Highlights
- •Progressive aging of the population represents a challenge for health care systems.
- •Diagnoses and drugs variables explain a relevant percentage of total costs variance.
- •ACG System predicts healthcare costs, improving the equity of the capitation system.
Abstract
Background
The Italian National Health Service (NHS) provides universal coverage to all citizens,
granting primary and hospital care with a copayment system for outpatient and drug
services. Financing of Local Health Trusts (LHTs) is based on a capitation system
adjusted only for age, gender and area of residence. We applied a risk-adjustment
system (Johns Hopkins Adjusted Clinical Groups System, ACG® System) in order to explain
health care costs using routinely collected administrative data in the Veneto Region
(North-eastern Italy).
Methods
All residents in the Veneto Region were included in the study. The ACG system was
applied to classify the regional population based on the following information sources
for the year 2015: Hospital Discharges, Emergency Room visits, Chronic disease registry
for copayment exemptions, ambulatory visits, medications, the Home care database,
and drug prescriptions. Simple linear regressions were used to contrast an age-gender
model to models incorporating more comprehensive risk measures aimed at predicting
health care costs.
Results
A simple age-gender model explained only 8% of the variance of 2015 total costs. Adding
diagnoses-related variables provided a 23% increase, while pharmacy based variables
provided an additional 17% increase in explained variance. The adjusted R-squared
of the comprehensive model was 6 times that of the simple age-gender model.
Conclusions
ACG System provides substantial improvement in predicting health care costs when compared
to simple age-gender adjustments. Aging itself is not the main determinant of the
increase of health care costs, which is better explained by the accumulation of chronic
conditions and the resulting multimorbidity.
Keywords
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Article info
Publication history
Published online: March 04, 2018
Accepted:
February 27,
2018
Received in revised form:
February 26,
2018
Received:
December 1,
2017
Identification
Copyright
© 2018 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
