Exploring factors that affect hospital referral in rural settings : a case study from Norway

INTRODUCTION: A patients needs and the seriousness of the disease are not the only factors that determine referral to hospital. The objective of this study was to analyse whether locum doctors (LDs) have a different pattern of referral to hospital from regular GPs (RGPs). METHODS: All hospital referrals for one year (n = 5566 patients) from two Norwegian rural primary health care (PHC) centres to the nearby district hospital were analysed with regard to ICD-10 diagnosis groups. A major difference between the PHCs was that one had a continuous supply of LDs while the other had a stable group of RGPs. The equal-sized communities were demographically and socio-culturally similar. RESULTS: The PHC centre mainly operated by short-term LDs referred a relatively high number of patients to the district hospital within the diagnosis groups of chapter VI Diseases of the nervous system (proportionate referral rate 210%; p = 0.010), and chapter IX Diseases of the circulatory system (proportionate referral rate 130%; p = 0.048), and a comparatively low number of patients for the diagnostic groups in chapter X Diseases of the respiratory system (p = 0.018), and chapter XIV Diseases of the genitourinary system (p = 0.039), compared with the norm of the district hospitals total population. The number and proportion of the total number of referrals, adjusted for population size, did not differ between the two rural communities. The LD-run PHC centre differed significantly from the total norm in 5 out of 19 ICD chapters, equal to 41% of the patients. CONCLUSIONS: Only one significant difference in hospital referrals related to ICD-diagnoses groups were found between the studied rural PHC centres, but the LD-run PHC differed from the total norm. These differences could neither be explained from the districts consumption of somatic hospital care nor the demographical differences, but were related to staffing at the PHC, that is LDs or RGPs. The analysis also revealed that possible under- and/or over-diagnosing of certain diseases occurred, both having potential medical consequences for the patient, as well as increasing healthcare expenditure