## 5 Discussion  
Diagnosis is a difficult task which requires the clinician to relate high dimensionality of data. Computer assisted medical decision-making may be the solution to deal optimally with the flood of data and explosion of knowledge occurring in the medical area [33]. In addition, expertise in laboratory test results interpretation emerges from years of experience. In this way, an expert system, which has the ability to compute a high amount of data and contains knowledge from expert results, is a useful tool for improving interpretation of laboratory tests outcomes. Insufficient communication and missing information are among the major factors contributing to unintended errors in medicine. Providing accurate and timely information at the point of care has the potential to make a significant reduction of these adverse events [34]. Furthermore, [PERSON], [PERSON] and [PERSON] analysed 100 cases of diagnostic errors, 33 of which led to death of the patient. These errors relate to different sources and problems of communication, especially with test results [35]. Our application is a framework which provides a knowledge base easy to interpret and modify by clinicians and stores patient data along with conducting data analysis. In this way, our system can be worthy to improve Spain Health care, currently suffering from a lack of coordination, including communication and loss of information issues [6]. On the other hand, our system proposes diagnoses in matter of seconds, referring also to parameter deviations which suggest each of these diagnoses proposed, helping the clinician to make a decision. According to [PERSON], expert systems with an explanation facility can enhance the quality of the decision making, improving performance in terms of speed and accuracy of judgments [36]. More accuracy together with less adverse events would lead to lesser waste of resources and necessity of supplementary tests. This is particularly relevant, since clinical laboratory costs increase rapidly, partly due to increment of laboratory use. For example, the Hospital Costa del Sol laboratory (Malaga, Spain) expenditures increase about 10%-15% annually [37]. Regarding all these aspects, our proposed system could lead to more efficient and less expensive primary health care. In summary, our system provides the followings advantages: (a) Proposal of most likely diseases taking into consideration laboratory test results, leading to better accuracy and consistent process of diagnosis; (b) advanced Informatics knowledge is not mandatory for the use of the system; (c) maintenance of the set of rules by only modifying an Excel Spreadsheet, without needing of recompiling or programming knowledge; (d) value for teaching in analysis' interpretations, because the system explains outcomes and suggestions. In this way it could be used to train medical students; and \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Computer I** & **Computer II** \\ \hline \multirow{2}{*}{Specifications} & I7-4510U 2.60 GHz 8.00 GB & I3-2370M 2.40 GHz 4.00 GB RAM \\  & RAM Windows 8.1 64 bits & Windows 8 64 bits \\ Number of cases & 40 & 40 \\ Maximum time (ms) & 754 & 1729 \\ Minimum time (ms) & 119 & 171 \\ Mean & 154.33 & 241.28 \\ Standard deviation & 100.11 & 237.73 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Speed performance of the expert system. (e) our system contributes by setting a framework which also allows improving communication and coordination between primary health care and further levels of health care. It is necessary to state limitations and omissions of the framework proposed, which suggest further research in order to overcome such issues:  
1. Prove system outcomes in several areas of diseases with the purpose of checking relevance and accuracy of system's diagnoses and suggestions. 2. The system does not have a learning method which allows the system to tune itself and grow by creating new rules. 3.