Medical Informatics in medical research - The Severe Malaria in African Children (SMAC) network's experience

被引:0
|
作者
Olola, C. H. O.
Missinou, M. A.
Issifou, S.
Anane-Sarpong, E.
Abubakar, I.
Gandi, J. N.
Chagomerana, M.
Pinder, M.
Agbenyega, T.
Kremsner, P. G.
Newton, C. R. J. C.
Wypij, D.
Taylor, T. E.
机构
[1] KEMRI, Wellcome Trust Res Labs, Kilifi Dist Hosp, Ctr Geog Med Res, Kilifi 80108, Kenya
[2] Albert Schweitzer Hosp, Tubingen, Germany
[3] Univ Tubingen, Inst Trop Med, Dept Parasitol, Tubingen, Germany
[4] Kwame Nkrumah Univ Sci & Technol, Sch Med Sci, Dept Physiol, Kumasi, Ghana
[5] Komfo Anokye Teaching Hosp, Kumasi, Ghana
[6] Royal Victoria Teaching Hosp, Banjul, Gambia
[7] Childrens Hosp, Clin Res Program, Boston, MA 02115 USA
[8] Michigan State Univ, Dept Internal Med, Coll Osteopath Med, E Lansing, MI 48824 USA
关键词
medical informatics computing; malaria; multi-center studies;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objectives: Computers are widely used for data management in clinical trials in the developed countries, unlike in developing countries. Dependable systems are vital for data management, and medical decision making in clinical research. Monitoring and evaluation of data management is critical. In this paper we describe database structures and procedures of systems used to implement, coordinate, and sustain data management in Africa. We outline major lessons, challenges and successes achieved, and recommendations to improve medical informatics application in biomedical research in sub-Saharan Africa. Methods: A consortium of experienced research units at five sites in Africa in studying children with disease formed a new clinical trials network, Severe Malaria in African Children. In December 2000, the network introduced on observational study involving these hospital-based sites. After prototyping, relational database management systems were implemented for data entry and verification, data submission and quality assurance monitoring. Results: Between 2000 and 2005, 25,858 patients were enrolled. Failure to meet data submission deadline and data entry errors correlated positively (correlation coefficient, r = 0.82), with more errors occuring when data was submitted late. Data submission lateness correlated inversely with hospital admissions (r = -0.62). Conclusions: Developing and sustaining dependable DBMS, ongoing modifications to optimize data management is crucial for clinical studies. Monitoring and communication systems are vital in multi-center networks for good data management. Data timeliness is associated with data quality and hospital admissions.
引用
收藏
页码:483 / 491
页数:9
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