Data for Action
Fed by extensive ITM & partner experience, this 3-week course helps you use the untapped power of routine data to incite policy change.
Deadline: 15 oktober 2022
A wealth of data are “routinely” collected to monitor the utilization and coverage of health services and activities, to follow-up the status of people at risk and/or to survey the appearance of health problems or life events.
Data sources of these monitoring and surveillance systems are mostly public but still insufficiently known and/or used. Lack of data management skills to deal with incomplete data sets and the limited knowledge of data analysis tools and frameworks/designs lead to a substantial underutilization of data.
However, policy makers and health managers need well-prepared information to tailor their decision making and action to the size, nature, and spread of health problems or to factors influencing service coverage for particular population groups.
The short course “Data for Action” will provide you with specific skills and tools to analyze and appraise evidence from longitudinal routinely collected data, taking into account its imperfections and biases. On the basis of case studies on diseases such as dengue, tuberculosis or plague, you will learn how to realize (interrupted) time series analysis and risk mapping with open access R-studio and QGIS software. You will also explore entry points for dialogue with policy makers and options to disseminate your findings effectively. The analysis of primary research data or ‘big data’ are outside the scope of this course. Study designs for the evaluation of health programmes are covered in the course “Design & Evaluation of Health Programmes”.
Are you a health professional, health system or programme manager or a researcher and are you involved in or interested in the analysis of routine/existing/secondary data and its use for action? Then this short course is for you.
The “Data for Action”-course draws on expertise of ITM staff and its partner institutions in data management and analysis, surveillance & monitoring systems and operational research. The course also builds on the rich exchange of experience between participants working in different systems and settings.
At the end of the course you will be able to:
- Define a health policy or programmatic information gap to be addressed with routine data analysis
- Identify strengths and limitations of a range of routine/secondary data sources and propose solutions to improve data collection, database building and data organisation
- Deal with incomplete data sets in the analysis
- Ensure data security and adherence to regulations, respecting ownership of data
- Use an appropriate design and tools for the analysis of different types of routine/secondary data
- Interpret and present the results of the analysis
- Identify tools and pathways to bring evidence and recommendations, based on the results of the analysis, towards policy makers for decision making and action