1
20
18
95
0
0
4
60
1
15
Lin
0.7
20
0.2
5
2
25
–
–
2
1
–
20
–
–
–
5
–
1.5
–
Int’l Cons. Group1
2
–
0.5
–
–
–
–
–
–
–
30
–
85.5
–
10
–
70
–
15.5
Hur
–
20
–
2
–
–
–
–
2
–
–
–
80
–
–
–
–
–
–
Stam-minger
–
–
–
–
–
–
–
2
–
–
–
–
–
–
–
–
–
–
–
Field
–
–
–
–
–
–
0.5
5
–
–
–
7.5
80
–
–
6
60
1
15
Hyun
1
15
0.3
4
4
50
–
–
3
–
–
–
–
–
–
8
–
2
–
Lantis
1.5
–
–
–
1
50
–
–
–
1
20
12
85
0.8
10
4.8
60
1.2
15
BUMC
1.6
20
0.2
3
3
18
0.5
1
1
1
20
15
85
0.8
10
5
60
1.5
15
More sen-sitive
2
20
0.5
3
2.5
20
0.5
2
1
1
20
20
85
0.8
7
5
60
1.5
15
Less sen-sitive
2
20
0.5
5
2.5
25
0.5
2
1
Our recommended settings and rationale
1 Sysmex advises clients to follow the recommendations of the International Consensus Group
-
–
-
–
–
–
4.99
100
1.69
100
Cleve-landClinic
1.99
100
0.2
100
2.01
19.99
0.1
100
–
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Adopting the ICG’s criteria is expected to reduce our manual review rate by one-third while preserving the false negative rate under 5%
92.9
32.925.7
2.0
48.534.7
92.3
72.2
91.2
45.7
25.7
4.7
24.9
66.4
81.6
45.9
-36.4%
NPVPPVClinical positive
rate
False negative
rate
False positive
rate
Specificity rate
Sensitivity rate
Manual review
rate
ICGbase
Outcome statistics: baseline vs. ICG criteria applicationPercent; n=3,243 samples
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BHCS Case Study
Leadership
Reduction of manual review rate by 36.4% with a false negative rate under 5%
2-4% Reduction of manual review rate will result in less impact.
Validation/Cost Reduction?
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Validation study accumulated specimens from each type of facility in BHCS but was purposefully agnostic to rates of abnormalities
50
99
127135150
185202202
228236
PLANOGRPIRVBASMCKBUMC CAR THH WAXGAR
Specimens collected from 10 facilitiesNumber of samples per facility, n=1,614Study design
Sample and data collection• 10 participating sites• 100 to 200 samples per site, 1,614 total samples
• Half normal and half with specific abnormalities delineated by CLSI
• 200-cell manual differentials by two different individuals
Analysis • Collected and analyzed in Excel
• Consensus amongst 4 hematopathologists
• Validation of excel model with comparison to Sysmex’s analysis
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Adopting the ICG’s criteria was expected to reduce our manual review rate by one-third while preserving the false negative rate under 5%, but did not
91.2
45.7
4.7
24.9
66.481.6
89.8
40.2
5.3
28.4
62.3
78.2
False positive
rate
Specificity rate
Sensitivity rate
NPVPPVFalse negative
rate
ValidationICG
Outcomes statistics: ICG flagging vs. validation studyPercent; n=1,614 samples
Area of concern
Why did our false negative
rate increase so
much?
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One hospitals was the statistical outlier pulling the mean up, and this hospital potentially will require different flagging parameters
3.30.01.32.73.03.13.54.05.15.3
36.4
5.3
PlanoIRV GAR GRPBASBHCS with
THHBP
CARWAXBUMCMCKTHHBP BHCSwithout THHBP
Overall false negative rates with and without The Heart Hospital Baylor Plano (THHBP) includedPercent, n=1,614
With THHBP
Without THHBP
Heart hospital with high rate of clinically less significant
giant platelets
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Immediate and sustained decrease in percentage of manual scans at Baylor All Saints Medical Center
0
10
20
30
40
50
1312111098765432 2221201918171615141
32.7
45.1
Flagging criteria
implemented
Manual review rates per weekPercent of total CBCs, starting on April 21, 2013, n=39,760 CBCs
Pre-change meanPost-change mean
P <0.05 by T test
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Initial implementation has reduced slide review rates by 27-42% per hospital and may be a significant savings lever
36.7
45.1
21.2
32.7
-27%
-42%
GRPBAS
PostPre
Hematology slide review ratesPercent
Total CBCsMan review rate, baseline• Scan rate, baseline• Manual diff rate, baseline
Scan volume, baselineMan diff volume, baseline
Man review rate, ICGScan volume, ICGMan diff volume, ICG
Cost per scan Cost per man diff
Potential savings
Savings if 50% capture rate
625,00053%24%29%
152,375178,875
34.5% 99,188 116,438 $7.79 $15.58
$1,387,107
$693,553
BHCS potential savings model from full implementation of ICG flagging criteria
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BHCS Case Study: Lessons Learned
• Constructive disagreement: a productive tool• Opinions and external comparisons: guide strategy
and improvement• However, each laboratory and practice setting is
different. • Actual solutions must be tailored to the specific
laboratory in question. • Data driven quantitative analysis brings clarity and
shifts improvement from guesswork to fact based decision making allowing laboratories to capture higher rates of cost reduction while ensuring quality.
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Conclusion
• Every Health Care Dollar is Precious• Creating dynamic work place culture that
stems from a clear and inspiring vision is necessary to drive towards excellence
• Institutions and organizations cannot be built without robust communication and professional relationship
• Although often undervalued, human capital is a key resource that hugely impacts cost.
• Although there are numerous tools to cut costs, the efficacy is blunted without the right organization infrastructure and leadership
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Thank you!