Using information on clinical conditions to predict high-cost patients
about
Using "big data" to capture overall health status: properties and predictive value of a claims-based health risk scorePredicting patients with high risk of becoming high-cost healthcare users in Ontario (Canada)Predicting cost of care using self-reported health status data.Analysing predictors for future high-cost patients using German SHI data to identify starting points for prevention.Using self-reported health measures to predict high-need cases among Medicaid-eligible adults.The Charlson comorbidity index can be used prospectively to identify patients who will incur high future costs.Predictive risk modelling in the Spanish population: a cross-sectional studyLinking individual medicare health claims data with work-life claims and other administrative dataEffects of longitudinal changes in Charlson comorbidity on prognostic survival model performance among newly diagnosed patients with hypertensionOnline Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.Predictors and outcomes of unplanned readmission to a different hospital.Effect of risk adjustment method on comparisons of health care utilization between complementary and alternative medicine users and nonusers.Identifying Future High Cost Individuals within an Intermediate Cost Population.Targeting patients for multimorbid care management interventions: the case for equity in high-risk patient identification.Predicting patient 'cost blooms' in Denmark: a longitudinal population-based study.Well-being and employee health-how employees' well-being scores interact with demographic factors to influence risk of hospitalization or an emergency room visit.Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project.A roadmap for designing a personalized search tool for individual healthcare providers.Identifying patients at risk for high medical costs and good candidates for obesity intervention.Age and the economics of an emergency medical admission-what factors determine costs?Identifying High-Cost, High-Risk Patients Using Administrative Databases in Tuscany, Italy.Culture-Sensitive Question Order Effects of Self-Rated Health Between Older Hispanic and Non-Hispanic Adults in the United States.High inpatient utilization among Veterans Health Administration patients with substance-use disorders and co-occurring mental health conditions.New semiparametric method for predicting high-cost patients.Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated health, and subjective life expectancy in survey instruments.Systematic review of high-cost patients' characteristics and healthcare utilisation
P2860
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P2860
Using information on clinical conditions to predict high-cost patients
description
2010 nî lūn-bûn
@nan
2010 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Using information on clinical conditions to predict high-cost patients
@ast
Using information on clinical conditions to predict high-cost patients
@en
type
label
Using information on clinical conditions to predict high-cost patients
@ast
Using information on clinical conditions to predict high-cost patients
@en
prefLabel
Using information on clinical conditions to predict high-cost patients
@ast
Using information on clinical conditions to predict high-cost patients
@en
P2860
P1476
Using information on clinical conditions to predict high-cost patients
@en
P2093
Joel W Cohen
John A Fleishman
P2860
P304
P356
10.1111/J.1475-6773.2009.01080.X
P577
2010-01-27T00:00:00Z