The of reporting and information system to

The past few decades has seen a surge in
the study and analysis relating to blood supply chain management, owing to its
criticality and a research trend. Many methodologies have been applied to find
solutions and insights that would improve the efficiency and effectiveness of
the blood supply chain. Several authors have applied integer optimization
models such as facility location, set covering, allocation, and routing to
address the optimization / design of supply chains of blood or other perishable
critical products. In addition, inventory management methods, Markov models as
well as simulation techniques have been used to handle blood banking systems.

Eric L.Peterson (1969) a computer
assistant developed a meaningful report in blood bank management by collecting
data, converting it into meaningful and processed it for further use.
Pierskella and Cohen (1972) addressed the issues of improper scheduling and
poor management will lead to wastage and shortage of blood products. They also
stated relationship between resource allocations, distribution policy, location
and capacity are the critical factors need to be addressed.

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 Bhatia and Raghuwanshi (2016) mentioned
unification of blood transfusion services to maintain the standard or
duplication of services, focus on quality of service provided, adoption of
newer technologies, strengthening of reporting and information system to
maintain the inventory will resolve the drawbacks in Indian blood supply chain
as inadequacy of blood storage centers, dominance of private sector over public
sectors, lack of proper facilities, storage & quality of services etc.

Alfonso et al., (2012)
developed a simulation model of blood collection systems for both fixed site
and mobile blood collection with walk in whole blood donors and scheduled
plasma and platelet donors which can be straightforwardly implemented with any
simulation language with numerical experiments.  Harshal and Raghavendra (2017) showed that
Thinking Process tools can be extremely powerful in constructing win – win
solutions for complex systems. The study reveals how one widely-held belief in
the blood banking world is the main reason behind the blood banks’ poor state
of affairs.   

Duan et al., (2014) proposed
a new simulation optimization (SO) framework is proposed for blood supply chain
inventory management with ABO blood group compatibility with three different
scenarios which will identify a near-optimal solution for each of these
scenarios and quantify the potential savings offered by ABO compatible
substitution. In the ABO compatible substitution scenarios, there is a clear
trend of the increased use of group O blood. Osorio et al.,
(2015) contacted a detailed review from 1960s to 2015 consist of the most
relevant papers in the blood supply chain and presented in five different
category which will give a thorough knowledge in blood supply chain.

Harshal and Raghavendra
(2015) conducted a study considering stock and life of blood products in
analyzing the performance of an ordering policy. They suggested by combining
age and stock based policy the performance will be much effective compared to
periodic reviews. Lowalekar, Harshal and Ravichandran (2011) given an optimal
level of components to be produced at a blood bank by satisfying the demand for
blood product with minimal cost.

 Erhabor
and Adias (2011) suggest blood component therapy allows several patients to
benefit from one unit of donated whole blood and also important for economic,
supply/demand reasons and to protect the national inventory at times of
national blood shortage which will in turn facilitate the optimal use of the
limited blood supply.

Lincoln C. Wood, Torsten
Reiners and Hari S. Srivastava (2016) in their paper highlight existing difficulties and
challenges to access market data where the firm lies upstream. This affects the
effectiveness of the decisions taken in the supply chain. Alternatively, they
propose incorporating the marketplace information into decisions making system
for an improved supply chain performance. They have stated that sentiment
analysis will counteract behavioural elements contributing to the Bull Whip
Effect.

Qinglin Duan, T. Warren Liao (2014) through their paper emphasise on using blood
substitution according to the ABO/Rh(D) compatibility if needed. Their research work tried different
levels for shelf life. The values were simulated and compared with base level. Their results suggested a reduction of
16% in outdates throughout the system.

Ivan Varela Rozados and
Benny Tjahjono (2014) in
their paper try to bridge the gap between 
big data analytics and Supply chain management. They developed a network linking
various operations and Supply chain levers. The authors explain
solution to various Supply chain problems using data analytic techniques. They
also recommend shifting from
standard supply chain approach to a combined approach of supply chain
management and data analytics to have greater understanding of the system and attain
higher efficiency.

Armin Jabbarzadeh, Behnam
Fahimnia and Stefan Seuring (2014)
in their research,
worked on blood supply chain network design for the case of disaster affected
zones. They extensively focussed on two aspects, namely, location and
allocation decisions. The decisions
were made using factors like injury to death ratio, hospital admission rate, blood
transfusion rate. Their Robust Optimization approach outperformed the Expected
Value approach.

Harshal Lowalekar & N. Ravichandran
(2014) in their paper
explain the blood supply chain scenario in the Indian context. They quite
vividly showcase the Indian scenario. They propose eight areas in the blood
supply chain, which needs research in India. They are, demand estimation,
campaign planning, effect of collection levels, inventory control policy,
componentization of blood, Integrate
simple models using IT, significance of regional or centralized blood bank,
micro marketing to bridge supply- demand gap, advancement in medical community
to adopt newer and better technologies.

E.Alfonso, X. Xie,
V.Augusto and O.Garraud (2013) in their paper, studied management of donor appointments on day to day
basis. They developed a petrinet model and then converted to discrete event
simulation model. They tried 80 different strategies. They found that, the
donor service level depended on both adequate human resources capacity and
appropriate appointment strategies. 

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