The National Aged Care Mandatory Quality Indicator Program (QI Program) was established to improve transparency, accountability, and continuous improvement in aged care services by mandating the collection and reporting of specific quality indicators.

However, as the program has expanded, encompassing more indicators, the administrative burden on aged care providers has also increased. This expansion has inevitably led to a higher risk of errors in data submission. Consequently, it has become increasingly important for providers to be vigilant about the types of errors that are most common, to mitigate risks and enhance data accuracy in their own practices.

This presentation unpacks six years of data quality challenges and improvements within the National Aged Care Mandatory Quality Indicator Program. It will leverage both the government’s published data and more detailed de-identified data from thousands of submissions made by MOA Benchmarking on behalf of homes since 2019. Given that MOA submits for nearly half of homes in Australia, we are well-placed to identify valuable data quality insights. These insights will 1) illustrate the most common errors made in data submissions, 2) provide characteristics of homes and services more likely to make specific types of errors, 3) demonstrate the risk of bias caused by poor data quality, and 4) present analysis of quality indicator data against key characteristics of homes. For all potential errors, the presenter will provide strategies and flagging rules for early detection prior to submission.

The errors reported will be presented as the prevalence of all submissions made. Analysis of characteristics of homes making errors will be undertaken using linear regression. The analysis against home characteristics will be presented using graphical methods and compared statistically using chi-square tests. Statistically significant values will be considered as those where p<0.05. Where appropriate, extensive data visualisation will be used to communicate key findings to the audience.

This presentation will equip aged care providers with actionable strategies to enhance data accuracy within the program. Additionally, it will provide insights into their risk profile through comparative analysis of home characteristics. By implementing these business rules, providers can significantly improve the integrity of their data submissions, ultimately leading to more informed decision-making and better care outcomes for residents. Moreover, with the impending expansion of a similar quality indicator program into home care, providers in this sector are likely to encounter similar challenges, making the lessons learned from residential aged care even more pertinent.