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Understanding Quality Indicators

The National Aged Care Mandatory Quality Indicator Program (QI Program) became compulsory on 1 July 2019. Quality management is complex and multidimensional. No single group of indicators is likely to capture all perspectives on quality of care. Over time, it is likely there will be an increase in mandatory reporting.

Implementation of the Single Quality Framework, will also require collection of data so that providers can monitor service delivery. When collecting data it is important to analyse the data and list actions taken to improve care services.

Mandatory quality indicators

  • pressure injuries

  • physical restraint

  • unplanned weight loss

  • falls and major injury (new)

  • medication management (new) including poly-pharmacy and use of anti-psychotic medicines.

Other regulatory authorities in the health care space, collect large data sets and it is likely that the Aged Care Quality and Safety Commission will expand the collection of data over time. The ability to collect, analyse and visualise trends in data over time will become increasingly important in the industry.

As as provider, you can consider what data to measure, so that you can understand more about service improvement and the delivery of better care.

Ideally measures of safety and quality will be:

  • clearly defined

  • supported by rationale that is backed by literature

  • easily collected, preferably from existing datasets

  • reliable and valid measures

. It is useful to think about how the data will be collected, the manual collection of data is difficult and time consuming. The optimum method is to automate the collection of data via care management software. This is something to consider when purchasing or upgrading care management software.

What type of data can you collect?

Before deciding what data to collect, it is important to think about the actions that may be taken in response to the data.

Lag Indicators - these measures refer to events that have already occurred, usually relating to events that have negative consequences for quality and safety. Lag indicators are easy to identify and collect data. The quality indicators that must be reported to the Aged Care Quality and Safety Commission are lag indicators.

Lead Indicators - are predictive and preventative measures that are proactive in nature. The challenge is the identification and collection of data on lead indicators.

Process Measures - relate to specific steps in the process and focus on reducing negative impacts. Process measures are important in demonstrating the use of evidence-based practice. Measuring process data allows you to identify root causes of problems. Falls risk assessment represent a process measure.

Outcome Measures - measure the effect or endpoint, both positive and negative, of an intervention or treatment. Outcome measures are common in health care and the selection of data points may skew the picture the data gives.

Outcome Measures include:

  1. Self-reported measures

  2. Performance-based measures

  3. Observer-reported measures

  4. Clinician-reported measures

The data set may be quantitative (numbers or percentages) or qualitative (experiences, consumer stories or a combination of both). For quantitative data the format of the data and the way numbers are presented can impact how we interpret data.

Let’s look at the categories of indicators as they apply to falls prevention. The number of falls and the number of falls with injury are both lag indicators as the event has already occurred.

The number of falls risk assessments completed is a lead indicator. By completing a falls risk assessment, the falls status of the consumer and the gaps where additional care and support required, are assessed. Care can be personalised to address the specific issues that are identified in the risk assessment.

Process indicators are measures of the things we do to prevent falls. For example, the falls risk assessment shows that the client is unsteady when walking, so they get a walking stick, and an appointment is made for the client to attend a physiotherapist who can give them specific exercises to improve balance. This shows the process steps which are required to resolve the issues identified in the risk assessment.

Outcome measure would be that the client has increased mobility and improved balance which may lead to a reduction in number of falls for that client.

Now that we understand lead and lag indicators as well as outcome and process measures lets look at the aged care quality indicators in the context of outcome, and process measures.


Once you have decided what to measure, which will include the mandatory measures, then the discussion can focus on how to measure.

The more information the numbers give you the better, so ideally you want to set up your measures in different formats:

  • Whole numbers are positive numbers from 0 to infinity. Whole numbers are a crude measure e.g., number of empty beds, number of falls.

  • Integers are positive and negative numbers, but still no fractions

  • Ratio is relationship between two numbers indicating how many times the first number contains the second. e.g., ratios of falls with injury divided by total number of falls, or number of falls divided by total number of episodes of care or falls divided by total number of clients.

Find out more

HBS offers a workshop on measurement and data analysis. In the webinar we will also discuss a group of common metrics that are collected by aged care providers and how to “slice and dice” the data, allowing you to understand how different views of data will give you different information. You will also develop an understanding of reviewing trends in data. Contact us to find out more.

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