## 1 Introduction  
The International Conference on Primary Health Care at Alma Ata in 1978, where the World Health Organization was seeking for advances in basic health services, with special emphasis on poor populations, took as its motto \"Health for all\" [1]. This motto strongly involves primary health care. As suggested by [PERSON] primary health care is a first-contact, continuous, comprehensive and coordinated care provided to undifferentiated populations by gender, disease, or organ systems [2]. The 1978 Alma-Ata Declaration was at first focused on low-income and middle-income countries. Five years later, its goals were extended to all over the world. Alma-Ata Declaration had a great importance in the 1984 reorganisation of Spanish primary health care, establishing principles which lead current primary health care. \"Health for all\" was not achieved by the year 2000, as it is now, and this encourages making efforts to revitalise primary health care [3]. Since then, a number of improvements have been made in primary health care in Spain. Focus has been put on teamwork among the several health professionals and more efficiency and quality of care delivery [4,5]. Nevertheless, a considerable amount of issues still takes place. For example, Spain has lack of interoperability between primary and specialty health care, due to heterogeneity of patients' clinical data storage, which leads to medical errors because of the lost relevant information about patients, as [PERSON] _et al._[6] stated. Losses of relevant information together with diagnosis errors involve matters as the increasing the time to properly treat the patient, which can lead life risks or irreversible health effects, as well as waste of money and other resources associated with unnecessary duplication of tests. A number of errors in laboratory medicine come from inappropriate election of laboratory tests and misinterpretation of laboratory results, which can be improved by using expert systems [7]. Based on these facts, our efforts focused on the developing of an Expert System that assists the health professional in order to make a prior and timely diagnose and set a treatment, settle the need of additional exams or dispatch the patient to a particular specialist. All of these contribute to strengthen primary health services. A significant amount of diagnoses are based on the interpretation of clinical tests, where samples are taken from the body, primarily blood and urine. Thus, our system proposes a set of likely diagnosis from a rule-based engine which takes into consideration urinalysis and blood tests outcomes. In this way, the doctor, supporting our system's suggestions with other signs and symptoms, would be able to take a decision on patient's prior diagnosis. Despite the reluctance over the usefulness of clinical decision support systems, a number of applications and expert systems have shown great performance and some of these have been successfully used for decades in health centers, as the HELP system [8]. Expert Systems have advantages like its performance is not affected by doctor's fatigue or mood, which strongly contributes to a good health service. It also can provide feedback to doctors, turning itself into an aid to increase the expertise of staff, as well as to provide consistent outcomes and ongoing availability. Thus, the aim of our system is to assist the process of diagnosis for medical staff in primary health care in order to improve quality, accuracy and agility of health service. It cuts costs, reduces wasting resources, which would mean better achievement of economy and efficiency indicators, which could be improved, as reported by literature. This paper is organised as follows. The next Section introduces clinical decision support systems and presents a literature review with most of the usual techniques. Section 3 explains system architecture, working of the rule-based proposed system, and system's validation.