2017
DOI: 10.1097/mlr.0000000000000735
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Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data

Abstract: These indices are effective methods to incorporate the influence of comorbid conditions in models designed to assess the risk of in-hospital mortality and readmission using administrative data with limited clinical information, especially when small samples sizes are an issue.

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Cited by 656 publications
(393 citation statements)
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“…We included people who were oral anticoagulant (OAC) naïve during the 12 months before the day of the first qualifying rivaroxaban or warfarin dispensing (index date); had ≥2 inpatient or outpatient ICD codes in any position for AF (ICD-10 = I48) without codes suggesting valvular disease; an inpatient or outpatient diagnosis code in any position for HF (ICD-10 = I50, I09.81) 11 ; and ≥12 months of continuous medical and prescription coverage prior to OAC initiation (baseline period). Individuals were excluded if they had a history of venous thrombo-embolism or orthopaedic arthroplasty, were pregnant, had a transient cause of NVAF, or were prescribed >1 OAC.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We included people who were oral anticoagulant (OAC) naïve during the 12 months before the day of the first qualifying rivaroxaban or warfarin dispensing (index date); had ≥2 inpatient or outpatient ICD codes in any position for AF (ICD-10 = I48) without codes suggesting valvular disease; an inpatient or outpatient diagnosis code in any position for HF (ICD-10 = I50, I09.81) 11 ; and ≥12 months of continuous medical and prescription coverage prior to OAC initiation (baseline period). Individuals were excluded if they had a history of venous thrombo-embolism or orthopaedic arthroplasty, were pregnant, had a transient cause of NVAF, or were prescribed >1 OAC.…”
Section: Methodsmentioning
confidence: 99%
“…Propensity scores were calculated using multivariable logistic regression incorporating frequently used variables and potential risk factors for differential OAC exposure ( Table 1) including demographics, co-morbidities, 11 components of the CHA 2 DS 2 -VASc and HASBLED scores, 12 and concomitant non-OAC medications identified during the 12 month baseline period.…”
Section: Methodsmentioning
confidence: 99%
“…Patient comorbidity was defined using the Agency for Healthcare Research and Quality Elixhauser 27,28 Comorbidity Index for readmissions. The Elixhauser comorbidity adjustment was developed in 1998 for use with hospital administrative discharge data and includes a set of 30 clinical conditions that exist prior to hospitalization, unrelated to the principal diagnosis, and likely to influence mortality and resource utilization within the hospital.…”
Section: Methodsmentioning
confidence: 99%
“…27 The Elixhauser Index, a single score that incorporates weights for each comorbidity, has been tested using HCUP databases and effectively incorporates the influence of comorbid conditions on the risk of readmission. 28 …”
Section: Methodsmentioning
confidence: 99%
“…Among the complications of CMS, acute myocardial infarction (AMI), congestive heart failure (CHF) and diabetes mellitus account for the top most common diagnoses for hospitalizations and post-acute care service uses (6,7). An estimated 16.5 million Americans >20 years of age have coronary heart disease (CHD) (6). About 3% of adults in the US have had a myocardial infarction (MI).…”
Section: Introductionmentioning
confidence: 99%