Credit Points 10

Legacy Code 401365

Coordinator Kingsley Agho Opens in new window

Description Most professions in the health sciences need to read and interpret data relating to individual health status, interpret health risks in communities, and engage in the evaluation of interventions, or impact of health policies or programs. Many public health practitioners are actively involved in surveillance, quantitative research and/or evaluation. This subject provides an opportunity to learn about making health service decisions using appropriate data. Students learn how to explore and use data that are assembled to replicate real patient data to both generate and answer questions. The focus may be managerial or clinical, or an integration of these. Students analyse the assembled patient dataset to generate and interpret health statistics, and translate them into health information and knowledge for decision-making. Students completing this subject develop the ability to explore health data and provide recommendations based on the findings.

School Health Sciences

Discipline Health, Not Elsewhere Classified.

Student Contribution Band HECS Band 2 10cp

Check your fees via the Fees page.

Level Postgraduate Coursework Level 7 subject

Restrictions

Students must be enrolled in a postgraduate program.

Assumed Knowledge

Competent use of Microsoft Excel, and high school mathematics (arithmetic, formulas and algebra, reading graphs).

Learning Outcomes

On successful completion of this subject, students should be able to:

1. Explore and organise data in order to generate reports and make recommendations
2. Identify and compare the relationship between data, information, knowledge and wisdom and how these elements inform practice, management, and policy
3. Explain data elements in contemporary health data terminologies

Subject Content

1.Health informatics
2.Describing and visualising health data using appropriate software e.g. Microsoft Excel and SPSS
3.Determining relationships between variables
4.Limitations of the data and analysis and risks of misinterpretation
5.Administrative Data and Clinical Data
6.Demography and Health Indicators
7.Working with Excel - Survival Analysis
8.Interpreting data to determine health service needs
9.Communication and dissemination of health information data to key stakeholders
10.Working in Excel (II): Time Series Analysis
3.Determining relationships between variables through data linkage
5.Unintended errors in technology
6.Standardisation of data
7.Privacy, security and confidentiality