Bringing Change by Measuring Impact

Health Information Management and Applied Epidemiology for Health Care Workers in South Africa

sa-data

Module 2

Basic Numeracy in Health Care: Counts, Frequencies and Categorical Variables

Learning Objectives

At the end of Module 2, you will be able to:

  • Demonstrate the correct use of counts and frequencies in describing and reporting on health care services.
  • Demonstrate skills in addition, subtraction, multiplication, and division of counts, as applied to common health-care-service scenarios.
  • Calculate and interpret fractions, proportions, and percentages in the context of health and health care.
  • Interpret the different forms of one-way frequency data summaries: frequency tables, bar graphs, pie charts, and scatter plots.
  • Interpret two-way frequency tables and charts.
  • Interpret two-way frequency tables (indicators among a particular sub-group).
  • Define the appropriate numerators and denominators for commonly used health indicators and estimates of health program coverage.
  • Evaluate the likelihood and believability of indicator values based on correct definitions of numerators and denominators.
  • Define the term categorical variables.
  • Explain the concept of variability of data, and its relevance in presenting summaries of health data using categorical variables.

In Module 1, we met Sister Zingy, a nurse, and several of her colleagues. As part of their daily duties, they are regularly called upon to use numbers and data. In this module, we will reinforce your skills in working with numbers. The goal is to build our skills to work with, and make sense of, data, so that we can use the data to improve health programs in our clinics and communities.

Pre-test (10 minutes)

Part 1: Counts (30 minutes)

Part 2: Fractions, Proportions, Percentages (30 minutes)

Part 3: Indicators (30 minutes)

Part 4: Indicators: Variables (20 minutes)

Part 5: Categorical Data (20 minutes)

  • Summary

    In this module, our goal was to build our numeracy skills to work with, and make sense of, data, in order to use the data to improve health programs in our clinics and communities.

    In Part 1, we learnt about counts, and how to present count data in one- or two-way frequency tables. We also learnt different graphical techniques for presenting data. We saw how Sister Zingy combined all these techniques to convey the patterns, relationships, and comparisons of data on the diarrhoea cases. We saw how she used the data for the ages of the patients and frequency of cases each day determine that the source of the outbreak was likely a school.

    In Part 2, we discussed how to calculate and interpret fractions, proportions, and percentages in the context of health care, and how they are important in further understanding and interpreting our data—for example, in calculating adherence rates.

    In Part 3, we talked about indicators. Building on what we learned about the data cycle in Module 1, we defined indicators as measures used to quantify, characterise, or evaluate a health care program. Indicators are often standardised, and expressed as an event (numerator) over a population (denominator) for a given period of time. We went through the process of understanding what an indicator is asking for by looking more closely at the meaning of the numerator, denominator, time frame, and location. We saw the need to check for trends (consistency) in indicators, and how the quality of data from the source documents is important in ensuring the indicators we are reporting are accurate.

    In Part 4, we covered the ways in which data variability can influence our decisions when choosing the period of time for reporting an indicator.

    Finally, in Part 5, we applied our new-found skills in numeracy and visual presentation to categorical data.

    In the next module, we'll be learning more about how to apply these numeracy skills to our data in order to continually improve the quality of services and health care offered to our patients!

Post-test (10 minutes)

  • References

    Baldi, B, Moore, DS. Practice of Statistics in the Life Sciences [CD-ROM]. New York: W.H. Freeman and Company; 2009

    Massyn N, Peer N, Padarath A, Barron P, Day C, editors. District Health Barometer 2014/15. Durban: Health Systems Trust; October 2015. [Accessible from the Health Systems Trust at the website http://www.hst.org.za/publications/district-health-barometer-201415-1]

    USAID/MEASURE Evaluation. Introduction to Basic Data Analysis and Interpretation for Health Programs Training Tool Kit. Version 1, May 29, 2011