External validation of a multivariable claims-based rule for predicting in-hospital mortality and 30-day post-pulmonary embolism complications.

Craig I Coleman,Jeff R Schein,Laura Becker,Concetta Crivera,W Frank Peacock,Michael Hull,Gregory J Fermann,Mary Ducharme,Erin R Weeda

doi:10.1186/s12913-016-1855-y

Abstract

BackgroundLow-risk pulmonary embolism (PE) patients may be candidates for outpatient treatment or abbreviated hospital stay. There is a need for a claims-based prediction rule that payers/hospitals can use to risk stratify PE patients. We sought to validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule for in-hospital and 30-day outcomes.MethodsWe used the Optum Research Database from 1/2008-3/2015 and included adults hospitalized for PE (415.1x in the primary position or secondary position when accompanied by a primary code for a PE complication) and having continuous medical and prescription coverage for ≥6-months prior and 3-months post-inclusion or until death. In-hospital and 30-day mortality and 30-day complications (recurrent venous thromboembolism, rehospitalization or death) were assessed and prognostic accuracies of IMPACT with 95 % confidence intervals (CIs) were calculated.ResultsIn total, 47,531 PE patients were included. In-hospital and 30-day mortality occurred in 7.9 and 9.4 % of patients and 20.8 % experienced any complication within 30-days. Of the 19.5 % of patients classified as low-risk by IMPACT, 2.0 % died in-hospital, resulting in a sensitivity and specificity of 95.2 % (95 % CI, 94.4–95.8) and 20.7 % (95 % CI, 20.4–21.1). Only 1 additional low-risk patient died within 30-days of admission and 12.2 % experienced a complication, translating into a sensitivity and specificity of 95.9 % (95 % CI, 95.3–96.5) and 21.1 % (95 % CI, 20.7–21.5) for mortality and 88.5 % (95 % CI, 87.9–89.2) and 21.6 % (95 % CI, 21.2–22.0) for any complication.ConclusionIMPACT had acceptable sensitivity for predicting in-hospital and 30-day mortality or complications and may be valuable for retrospective risk stratification of PE patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-016-1855-y) contains supplementary material, which is available to authorized users.

Highlights

Low-risk pulmonary embolism (PE) patients may be candidates for outpatient treatment or abbreviated hospital stay
Of the 19.5 % of patients classified as low-risk by IMPACT, 2.0 % died in-hospital, resulting in a sensitivity and specificity of 95.2 and 20.7 % and a negative predictive value (NPV) of 98.0 % (Table 3)
We assessed 30-day all-cause mortality, and found IMPACT to have similar sensitivity and NPV (95.9 and 98.0 %, respectively) to clinical tools such as PE severity index (PESI), simplified PESI (sPESI) and the Hestia criteria [5]. These results support those of a smaller (N = 807) single-site study of computed tomography-confirmed PE patients published by Weeda and colleagues [9] that compared IMPACT’s predictive accuracy for 30-day all-cause mortality to that of PESI, sPESI and Hestia

Summary

Introduction

Low-risk pulmonary embolism (PE) patients may be candidates for outpatient treatment or abbreviated hospital stay. We sought to validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule for in-hospital and 30-day outcomes. According to US and European PE treatment guidelines [3, 4], PE patients deemed at low-risk of experiencing early post-PE complications (including mortality) and who have adequate home circumstances should be considered candidates for treatment at home or following an abbreviated hospital admission. The In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule was derived [6] and subsequently validated in multiple external administrative databases for this purpose [7, 8] and has shown prognostic accuracy for predicting in-hospital mortality similar to that of the PE severity index (PESI), simplified PESI (sPESI) and Hestia criteria. We sought to externally validate IMPACT’s accuracy for predicting in-hospital and 30-day outcomes using administrative claims data contained in the Optum Research Database

Methods

Results

Discussion

Conclusion