SETTING INVENTORY LEVELS FOR A CENTRALLY LOCATED BLOOD BANK
OF A METROPOLIS - A SIMULATION, APPROACH
Shoukath Ali, K. and Ramaswamy, N.
Department of Mechanical Engineering
Indian Institute of Technology, Bombay’ 400 076, INDIA.
Abstract
Blood is a scarce and non-synthesisable resource which .would
perish eventually when kept under artificial storage. The major
problem encountered in blood bank administration is that of making
decisions on policies. for. setting up inventory levels to meet
the needs as soon.as.they.arise and simultaneously keep the expiry
of..blood on the shelf..within reasonable limits. The ‘selection
of such policies is greatly influenced. by,.demand,. daily transfus-
ion,, shortages, outdating and shortage-outdate rates.
A. true mathematical inventory modelling is nearer to impossi-
bility due to the complexity of..interaction between. these vari-
ables and the stochastic. nature of. the. processes involved.
Early works have shown that there exists a universal rela-
tionship between these variables that holds for all. blood types.
Statistical methods will yield the inventory levels to be. set
up on the jbasis of .these variables.. But this warrants cumbersome
analysis of extensive data collected.over a minimum period. of
12 months. The volume of work involved makes this method unwieldy.
Simulation tending towards a.systems approach appears to be more
effective .and -efficient..in. the analysis. of such.. inventory
situations. The objective. of this study is to investigate and
analyse with the use.of computer. simulation, the relationship
between inventory levels, mean demand and shortage-outdate rates
for all Rh system blood types in a centrally located blood bank
of.a..metropolis like .Bombay. Environmental study of present day
management of independant. blood banks.has also been performed.
Introduction
The practice of blood transfusion and storage methods have undergone
tremendous transformations during the last few years. The bulk of the litera-
ture produced so far discussing and suggesting management policies for blood
banks has nearly’ become of no practical use, thanks to the ‘sophistication
and ‘consequent complexity added to~ the whole system. Despite continued
research on cryogenic’ preservation of whole blood and : blood . components
Page 1
Page 2 System Dynamics '91
no practical solutions have come out of the cryocooled vaults of the labora-
tories. A remarkable achievement in this side is the enhancement of the
life of whole blood from the earlier 21 days to 35 days using Citrate-
Phosphate-Dextrose-Adenine(CPDA) instead of Acid-Citrate-Dextrose(ACD)
solutions. The statistical effects of varying life span of whole blood over
a wide range have been studied by Pegels (1978) using simulation approach.
In Operations Research the very idea of perishability of inventory
items was sparked off: by ‘blood bank ‘management’ problems. Researchers
like Millard (1960), Elston and Pickrell (1963), Jennings (1973), Brodheim
et.al. (1975), Cohen and Pierskella (1975) and Costas Sapountzis (1984,1989)
have presented extensive mathematical analyses. Nonetheless. the actual
problem seems to be too complex to be discussed by single mathematical
models.
One of the major drawbacks of the mathematical models is lack of
emphasis on the information needs for the blood bank inventory control.
Consequently the policies evolved treat blood. as a mere commercial perish-
able product.
During the data collection phase of the present study, this inadequacy
was observed by the authors. The finest example is that of the concept
of ordering of inventory items. No medical professional could conceive of
the idea of 'ordering' for blood as and when needed except for the requests
for emergency shipments from other hospitals. Even in such cases lack of
a coordinated information system quite often marr the efficient operation
of the bank. Outdating which is a key parameter considered in most models
seems to be of no importance in a metropolis like Bombay where short.age
is the one and only problem. It was also noticed tiat a majority of the
hospital blood banks failed in’ maintaining records of occurences of shortage.
This naturally leads to wrong predictions of future demand.
Jennings (1969) has neatly- pointed out the information needs and the
Technical Manual of American Association of Blood Banks (1977) has presented
an elaborate treatise on the standards to be maintained by the blood banks,
in respect of records, tests, procedures etc.
Catassi and Peterson (1966) were the first to bring out a proposal
for an information based management system for blood banks. Later Jennings
(1968), Stewart and Stewart (1968), Hirsch et.al.(1970) and Brodhein (1978)
proposed various computer based systems for the surveillance of inventory
control. .
Computer simulation study of the management policies for determining
optimum inventory levels was done by Elston and Pickrel (1963) using UNIVAC
1105. They considered a class of ordering policies assuming an arbitrary
25:4 ratio of the costs of shortage to outdating. The study revealed that
following a FIFO(First-In-First-Out) policy, the average age of blood in
store could be enhanced when the, random input is doubled. Another major
work. using simulation methods was that of Cohen and Pierskella. (1975) on
management strategies, for administration of a regional blood bank. Based
on the assumption. of a relatively fixed supply of. donors, the effect of
controlling the ordering, issuing and.cross matching policies on the. systems
are studied. .They showed that. FIFO dominates. LIFO(Last-In-First-Out) over
System Dynamics '91 Page 3
a reasonable range of crossmatch release period, D. Optimal policies with
a view to minimize percentage shortages and percentage outdating of all
blood groups are suggested by Prem Vrat and Khan (1976) on the basis
of a simulation model similar to the inventory bank model proposed by
Elizer Naddor.
Systems Approach to Blood Bank Management
Jennings' whole blood inventory model (Fig. 1) encouraged researchers
to consider blood banking as a dynamic system. Flow of material (blood)
in the system is analogous to that of a. dynamic system. Studying issues
of such a system from a system-perspective results in a better understanding
of the poor system performance. This approach emphasises the connections
among the various parts that constitute a whole. The system thinking is
concerned with connectedness and wholeness (Nancy Roberts et.al. 1983).
The problem is looked upon from an integrated vantage point.
OTHER HOSPITALS
t
OTHER
DEMAND
BLOOD BANKS: UNASSIGNED [————*] ASSIGNED
DONOR SOURCE BLOOD BLOOD Po .
DEMAND
t Y +————| INVENTORY A -
RANDOM DONORS NVENTOR RELEASE ° use GE
OUTDATING OUTDATING
FIG: 1 CLASSICAL BLOOD INVENTORY MODEL
The model building process involves the following phases.
Conceptual Problem definition
System conceptualization —————__J
Model representation © ——W—____
Technical Model behaviour Refinement
4
Model evaluation
Policy analysis and model use
The modelling process uses two important schemes to highlight the
dynamics. of the system, i.e. thinking about how the quantities vary through
time and thinking about whether a substantial feedback relationship exists.
Page 4 System Dynamics '91
Simple causal-loop diagrams of the blood inventory system are shown
in Fig. 2(a) and (b).
® ®
suortace +
ia NY
BLOOD
Brood brane WeentoRe USAGE
“USAGE
INVENTORY ever
LEVEL ; |
Se mares
RATES
FIG. 2, SIMPLE CAUSAL LOOP DIAGRAMS FOR BLOOD INVENTORY
System Under Study
The present study was conducted in a major government hospital in
the metropolitan city of: Bombay.-In India. the blood transfusion services
are far from satisfactory...Studies have..shown that there is a huge gap
of about 3.5 million units per year between the need and actual availability
for transfusion. The ‘actual availability in-1990 was just 1.5 million units
as against the minimum requirements of about 5 million units. 75% of the
blood banks of the country..operate in a highly -unsatisfactory manner due
to a host of reasons - absence of well developed voluntary programmes,
lack of a unified approach and the improper rule-of-thumb management
policies, in spite of the standards and administrative guidelines set by
the Directorate General of Health Services. The blood transfusion services
are primarily confined. to metropolitan cities. Bombay city has as much
as 50 blood banks licenced by the State Food and Drug Administration (FDA)
and all these. banks. work on. donor/replacement basis and most ‘of them have
transfusion facilities for in-patients of the attached hospitals.
There are 7 hospital blood banks attached to the centre under study.
During. the year 1989-90 the total. blood requirement of Bombay city was
as much as 2 lakhs units out of which 8- 10% was supplied through this
centre.
The system model was developed, whose details are shown in Fig.
3 which reveals the complexity of the set up. The model brings out the
highly -random nature of the. .blood supply, demand usage, shortage and
outdate characteristics. The model was used for purposes of comparison
of .alternate: inventory policies of a regional blood centre. Evolution of an
effective and efficient. management policy is absolutely dependant upon the
daily monitoring .of.the inventory level and variation of this level.
System Dynamics '91 Page 5
BLOOD COLLECTION
RETURNED ENTER BLOOD
FOR REUSE INPUT DATA _& AGE
SEROLOGICAL TESTS
TYPING & LABELLING
ENTER AGE &
TEST DATA
SUITABLE
ENTER CAUSES {4 piscaro |
FOR USE
2
ENTER ISSUE
<isd> uniTs UseD ENTER AGE (0)
NUMBERS FOR COMPONENTS & INVENTORY
(0) us Seep DETAILS
©
yar ENTER AGE &
INVENTORY Pin
TA
a REQUISITIO
‘ORDER FOR ;
+
Secewte CROSS PHYSICIAN
MATCHING REQUISITION cross,
+ MATCHING
POS TPONE Ser
SURGERY ve OUTDATED
5 DURING PRESER- ISSUEUUNITS
VATION NUMBER
wo) [oiscaro | 2 :
NO <> NO
2) TSSUE TO ves
OTHER HOSPITALS
ourpateD No
RETURNED NO Gend QURING RESER-
FOR st
RECYCLING
Yes
©)
® FOR: REO BLOOD CELLS ONLY
+ RESERVED FOR A PARTICULAR “PATIENT” > *
sf CROSS MATCHED FOR TWO OR MORE PATIENTS SIMULTANEOUSLY ~
FIG. 3 SYSTEM FLOW DIAGRAM
Page 6 System Dynamics '91
Collection and Analysis of Data
The model is generally applicable to all Rh system blood types with
possible variations in the case of rarest groups, namely B Rh(negative)
and AB. Rh(negative). Data on daily collection of blood, usage and discarding
of all Rh system groups were collected’ for 12: months from January to
December. This provided the basis for the computation of probability distri-
bution of these parameters for the simulation study.
Table 1 shows the inventory details of the blood centre reduced to
monthly basis.
TABLE 1 Blood Bank Inventory Details*
Month Openiig COM ecHon Usage Discarded
; AB A B O- Total
Jan. 337 136 = 563 651 735 2085 1839 124
Feb. 459 80 389 402 446 1317 1231 49
Mar. 496 86 472 522 651 1731 1544 63
Apr. 620 93 372 323 540 1327 1320 35.
May 592 72 190 222 256 740 1060 19
Jun. 248 68 284 239 321 912 | 1034 42
Jul. 84 117... 336 426 469 1348 1051 75
Aug. 306 103... 322 355 528 1308 1383 42
Sept. 189 77 269 325 330 1001 1020 37
Oct. 133 70 257 241 333 901 845 49
Nov. 140 114 344 454 506 1411 1118 56
Dec. 377 126 467 498 708 1799 1816 105
*Units of blood (bottles) on monthly. basis.
Table 2 shows some of the operating characteristics of the blood bank
computed from the data collected.
TABLE 2 Opérating Characteristics of the Blood Bank**
Beginning inventory level = 15-units
Physician requirement > 50 units
Shipment from various sources < 15 units
Quantity received from other hospitals < 10 units
Blood collected from relatives etc < 15 units
Fraction of blood cross matched = 80-100%
Blood demand usage = 50 units
Time spent in assigned state =
Fraction of cross matched blood actually used =,
Fraction of blood outdated in store <
Fraction of blood discarded during tests
**All groups put together on average daily basis.
Quantity and age of blood in store are taken as the level variables
characterizing the state of the system at any particular time.
System Dynamics '91
Page 7
Results and Conclusions
is a Fortran-based version of DYNAMO.
mean daily demand and shortage-outdate rates. These provide means for
the calculation of desired inventory levels on the basis of shortages and
outdates.
f ro0r
a 5
>
3 sok
pr
&
= cop
e
z L
> 40 sHoRTAGe _ NO. OF OCCURENCES OF SHORTAGE
7 RAT. 4
a e NO. OF DAYS DEMANO OCCURS
9
< 20
«
ws
z
1 aT 1 i Lo i L J
° 10 20 30 «4050 60. 70 80 90 100
AVERAGE INVENTORY LEVEL ——&
100
40
20
AVERAGE DALY DEMAND —®>
FIG. 4 SHORTAGE RATE CHARACTERISTICS
sor
60;
oUuTDATE __UNITS OUTDATED
RATE UNITS USED + OUTDATED
L 1 1 1 1 J
10 20 30 40 50 60 70 80 8690 100
AVERAGE DALY DEMAND ——®>
FIG. 5 OUTOATE RATE CHARACTERISTICS
Simulation analysis was done on an IBM 360 using DYNAMO II/F_ which
Fig. 4°and Fig. 5 show the relationship between the inventory levels,
Page 8
System Dynamics '91
As
increases
the life of blood in-store increases the probability of outdating
more rapidly in the case of rare groups compared to the very
common(Fig. 6).
PROBABILITY OF
OUTDATING —»
10
1 1 |
o 5 10 15 2a
LIFE OF BLOOD IN STORE ——e
FIG.6 PROBABILITY OF OUTOATING OF BLOOD GROUPS
It was observed that except for extremely large inventory levels
practically possible, outdating was always less then 5% and shortages occur
as high as 20-25% or even higher. And due to the absence of proper recor-
ding of the shortage occurences, the simulated values are possibly on the
lower side.
The results of the study emphasize the need for an integrated approach
in blood
bank management. The following suggestions are putforth by the
authors in this regard for better performance.
1.
2.
3.
4,
5
6.
A coordinated effort with other blood banks.
Providing facilities for fractionation and pheresis in all major
banks.
Enhanced use of components instead of whole blood.
More reliable methods in the operation of surveillance centres
to reduce blood wastage which is approximately 5% now.
A computer. based system for calling blood donors from selected
panels. .
Double cross matching to. avoid return of the blood to the storage
and possible recycling of blood returned from other hospitals. »
Acknowledgements
The authors are indebted to Dr. N.B. Jaju, St. George's Hospital,
Bombay,
and Dr.
who is presently Secretary of Federation of Bombay Blood Banks
Vijaya Laxmi Ray, K.E.M. Hospital, Bombay. for their cooperation
during this study.
System Dynamics '91 Page 9
References
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Cohen and Pierskella. 1975. Management Policies for a Regional Blood Bank.
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Costas Sapountzis. 1984. Allocating Blood to Hospitals from a Centralised
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Costas Sapountzis. 1989. Allocating Blood to Hospitals. Journal of Operations
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