Validation of the Inhospital Mortality for Pulmonary Embolism Using Claims Data (IMPACT) Prediction Rule within an All-Payer Inpatient Administrative Claims Database

Background: Current guidelines suggest that low risk pulmonary embolism (PE) patients may be managed as outpatients or with an abbreviated hospital stay. There is need for a claims-based prediction rule that payers and hospitals can use to efficiently risk stratify PE patients.  The authors recently derived a rule found to have high sensitivity and moderate specificity for predicting in-hospital mortality.

Objective: To validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule originally developed in a commercial claims database in an all-payer administrative database restricted to inpatient claims.

Methods: This study utilized data from the 2012 Healthcare Cost and Utilization Project Nationwide Inpatient Sample (NIS).  Adult PE admissions were identified by the presence of an appropriate International Classification of Diseases, ninth edition, Clinical Modification (ICD-9-CM) code either in the primary position or secondary position when accompanied by a primary code for a PE complication. The IMPACT rule, consists of age + 11 weighted comorbidities calculated based upon the maximum of 25 ICD-9-CM diagnosis codes and 25 procedural codes reported for each discharge in the NIS (myocardial infarction, chronic lung disease, stroke, prior major bleeding, atrial fibrillation, cognitive impairment, heart failure, renal failure, liver disease, coagulopathy, cancer), and was used to estimate patients’ risk of in-hospital mortality. Low risk was defined as in-hospital mortality ≤1.5%.  We present the validity of the rule by calculating prognostic test characteristics and 95% confidence intervals (CIs). In order to estimate the potential cost savings from an early discharge, we calculated the difference in total hospital costs between low-risk patients having and not having an abbreviated hospital stay (defined as ≤1, ≤2 or ≤3 days).  

Results:  A total of 34,108 admissions for PE were included (46.7% male, mean ± standard deviation age of 61.9±17.2); and we observed a 3.4% in-hospital PE case-fatality rate. The IMPACT prediction rule classified 11,025 (32.3%) patient admissions as low-risk; and had a sensitivity of 92.4% (95%CI=90.7-93.8), specificity of 33.2% (95%CI=32.7-33.7), negative and positive predictive values of 99.2% (95%CI=99.0-99.4) and 4.6% (95%CI=4.4-4.9) and a C-statistic of 0.74 (95%CI=0.73-0.76) for in-hospital mortality.  Low-risk patients had significantly lower in-hospital mortality (0.8% vs. 4.6%, odds reduction of 83%; 95%CI=79-87), shorter LOSs (-1.2 days, p<0.001) and lower total treatment costs (-$3,074, p<0.001) than patients classified as higher-risk. Of low-risk patients, 13.1%, 31.1% and 47.7% were discharged within 1, 2 and 3 days of admission. Low-risk patients discharged within 1 day accrued $5,465 (95%CI=$5,018-$5,911) less in treatment costs than those staying longer.  Discharge within 2 or 3 days in low-risk patients was also associated with a reduced cost of hospital treatment [$5,820 (95%CI=$5,506-$6,133) and $6,314 (95%CI=$6,031-$6,597), respectively] when compared to those staying longer.

Conclusion:  The prior claims-based in-hospital mortality prediction rule was valid when used in this all-payer, inpatient only administrative claims database.  The rule classified patients’ mortality risk with high sensitivity and had a high negative predictive value; and consequently, may be valuable to those wishing to benchmark rates of PE treated at home or following an abbreviated hospital admission.