Abstract
Objectives To develop a formula for allocating resources for
commissioning hospital care to all general practices in England based
on the health needs of the people registered in each practice
Design Multivariate prospective statistical models were developed in
which routinely collected electronic information from 2005-6 and 2006-7
on individuals and the areas in which they lived was used to predict their
costs of hospital care in the next year, 2007-8. Data on individuals
included all diagnoses recorded at any inpatient admission. Models were
developed on a random sample of 5 million people and validated on a
second random sample of 5 million people and a third sample of 5 million
people drawn from a random sample of practices.
Setting All general practices in England as of 1 April 2007. All NHS
inpatient admissions and outpatient attendances for individuals registered
with a general practice on that date.
Subjects All individuals registered with a general practice in England
at 1 April 2007.
Main outcome measures Power of the statistical models to predict the
costs of the individual patient or each practice’s registered population
for 2007-8 tested with a range of metrics (R2 reported here). Comparisons
of predicted costs in 2007-8 with actual costs incurred in the same year
were calculated by individual and by practice.
Results Models including person level information (age, sex, and ICD-10
codes diagnostic recorded) and a range of area level information (such
as socioeconomic deprivation and supply of health facilities) were most
predictive of costs. After accounting for person level variables, area level
variables added little explanatory power. The best models for resource practice level, and about 12% at the person level. With these models,
the predicted costs of about a third of practices would exceed or
undershoot the actual costs by 10% or more. Smaller practices were
more likely to be in these groups.
Conclusions A model was developed that performed well by
international standards, and could be used for allocations to practices
for commissioning. The best formulas, however, could predict only about
12% of the variation in next year’s costs of most inpatient and outpatient
NHS care for each individual. Person-based diagnostic data significantly
added to the predictive power of the models.
commissioning hospital care to all general practices in England based
on the health needs of the people registered in each practice
Design Multivariate prospective statistical models were developed in
which routinely collected electronic information from 2005-6 and 2006-7
on individuals and the areas in which they lived was used to predict their
costs of hospital care in the next year, 2007-8. Data on individuals
included all diagnoses recorded at any inpatient admission. Models were
developed on a random sample of 5 million people and validated on a
second random sample of 5 million people and a third sample of 5 million
people drawn from a random sample of practices.
Setting All general practices in England as of 1 April 2007. All NHS
inpatient admissions and outpatient attendances for individuals registered
with a general practice on that date.
Subjects All individuals registered with a general practice in England
at 1 April 2007.
Main outcome measures Power of the statistical models to predict the
costs of the individual patient or each practice’s registered population
for 2007-8 tested with a range of metrics (R2 reported here). Comparisons
of predicted costs in 2007-8 with actual costs incurred in the same year
were calculated by individual and by practice.
Results Models including person level information (age, sex, and ICD-10
codes diagnostic recorded) and a range of area level information (such
as socioeconomic deprivation and supply of health facilities) were most
predictive of costs. After accounting for person level variables, area level
variables added little explanatory power. The best models for resource practice level, and about 12% at the person level. With these models,
the predicted costs of about a third of practices would exceed or
undershoot the actual costs by 10% or more. Smaller practices were
more likely to be in these groups.
Conclusions A model was developed that performed well by
international standards, and could be used for allocations to practices
for commissioning. The best formulas, however, could predict only about
12% of the variation in next year’s costs of most inpatient and outpatient
NHS care for each individual. Person-based diagnostic data significantly
added to the predictive power of the models.
| Original language | English |
|---|---|
| Pages (from-to) | 1-16 |
| Journal | British medical journal |
| Volume | 343 |
| Issue number | 7833 |
| DOIs | |
| Publication status | Published - 26 Nov 2011 |
Keywords
- Adult Aged Budgets Costs and Cost Analysis England Female *Financial Management General Practice/*economics/organization & administration Humans Male Middle Aged *Models, Economic Multivariate Analysis Prospective Studies Resource Allocation/*economics State Medicine/economics