Network Data Lab - Topic 5: Waiting Lists

Project Description

This Health Foundation Network Data Lab (NDL) project linked elective waiting list records to primary and secondary care datasets for over 3 million patients across the Cheshire & Merseyside Integrated Care Board, covering waiting list start dates from April 2022 to March 2024.

The study aimed to understand who is waiting for elective treatment, how long they wait, why they leave the waiting list, and what the health consequences of longer waiting are.

Key areas of analysis:

• Cohort linkage: Matched Waiting List Minimum Data Set (WLMDS) records to SUS-APCS, SUS-OPA, SUS-ECDS, and GP datasets using patient ID, treatment function, and RTT start date, producing a linked cohort of 1.8 million elective pathways
• Inequalities in wait length: Described variation by age, gender, ethnicity, deprivation, frailty, and long-term condition status — finding that minority ethnic groups face systematically longer delays, and that patients with unknown LTC/frailty status also wait longer
• Specialty analysis: Identified Trauma & Orthopaedics, ENT, Gynaecology, and Neurology as having the highest proportions of long waiters (19+ weeks), while Elderly Medicine and General Internal Medicine show shorter waits
• Removal reasons: Of 1.82 million pathways, 46% received first treatment, 30% were given a decision not to treat, and 0.5% died before treatment — with notable inequalities by specialty, gender, ethnicity, and deprivation
• Healthcare activity before, during, and after waiting: Compared GP appointments, A&E attendances, and prescribing (including depression and pain relief medications) across the three periods, finding that prescribing peaks during the waiting period
• Difference-in-Differences (DiD) analysis: Estimated the causal impact of wait length on A&E and GP utilisation for three procedures (hip replacement, cholecystectomy, cardiothoracic surgery), finding a statistically significant increase in A&E attendances for hip replacement patients waiting 19–30 weeks

The project included a PPIE component with structured interviews covering patient experience of waiting for specific procedures and broader NHS elective care, with findings informing the analytical priorities.

Skills Used

• SQL / R / RStudio (data linkage, GLM, Difference-in-Differences)
• NHS Secure Data Environment (SDE / NDL)
• Waiting List Minimum Data Set (WLMDS)
• Multi-dataset linkage (SUS-APCS, SUS-OPA, SUS-ECDS, GP)
• Health inequalities analysis
• Causal inference (DiD)
• Public and Patient Involvement and Engagement (PPIE)