ABSTRACT
OBJECTIVE: This study investigates the impact of primary care utilisation of a symptom-based head and neck cancer risk calculator (Head and Neck Cancer Risk Calculator version 2) in the post-coronavirus disease 2019 period on the number of primary care referrals and cancer diagnoses. METHODS: The number of referrals from April 2019 to August 2019 and from April 2020 to July 2020 (pre-calculator) was compared with the number from the period January 2021 to August 2022 (post-calculator) using the chi-square test. The patients' characteristics, referral urgency, triage outcome, Head and Neck Cancer Risk Calculator version 2 score and cancer diagnosis were recorded. RESULTS: In total, 1110 referrals from the pre-calculator period were compared with 1559 from the post-calculator period. Patient characteristics were comparable for both cohorts. More patients were referred on the cancer pathway in the post-calculator cohort (pre-calculator patients 51.1 per cent vs post-calculator 64.0 per cent). The cancer diagnosis rate increased from 2.7 per cent in the pre-calculator cohort to 3.3 per cent in the post-calculator cohort. A lower rate of cancer diagnosis in the non-cancer pathway occurred in the cohort managed using the Head and Neck Cancer Risk Calculator version 2 (10 per cent vs 23 per cent, p = 0.10). CONCLUSION: Head and Neck Cancer Risk Calculator version 2 demonstrated high sensitivity in cancer diagnosis. Further studies are required to improve the predictive strength of the calculator.
ABSTRACT
BACKGROUND: Variation in general practice (GP) referral rates to outpatient services is well described however variance in rates of referral to acute medical units is lacking. OBJECTIVE: To investigate variance in GP referral rate for acute medical assessment and subsequent need for hospital admission. METHODS: A retrospective cohort study of acute medical referrals from 88 GPs in Lothian, Scotland between 2017 and 2020 was performed using practice population size, age, deprivation, care home residence, and distance from hospital as explanatory variables. Patient-level analysis of demography, deprivation, comorbidity, and acuity markers was subsequently performed on referred and clinically assessed acute medical patients (n = 42,424) to examine how practice referral behaviour reflects clinical need for inpatient hospital care. RESULTS: Variance in GP referral rates for acute medical assessment was high (2.53-fold variation 1st vs. 4th quartile) and incompletely explained by increasing age and deprivation (adjusted R2 0.67, P < 0.001) such that significant variance remained after correction for confounders (2.15-fold). Patients from the highest referring quartile were significantly less likely to require hospital admission than those from the third, second, or lowest referring quartiles (adjusted odds ratio 1.28 [1.21-1.36, P < 0.001]; 1.30 [1.23-1.37, P < 0.001]; 1.53 [1.42-1.65, P < 0.001]). CONCLUSIONS: High variation in GP practice referral rate for acute medical assessment is incompletely explained by practice population socioeconomic factors and negatively associates with need for urgent inpatient care. Identifying modifiable factors influencing referral rate may provide opportunities to facilitate community-based care and reduce congestion on acute unscheduled care pathways.
Managing the populations need for urgent medical care is challenge in many healthcare systems and overcrowding of urgent medical services negatively affects patient experience and can affect timely treatment. In the United Kingdom, the primary sources of patients attending for acute medical care are self-attendance to the hospital or by way of referral by a primary care physician (general practitioner). These data for the first time demonstrate high variation in referral rates for acute medical assessment between general practices which is incompletely explained by factors such as the age, deprivation, distance to the hospital or care home residence status of the care home population. Analysis of over 40,000 of these referrals for urgent medical care was subsequently undertaken to further investigate this variation. After adjusting for important clinical factors, patients referred from "high referring" practices were over 50% less likely to require inpatient hospital care than patients from lower referring practices. This suggests that the threshold for referral varies greatly between individual primary care clinicians, practices, or practice populations and many of these patients may have been suitable for less urgent community-based care. Identification of modifiable factors that account for this unexplained variation may facilitate community-based care and improve patient experience by reducing unnecessary attendance and congestion in already busy emergency care services.