The interpretation of the reasons for encounter 'cough' and 'sadness' in four international family medicine populations

Inform Prim Care. 2012;20(1):25-39. doi: 10.14236/jhi.v20i1.45.

Abstract

Background: This is a study of the relationships between common reasons for encounter (RfEs) and common diagnoses (episode titles) within episodes of care (EoCs) in family practice populations in four countries.

Method: Participating family doctors (FDs) recorded details of all their patient contacts in an EoC structure using the International Classification of Primary Care (ICPC), including RfEs presented by the patient, and the FDs' diagnostic labels. The relationships between RfEs and episode titles were studied using Bayesian methods.

Results: The RfE 'cough' is a strong, reliable predictor for the diagnoses 'cough' (a symptom diagnosis), 'acute bronchitis', 'URTI' and 'acute laryngitis/tracheitis' and a less strong, but reliable predictor for 'sinusitis', 'pneumonia', 'influenza', 'asthma', 'other viral diseases (NOS)', 'whooping cough', 'chronic bronchitis', 'wheezing' and 'phlegm'. The absence of cough is a weak but reliable predictor to exclude a diagnosis of 'cough', 'acute bronchitis' and 'tracheitis'. Its presence allows strong and reliable exclusion of the diagnoses 'gastroenteritis', 'no disease' and 'health promotion/prevention', and less strong exclusion of 'adverse effects of medication'. The RfE 'sadness' is a strong, reliable predictor for the diagnoses 'feeling sad/depressed' and 'depressive disorder'. It is a less strong, but reliable predictor of a diagnosis of 'acute stress reaction'. The absence of sadness (as a symptom) is a weak but reliable predictor to exclude the symptom diagnosis 'feeling sad/depressed'. Its presence does not support the exclusion of any diagnosis.

Conclusions: We describe clinically and statistically significant diagnostic associations observed between the RfEs 'cough' and 'sadness', presenting as a new problem in family practice, and all the episode titles in ICPC.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Cough / diagnosis*
  • Cough / epidemiology
  • Depression / diagnosis*
  • Depression / epidemiology
  • Diagnosis, Differential
  • Electronic Health Records / statistics & numerical data
  • Episode of Care*
  • Europe / epidemiology
  • Family Practice / statistics & numerical data*
  • Humans
  • Incidence
  • Japan / epidemiology
  • Likelihood Functions
  • Prevalence