TY - JOUR
T1 - Computerized clinical decision support system for a public health program for the prevention of preeclampsia
AU - Rivas-Echeverría, Carlos
AU - Matamoros, Alejandra
AU - Torrealba, Ana
AU - Rivas, Francklin
AU - González, Solange
AU - Sánchez, Racely
AU - Molina, Lizmar
PY - 2006/1
Y1 - 2006/1
N2 - In this article we describe the development of the prototype of the "Expert System for the Preeclampsia Prevention Program" (ESPPP), a computer-based clinical decision support system that suggests the most appropriate diagnostic and therapeutic strategies in order to deliver the best possible individualized clinical practice based on evidences in the realm of hypertensive disorders of pregnancy (HDP). ESPPP was designed to be used to train physicians and to guide them to accurately perform ali the activities of a public health program ("Preeclampsia Prevention Program" or PPP) while fulfilling the data base of the epidemiological surveillance system for this program. ESPRE (expert system for the diagnosis an treatment of preeclampsia), a previously developed decision support system, was readily adopted by physicians who believed it would have a positive impact on the quality and efficiency of care, however, dissatisfaction with system capabilities (such as non-updateability of roles, time consumption and some resources), for both physicians and PPP's, authorities moved us to develop another system with an improved rules-editor and better resources. ESPPP consists on two main modules: The Knowledge Base Editor, fed with the clinical based evidences and guidelines and, the Diagnostic/Therapeutical Application, which guides the doctor on the assessment of and recommendations for the patient. ESPPP applies pragmatic criteria based on evidences and PPP's guidelines for diagnosing, classifying and suggesting the appropriate treatment of the HDP and their complications. This system guides the users for rapid, easy and systematically collecting patient information, and based on those items that leads to the possible diagnose and treatment for that patient. We will describe the design, modules and capabilities. Preliminary results and plans for further analysis are reported.
AB - In this article we describe the development of the prototype of the "Expert System for the Preeclampsia Prevention Program" (ESPPP), a computer-based clinical decision support system that suggests the most appropriate diagnostic and therapeutic strategies in order to deliver the best possible individualized clinical practice based on evidences in the realm of hypertensive disorders of pregnancy (HDP). ESPPP was designed to be used to train physicians and to guide them to accurately perform ali the activities of a public health program ("Preeclampsia Prevention Program" or PPP) while fulfilling the data base of the epidemiological surveillance system for this program. ESPRE (expert system for the diagnosis an treatment of preeclampsia), a previously developed decision support system, was readily adopted by physicians who believed it would have a positive impact on the quality and efficiency of care, however, dissatisfaction with system capabilities (such as non-updateability of roles, time consumption and some resources), for both physicians and PPP's, authorities moved us to develop another system with an improved rules-editor and better resources. ESPPP consists on two main modules: The Knowledge Base Editor, fed with the clinical based evidences and guidelines and, the Diagnostic/Therapeutical Application, which guides the doctor on the assessment of and recommendations for the patient. ESPPP applies pragmatic criteria based on evidences and PPP's guidelines for diagnosing, classifying and suggesting the appropriate treatment of the HDP and their complications. This system guides the users for rapid, easy and systematically collecting patient information, and based on those items that leads to the possible diagnose and treatment for that patient. We will describe the design, modules and capabilities. Preliminary results and plans for further analysis are reported.
KW - Artificial intelligence
KW - Expert systems
KW - Hypertensive disorders of pregnancy
KW - Medical diagnosis
KW - Preeclampsia
UR - https://www.scopus.com/pages/publications/30144441981
M3 - Article
AN - SCOPUS:30144441981
SN - 1790-0832
VL - 3
SP - 133
EP - 139
JO - WSEAS Transactions on Information Science and Applications
JF - WSEAS Transactions on Information Science and Applications
IS - 1
ER -