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Microcomputer applications in health population surveys: experience and potential in developing countries.
Summary
Successfully applying microcomputer technology in developing countries requires careful planning and adaptation to local needs. Collaboration, task-oriented training, and local maintenance are crucial for effective adoption and utilization of these tools in health and development projects.
Area of Science:
- Health Informatics
- Development Studies
- Computer Science Applications
Background:
- Rapidly evolving microcomputer technology makes literature quickly outdated.
- Published information on microcomputer applications in health and development is often difficult to find or obsolete.
- Field experience with early microcomputers offers valuable insights for new projects.
Purpose of the Study:
- To provide practical summary points for applying microcomputer technology in health and population surveys in developing countries.
- To highlight essential considerations for successful implementation and utilization of microcomputers in field data collection.
- To share lessons learned from literature and field experience.
Main Methods:
- Review of existing literature on microcomputer applications in developing countries.
- Analysis of field experience with first-generation microcomputers in health/population surveys.
- Identification of key factors for successful technology adoption and utilization.
Main Results:
- Careful planning, adaptation to field conditions, and consideration of survey complexity are essential.
- Collaboration among staff, task-oriented on-the-job training, and local maintenance are critical.
- Utilizing microcomputers for time-consuming tasks and fostering a user community enhances adoption and results.
Conclusions:
- Successful microcomputer implementation hinges on meticulous planning, user involvement, and tailored technological solutions.
- Local capacity building for maintenance and repair is vital for sustainability.
- While custom programming may be needed, off-the-shelf software can be suitable for specific data management tasks, requiring careful cost-benefit analysis.