Demand for mental health services is growing fast, with services in England receiving a record 4.6 million referrals in 2022 (up 22% from 2019)¹, and data suggesting one in four people will experience a mental health problem of some kind each year in England².
The NHS recently released waiting list statistics for urgent and emergency mental health care, revealing that demand is still at an all-time high, with bed occupancy above 95% across NHS mental health hospitals³.
The backlog of individuals seeking urgent support has surged, placing significant pressure on an already stretched system, leading to extended waiting times for those in need.
With this in mind, Michael Watson, Principal Consultant at healthcare consultancy Acumentice, shares five data strategies that can support the NHS in achieving a shorter mental health waiting list:
1. Data discovery
Data discovery is a pivotal strategy for NHS mental health waiting list management involving systematically exploring and consolidating data from diverse sources, such as Electronic Patient Records (EPRs), spreadsheets, and locally held lists. The primary objective is to combine these disparate data fragments into a cohesive and streamlined system. This process involves cataloguing data sources, integrating data for a comprehensive view of patient care, assessing data quality, ensuring data compliance, and managing accessibility.
Michael adds: ”Discovering data is not just about gathering it but also about looking at all data and finding vital information to help make better decisions and improve patient care. We must keep an eye on the data and be ready to change as things in the data world change.
”The knowledge gained through data discovery guides the development of a broader data strategy for NHS mental health services, laying the foundation for data-driven healthcare improvements that can optimise resource allocation and patient outcomes.”
2. Patient tracking list (PTL)
“Patient Tracking List (PTL) optimisation is a crucial strategy for improving the management of service users, enhancing transparency and corporate visibility by allowing stakeholders to monitor patients’ progress at various stages of their healthcare journey. Currently, most mental health providers measure clock start to assessment, not the events in between. This needs to change, and the whole patient pathway needs to be measured against the new waiting time standard,” Michael advises.
Efficient patient care is ensured by dedicated Patient Team Leaders (PTLs) overseeing the entire patient journey. This strategy uses data analysis to find areas for improvement, allocate resources wisely, and make informed decisions. It’s an ongoing process with constant monitoring and adjustments to reduce wait times and provide timely care.
3. Data gap analysis
Identifying missing data is a fundamental strategy, reviewing Electronic Patient Records (EPRs) to pinpoint gaps in data, particularly within areas like outcome recording. It also involves assessing the quality of existing data, ensuring its accuracy and reliability to identify and prioritise key data elements essential for informed decision-making and patient care assessment.
Michael states: “To ensure data consistency and easier analysis, standardise and integrate data sources. Improve data quality through internal processes like updated collection methods, staff training, and validation checks. Maintain high data quality standards through continuous monitoring and feedback loops, aiming to use data for better patient waiting lists, care, and decision-making.”
4. Operational intelligence
Operational intelligence is another data-driven strategy essential for enhancing the efficiency and effectiveness of NHS mental health services. It begins with analysing existing data sources to uncover insights into the operational aspects of healthcare delivery. By examining this data, such as waiting lists and EPRs, healthcare providers can identify where delays occur in patient pathways and recognise bottlenecks and inefficiencies in referral, assessment, or treatment stages.
“One of the key benefits of operational intelligence is its ability to guide resource allocation. By understanding where delays occur and why they happen, healthcare providers can allocate personnel, equipment, and facilities to the most needed areas, improving patient flow and reducing wait times,” Michael advises.
5. Ongoing caseload management
Examining the ongoing caseload of long-term patients within NHS mental health services is a strategic approach designed to optimise resource allocation, improve patient-centred care, and enhance the overall efficiency of mental health services.
“By reassessing long-term cases, healthcare providers can efficiently manage treatment resources, ensuring that patients receive the appropriate level of care tailored to their evolving needs. By making sure they are being appropriately managed, space is then freed up to treat other patients,” Michael adds.
Case study: The impact of a new Pathway Patient Tracking List (PTL)
To build a new set of technical systems to allow for whole pathway waiting times to be published in a single patient tracking list (PTL), Barnet, Enfield and Haringey Mental Health NHS Trust and Camden & Islington NHS Foundation Trust appointed Acumentice. The two Trusts were eager to understand the total waiting times of their service users and be early adopters of the new waiting times standards to be introduced nationally for community mental health in April 2024.
Before Acumentice’s support, there were only two waiting lists at these Trusts: a wait to first contact or appointment and a separate wait to second contact or appointment waiting list. This meant that the two organisations did not have visibility over the complete waiting time since referral. This disjointed data could not accurately indicate how waiting times could be reduced across the whole patient journey.
Acumentice visually deﬁned and mapped clinical and administrative pathways with each patient touchpoint and event. Over 60 million patient events and activities were mapped, including two million pathways across circa 640,000 patients. This patient pathway data and new technical systems, such as performance tracking dashboards and architecture to extract critical data sets, have supported the trust by showcasing key waiting time metrics to inform future patient experience improvements and help meet the 2024 waiting time standard.
Michael concludes: “With the demand for mental health services only going upwards and the new waiting time standards set to be introduced at some point soon, the importance of having the right data strategies in place to allow mental health providers to manage and cut waiting lists is clear.
“By combining the above data strategies, these providers can ensure they get a handle on their waiting lists and, more crucially, start to bring them down so people get seen a lot sooner and don’t need to resort to heading to A&E in a state of crisis, for example”.