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• W2000591074 abstract "BackgroundA major challenge facing the National Health Service in England is coping with the demand caused by a growing and ageing population. However, the prevalences of some chronic conditions within the population are also rising. We explore the additional increase in demand that this increase might cause.MethodsWe grouped hospital services in England into four types: elective inpatient, emergency inpatient, outpatient, and accident and emergency. We built a model for each type to predict the health-care activity for a person, based on their age, sex, geographical region, whether they died within that year, and presence of some chronic conditions. Data were collected from the National Health Service and the Office for National Statistics. We linked these data for 2009–10 for each person with a pseudoanonymised unique person identifier. We selected 12 conditions: arthritis, asthma, cancer, chronic obstructive pulmonary disease, coronary heart disease, dementia, diabetes, epilepsy, heart disease, mental illness, renal disease, and stroke. We identified the codes from International Classification of Diseases 10 specific for each condition. People were flagged as having an illness if at least one related code appeared in the diagnosis codes from the inpatient data in the year. Models were built on a 10% sample of the population. We used a least squares regression model for each hospital activity type to estimate the personal activity associated with the independent variables. We used a Poisson transformation to account for the skew caused by high numbers of people with no activity. We calculated cost of predicated activity with the average cost for the combination of dependent variables in 2009–10. To estimate the effect of future prevalence of chronic conditions, we identified the number of people with relevant diagnosis codes in Hospital Episode Statistics between 2004–05 and 2009–10 by age and sex. We then forecast the proportion of people in each group likely have each condition with Office for National Statistics principal population estimates for the same period as a denominator. To test the effect of population growth versus increased prevalence, we ran the model holding prevalence at the 2009 value, increasing the population (population effect); then holding the population steady and changing the prevalence (condition effect). Finally, we ran the model with both increasing to get an overall prediction.FindingsHospital costs caused by population growth will increase from £38·7 billion to £45·0 billion (16% increase) from 2009–10, to 2021–22. However, if the present trend for treating conditions in hospitals is applied to the 2009 population, hospital costs would rise to £45·5 billion (18% increase) by 2021–22. The predicted increase from combination of the two drivers for demand is 38% (to £53·3 billion), far more than because of population growth alone.InterpretationMore than half of the additional demand for health services over the next decade will be caused by an increase in the prevalence of chronic conditions, rather than population growth and ageing. The forecast assumes that the methods used to record diagnoses codes have been constant. Some of the increase in prevalence of chronic conditions is probably caused by an increase in the number of comorbidities recorded during an inpatient stay.FundingNuffield Trust." @default.
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• W2000591074 date "2012-10-01" @default.
• W2000591074 modified "2023-10-16" @default.
• W2000591074 title "Future demand for health care: a modelling study" @default.
• W2000591074 doi "https://doi.org/10.1016/s0140-6736(13)60306-2" @default.
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