This Introduction to Data Quality course will ensure that district hospital data managers understand the importance of data quality in decision making, understand the key quality problems associated with the common sources of data used for assessment of progress and performance of the health sector, and create plans to rectify data quality issues.
The World Health Organization's Data Quality Tool in the Rwanda Health Management Information System (RHMIS) simplifies the steps that must be taken to conduct data quality assessments. Data managers and data quality auditors who take this course will gain the knowledge and skills to efficiently navigate the tool and produce strong and comprehensive data quality results.
This course focuses on data collection tools and methods used by RHMIS whether for case based and aggregate data collection and reporting. It will introduce to learner the data collection tools(forms, registers, patient file and, etc) and also to the methods used to report health data national wide. This include web, SMS, USSD, and Andoid data entry methods as well as PDF data entry and Manual data import. The course has practical exercises and quizzes throughout the course period to ensure learner get the whole concepts and prepare you for the course end evaluation and final certification at the end of the module.
The focus of this course includes the study of health data entry, retrieval, analysis and presentation by the Health professional. Learners will critically examine different steps in data entry, retrieve and data analysis. Data presentation, quality assurance will be explored as the Health Management Information System professional contributes to, and aids in the facilitation of the decision-making process.
This course explores how MoH affiliated staff can
describe the significance, necessity, and key components of the HMIS Dashboard.
Participants will also strengthen their ability to use the HMIS Dashboard to obtain
the data on specific indicators in which they wish to explore.
One of the gaps at the decentralized level is that district health staffs, district health management teams (DHMTs) and other district authorities are not making sufficient use of geographic information systems (GIS) tools available to them for evidence-based decision making. This is especially the case for identifying new locations for health posts, monitoring geographic distribution of disease burden or risk factors to better target their interventions. “QGIS” is “a professional” GIS software which is open (served for free) with functionalities to visualize, manage, edit, analyze data, and compose printable maps. Building capacity of decentralized level staff in QGIS would improve the use of data for decision making, especially in the areas of high interest such as family planning, malaria, and maternal and neonatal health.