Critical considerations and best practices in managing finances and the lab bottom line

Ziad Peerwani M.D.Tawam Hospital

June 1, 2016

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….

What We Are Not Discussing (In Detail):

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

What is Value?

What is Value?

Value70% of Decisions

2-4% of Net Revenue

Allocation of Resource: Multi-tiered

Total Resources Available to a Country

Allocation of Resource: Multi-tiered

HealthCareMilitary

Education

Infrastructure

Allocation of Resource: Opportunity Cost

Healthcare

Military

Education

Infrastructure

Other

HealthCare

Military

Education

Infrastructure

Allocation of Resource: Multi-tiered

ResearchPatient Care

Infrastructure

Public Health

Healthcare

Allocation of Resource: Multi-tiered

Eventually…

Allocation of Resource: Multi-tiered

Laboratory Medicine

Hospital

Allocation of Resource: Scarcity

HealthcareDemand

HealthcareResources>

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

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

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

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.

“I think that the good and the great are only separated by the willingness to sacrifice.”

Kareem Abdul-Jabbar

Vision and Mission: Creating Culture and Aligning Strategy

Radiology

Nursing

Laboratory

Clinical

Pharmacy

Vision and Mission: Creating Culture and Aligning Strategy

Radiology

Nursing

Laboratory

Clinical

Pharmacy

VisionMission Alignment

• Engagement• Payroll efficiency• Communication Barriers• Downtime• Safety• Employee Retention • Turnover• Managers’ Performance• Corporate Change• Etc

Cost of Poor Communication

Cost

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.

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

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

Age of Human Capital

…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

Age of Human Capital

Time

Valu

e to

Com

pany

Training Status Quo

Employee Start

Time

Valu

e to

Com

pany

Training Status Quo

Employee engagement, recognition,

development, and great

management

Effective Human Capital

Management

Age of Human Capital

Time

Valu

e to

Com

pany

Age of Human Capital

Value

Quality + Service

Cost

Cost of Poor Human Capital Management

Time

Valu

e to

Com

pany

Age of Human Capital

Recruitment: matching skills with workflow

Time

Valu

e to

Com

pany

Age of Human Capital Starting point does not reflect potential

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%

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

–

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

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.

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

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

–

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

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?

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

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?

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

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

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

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.

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

Thank you!