Implementation > Executing the implementation > Data management and analysis

Effective data management and analysis are crucial for implementation and continuous improvement. This section outlines key considerations for collecting, analysing and utilising data.

Importance of data collection

Systematic data collection enables organisations to monitor the effectiveness of the psychosocial matched care system, identify areas for improvement and make data-driven decisions. It also supports transparency and accountability in the implementation process.

Types of data to collect

•Screening results (for example, ÖMPSQ-SF scores)

•Intervention outcomes (for example, RTW rates and claim durations)

•Process measures (for example, time from screening to intervention)

•Stakeholder feedback (for example, worker satisfaction and case manager experiences)

•Cost-related data (for example, healthcare and total claim costs)

Data analysis techniques

•Trend analysis to track changes over time

•Comparative analysis between intervention and any control groups

•Comparative analysis of provider outcomes

•Cost-benefit analysis to assess the financial impact of the program

•Qualitative analysis of stakeholder feedback

Privacy and security considerations

Organisations should:

•implement robust data protection measures to ensure the confidentiality and security of sensitive health information

•Adhere to relevant data protection regulations, and

•obtain necessary consents for data collection and use.