Improve Tech Pre Calibration Project Book

DMAIC Project Report

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DMAIC BB DMAIC GB

Project Title: Improve Technetium Pre-calibration
Project Number (1st, 2nd, 3rd…): 2nd
Instantis Project ID#:
Project Leader Name: Ramesh Rajan
Project Leader Job Title: Process Engineer
Imaging Solutions/Nuclear Pharmacy
Segment/GBU/Division/Plant/Region:
Operations

improvetechprecalibrationprojectbook-12584117210388-phpapp01.doc

Executive Summary
The Nuclear pharmacy network comprises 1/3 of the total Imaging division revenue.
Technetium-99 is a primary radioactive isotope which is used for various diagnostic
procedures at hospitals, imaging centers etc. This represents 80% of the pharmacy
product portfolio. The product has an extremely short shelf life; a 6 hour half-life and
hence is critical that it be used efficiently and in the most cost-effective manner. The pre-
calibration time of the product is time elapsed between when the product was dispensed
to the time it was used for the intended application.

Currently significant amount of Tc-99 was decaying at the customer site (>6hrs).
Historical data showed pre-calibration time for Tech products averaging at approx 8
hours. This represents significant product decay and lost revenue to the pharmacy
network. There was also a large degree of inconsistency in pharmacies adhering to
Pre-calibration policies with their customer base.

The goal of the project was to improve the pre-calibration time on Technetium base
products. Data collection was carried out by developing query language which helped in
presenting accurate data that gave high visibility to this project.

Through the use of the DMAIC methodology this project used tools such as VOC,
FMEA, Hypothesis test that focused primarily in improving the pre-calibration times for
Tech based products by implementation of the following:

- Revenue stream programming change to charge activity beyond the 6 hour pre-cal limit
-Customer letter from marketing addressing the goal to maximize the availability
of technetium 99m (Tc 99m) for patients, using as much as possible in procedures rather
than allowing it to decay on the shelf. These new policies would be designed to
encourage unit dose customers use a more “just in time” approach.

- Sales rep training on the Tc conservation program to help facilitate in changing
customer behavior; i.e. Move orders to later scheduled runs. To promote lower pre-
calibration times, Covidien will charge for pre-calibration activity beyond six hours,
new charges will be based on bulk Tc-99 pricing. Bulk Tc-99 will be calibrated for actual
delivery time, unless customer chooses to pay for additional activity

Annual impact estimated from this project is $3million/year. Results taken after program
launch in Oct 09 shows savings of $300K validate the projected revenue.

The final metrics for the project are as follows:

Name of Metric Baseline Goal Actual(A)-Oct09
Pre-calibration time 8.15 6.0 7.15

.

2


Define
Project Charter
Operational Excellence – Team Charter
Program Name: Improve Tech Pre-calibration Total Savings Identified ($ $3 Million/yr
value)
Team Leader: Ramesh Rajan
Team Champion: Dave Becker Product or Service Impacted Nuclear Pharmacies
Business Unit: Imaging Solutions MBB:
Start Date: April 2009 Target Completion Date: October 2009
Element Description Team Charter
1. Process: The process in which the The pharmacy network holds significant improvement opportunities
opportunity exists. in reducing length of pre-calibration time on technetium based unit
dose products and calibrating bulk doses at their delivery time.
2. Problem Describe the problem that needs Currently significant amount of Technetium 99 is decaying at the
Description: to be solved, or the opportunity customer site which results in product waste and lost revenue.
to be addressed. Global moly shortage severely impacts product availability.
3. Objective: What improvement is targeted? Reduction in Tech pre-calibration time would yield significant cost
reduction to the pharmacy business. In addition it will improve
product availability and increase patient access to Tc99 products.
Saved Technetium could be sold at favorable price to a customer.
4. Metrics: What are the measurements Name of Baseline Goal Entitlement* Units of
that quantify program progress Metric Measure
and success? Precalibration 8.15 6.0 Hours
*W hat is the bes t the process is time
expec ted to pro duc e?

5. Business Results: What is the improvement in Cost Cost WIP/ Cash Labor Inc.
business performance? Reduction Avoidance Inventory Flow Savings Sales
Please list any other Reduction
improvements on a separate X X
sheet as needed.
6. Program Scope: Which parts of our business Included Excluded
processes will be considered? The project will focus on all All other products
Which customer segments, Technetium based products
organizations, geographies, and which represent 80% of a
timeframe? customer product portfolio.

7. Team Members: Names and roles of team Ramesh Rajan, Dave Becker ,Jeanne Landers, Terese Lafeber,
members Carolyn Samra, Andy Farrow, Brian Courtney, Pharmacy Regional
Managers.

8. Benefit to External Who are the final customers, Reduction in pre-calibration time will reduce cost, improve product
Customers: what are their most critical availability to external customer and help mitigate the global moly
requirements/measurements, shortage issue. In addition it will allow greater patient access to the
and what benefits do we expect product.
to deliver to them?
8. Schedule: Give the key milestones and Key Project Dates
dates. Project Start April 2009
Define Complete May 2009
Measure Complete July 2009
Analyze Complete August 2009
Improve Complete September 2009
Control Complete October 2009
9. Budget: What financial resources are $5000 for TRON programming.
required for the team?

10. Support Required: Do you anticipate the need for IS programming, TRON user training, customer communications.
any special capabilities,
hardware, trials, etc.?

3

SIPOC Map
A SIPOC diagram was generated to provide a high level view of the Tech pre-calibration
process. This tool helped the team to understand important inputs and outputs to the
process.

SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Pharmacy receives customer
Customer(Hospital, Standing, Demand order for Tech dose with Customer-Hospital,
Presciption
Independent) Orders,TRON requested delivery and Independent user
calibration time

Dispense dose with activity
Pharmacist ,Technician Customer Order Dispensed dose Customer-Hospital
related to calibration time

Tech dose is ship confirmed
Pharmacy Bill of Lading, TRON Shipconfirmed Dose Courier
and taken for delivery

Dose is delivered to customer
Pharmacy Driver , Bill of Lading Delivered dose Customer-Hospital
at requested delivery time

Pharmacy bills customer for
Pharmacy Dose charges Customer Invoice Customer
dose includes freight charge.

Customer(Hospital, Pharmacy collects sales
Customer Invoice Sales Revenue Pharmacy
Independent) revenue from dose sale

Voice of the Customer/Business
The team also undertook a brainstorming exercise to come up with key customer
requirements. This “Voice of Customer” exercise showed the key outputs for the
project .These outputs influence the end customer (i.e. hospitals etc) in maintaining
reliable and quality supply. At the same time they also affect the pharmacies which are an
internal customer as it will help in reducing product decay and capture lost revenue due
to excessive pre-calibration.

Reduce Tc Pre- Limit Precalibratiion time compared to current practice to save Tech waste
Mimimize bulk dose waste by shrinking calibration limits
calibration Maintain accurate delivery time in TRON

Maintain ontime supply of Tech product to customer
Voice of the On Time Delivery Need more Technetium due to global "Moly" shortage

Customer Minimize product shortage

Develop efficient production schedule at pharmacy
Efficient Maintain efficient delivery routing for customer profile

4


Project Y’s (KPOV’s)
At the end of the Define Phase the team decided to focus on reducing the pre-calibration
time on Technetium products as the key Output (Big Y). This would be achieved while
still meeting product demand and delivery expectations.

Key Process Output Variable
• Reduce Precalibration time on Technetium based products

Other Important Factors
• Maintain product supply as per customer demand
• Meet customer delivery schedules

5


Measure
Process Map
A flowchart was developed to show the sequence and flow in the pre-calibration process.
Using this, the teams were able to breakdown and understand the intermediate steps and
determine inputs and outputs for each major step.
Process Flow Map for Tc 99 Precalibration

Pharmacy receives Customer
Calibration time, Standing/Demand Order for Tech
Delivery time dose
Pharmacist
enters order in
TRON and
generates
prescription

Dispense Dose with activity related Check
to calibration time Order

Is dose matching with BOL
NO

YES

Tech dose is ship confirmed and
taken for delivery

Dose delivery to customer at
requested delivery and calibration
time

Pharmacy bills customer and
collects sales revenue for dose sale
Pharmacy
Invoicing
$$
Pharmacy adds new customer ,
negotiates existing customer
contracts, communicates any
change in policy or contract

6

Cause and Effects Matrix
In order to prioritize the input variables affecting the output requiring improvement, the
team used a Cause and Effect (C&E) matrix. A Pareto was also done on the top raking
critical inputs from the C&E with a cut-off of 200. This tool helped to focus on the few
critical inputs which affect the output.
Cause and Effect
Matrix
Rating of Importance to
9 10 8 9
Customer
1 2 3 4

Requested Activity at calibration

Availability of Tech products
On Time Deliveries

Drops per Delivery
time
Total
Process Step Process Input
Calibration,delivery time,
Pharmacy receives
1 calibration policy,Customer 9 9 3 9 276
customer order
communication
Pharmacy negotiates
Calibration policy, Customer
6 existing contracts, 3 9 9 9 270
contract, Communication
communicates changes
Dose Dispensed with
Customer Order,TRON,
2 activity related to 3 9 3 9 222
Calibration,Dely time
calibration time
Tech dose ship confirmed
3 Dispensed dose, BOL 9 9 3 0 195
and ready for delivery
Dose delivered to customer
4 at requested delivery and Dose, BOL, Driver 9 9 3 0 195
calibration time
Pharmacy bills customer
5 and collects revenue from Sales Invoice, Freight Bill 1 9 9 1 180
dose sale
0
0
306

540

240

252

Total
Lower Spec
Target
Upper Spec

7


Pareto of C&E matrix

C &E Pareto Analysis
1400
100
1200
1000
80

Percent
Count

800 60
600
40
400
200 20
0 0
Process Inputs
on n e L r il l
i io tim O ve tB
at at ,B ri h
ic ic el
y
se
D ig
un un ,D do
L, re
m
m m
on d BO ,F
co om r at i se e, ic
e
er ,C b en os vo
m ct ali i sp D In
to ra ,C D
us nt N les
,C co R O Sa
cy er r ,T
oli m
de
n
p
u sto r
O
ti o ,C r
ra cy me
li b li to
ca po us
e, ion C
tim at
y br
v er ali
eli C
d
n,
ti o
ra
lib
Ca

FMEA
The FMEA focused on specific process failures that would affect the Tech pre-calibration
process and which would cause product decay and lost revenue. A RPN cut-off of 300
was established by the team for taking the critical inputs coming out of the FMEA into
the Analyze phase.

8

Improve Tech Prepared by: Ramesh
Process or Product Name:
Precalibration Rajan
Responsible: Ramesh Rajan FMEA Date (Orig) _September 29th, 2009_______

S O D R
Potential Failure Potential Failure
Process Step Input E Potential Causes C Current Controls E P
Mode Effects
V C T N

How Severe is the

How well can you
effect to the

detect cause or
How often does
cause or FM
cusotmer?

occur?

FM?
Step of the process Input under investigation? In what ways does What is the impact What causes the Key Input to go What are the existing
under investigation the Key Input go on the Key Output wrong? controls and procedures
wrong? Variables (Customer (inspection and test) that
Requirements) or prevent either the cause or
internal the Failure Mode?
requirements? Should include an SOP
number.
Pharmacy receives Excessive Product decay , Lost
TRON 8 Lack of limits on calibration time 7 None 8 448
customer order precalibration revenue
Dose dispensed with
Inaccurate delivery Customer Delivery
activity related to Expected Delivery time Product Decay 7 Customer Behaviour 8 7 392
time schedule
calibration time
Pharmacy negotiates
Miscommunicaiton Lost revenue due to
existing contracts, Customer Contract, Lack of attention to true need, Customer Communication
or lack of product decay, 8 8 6 384
communicates Calibration policy overemphasis on safety insurance by Sales reps
standardized policy excess inventory
changes
Pharmacy receives Excessive Historical customer behaviour,
Calibration time Product Decay 9 8 Customer Communication 5 360
customer order precalibration resistant to change
Lost revenue due to
Customer Contract, No adherence to Customer demand, variation in Customer Communication
product decay, 8 7 6 336
Calibration policy policy Tech needs by Sales reps
excess inventory
Pharmacy receives Excessive Unfavourable product Lack of standardized
Calibration time 9 7 Contract, Calibration policy 5 315
customer order precalibration margin policy/contract terms
Inaccurate delivery Lack of foresight, Product Delivery time loaded in
Expected Delivery time Product Decay 7 8 4 224
time Insurance TRON
Pharmacy receives Incorrect activity Product decay, loss No activity limits in TRON, wrong
TRON 6 6 TRON checks 2 72
customer order dispensed of revenue order entry

0
0

Pareto of FMEA

Pareto of FMEA RPN
2500 100
2000 80

Percent
Count

1500 60
1000 40
500 20
0 0
Potential Failure Mode n e ic y icy er
t io t im ol l th
ra y p po O
a lib er d to
ec liv ize
de rd ce
pr da en
iv
e
a te n er
ss ur ta h
ce c fs ad
Ex ac o
No
In k
lac
or
n
it o
n ic a
u
m
o m
isc
M
Count 1123 616 384 336 72
Percent 44.4 24.3 15.2 13.3 2.8
Cum % 44.4 68.7 83.9 97.2 100.0

The key inputs from the FMEA were Calibration time, Delivery time, Customer contracts
and TRON.

9

Gage R&R
Data collection for the Measure phase was obtained from queries generated from the
TRON system A Gage R&R study was then conducted to test the precision of the
measurement system and this was done with the help of 2 operators on the critical metric;
Average pre-calibration time.

A Gage R&R review showed the variation due to repeatability and reproducibility to be
at 3% and part-to part variation at 99% which showed the measurement system was very
accurate.

Gage R&R for Over 6 hr precalibration time

Gage R&R Study - ANOVA Method

Two-Way ANOVA Table with Interaction

Source DF SS MS F P
Sample 34 95.0457 2.79546 3007.40 0.000
Operator 1 0.0037 0.00370 3.98 0.054
Sample * Operator 34 0.0316 0.00093 * *
Repeatability 70 0.0000 0.00000
Total 139 95.0810

Alpha to remove interaction term = 0.25

Gage R&R

%Contribution
Source VarComp (of VarComp)
Total Gage R&R 0.000504 0.07
Repeatability 0.000000 0.00
Reproducibility 0.000504 0.07
Operator 0.000040 0.01
Operator*Sample 0.000465 0.07
Part-To-Part 0.698633 99.93
Total Variation 0.699137 100.00

Study Var %Study Var
Source StdDev (SD) (6 * SD) (%SV)
Total Gage R&R 0.022457 0.13474 2.69
Repeatability 0.000000 0.00000 0.00
Reproducibility 0.022457 0.13474 2.69
Operator 0.006288 0.03773 0.75
Operator*Sample 0.021558 0.12935 2.58
Part-To-Part 0.835843 5.01506 99.96
Total Variation 0.836144 5.01687 100.00

Number of Distinct Categories = 52

10

Gage R&R Study
Reported by :
G age name: Tolerance:
D ate of study : M isc:

Components of Variation Over 6 hr precalibration time by Sample
100 % Contribution 4.5
% Study Var
3.0
Percent

1.5
50
a ta ll e m n o d us d a s n er it le rg l le n a s a es is mi rd o i a ok h d w co is ul t e o re
on n svi he st o ag la n b oo all yto nv tr o da u sv i st o n s in d e l ph i a f o nd ph r o rg la n na c s ou Pa e led ar
i
t o tla l t le o i c e m w D Da De De er ri is b ick ou Ka a L ng em M M il r la de eb s buort agi a n t L St t P To sb
A l A Be t h B Ch lev o lo es t u d a H H om s A M O i la in it t P S F r S S e
Be C C Cr i lk
0 La H L Lo Ph P P n W
Ft Sa
Gage R&R Repeat Reprod Part-to-Part
Sample
R Chart by Operator
Over 6 hr precalibration time by Operator
Bernard Ramesh
0.5 4.5
Sample Range

_ 3.0
0.0 LCL=0
UCL=0
R=0
1.5

-0.5 Bernard Ramesh
Operator
Xbar Chart by Operator
Bernard Ramesh Operator * Sample Interaction
4.5
4.5
Operator

Average
Sample Mean

3.0 Bernard
3.0 Ramesh
_
_ 1.5
LCL=2.146
UCL=2.146
X=2.146
a ta l le m n o d us d a s n er it l e rg l l e n a s a es is m ir d o ia ok h d w co is u l te o re
1.5 o n n svi he sto ag la n b ooally ton v t roda u svi to ns indel p hi a fo ndphr o rg la nna cis ouP a e leda r
to t l a t le o ic e mw D a e e r isb ck s a L g m M il la e b bur t gi n L t P o b
l
Al A Be th B C hevo loes t D D D dea r i HiHo u K a AnM e MO rlad inei tts PoS a r a St S St Tk es
Be Cl C Cr u ms i F il
La H Lo L o Ph P P n W
Ft Sa

Sample

Data Normality
Data was collected on average pre- time calibration by pharmacy for June09 and it
showed it was normal.

Normality Test for
Normal
99
Mean 8.151
StDev 0.8384
95 N 35
AD 0.180
90
P-Value 0.910
80
70
Percent

60
50
40
30
20

10

5

1
6 7 8 9 10
Average precal time June

11


Process Capability
Process Capability Sixpack of Average precal time June
I Chart Capability Histogram
LSL USL
UCL=10.669
S pecifications
Individual Value

10.0
_ LS L 0
X=8.151 USL 6
7.5

LCL=5.633
5.0
1 4 7 10 13 16 19 22 25 28 31 34 0.0 1.5 3.0 4.5 6.0 7.5 9.0

Moving Range Chart Normal Prob Plot
UCL=3.093
A D : 0.180, P : 0.910
3.0
Moving Range

1.5
__
MR=0.947

0.0 LCL=0
1 4 7 10 13 16 19 22 25 28 31 34 5.0 7.5 10.0

Last 25 Observations Capability Plot
Within Within O v erall
9
S tD ev 0.839367 S tDev 0.838408
Values

8
Cp 1.19 Pp 1.19
O v erall
C pk -0.85 P pk -0.86
7 C pm *
S pecs
15 20 25 30 35
Observation

For the process capability calculations, the lower Specification limit was chosen as 0
hours and the upper limit was taken at 6 hours. The Cpk value of - 0.85 shows that the
process capability is less than favorable and there is vast scope for improvement.

12


Data Collection
Data collection for the Measure phase was collected from TRON queries that measured
the average pre-calibration time across the pharmacy network for June09. This was taken
as the baseline.

For this project the Average pre-calibration time is taken as the (Y). The pre-calibration
time is defined as the time elapsed between the expected delivery time of the product and
its calibration time.

13


14


Baseline Metrics
From the data collected in June09 the report showed the following baselines

Baseline Measurements
Jun-09

Pharmacy Average Time over Delivery time( Bulks) Average Precalibration time June

Ft Lauderdale 5.12 7.87
Crestwood 5.00 9.60
Kansas 2.00 7.95
Chicago 3.00 7.87
St Louis 6.25 6.98
Orlando 3.00 8.98
St Pete 3.00 7.87
Miami 4.00 9.04
Memphis 0.00 10.00
Atlanta 5.00 8.81
Boston 3.00 6.62
Wilkesbarre 3.00 7.12
Milford 3.00 7.41
Pinebrook 3.00 7.21
Hicksville 3.00 8.11
Hariisburg 4.00 7.80
Bethlehem 4.00 7.43
Altoona 4.25 7.38
Philadephia 3.00 8.10
Dallas 4.00 9.20
Los Angeles 3.00 7.52
Loma Linda 2.00 8.24
San Francisco 3.00 7.68
St Paul 3.00 9.50
Portland 4.00 8.34
Denver 3.00 8.12
Houston 3.00 8.46
Saginaw 2.15 7.62
Toledo 3.00 8.85
Colombus 3.00 6.65
Dayton 2.00 8.56
Detroit 3.00 8.66
Beltsville 3.00 8.67
Cleveland 3.00 9.25
Pittsburgh 3.00 7.81

Average 3.25 8.15

15


Savings Summary
Tc-99 Conservation Plan
Annual Summary Impact

Bulk Precal
Beltsville 201,617 24,697
Cleveland 182,709 21,821
Hicksville 136,829 47,663
Pinebrook 165,864 6,599
Dallas 141,738 39,835
Los Angeles 142,937 4,037
St Pete 148,092 9,581
Denver 124,645 4,459
Orlando 107,840 13,175
Pittsburgh 81,113 52,328
Crestwood 107,076 34,832
St Paul 95,212 12,132
Boston 113,921 4,489
Harriburg 80,833 5,568
Detroit 73,360 3,802
Chicago 66,786 5,666
Milford 63,819 776
Dayton 38,784 6,496
Altoona 71,915 15,905
Wilkes Barre 60,352 3,273
St Louis 53,632 8,019
Bethlehem 63,835 4,635
Houston 25,771 2,203
Ft Lauderdale 54,235 5,967
Colombus 33,115 14,977
Philadelphia 45,994 5,390
Atlanta 40,616 5,900
Portland 21,396 3,756
San Francisco 27,539 4,327
toledo 22,373 5,967
Kansas City 20,967 6,968
Saginaw 23,145 1,298
Miami 29,064 7,046
Loma Linda 10,599 11,210
Cinci 9,582 1,516
Memphis - 5,151
$2,687,299 $411,461

Bulk = All doses sold as Bulk calibrated at expected delivery time

Precal = All unit doses which exceed a 6 hour window between expected delivery and calibration time

16


Analyze

Basic Statistics
Basic statistics were gathered on the key output to determine stability and shape.
Normality test was also done on the key output which showed data as a normal curve.

Summary for Average precal time June
A nderson-D arling N ormality Test
A -S quared 0.18
P -V alue 0.910

M ean 8.1511
S tDev 0.8384
V ariance 0.7029
S kew ness 0.223511
Kurtosis -0.483646
N 35

M inimum 6.6209
1st Q uartile 7.5226
M edian 8.0986
3rd Q uartile 8.8137
7 8 9 10 M aximum 10.0000
95% C onfidence Interv al for M ean
7.8631 8.4391
95% C onfidence Interv al for M edian
7.8038 8.5280
95% C onfidence Interv al for S tDev
9 5 % C onfidence Inter vals
0.6782 1.0985
Mean

Median

7.8 8.0 8.2 8.4 8.6

The Mean of the data was 8.15 hours while the median is 8.09 which indicate both are
very close to each other.

Descriptive Statistics: Average precal time June

Variable N N* Mean SE Mean StDev Minimum Q1 Median
Average precal time June 35 0 8.151 0.142 0.838 6.621 7.523 8.099

Variable Q3 Maximum
Average precal time June 8.814 10.000

17


Graphical Analysis
Box plot of Pre-calibration time by pharmacy showed there exists a difference
between means of data between pharmacies of different size. The pre-
calibration time variation among pharmacies showed there was a lack of
standardized policy related to pre-calibration time. The frequency graph shows
historically there have been excessive pre-calibration times practiced at
multiple sites with times extending as far as midnight which accounts for
substantial product decay and lost revenue.

Boxplot of Average Precalibration time

10.0

9.5
Average Precalibration time

9.0

8.5

8.0

7.5

7.0

6.5
Large Medium Small
Pharmacy Size

18

Graph of Calibration time V/s Frequency
90

80

70

60
Frequency

50

40

30

20

10

0
10:30:00 12:30:00 13:00:00 13:15:00 13:30:00 13:45:00 14:45:00 16:00:00 23:59:00
Calibration time

Hypothesis Testing
Regression
A Regression analysis was performed with the Key input variables and the Key
output variable. The Calibration time and Expected delivery time are the critical
Project Input Variable (KPIV) with the highest correlation to Average Pre-
calibration time and is the root cause for pharmacies having excessive pre-
calibration time. In addition some of the other critical inputs such as TRON and
customer contracts were also taken into consideration for the Improve phase. A
another regression equation was also tested to see correlation between Value of
Tech waste due to excessive pre-calibration time and the Pre-calibration time
and there exists a high degree of correlation between them.

Regression Analysis: Average over 6 h versus Activity, ASP,

The regression equation is
Average over 6 hour Precal = - 4.99 - 0.00775 Activity - 0.31 ASP
+ 20.6 Calibration time - 19.3 Delivery time

Predictor Coef SE Coef T P
Constant -4.9892 0.4866 -10.25 0.000
Activity -0.007749 0.006703 -1.16 0.257
ASP -0.314 1.081 -0.29 0.774
Calibration time 20.556 1.088 18.88 0.000
Delivery time -19.292 1.504 -12.83 0.000

S = 0.219942 R-Sq = 95.2% R-Sq(adj) = 94.5%

19

Analysis of Variance

Source DF SS MS F P
Regression 4 28.5317 7.1329 147.45 0.000
Residual Error 30 1.4512 0.0484
Total 34 29.9829

Source DF Seq SS
Activity 1 0.1078
ASP 1 0.0673
Calibration time 1 20.3951
Delivery time 1 7.9615

Regression Analysis: Tech value o versus Average over, Activity, ASP

The regression equation is
Tech value over 6 hour precal = - 864 + 296 Average over 6 hour Precal
+ 79.8 Activity - 2450 ASP

Predictor Coef SE Coef T P
Constant -864 1772 -0.49 0.629
Average over 6 hour Precal 296.3 143.4 2.07 0.048
Activity 79.83 25.16 3.17 0.004
ASP -2450 5589 -0.44 0.664

S = 780.531 R-Sq = 32.4% R-Sq(adj) = 25.4%

Analysis of Variance

Source DF SS MS F P
Regression 3 8465699 2821900 4.63 0.009
Residual Error 29 17667618 609228
Total 32 26133318

T-Test- A 2 sample T test was also conducted to test the difference between Average
Pre-calibration time in June before the project was implemented and the time in October
after implementation. The analysis showed that the pre-calibration time dropped by an
average 1 hour with the project implementation.

Two-Sample T-Test and CI: Average precal time June, Average Precal time Oct

Two-sample T for Average precal time June vs Average Precal time Oct

N Mean StDev SE Mean

20

Average precal time June 35 8.151 0.838 0.14
Average Precal time Oct 35 7.151 0.838 0.14

Difference = mu (Average precal time June) - mu (Average Precal time Oct)
Estimate for difference: 1.000
95% CI for difference: (0.600, 1.400)
T-Test of difference = 0 (vs not =): T-Value = 4.99 P-Value = 0.000 DF = 68
Both use Pooled StDev = 0.8384

Results
Since the p-value is less than 0.05 we reject the null hypothesis which was taken as there
was no difference between the 2 populations and conclude that there is a positive
difference between the pre-calibration time measured before the project was implemented
to the time measured after which means the time has decreased since project
implementation and this is a favorable impact resulting from the project.

Project X’s
Key input variables coming out of the Analyze were

Calibration time – This is the time at which the requested dose is used for its intended
application. The pharmacist calculates activity that needs to be filled based on customer
requested calibration time.
Delivery time – This is the time when the customer requests delivery of the product at
it’s location.
Customer Contract – Contract is a binding document between Covidien and the
customer which contains information related to pricing, dose limits, calibration times and
freight policy. All negotiated contracts define the long-term commitment between
Covidien and its customers.
TRON – The system used by the pharmacy network to carry out all operations from
order processing to delivery of finished product. Since it’s a central processing system for
the network, it has a significant impact on operations related to Technetium products.

21


.

Improve
Solutions Identified

Critical inputs from the Analyze phase was taken into consideration for improvement in
this phase and the “Tc Conservation program” which was launched across the network
captures all the improvements which were implemented in the field to achieve the desired
objective of reducing pre-calibration time and capturing lost revenue due to excessive
pre-calibration time.

Current issues identified with Tc-99m utilization

Significant amount of Tc-99 decaying at the customer site (~6hrs)
- 50% of all doses dispensed with greater than 6 hours time
- much bulk-tech is ordered with pre-cal for 12:00 am
- In past, customers believed “Tc-99 is cheap”, the agent is expensive
- customers like security of receiving daily doses early
- past delivery issues may drive behavior for this “insurance” time
- lack of standardized calibration policy and no pre-calibration limits in TRON

Tech Conservation - Opportunity

Valuing the saved material at current ASP -> Huge $$$’s
• Allows greater patient access to Tc-99m or charge for overage
• With generator shortages now and in FY10, we need fast action

22

• Excellent time to begin changing market behavior
• Next Steps
- Meeting held with IS requesting TRON changes (80 hrs)
- Roll out with Sales management on 8/10/09
- Rep and pharmacy web-training (8/28 & 8/31)
- Customer letter from marketing distributed on 9/1.
- Reps have customer discussions in September
- Target Go Live targeted for 9/26/09 (first day of FY10)

Customer Letter – Summary of Program:

Customer letter will be sent on 9/01/09, which will explain….

• Ongoing concern over global Moly supply
• Significant investment required to improve availability
• Our goal to increase patient access to Tc-99m based products
• Covidien committed to servicing maximum number of patients
• New conservation programs beginning on Sept. 26th, 2009(est.)
• To promote lower pre-calibration times, Covidien will charge for pre-calibration
activity beyond six hours
• New charges will be based on bulk Tc-99 pricing
• Bulk Tc-99 will be calibrated for actual delivery time, unless customer chooses to pay
for additional activity

Example #1 - Limit pre-calibration to 6 hours (expected delivery to cal time)

Example: Customer orders 30 mCi of Sestamibi calibrated for
1300, but wants it delivered with an expected delivery time of
0600. This would trigger a charge up, using the R005A0 code and
decay factor to charge them the customer’s bulk Tc-99m charge
(say $0.31/mci). We would charge the customer for the hours
beyond the 6 hr limit. In this case, it is one hour, so we would

23

charge the customer $0.31 x (30mCi/.891)-30 mCi = $1.14 using a
new item code R005PC – TC-99M PRE-CAL OVER TIME
LIMIT which will be attached to the dose for reimbursement

Bulk tech will no longer be calibrated past delivery times.

Customer Impact Analysis - example
This is a calculation of the new cost to each customer if they do not change.
Example from the month of June:
Customer Name Tech Value over recommended qty Tech value over 6 hrs pre-cal at ASP
ALBERT EINSTEIN MED CTR Total $0.00 $1,826.52
ATLANTIC MEDICAL IMAGING,GALLOWAY,NJ Total $0.00 $31.39
BOOTH RADIOLOGY Total $0.00 $98.36
CAPE MAY COURT HOUSE AMI Total $0.00 $23.97
CARDIAC DIAGNOSTIC CENTER,LEWES,DE Total $0.00 $0.96
CARDIAC DIAGNOSTIC CENTER,MIDDLETOWN,DE Total $0.00 $32.96
CARDIAC DIAGNOSTIC CENTER,WILMINGTON,DE Total $0.00 $2.04
CARDIOLOGY MEDICAL ASSOC,PHILADELPHIA,PA Total $0.00 $45.27
CARDIOVASCULAR SOLUTIONS,PHILADELPHIA,PA Total $0.00 $116.50
CHERRY HILL CARDIAC DIAGNOSTIC Total $0.00 $111.73
COMM MED CTR Total $134.85 $473.56
DOVER CDC,DOVER,DE Total $1.55 $1.15
EINSTEIN CTR ONE RADIOLOGY Total $1.55 $84.30
KIMBALL MEDICAL CENTER,LAKEWOOD,NJ Total $0.00 $1,690.34
LINWOOD AMI Total $0.00 $46.51
METHODIST HOSPITAL,PHILADELPHIA,PA Total $0.00 $313.70
MOSS REHAB/EINSTEIN AT ELKINS PARK Total $0.00 $371.03
NORTH WILMINGTON CDC Total $0.00 $2.04
PAMI Total $0.00 $59.12
RADIOLOGY ASSOCIATES,WILMINGTON,DE Total $0.00 $11.92
SOUTH JERSEY HEART GROUP,SEWELL,NJ Total $0.00 $1.97
THOMAS JEFFERSON U HOSP Total $0.00 $185.50
UNION HOSP OF CECIL CNTY Total $0.00 $1,343.71
WACHSPRESS & SHATKN CARDIO, VINELAND, NJ Total $0.00 $27.97
24
Grand Total $139.50 $7,013.32


25


Sales Rep Actions & Timeline:
• Study the customer letter and understand the key points
• Review the customer impact analysis with Regional manager
• Work with pharmacy manager
• Develop preliminary plan using customer knowledge to minimize customer
impact
• Shift doses to later deliveries, while minimizing impact on delivery costs
• Visit with customers
• Provide the customer a choice to remain with the status quo or shift schedule
• Finalize a plan for each customer with your pharmacy
• Understand changes to invoices

• Corporate will add pricing for bulk tech at rep guideline for customers
not having this item code currently on their contract

8/28 or 8/31 Wk of 8/31 Wk of 9/7 Wk of 9/14 Wk of 9/21 Sat. 9/26

- Meet with customers
Attend - Meet with customers Finalize plan with -Target Go Live
Web- Meet with Reg. Mgr pharmacy
training Meet with pharmacy
team
Review customers
Develop plan

26


Sales Rep talk track:
• Reference the customer letter
• Explain that Tc-99m shortage will continue far into 2010
• Our focus is on increasing patient access to Tc-99m products
• Asked your customers to use Tc-99m more efficiently
• Explain how doses can be delivered on later runs
If they purchase bulk tech, explain new pre-calibration policy
Give them their options for:
1 Unit doses with excess (> 6 hours) of calibration
a.) Move doses to later scheduled runs
b.) Pay for extra activity
2 Bulk Tc-99m orders
a.) Move orders to later scheduled runs
b.) Reduce sizes of bulk Tc-99m orders
c.) Pay for extra activity
d.) Eliminate bulk Tc-99m orders and utilize STAT unit dose
orders where needed.
• It’s the customers choice
• Use your Tools -> Moly calendar, delivery schedules, customer impact
analysis, Moly shortage update letter

Pharmacy Managers Actions:
• Study the customer letter and understand the key points
• Review the customer impact analysis with your sales team
• Develop a preliminary plan to minimize customer impact
• Ensure you are capturing accurate expected delivery times in TRON for
all customer orders.
• Consider shifts in delivery schedules without increasing costs
• Utilize existing scheduled runs and routes
• If freight costs exceed Tc-99m savings, exceptions approved by VP Ops, VP
of Sales, and Marketing through email.
• Make certain to capture freight revenue for these exception accounts
• Understand changes to TRON and invoices
• Finalize a plan for each customer
• On Go Live date, begin calibrating all bulk tech at delivery time

• Note that corporate will add pricing for bulk tech at rep guideline for
customers not having this item code currently on their contract

27


TRON Invoice change?

Invoices will show the added Tc-99 charges similar to I-131 caps.

Invoices will reflect any necessary surcharges on the line following the applicable dose,
assigned to the same prescription number for reporting ease.

The following product codes and descriptions will appear to indicate the surcharge type(s):

R005PC - TC-99M SODIUM PERTECHNETATE ACTIVITY OVER PRE-CALIBRATION
TIME LIMIT (PER MCI)

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Control
The updated process flow shows the changes made to the TRON pharmacy
system to generate invoices capturing the surcharge for products exceeding the
6 hour pre-calibration limit.
Updated Process Map

Updated Process Flow Map for Tc 99 Precalibration

Pharmacy receives Customer Standing /
Calibration time, Demand Order for Tech dose
Delivery time Pharmacist
enters order in
TRON and
generates
prescription

Dispense Dose with activity related to Check
calibration time Order

Is dose matching with BOL
NO

YES

Tech dose is ship confirmed

Is unit dose over 6 hour pre - YES
calibration?Bulk dose over delivery
time?
Excess
surcharge
billed to
NO
customer
invoice
Dose delivery to customer at requested
delivery and calibration time

Pharmacy
Invoicing
$$
Pharmacy bills customer and collects sales
revenue for dose sale

Exception sent to
Pricing for
adjustment and
surcharge
Pharmacy adds new customer , negotiates adjusted to $0
existing customer contracts , communicates
any change in policy or contract
Exception raised if
freight revenue
exceeds Tech
Customer changes delivery schedule , savings
adjusts calibration times to adhere to Tech
Conservation program

29

Improve Tech Pre Calibration Project Book

Improve Tech Pre Calibration Project Book

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