TY - CHAP
T1 - Improving Decision-Making for Clinical Research and Health Administration
AU - Pomares-Quimbaya, Alexandra
AU - González, Rafael A.
AU - Bohórquez, Wilson Ricardo
AU - Mauricio Muñoz, Oscar
AU - Milena García, Olga
AU - Londoño, Dario
N1 - Funding Information:
This work is part of the project entitled “Identificación semiautomática de pacientes con enfermedades crónicas a partir de la exploración retrospectiva de las historias clínicas electrónicas registradas en el sistema SAHI del Hospital San Ignacio” funded by Hospital Universitario San Ignacio and Pontificia Universidad Javeriana.
PY - 2014
Y1 - 2014
N2 - This chapter presents a health decision-support system called DISEArch that allows the identification and analysis of relevant EHR for decision-making. It uses structured and non-structured data, and provides analytical as well as visualization facilities over individual or sets of EHR. DISEArch proves to be useful to empower researchers during analysis processes and to reduce considerably the time required to obtain relevant EHR for a study. The analysis of semantic distance between EHR should also be further developed. As with any information systems project, a conversation needs to be put in place to realize the full potential that IT-based systems offer for people, in this case within the medical domain. It is a mutual learning experience that requires constant translations, frequent prototype discussions, grounding of new IT-based support in current practices and clear identification of existing problems and future opportunities that are opened up in order to enrich the momentum of the project, enlarge the community of early adopters and guaranteeing the continued financial, scientific and administrative support for the project from management stakeholders. Our experience is very positive and we intend to further pursue this approach and extract lessons learned for similar projects.
AB - This chapter presents a health decision-support system called DISEArch that allows the identification and analysis of relevant EHR for decision-making. It uses structured and non-structured data, and provides analytical as well as visualization facilities over individual or sets of EHR. DISEArch proves to be useful to empower researchers during analysis processes and to reduce considerably the time required to obtain relevant EHR for a study. The analysis of semantic distance between EHR should also be further developed. As with any information systems project, a conversation needs to be put in place to realize the full potential that IT-based systems offer for people, in this case within the medical domain. It is a mutual learning experience that requires constant translations, frequent prototype discussions, grounding of new IT-based support in current practices and clear identification of existing problems and future opportunities that are opened up in order to enrich the momentum of the project, enlarge the community of early adopters and guaranteeing the continued financial, scientific and administrative support for the project from management stakeholders. Our experience is very positive and we intend to further pursue this approach and extract lessons learned for similar projects.
KW - Data mining
KW - Health-care DSS
KW - IT service system
UR - http://www.scopus.com/inward/record.url?scp=84886043199&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39928-2_9
DO - 10.1007/978-3-642-39928-2_9
M3 - Chapter
AN - SCOPUS:84886043199
SN - 9783642399275
T3 - Intelligent Systems Reference Library
SP - 179
EP - 200
BT - Engineering and Management of IT-based Service Systems
A2 - Mora, Manuel
A2 - Gomez, Jorge Marx
A2 - Garrido, Leonardo
A2 - Perez, Francisco Cervantes
ER -