Table 6 Data custodian and user perspectives on barriers and enablers of secondary use of primary care data

BARRIERS (themes arising)

Fear, reticence and lack of trust

GP concerns for patient privacy and not perceiving value in secondary data use impacting willingness share data.

Fear or lack of trust of data security. Fear of privacy breaches or ‘illegal’ data use resulting in harm. GPs’ fear that they record data of insufficient quality for sharing. Fear that sharing data may increase government control of GPs (lack of trust of government).

Leadership, governance & ethical constraints

Leadership, legal and regulatory issues: confused determination of who ‘owns’ or is ‘in charge’ of data. Federal-state divide and no ‘national approach’ to data collection. Limited engagement between key stakeholders. Protection of intellectual or commercial interesting as barrier to coordination of effort to optimise data use, thus leading to duplication of effort.

Ethics and governance: Barriers to access including stringent ethical constraints, data governance protocols, data access controls and confidentiality restrictions. Lack of transparency of consent models, governance processes and methodologies leading to lack of trust in data sharing. Expensive, cumbersome and slow processes for data access approvals.

Lack of clarity on what constitutes ‘deidentified’ data and concern about sharing ‘deidentified’ data without explicit patient consent.

Lack of data availability

Lack of available longitudinal patient data. Incomplete data entry by service providers.

Lack of access due to cost or awareness

Limited knowledge about what data are available and how to access it. Prohibitive cost to access data for research. The high costs charged by vendors to use their data extraction tools and to access extended tool applications and enhancements.

Lack of expertise, experience & incentive

Too few clinicians involved in planning data analyses and in reaching research conclusions. General practice staff not motivated to collect clean, accurate and complete data. Absence of shared vision/capacity to build systems to utilise current non-standardised data sources.

Barriers to data linkage

Inability to link patient data. Lack of a reliable individual person identification numbers for data linkage. Lack of availability of, and access to, some datasets needed for linkage (lack of stakeholder agreement and governance arrangements).

Technical systems barriers

(and lack of systems to improve data quality and quantity)

Lack of standardisation and interoperability of electronic medical records (EMRs) and their coding, classifications, data definitions, and of data extracted using different extraction tools, leading to variable data structures and quality decreasing data utility. Inconsistent and poor mapping of medical terms within clinical software systems.

Data extractions tools unable to collect from all clinical software systems. Poor data quality (completeness, cleanliness, granularity) as barrier to better use. Inadequate national digital health record, lack of primary care minimum data set and lack of consensus on what a minimum dataset should include. Relatively few providers of data warehousing.

Health system & resource barriers

Structural: Most primary care providers as private businesses where owner has choice in data capture systems and voluntary data sharing; and the public being free to visit any practitioner, a barrier to longitudinal patient records.

Workforce: The high general practice staff turnover negatively impacting data input and quality (brain drain).

Timelines: slow release of data affecting timeliness of evaluation and needs assessments.

Funding/Cost:

 Lack of funding to collect and analyse data and to support the implementation of findings;

 Lack of motivation, capacity, resources and education to prioritise data input and improve data quality;

 Lack of research resources to interpret data (including for Primary Health Networks to interpret for planning purposes);

 Insufficient research and skills/capacity building funding for the academic primary care sector.

ENABLERS (themes arising)

Qualities

Build primary care provider and public trust of data custodians and users. Reassurance of appropriate use of data. Grow awareness and knowledge of the value and application of primary care data (create shared vision). Ensure transparency in data access and use. Use innovative and forward-thinking solutions. Altruism prompts data sharing.

Leadership

Leadership from: Universities (for expertise and engagement in secondary use); Primary Health Networks (utilising their relationships with general practice); GP Colleges; and other organisations as appropriate

Governance

Improved, ‘tighter’ or ‘clearer’ governance with: unambiguous and agreed strategic framework(s), agreed processes, clarity of government position, incorporation of robust safeguards for dataaccess and use. Clearer guidelines and steps on how to deidentify data and recognise when data are no longer deidentified and complies with both state and national privacy and data protection legislations. Support for national adoption of a single GP data extraction tool and centralised coordination and management of GP data (to decrease duplication of effort). Incentive payments to clinicians to encourage improvement of data quality & data sharing

Partnerships and capacity building

Facilitate engagement between key stakeholders: clinicians, consumers, government, researchers, Primary Health Networks. Expand practice-based research-oriented networks to facilitate access to primary care data.

Educate: Open pathways to greater secondary use of data by turning clinicians’ data into knowledge delivered back to them for business and care improvement. Have clinicians benefit from review and audit of their own data so they experience how accurate vs inaccurate data capture can benefit or limit them. Build researchers’ capacities to access and interpret data.

Enable consumers to understand the research value of primary care data (especially when linked to other datasets) and build on public expectation/perception that policymakers may already use linked data systems to improve services.

Raise cross-sector capacity of and willingness for data linkage.

Technologies and method development

Better use of secondary data through advancement in computing hardware and software technologies, interoperability of data collection tools, or adoption of a single extraction too capable of working across multiple vendor software packages.

Improved portals for practice display of data to encourage continuous quality improvement in data capture.

Advancement in: data storage and IT security, technical cross-sectoral capability to enable data linkage, data and coding standardisation/consistency, systematic data quality assurance, mechanisms for appropriate data interpretation.

Resources

Funding to:

Train primary care staff and clinicians in health informatics and educate on data value and best practice data collection, quality improvement and better use of own data (workforce upskilling). Have computer scientists and health informaticians support practices to capture quality data and enable its use. Build a national primary care dataset that is accessible and affordable for researchers and provide incentives to primary care practices to share data.

Extraction tools that meet data user-needs.

Time to demonstrate good outcomes resulting from secondary use of primary care data.