The need for general medical services: a literature review

Abstract

General Medical Services (GMS) are provided mainly through Family Practices, on a demand led basis: that is, there is no cash limit expect for certain specified selected services such as Practice Nurses etc. Nevertheless, since 1948, the Medical Practices Committee (MPC) have influenced the delivery of GMS through a system of allowances for areas designated as under-doctored; and, of course, there are deprivation payments (mostly in urban areas) and the rural practice allowance. However, there have been questions about the extent to which the provision of GMS - and specifically the distribution of General Practitioners (GPs) between areas - is equitable. The purpose of this review of the literature on the need for GMS was to provide a background to discussions about ways in which the current methods being used to guide the MPC decisions about the distribution of GPs could be improved. In the first section, this context and the current situation are briefly described. Before discussing the determinants of consultations workload, we show, in the second section, how the proportions actually getting as far as a consultation are considerably smaller than the proportions claiming at any one time to be ill, and set out a crude model of the pathways to a consultation, which sets the framework for the subsequent review. We also discuss the controversies over the measurement of workload itself: ideally, we want to be able to measure ‘real’ utilisation including both the length and complexity of the consultation, whilst controlling for variations between general practitioners. The factors influencing the demand for primary care are considered in the third section. Demand for primary care consultations is influenced by certain socio-economic factors (age, sex, housing tenure, unemployment, social class, family structure/marital status, rural/urban residence, ethnic group) which are related to the prevalence and incidence of illness. Less reliable, but equally important determinants of demand, are the pathways to primary care charted by individuals on the basis of the patient's perceptions of illness and illness behaviour which are set out in section two. Other factors affecting the demand for primary care consultations are considered in the fourth section under the headings of accessibility and organisation of primary care. Accessibility whether in terms of cultural, financial; or physical barriers does make a difference: proximity to a primary care facility increases consultation patterns whereas distance decreases consultation rates. Appointment systems do influence patient demand: in particular follow-up appointments may increase because of the transfer of services from secondary to primary care. Second, there is no conclusive evidence that list size affects GMS utilisation although large list sizes may restrict the amount of time available for individual patients: in some circumstances this may reduce the quality of care provided. Third, preventative services, whilst not always utilised by those most at risk, generate significant added workload. Fourth, the 1990 contract has increased administrative burdens and, by virtue of the availability of clinics, generated added medical workload. In the fifth section, supply issues are briefly considered. Patients do attend A&E departments - especially when they are close - for conditions often more appropriate for primary care but the reasons for this behaviour are complex and difficult to reverse. There are statistical techniques available for adjusting for supply, although this will always be a complicated procedure in this area unless analysis is restricted to individual data. The characteristics of high attenders or those demonstrating increased SPCRs can be summarised • Frequent attendance is often associated with a defined illness whether physical or mental, and this is reflected in a substantial number of GP initiated follow up appointments. • High users perceive themselves to be ill and are anxious or fearful about their symptoms but have faith in the GP rather than a belief in self care. • Increased GMS utilisation is associated with: families with high attendance rates; social classes 4 and 5; ethnic minorities; women; the unemployed; mobile populations; and people from deprived areas. Patients whose response to illness is less likely to be to consult a GP are less prone to worry about symptoms; feel in greater control of their lives; are more sceptical of the effectiveness of the GP's treatment, sometimes as a result of an unsatisfactory past or family experience; and are more prone to use and believe in self care and rely on/possess social/friendship networks. There are therefore a wide range of factors associated with consultations. The few multivariate analyses that have been carried out are discussed in the sixth section: their results demonstrate that both self-reported ill-health and socio-economic deprivation independently affect the level of consultations. There has therefore been a considerable amount of research; in the concluding section we argue that more of the same will not help. The problem is that the different data sets available - although leading to very similar conclusions - each only provide a partial picture. In order to improve on existing evidence, we need data on consultations from a representative sample of practices over a period where data is recorded on both the length and markers for complexity, whilst the patients on their lists are asked to complete a brief questionnaire about both their self-perceived health and their socio-economic status. Nevertheless, despite these problems - which are not, in principle, any more severe than those confronted in other areas where resource allocation formulae have been developed - there is a consensus about the factors influencing the need for GMS (even though there are queries about the consultation measure itself): • first, self-reported ill-health does reflect real morbidity as well as trivial complaints and is a powerful determinant of the propensity to consult; and • second, there are a range of socio-economic factors which are associated with the likelihood of consultation over and above ill-health whether measured in terms of self-report or ‘objectively’. On this basis, a formula could therefore be developed incorporating both a morbidity variable and a combination of socio-economic variables.primary care, general medical services, socio-economic factors