The effect of local hospital waiting times on GP referrals for suspected cancer

INTRODUCTION

Reducing waiting times is a major policy objective in publicly-funded healthcare systems. However, reductions in waiting times can produce a demand response, which may offset increases in capacity. Early detection and diagnosis of cancer is a policy focus in many OECD countries, but prolonged waiting periods for specialist confirmation of diagnosis could impede this goal. We examine whether urgent GP referrals for suspected cancer patients are responsive to local hospital waiting times.

METHOD

We used annual counts of referrals from all 6,667 general practices to all 185 hospital Trusts in England between April 2012 and March 2018. Using a practice-level measure of local hospital waiting times based on breaches of the two-week maximum waiting time target, we examined the relationship between waiting times and urgent GP referrals for suspected cancer. To identify whether the relationship is driven by differences between practices or changes over time, we estimated three regression models: pooled linear regression, a between-practice estimator, and a within-practice estimator.

RESULTS

Ten percent higher rates of patients breaching the two-week wait target in local hospitals were associated with higher volumes of referrals in the pooled linear model (4.4%; CI 2.4% to 6.4%) and the between-practice estimator (12.0%; CI 5.5% to 18.5%). The relationship was not statistically significant using the within-practice estimator (1.0%; CI -0.4% to 2.5%).

CONCLUSION

The positive association between local hospital waiting times and GP demand for specialist diagnosis was caused by practices with higher levels of referrals facing longer local waiting times. Temporal changes in waiting times faced by individual practices were not related to changes in their referral volumes. GP referrals for diagnostic cancer services were not found to respond to waiting times in the short-term. In this setting, it may therefore be possible to reduce waiting times by increasing supply without consequently increasing demand.

Wearable Collector for Noninvasive Sampling of SARS-CoV-2 from Exhaled Breath for Rapid Detection

Airborne transmission of exhaled virus can rapidly spread, thereby increasing disease progression from local incidents to pandemics. Due to the COVID-19 pandemic, states and local governments have enforced the use of protective masks in public and work areas to minimize the disease spread. Here, we have leveraged the function of protective face coverings toward COVID-19 diagnosis. We developed a user-friendly, affordable, and wearable collector. This noninvasive platform is integrated into protective masks toward collecting airborne virus in the exhaled breath over the wearing period. A viral sample was sprayed into the collector to model airborne dispersion, and then the enriched pathogen was extracted from the collector for further analytical evaluation. To validate this design, qualitative colorimetric loop-mediated isothermal amplification, quantitative reverse transcription polymerase chain reaction, and antibody-based dot blot assays were performed to detect the presence of SARS-CoV-2. We envision that this platform will facilitate sampling of current SARS-CoV-2 and is potentially broadly applicable to other airborne diseases for future emerging pandemics.