Bringing Change by Measuring Impact

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

sa-data

Module 10

Bringing It All Together

Learning Objectives

By the end of Module 10, you will be able to:

  • Explain what indicators are, why and how they are used, and how they are selected for use in monitoring and evaluating health programs (Module 1).
  • Explain the patient care pathway and data cycle (Module 1) for the case study.
  • Distinguish between monitoring and evaluating health programs (Module 1).
  • Demonstrate correct use of counts and frequencies to describe and report on health care services (Module 2).
  • Calculate and interpret fractions, proportions, and percentages in the context of health and health care (Module 2).
  • Interpret frequency data summaries in different presentation formats (data tables, bar graphs, pie charts, scatter plots) (Module 2).
  • Demonstrate how to measure CQI indicators, display data, evaluate trends, and interpret results using data available in South African clinical settings (Module 3).
  • Calculate summaries of location and spread to create data summaries using real-world numerical health data (Module 4).
  • Use tables and graphs to show distribution and central tendency of numerical data (Module 4).
  • Explain the importance of data quality, and the implications of poor data quality (Module 5).
  • Define, calculate, and interpret measures of frequency: prevalence, cumulative incidence, and incidence rate (Module 6).
  • Summarise the principles for comparing disease risk between two groups and establishing associations (analytic epidemiology), and define, calculate, and interpret measures of association: relative risk and odds ratio (Module 6).
  • List the criteria that epidemiologists use to assess the likelihood of a causal exposure-disease relationship (Module 7).
  • Define bias and confounding in epidemiologic studies, and describe the main categories of bias (Module 7).
  • Describe the characteristics of different studies: descriptive vs. analytical, qualitative vs. quantitative, and prospective vs. retrospective (Module 7).
  • Describe the characteristics, strengths, and weaknesses of different types of analytical studies (cross-sectional, case-control, and cohort studies) and randomised controlled trials (Module 7).
  • Describe different quantitative data collecting techniques, and their advantages and disadvantages (Module 7).

The purpose of Module 10 is to pull everything we have learned together, apply it, and practise it using one big case study. We will integrate what we have learned about the importance of data, using numeric indicators in quality improvement, calculating data summaries, and studying health problems using various study designs, and more!

Pre-test (10 minutes)

Part 1: Introduction (30 minutes)

Part 2: The Patient & Data Pathway (15 minutes)

Part 3: Monitoring, Evaluation, & Indicators (30 minutes)

Part 4: Quality Improvement (45 minutes)

Part 5: Applied Epidemiology (30 minutes)

  • Summary

    In Part 1, we learned about some of the struggles patients face in taking IPT, and the challenges clinics have in implementing the treatment. We also learned about the national guidelines for IPT, and how they help prevent transmission of TB.

    In Part 2, we reviewed the patient and data pathways for patients like Andiswa who are taking IPT.

    In Part 3, we went through a scenario that allowed us to discuss indicators, treatment targets, and the types of monitoring and evaluation activities the Mzansi team should be doing with respect to IPT.

    In Part 4, we used quality improvement processes to look at how Mzansi Clinic can increase IPT adherence among their patients.

    In Part 5, we applied some epidemiology concepts to the IPT scenario. This module provided many opportunities along the way to practise and apply what you’ve learned about epidemiology.

    Now, it is time for congratulations! You’ve completed Module 10, which means you’ve also completed the course!

Post-test (10 minutes)

  • References

    Golub JE, Pronyk P, Mohapi L, et al. Isoniazid preventive therapy, HAART and tuberculosis risk in HIV-infected adults in South Africa: a prospective cohort. AIDS. 2009;23(5):631-6.