InterCriteria Analysis of data for blood collection in the Transfusion Hematology Department , University Hospital “ St

Maintaining a supply of safe blood and blood products is a national priority in many countries in the European Union. Achieving this aim requires the development and implementation of a national policy and the development of guidelines to the departments of transfusion hematology. There are a number of guidelines that spell out how quality and safety can be achieved. One of the most important factors for the improvement of the work of these departments is the number of the blood sample investigations of the donors and patients. In the present


Introduction
Blood sampling and transfusions are an important part of hematologic care. Blood collection is an important preanalytical component of hematological testing and for the future transfusion which is the transfer of blood, its components, or products from one person (donor) into another person's bloodstream (recipient). Blood samples are usually collected daily from different collection points, such hospitals and health centers, and transported to a central laboratory for testing. The blood center is the location for the collection, receipt, processing, testing, storing and distribution of blood [1]. These centers are working according to some well-established standards. Directive 2002/98/EC has set standards of quality and safety for the collection, testing, processing, storage and distribution of human blood and blood components, which were further clarified and augmented by directives Directive 2004/33/EC devoted to the technical requirements, Directive 2005/61/EC focused on the monitoring and reporting of serious adverse events and reactions and Directive 2005/62/2005 which deals with the quality systems requirements [2]. There are a number of factors determining the good and efficient work of such centers. In general, the number of the blood samples and the quality of the performed tests are indicators for the well-organized management of the hematological departments. Any test performed in the laboratory of the blood center is subject to a variety of conditions that may influence the outcome of the result. Some of them include the sample itself, the test method, reagents used, and different operators carrying out the same process. Blood sample tests performed from the donors and patients are divided in two major groups: the laboratory tests of the donors and the immunohematological studies of the patients. The main laboratory tests performed on the collected blood from the donors are: • Determination of the blood group from the ABO blood group system, • Determination of Rh phenotype, • Hemoglobin test.
The immunohematological studies of the patients are: • Determination of the blood group from the ABO blood group system, • Determination of Rh D antigen, • Anti-erythrocyte allo-antibodies tests, • Immunohematological studies in neonates for CKD (chronic kidney disease), • Blood compatibility tests, • Other blood tests (subgroup).
In the present paper application of the InterCriteria analysis approach to data about the blood collection and the number of the performed tests on the collected blood from the donors and the patients in the Department of Transfusion Hematology University Hospital "St. Anna", during a period of four years (2014-2018) is presented. The aim is to detect and analyse the dependencies between the investigated years, based on the available data.

Notes on the InterCriteria Analysis
Let be a fixed set of indices and ℛ be the set of the real numbers. By IM with index sets and ( , ⊂ ), we denote the object: . . .
In [3], different operations, relations and operators were defined over IMs. Here, we shall briefly remind some of them.
Then we can construct the IM : where for every , (1 ≤ ≤ , 1 ≤ ≤ ): (1) is a criterion, taking part in the evaluation, is an object, being evaluated.
, is a variable, formula or , = ⟨ , , , ⟩ is an intuitionistic fuzzy pair, that is comparable about relation with the other -objects, so that for each , , : is defined. Let be the dual relation of in the sense that if ( , , , ) is satisfied, then ( , , , ) is also satisfied. For example, if " " is the relation "<", then is the relation ">", and vice versa. Therefore, ⟨ , , , ⟩ is an IFP. Now, we can construct the IM that determines the degrees of correspondence between criteria 1 , . . . , . Based on these degrees of correspondence we can measure how close as behavior the criteria are. For further details we refer the interested reader to [5,6].

Application of the InterCriteria Analysis
The ICrA approach was applied to data obtained from the laboratory tests of the donors and the immunohematological studies of the patients during a period of four years in the Department of Transfusion Hematology University Hospital "St. Anna". Eight indicators with a given weight are used: • Determination of the blood group from the ABO blood group system, • Determination of Rh phenotype, • Hemoglobin test, • Determination of Rh D antigen, • Anti-erythrocyte allo-antibodies tests (AEAAD), • Immunohematological studies in neonates for CKD (chronic kidney disease), • Blood compatibility tests (BCT), • Other blood tests (subgroup).
We have applied the ICrA to the data summarized in Table 1 and we have obtained the results shown in Tables 2 and 3. The visual interpretation of the results may be seen on Figure 1. The years with greatest positive consonance (in accordance with [5]), for the scale are 2014, 2017 and 2018, indicating that there may have been some difference with regard to 2015-2016 period.
Further we have considered data for the blood donors divided in age-groups for the different years. The data is given in Tables 4 and 5. The results are shown in Figure 2. It is noteworthy that for the male donors the years "2017-2018" are in strongest positive consonance while for the female donors the years that are in strongest positive consonance are: "2014-2015", followed closely by "2017-2018". Table 3. The values of resulting from the application of ICrA   Naturally, given the relatively small size of the considered data it is not possible to claim with absolute certainty that our interpretations are doubtlessly valid but they provide a starting point for further investigations.