Access, continuity of care and consultation quality: which best predicts urgent cancer referrals from general practice?

J Public Health (Oxf). 2014 Dec;36(4):658-66. doi: 10.1093/pubmed/fdt127. Epub 2014 Jan 23.

Abstract

Background: For some cancers, late presentation is associated with poor survival. In England, less than half of patients are diagnosed following a general practitioner-initiated urgent referral. We explore whether particular practice or practitioner characteristics are associated with use of the urgent referral system.

Methods: The study sample was 603/614 practices in the East Midlands. Logistic regression models were fitted to investigate relationships between cancer detection rate, how easy it is to book appointments quickly, in advance or with a preferred doctor, and whether patients have confidence and trust in the doctor.

Results: The percentage of patients who definitely have confidence and trust in the doctor was positively associated with the cancer detection rate [odds ratio = 1.08 (95% confidence interval (CI) 1.01, 1.15) per 10 percentage points]. When all four survey variables were modelled together, the percentage of patients who were able to see a preferred doctor was negatively associated with the cancer detection rate [odds ratio = 0.93 (95% CI 0.88, 0.98) per 10 percentage points].

Conclusions: Our analyses suggest that in the UK National Health Service, confidence and trust in the doctor may be more important in cancer detection than the ease of access or whether there is choice of doctor.

Keywords: cancer; diagnosis; primary care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Appointments and Schedules
  • Black People / statistics & numerical data
  • Continuity of Patient Care
  • Databases, Factual
  • England
  • Female
  • General Practice
  • Health Services Accessibility
  • Humans
  • Linear Models
  • Logistic Models
  • Male
  • National Health Programs
  • Neoplasms / diagnosis
  • Neoplasms / psychology*
  • Patient Satisfaction / statistics & numerical data*
  • Physician-Patient Relations*
  • Quality of Health Care
  • Referral and Consultation / statistics & numerical data*
  • Trust
  • White People