Bringing Change by Measuring Impact

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

sa-data

Module 3

Using Data for Quality Improvement

Learning Objectives

At the end of Module 3, 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.

Module 1 introduced us to the need for monitoring and evaluation as part of effective public health practice, and Module 2 taught us some of the basics of working with data in the health care setting. Building on that, in Module 3 we will explore how to use indicator data in our quality improvement efforts by learning about what makes good quality improvement (QI) and an effective QI team, what tools we can use to carry out QI tasks, and how to carry out a PDSA (plan, do, study, act) cycle to improve public health processes.

In Module 1, we were introduced to patients and healthcare workers at Mzansi Clinic and we learned about missed opportunities in care for these patients (like Andiswa and Nomzamo). These missed opportunities could be symptoms of clinic-wide problems and may represent outcomes of a system of health care that needs improvement. In many cases, the problems can be resolved or at least improved upon through better data and information management; other problems require changes or even a redesign of the system. This module will explain in detail how following a quality improvement (QI) cycle can address these problems. The missed opportunities in Module 1 are identified as problem statements in Module 3.

In this module we will look at two specific missed opportunities with regards the care of patients we met in Module 1.

  • Andiswa: Recall that Andiswa, Nomzamo’s daughter, learns she is infected with HIV and enrols on HIV antiretroviral therapy (ART) to treat her HIV disease. She is scheduled for a viral load test after 6 months on ART. This test is done but fails to yield a valid result and her health care team fails to recognize this for some time.
  • Nomzamo: Recall that Nomzamo, a grandmother, presents to Thabo (the community health worker) with signs of tuberculosis. Thabo refers her to the clinic for screening; however, before she fully establishes a regular pattern of follow up of her treatment, she fails to return to the clinic. This loss to follow up is not recognized immediately, and this signals a missed opportunity with respect to the appointment system and the coordination between the clinic and the community health worker.

Module 3 will also look at several other scenarios where improvement is needed in Mzansi Clinic. We will learn how to thoroughly analyse the issues leading to each missed opportunity, how to plan for process changes to improve upon such problems in the future, and how to use data to measure whether our changes work.

Pre-test (10 minutes)

Part 1: Quality, Quality Improvement & Continuous Quality Improvement (15 minutes)

Part 2: Teamwork (15 minutes)

Part 3: QI Tools (30 minutes)

Part 4: Testing Changes & Implementing Improvements (45 minutes)

Part 5: Run Charts (15 minutes)

  • Summary

    Module 3 focussed on how to use data for quality improvement.

    We learnt about this by first defining the terms quality, quality improvement (QI), and continuous quality improvement (CQI) in Part 1.

    We then moved on to discussing the importance of teamwork, including the composition, roles, and responsibilities of a facility-based QI team, in Part 2.

    In Part 3, we got into the meat of this Module by learning about various quality improvement tools we can use in our work and to assist us at each stage of the QI cycle. The main tools we discussed were the National Core Standards, process mapping/flow charts, Five-S, the Five Whys, and root-cause (fishbone) analysis.

    In Part 4, we learnt about how to test changes and implement improvements through the Model for Improvement and Plan-Do-Study-Act (PDSA) cycle.

    In Part 5, we learnt about run charts.

Post-test (10 minutes)