The Laboratory-Based Intermountain Validated Exacerbation (LIVE) Score Identifies Chronic Obstructive Pulmonary Disease Patients at High Mortality Risk.

Denitza P Blagev,Matthew M Churpek,Dave S Collingridge,Mehrdad Arjomandi,Richard A Mularski,Kyle A Carey,Susan Rea,Siyang Zeng,Benjamin D Horne,Valerie G Press

doi:10.3389/fmed.2018.00173

Abstract

Background: Identifying COPD patients at high risk for mortality or healthcare utilization remains a challenge. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR.Methods: Cluster analysis was used in 5,006 patients with COPD at Intermountain to identify clusters based on a large collection of clinical variables. Recursive Partitioning (RP) was then used to determine a preferred tree that assigned patients to clusters based on a parsimonious variable subset. The mortality, COPD exacerbations, and comorbidity profile of the identified groups were examined. The findings were validated in an independent Intermountain cohort and in external cohorts from the United States Veterans Affairs (VA) and University of Chicago Medicine systems.Measurements and Main Results: The RP algorithm identified five LIVE Scores based on laboratory values: albumin, creatinine, chloride, potassium, and hemoglobin. The groups were characterized by increasing risk of mortality. The lowest risk, LIVE Score 5 had 8% 4-year mortality vs. 56% in the highest risk LIVE Score 1 (p < 0.001). These findings were validated in the VA cohort (n = 83,134), an expanded Intermountain cohort (n = 48,871) and in the University of Chicago system (n = 3,236). Higher mortality groups also had higher COPD exacerbation rates and comorbidity rates.Conclusions: In large clinical datasets across different organizations, the LIVE Score utilizes existing laboratory data for COPD patients, and may be used to stratify risk for mortality and COPD exacerbations.

Highlights

Chronic obstructive pulmonary disease (COPD) is a disease of increasing prevalence and mortality worldwide [1, 2]
While pulmonary function tests (PFT) are the cornerstone of diagnosis and treatment of COPD, functional impairment, disability, and overall mortality have been inadequately predicted by the forced expiratory volume in 1 second (FEV1) alone [3,4,5,6,7,8]
While prior risk scores in COPD have used PFT and dyspnea scores to identify subgroups of COPD patients [20], those data are not routinely available to be queried in most current Electronic Health Records (EHRs), and have limited utility when designing interventions to improve COPD care within a healthcare system

Summary

Introduction

Chronic obstructive pulmonary disease (COPD) is a disease of increasing prevalence and mortality worldwide [1, 2]. Several risk stratification tools have been developed, which predict mortality in COPD patients [20,21,22]. While prior risk scores in COPD have used PFT and dyspnea scores to identify subgroups of COPD patients [20], those data are not routinely available to be queried in most current Electronic Health Records (EHRs), and have limited utility when designing interventions to improve COPD care within a healthcare system. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR

Objectives

Methods

Results

Conclusion