National Health Reform

Concept of Operations: Relating to the introduction of a Personally Controlled Electronic Health Record System

4.2.1 Data quality

Ensuring a high standard of data quality is an essential requirement for the PCEHR System. High levels of data quality are required to assist healthcare providers and individuals in making safe healthcare decisions. Data quality within the PCEHR System will be ensured through a combination of validation of data loaded into the system, working with operators or source systems to improve the quality of data they are able to provide and by ongoing monitoring of data quality.

Validation

One tactic employed by the PCEHR System to ensure data quality meets a minimum standard is to validate clinical documents loaded into the system. Validation includes:

• Ensuring that the structure and content of clinical document matches the template describing its content structure and data types (see Section 6.5.1 for the template service).
• Ensuring the integrity of any included identifier for individuals, healthcare providers or organisation.

Clinical documents that fail validation will be rejected by the PCEHR System and the source system will need to supply a corrected version.

Quality of data within source systems

The PCEHR System relies on data extracted from a range of source systems, which means the quality of the data in the PCEHR System is dependent on the quality of the data in the source system.

To help ensure that source systems are capable of providing data to a minimum standard, any systems that connect to the PCEHR System will be required to undergo conformance assessment prior to obtaining a PCEHR System Notice of Connection (see Section 7.4).

To help healthcare organisations meet a set of minimum standards around data quality within their source systems, the Change and Adoption Program will include an element devoted to enhancing the quality of data within source systems (see Section 8.4.2).

Monitoring data quality

Achieving a high standard of data quality will be challenging, as it will require continuous measurement and targeted improvements in culture, policies, processes and technology. To help support this change over time, the PCEHR System will implement a quality management framework and system that addresses the fundamentals of data quality, including:

• Stakeholder-driven identification of key metrics and their associated collection protocols on quality dimensions such as accuracy, completeness, consistency, currency, timeliness, fitness for use, provenance and compliance.
• The identification of minimum levels to be achieved within a specified timeframe.
• Preventative and corrective actions to be taken to improve data quality (including technical solutions such as enhancing data entry screens or fixing back-end system issues and non-technical solutions such as training).
• The creation of a series of data quality reports (e.g. via a ‘data quality dashboard’) to help profile and track different metrics in relation to their targets.
• The introduction of an issue tracking system to track known issues and progress of corrective actions.

The quality management system will be embedded within a broader governance model (see Section 7.2) and will also be embedded within a Service Level Agreement and subject to performance management.

Achieving high standards of data quality is a not a single step process. It will be a process that runs over the entire life of the PCEHR System and will require continuous improvement.

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