Closing the gap: using prevalence models for long-term conditions in the United Kingdom.
Until now, most healthcare policies have been focused on the relatively small number of patients with long-term conditions who suffer from a high disease burden, and less attention has been directed toward detecting patients with undiagnosed long-term conditions. In the United Kingdom, population-based data on the prevalence of disease detected in primary care are now available. Prevalence models for diabetes, coronary heart disease, hypertension, and chronic obstructive pulmonary disease provide survey-based estimates for small populations based on local data on known risk factors. These suggest that a significant proportion of prevalent disease remains undiagnosed. Other models are being developed. More systematic case finding to close disease prevalence gaps may be cost-effective, but case-finding strategies need to be tested and current and new models require validation.
Department of Primary Care and Social Medicine, Imperial College London, London, United Kingdom. M.soljak@imperial.ac.uk
Michael
M
Soljak
Julian
J
Flowers
D002908:Chronic Disease / Q000453:epidemiology*; D004812:Epidemiologic Methods; D015658:HIV Infections / Q000453:epidemiology; D006801:Humans; D015233:Models, Statistical; D015995:Prevalence; D029424:Pulmonary Disease, Chronic Obstructive / Q000453:epidemiology; D013222:State Medicine; D006113:United Kingdom / Q000453:epidemiology