The development of the Primary Care Clusters Multidimensional Assessment (PCCMA): A mixed-methods study

Area of Science:

• Health Services Research
• Primary Care Management
• Healthcare Quality Improvement

Background:

• A robust primary care (PC) system is crucial for efficient, high-quality healthcare.
• Multidisciplinary/multiagency teams (PC clusters) are increasingly adopted globally to deliver PC at scale.
• A systematic and comprehensive assessment tool for PC clusters is needed.

Purpose of the Study:

• To develop a quantitative instrument for systematically assessing primary care (PC) clusters.
• To create a comprehensive evaluation tool for multidisciplinary/multiagency PC teams.
• To inform healthcare policy on PC cluster models.

Main Methods:

• A non-experimental, mixed-methods study involving PC cluster leads and stakeholders in Wales.
• Four work packages included interviews, a systematic review of assessment frameworks, expert group drafting, and stakeholder workshops.
• A 53-indicator online assessment tool was developed and evaluated.

Main Results:

• A novel, 53-indicator assessment instrument covering 11 systemic dimensions of PC was finalized.
• The instrument provides a comprehensive evaluation of PC cluster functioning.
• The tool was developed through rigorous mixed-methods research and stakeholder engagement.

Conclusions:

• The developed instrument offers a systematic and comprehensive method for evaluating primary care (PC) clusters.
• This 360-degree assessment tool can guide healthcare policy decisions for PC cluster expansion and adjustment.
• The instrument supports evidence-based improvements in scaled-up PC service delivery.