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[Predicting individual risk of high healthcare cost to identify complex chronic patients].
- Source :
-
Gaceta sanitaria [Gac Sanit] 2014 Jul-Aug; Vol. 28 (4), pp. 292-300. Date of Electronic Publication: 2014 Apr 13. - Publication Year :
- 2014
-
Abstract
- Objective: To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients.<br />Methods: A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC).<br />Results: Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902).<br />Conclusions: High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care.<br /> (Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.)
- Subjects :
- Ambulatory Care economics
Ambulatory Care statistics & numerical data
Area Under Curve
Chronic Disease epidemiology
Comorbidity
Cross-Sectional Studies
Delivery of Health Care, Integrated statistics & numerical data
Diagnosis-Related Groups
Female
Forecasting
Health Maintenance Organizations statistics & numerical data
Health Resources statistics & numerical data
Health Services Needs and Demand
Hospitalization economics
Humans
Male
Predictive Value of Tests
Prescription Fees statistics & numerical data
Risk
Sensitivity and Specificity
Spain epidemiology
Chronic Disease economics
Delivery of Health Care, Integrated economics
Health Care Costs statistics & numerical data
Health Maintenance Organizations economics
Health Resources economics
Models, Economic
Subjects
Details
- Language :
- Spanish; Castilian
- ISSN :
- 1578-1283
- Volume :
- 28
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Gaceta sanitaria
- Publication Type :
- Academic Journal
- Accession number :
- 24725630
- Full Text :
- https://doi.org/10.1016/j.gaceta.2014.03.003