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HSM201 Health Measurement and Analysis (8)

Abstract

This subject introduces the measures used in health services management, epidemiology and biostatistics, and develops the skills necessary for the description and analysis of quantitative health science and epidemiological data.

+ Subject Availability Modes and Location

Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: HSM201
Where differences exist between the handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration Grading System School:
One sessionHD/FLSchool of Biomedical Sciences

Assumed Knowledge

HSM161

Learning Outcomes

Upon successful completion of this subject, students should:
be able to:
- understand the various measurements commonly used in health service management;
- describe and assess health related data by using biostatistical principles, and evaluate conclusions based on such data;
- critically analyse the application of statistical measures in published reports of research in health service management;
- select and apply descriptive and/or inferential statistics appropriate to the requirements of health service management particularly with respect to project or problem-solving activities.

Syllabus

The subject will cover the following topics:
- introduction to the essential mathematical techniques for health measurement and analysis; - overview of the concept of measurement and its application to quantitative analysis in health science, epidemiology and health services management. This includes epidemiological and demographic measures, hospital bed statistics, and some productivity and quality measures used in health services management; - descriptive statistics - tools used to summarise the characteristics of data sets. Measures of central tendency and dispersion. An overview of data collection, description and analysis tools including the use of computer applications for the purposes of data analysis and the presentation of results. Interpretation of results. Interpretation of results; - distributions and probability. The 'normal' distribution and the Students t-distribution; - correlation and regression; - hypothesis testing, inferential statistical techniques including ANOVA, (t-tests) Chi-Square and simple linear regression; - statistics in research.

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The information contained in the 2018 CSU Handbook was accurate at the date of publication: 18 October 2017. The University reserves the right to vary the information at any time without notice.