How will health needs be measured in districts? Implications of variations in hospital use

Abstract

Under the proposals in Working for Patients, Health Authorities will need to assess health needs in the populations for which they will become responsible, in order to ensure that optimal contracts are placed for hospital care. It seems inevitable that this process will have to be based at least in part on previous utilization data. Utilization data are known to be strongly influenced by the supply of facilities, particularly beds; unless this can be taken into account there is a likelihood that historical patterns will simply be perpetuated whether justified or not. We have used multiple regression analysis with nationally available data to investigate the effects of supply as well as of need and demand indicators on variations in hospital utilization rates. We describe how the approach may be taken by Health Authorities as the basis for a staged assessment of local levels of utilization, so that they may target further and more detailed investigation more efficiently.

Health needs assessment: Development and importance of health needs assessment

“…Demand from patients for a service can depend on the characteristics of the patient or on the media's interest in the service. Demand can also be induced by supply: geographical variation in hospital admission rates is explained more by the supply of hospital beds than by indicators of mortality 21 22; referral rates of general practitioners owe more to the characteristics of individual doctors than to the health of their populations 23…”

The continuing rise in emergency admissions

“…Supply side factors are also important 11. These include the continuing consultant expansion of about 2% a year and, as predicted by Roemer's law, admissions increasing to the limit of bed availability 1.…”

Assessing the Health Needs of a Population

“…The demand of patients for health care services can also be influenced by characteristics of individual doctors or health care organisations, as shown in Table 1. For example, a research study showed that hospital admission rates were influenced more strongly by the availability of beds than by the prevalence of illness in the local population (Kirkup & Forster, 1990).…”