What is data quality?
Data quality is the degree to which a given dataset meets requirements on accuracy, completeness, consistency, validity, uniqueness, and timeliness. Quality data is critical in the healthcare industry.
Why is it important?
Data is a source which provides evidence.
In primary healthcare, data quality can impact greatly on the care a patient receives.
If data quality is not being continuously monitored and improved it can cause a series of negative impacts, resulting in:
- Poorer services provided to patients
- Decrease in patient and staff satisfaction
- Decrease in business revenue
On the other hand, good quality data enables care providers and managers to be better decision-makers and optimises the healthcare coverage as well as service quality.
Continuously working on data quality can benefit general practice in different ways:
- Improve patient experience in terms of accessing safer care, which results in better health outcomes
- Improve effectiveness in communication between healthcare professionals internally and externally
- Better management of population health by reducing the burden of disease and health inequalities across the region
In addition to the above benefits, continuous improvement in data quality, which includes maintaining patients’ health records clearly and accurately, also increases the chance of practices obtaining accreditation from AGPAL, as it is one of the main criteria under the RACGP Standards for general practices, 5th edition.
Continuously working on data quality enables general practices to increase business revenue.
Practices who participate in Practice Incentives Program Quality Improvement (PIP QI) qualify to receive incentive payments when they:
- Participate in continuous quality improvement and
- Provide the PIP Eligible Data Set to your local Primary Health Network (PHN)
How practices can improve their data quality
General practices can ensure high-quality data by developing relevant policies and procedures, and through education and training to staff. Continuously creating action plans with progress measures is another effective method.
South Western Sydney PHN’s Quality Improvement in Primary Care (QIPC) is a data-driven QI program to assists general practices continuously improve data quality by identifying gaps using a clinical audit tool – POLAR – and completing a Model for Improvement (MFI) plan with one of our officers every quarter.
The data quality page within QIPC Clinic report in POLAR uses a traffic light colour system to indicate the practice’s data quality performance against RACGP Accreditation standards 5th edition:
- Green indicates meeting the RACGP standard
- Orange indicates within 20 per cent of the RACGP standard
- Red indicates more than 20 per cent from the RACGP standard
This gives practices an overview of their data quality and to easily identify which item or patient has requires more information in the clinical software.
POLAR’s company also has a tool called Walrus which everyone in the practice can use to find areas with missing data.
Walrus also provides information on data quality, risk/clinical, PIPQI, MBS item eligibility, as well as patient timelines, patient summaries and clinical graphs.
Speak to a QIPC officer about using Walrus in your practice.
Continuous data quality improvement is simplified for practices who partner with SWSPHN and participate in the QIPC program, and gain access to resources and guidance on using POLAR.
Links
RACGP Standards for general practices, 5th edition
POLAR and WALRUS: edu.polarexplorer.org.au
Help us improve
We welcome your feedback or suggestions on the QIPC program. To help us improve, please complete the evaluation form:
QIPC Program Evaluation
Please contact your assigned Practice Support officer or Health Systems Improvement officer if you would like further information about QIPC program or support in using POLAR and Walrus.
Contact the SWSPHN HSI team via email at HSIsupport@swsphn.com.au to learn more about QI activities.
Additional resources are available on the SWSPHN QIPC webpage.