Subscribe to RSS
DOI: 10.1055/s-0038-1634108
Medical Informatics in Medical Research
The Severe Malaria in African Children (SMAC) Network’s ExperiencePublication History
Received: 15 April 2005
accepted: 29 November 2005
Publication Date:
07 February 2018 (online)
Summary
Objectives: Computers are widely used for data management in clinical trials in the developed coutries, 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 an 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 occurring 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.
-
References
- 1 Taylor TE, Olola CHO, Agbenyega T, Kremsner P, Newton C, Missinou M. et al Standardized data collection for multi-centered clinical trials of severe malaria in African children: establishing the SMAC network. Transactions of the Royal Society of Tropical Medicine and Hygiene 2005; 100: 615-22.
- 2 Booman M, Sharp B, Martin C, Manjate B, la Grange J, David D. Enhancing malaria control using a computerised management system in southern Africa. Malaria Journal 2003; 2 (01) 13.
- 3 Kobayashi J, Phompidae S, Tomac T, Looareensuwanf S, Tomad H, Miyagic I. The effectiveness of impregnated bed net in malaria control in Laos. Acta Tropica 2004; 89: 299-308.
- 4 Caloto T, Huerta C, Moreno T, Guerra D, Alcaide J, Castells C. et al Quality control and datahandling in multicentre studies: the case of the Multicentre Project for Tuberculosis Research. BMC Medical Research Methodology 2001; I: 14.
- 5 HIM AL. Highland Malaria Project: New systems for predicting and detecting malaria epidemics in the East African Highlands. In: Inter-country workshop: New district-level surveillance systems for early detection of malaria epidemics in Kenya and Uganda. February 14-16. 2002. Milimani Resort Hotel, Kisumu, Kenya 2002
- 6 Pogash RM, Boehmer SJ, Forand PE, Dyer A-M. Kunselman SJ. Data Management Procedures in the Asthma Clinical Research Network. Controlled Clinical Trials 2001; 22 (6, Supplement 1) S168-S180.
- 7 Kawado M, Hinotsu S, Matsuyama Y, Yamaguchi T, Hashimoto S, Ohashi Y. A comparison of error detection rates between the reading aloud method and the double data entry method. Controlled Clinical Trials 2003; 24 (05) 560-9.
- 8 FileMaker Inc. File MakerPro. California: File Makerpro Inc 1984 2001
- 9 Microsoft® Corporation. Microsoft ® Studion 6.0 (visual foxpro 6.0). Enterprise ed. Texas, USA 1999
- 10 Microsoft® Corporation. Microsoft Office 97. Texas, USA. 1997
- 11 SPSS Inc. SPSS for Windows V8 (cited; available from. www.spss.com
- 12 Yourdon E. Modern Structured Analysis. Paperback ed: Prentice-Hall ECS Professional 1989
- 13 Clarke K, Hartswood M, Procter R, Rouncefield M, Slack R. Trusting the Record. Methods Inf Med 2003; 42: 345-52.
- 14 Faber MG. Design and introduction to an electronic patient record: how to involve users. Methods Inf Med 2003; 42: 371-5.
- 15 STATA. STATA 8 for Windows. Texas, USA: STATA press 2004
- 16 Timmons S. Resistance to computerized care planning systems by qualified nurses working in the UK NHS. Methods Inf Med 2003; 42: 471-6.
- 17 Goundry P. Changes in the national health service and the effects on the hospital library service: a case study based on the cumberland infirmary. Health libraries review 1995; 12 (04) 261-6.
- 18 Tuttle MS. Editorial comments: Medical informatics challenges of the1990s: acknowledging secular change. Journal of the American Medical Informatics Association (JAMIA) 1997; 4 (04) 322-4.
- 19 Kendall M, Eve J. Changes through IT in public libraries: Advantages of carrying out research via a training course. LIBRES: Library and Information Science Research 2000; 10 (01) 1058-6768.
- 20 Lorenzi NM, Riley RT. Review paper: Managing change - an overview. Journal of the American medical informatics association (JAMIA) 2000; 7 (02) 116-24.
- 21 Missinou MA, Olola CHO, Issifou S, Matsiégui PB, Adégnika AA, Borrmann S. et al Short report: Piloting Paperless Data Entry for Clinical Research in Africa. The American Journal of Tropical Medicine and Hygiene 2005; 72 (03) 301-3.
- 22 Webster C. A methodology for incorporating web technologies into a computer-based patient record, with contributions from cognitive science. International Journal of Medical Informatics 2002; 68 1-3 39-47.