At Redmoor Health, we are dedicated to helping PCNs optimise their demand and capacity management. Our Optimise Demand and Capacity project aims to utilise data analytics and best practices to provide insights into patient engagement, service usage, and capacity planning.
Optimise Demand & Capacity
Why it's important
Optimising demand and capacity management is crucial for efficient practice operations and ensuring high-quality patient care. By leveraging data analytics, PCNs can make informed decisions, allocate resources effectively, and improve patient satisfaction.
What the project is about
The Optimise Demand and Capacity project focuses on gathering and analysing data from various sources to provide a clear picture of demand and capacity at the PCN level. This helps in identifying trends, making data-driven decisions, and optimising the use of available resources.
Scope
- Engagement Metrics: Using messages to deflect demand from reception and track engagement metrics. Shared PCN posts to enhance communication.
- Website Comparisons: Learning from website comparisons at the PCN level and identifying shared services.
- Telephony and Messaging Comparisons: Comparing telephony, messaging, NHS App, and online consultations to ensure consistent supplier use within the PCN.
- Planned PCN Capacity: Planning and sharing resources at the PCN level to optimise capacity.
- Appointment Book Configuration: Effectively configuring and using the appointment book, including ARRS roles at the PCN level.
- System Identification: Identifying PCN-wide systems and exploring what data can be gathered and shared with practices.
- Data Interpretation: Understanding and interpreting data to draw meaningful insights at the PCN level.
- Data-Driven Decisions: Identifying and following data-driven decisions and trends at the PCN level.
- Comparisons and Shared Services: Making comparisons at the PCN level and identifying shared services.
- Digital Inclusion Gaps: Using data to inform practices where gaps in digital inclusion exist and how to address them at the PCN level.
- PCN Data-Driven Decisions: Making data-driven decisions at the PCN level to enhance demand and capacity management.
Key components
- Engagement Tracking: Monitoring patient engagement through various metrics and shared PCN posts.
- Task Analysis: Understanding the most commonly used online tasks by patients and making necessary comparisons at the PCN level.
- Comprehensive Data Review: Conducting detailed data analytics of communication and consultation tools at the PCN level.
- Capacity Planning: Developing strategies for effective capacity management based on data insights at the PCN level.
- Appointment Book Optimisation: Optimising the configuration and use of the appointment book, including the integration of ARRS roles.
- Systematic Data Collection: Identifying and integrating data from various PCN-wide systems for comprehensive analysis.
- Insight Generation: Interpreting data to generate actionable insights at the PCN level.
- Trend Identification: Tracking and analysing trends to inform PCN-level decisions.
- Health Demand Analysis: Determining high-demand areas through population health data.
- Addressing Digital Gaps: Identifying and addressing gaps in digital inclusion using data at the PCN level.
- Appointment Utilisation: Monitoring and optimising the use of appointments based on data analysis.
Outputs
- Detailed Reports: Comprehensive reports on engagement metrics, task usage, and capacity planning at the PCN level.
- Optimised Processes: Implementing data-driven improvements in practice processes across the PCN.
- Resource Allocation: Enhancing resource allocation based on demand and capacity insights at the PCN level.
- Improved Patient Access: Enhancing patient access to services through optimised appointment management and digital inclusion.
Impact
- Informed Decisions: Making informed decisions based on detailed data analysis at the PCN level.
- Efficient Resource Use: Optimising the use of resources to meet patient demand effectively.
- Enhanced Patient Care: Improving patient care and satisfaction through better access and engagement.
- Reduced Workload: Reducing the workload on staff by streamlining processes and using data-driven strategies.
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