Faster Diagnosis and Treatment for Cancer: Assessing Patient Pathways Using a Panel Regression Analysis of the English National Cancer Registration Data.

OBJECTIVES: Timely treatment is crucial for patients with cancer, affecting both their experience and outcomes. This study examined events that shorten or extend cancer pathways. METHODS: A cohort of breast, lower gastrointestinal, lung, and prostate cancers diagnosed between 2015 and 2016 in England were identified using cancer registration data. This was linked to Hospital Episode Statistic data, Cancer Waiting Times data, and specialized treatment data sets to highlight key events and dates in the pathways of 236 205 patients. Our fixed-effects panel regression included straight-to-test first appointments, multiple tests on the same day, number of multidisciplinary team meetings, appointment cancellations, trust fixed effects, and patient factors, including sex, ethnicity, index of multiple deprivations, age, comorbidities, stage, and route to diagnosis. RESULTS: Patients with straight-to-test, multiple tests on the same day, and who were discussed in a single multidisciplinary team meeting waited a shorter time for treatment (-5, -4, and -7 days, respectively). Cancelled appointments and attending multiple providers were associated with longer pathways (+11 and +9 days). CONCLUSIONS: Our findings highlight specific areas in which redesigning cancer pathways and transfers between hospitals could potentially lead to less waiting time for treatment, and suggest that policies aimed at reducing cancellations, by patients or hospitals, have the potential to improve waiting times.

Waiting times in emergency departments: exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data.

BACKGROUND: Long lengths of stay (also called waiting times) in emergency departments (EDs) are associated with higher patient mortality and worse outcomes. OBJECTIVE: To add to the literature using high-frequency data from a large number of hospitals to analyse factors associated with long waiting times, including exploring non-linearities for 'tipping points'. METHODS: Multivariate ordinary least squares regressions with fixed effects were used to analyse factors associated with the proportion of patients in EDs in England waiting more than 4 hours to be seen, treated and admitted or discharged. Daily situation reports (Sitrep), hospital episode statistics and electronic staffing records data over 90 days between December 2016 and February 2017 were used for all 138 English NHS healthcare providers with a major ED. RESULTS: Higher inpatient bed occupancy was correlated with longer ED waiting times, with a non-linear association. In a full hospital, with 100% bed occupancy, the proportion of patients who remained in the ED for more than 4 hours was 9 percentage points higher (95% CI 7.5% to 11.1%) than with an 85% occupancy level. For each percentage point change in the following factors, the proportion of ED stays over 4 hours also increased: more inpatients with hospital length of stay over 21 days (0.07%, 95% CI 0.008% to 0.13%); higher emergency admissions (0.08%, 95% CI 0.06% to 0.10%); and lower discharges relative to admissions on the same day (0.04%, 95% CI 0.02% to 0.06%), the following day (0.05%, 95% CI 0.03% to 0.06%) and at 2 days (0.05%, 95% CI 0.04% to 0.07%). CONCLUSIONS: These results suggest that tackling patient flow and capacity in the wider hospital, particularly very high bed occupancy levels and patient discharge, is important to reduce ED waiting times and improve patient outcomes.