Validation of Risk Score in Predicting Early Readmissions in Decompensated Cirrhotic Patients: A Model Based on the Administrative Database

Mumtaz, Khalid; Issak, Abdulfatah; Porter, Kyle; Kelly, Sean G.; Hanje, James; Michaels, Anthony; Conteh, Lanla; El‐Hinnawi, Ashraf; Black, Sylvester M.; Abougergi, Marwan S.

doi:10.1002/hep.30274

Cited by 24 publications

(34 citation statements)

References 24 publications

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“…Tapper et al used a nationwide database to report 13% and 21% readmission rates at 30 and 90 days respectively. In a recent study by Mumtaz et al, using the NRD in 2013, the authors reported higher readmission rates (27% at 30 days) compared to our findings. The higher rate observed in the Mumtaz study may be attributed to their using non‐validated ICD‐9 codes, which could overestimate cirrhosis cases .…”

Section: Discussioncontrasting

confidence: 62%

“…Unfortunately, previous studies that assessed readmission rates had significant limitations, including being driven from tertiary care centre populations, not identifying predictors of readmissions unique for each decompensated feature, not using validated cirrhosis codes and/or not assessing the economic burden on the healthcare system . As such, we used the largest nationwide readmission database in the United States to estimate hospital readmission rates and evaluate the hospitalization costs among patients with cirrhosis.…”

Section: Introductionmentioning

confidence: 99%

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Nationwide estimates and risk factors of hospital readmission in patients with cirrhosis in the United States

Shaheen

Nguyen

Congly

et al. 2019

Liver International

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Background The burden of cirrhosis on the healthcare system is substantial and growing. Our objectives were to estimate the readmission rates and hospitalization costs as well as to identify risk factors for 90‐day readmission in patients with cirrhosis. Methods We conducted a weighted analysis of the 2014 Nationwide Readmission Database to identify adult patients with cirrhosis‐related complications in the United States and assessed readmission rates at 30, 60 and 90 days post‐index hospitalization. Predictors of 90‐day readmissions were identified using weighted regression models adjusting for patient and hospital characteristics; the national estimate of hospitalization costs was also calculated. Results Of the 58 954 patients admitted with cirrhosis‐related complications in 2014, 14 910 (25%) were readmitted within 90 days because of cirrhosis‐related complications. The main causes of readmission were ascites (56%), hepatic encephalopathy (47%) and bleeding oesophageal varices (9%). Independent predictors of 90‐day readmissions were male sex (adjusted OR [aOR]: 1.08, 95% CI, 1.04‐1.13), age <60 (aOR: 1.27, 95% CI, 1.22‐1.32), privately insured (aOR: 0.74, 95% CI, 0.70‐0.77), having ≥3 comorbid conditions (aOR: 1.27, 95% CI, 1.14‐1.42) and being discharged against medical advice (aOR: 1.41, 95% CI, 1.25‐1.59). The weighted cumulative national cost estimate of the index admission was $1.8 billion, compared to $0.5 billion for readmission. Conclusions A quarter of patients admitted with cirrhosis‐related complications were readmitted within 90 days, representing a significant economic burden related to readmission of this population. Interventions and resource allocations to reduce readmission rates among cirrhotic patients is critical.

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Section: Discussioncontrasting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Nationwide estimates and risk factors of hospital readmission in patients with cirrhosis in the United States

Shaheen

Nguyen

Congly

et al. 2019

Liver International

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“…Readmission risk score may highlight the need for targeted interventions to decrease rates of readmission within high-risk populations. (16) However, some factors are not easily manageable due to their complexity such as culture, socioeconomic status, and health insurance.…”

Section: Discussionmentioning

confidence: 99%

Thirty‐Day Readmission and Cost Analysis in Patients With Cirrhosis: A Nationwide Population‐Based Data

Chirapongsathorn

Poovorawan²,

Soonthornworasiri³

et al. 2020

Hepatol Commun

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Accurate population‐based data are needed on the rate, economic impact, and the long‐term outcomes of readmission among patients with cirrhosis. To examine the rates, costs, and 1‐year outcomes of patients readmitted within 30 days following their index hospitalization for complications of cirrhosis, we conducted a nationwide, population‐based cohort study involving all patients with cirrhosis in Thailand from 2009 through 2013, using data from the National Health Security Office databases, which included those from nationwide hospitalizations. Readmission was captured from hospitals at all health care levels across the country within the Universal Coverage Scheme. For the 134,038 patients hospitalized with cirrhosis, the overall 30‐day readmission rate was 17%. Common causes of readmission consisted of complications of portal hypertension (47%) and infections (17%). After adjusting for multiple covariates, predictors of 30‐day readmission included hepatocellular carcinoma (odds ratio [OR] 1.95, 95% confidence interval [CI] 1.84‐2.06), human immunodeficiency virus–related admission (OR 1.81, 95% CI 1.51‐2.17) and cholangiocarcinoma (OR 1.64, 95% CI 1.3‐2.05). In all, 2,936 deaths (13%) occurred during readmission, and an additional 14,425 deaths up to 1 year (63.5% total mortality among readmitted patients). Causes of death were mostly from liver‐related mortality. Average cost at index admission for those with a 30‐day readmission were significantly higher than those readmitted beyond 30 days or not readmitted. Conclusions: Patients hospitalized with cirrhosis complications had high rates of unscheduled 30‐day readmission. Average hospitalization costs were high, and only 36.5% of patients readmitted within 30 days survived at 1 year.

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“…These admissions and readmissions in cirrhosis are prevalent and are a major cause of healthcare expenditure . However, prediction models using clinical biomarkers alone are largely suboptimal, with relatively low c‐statistics in population‐based and cohort studies . Therefore, despite mandates to reduce hospitalisations, readmissions and early post‐discharge follow‐up efforts, these efforts are often hampered by the lack of definition of the group at greatest risk …”

Section: Introductionmentioning

confidence: 99%

“…1,2,[4][5][6] However, prediction models using clinical biomarkers alone are largely suboptimal, with relatively low c-statistics in population-based and cohort studies. 7,8 Therefore, despite mandates to reduce hospitalisations, readmissions and early post-discharge follow-up efforts, these efforts are often hampered by the lack of definition of the group at greatest risk. 7,9 Cirrhosis is associated with altered gut microbiota composition and function, which can affect the development and propagation of several complications such as hepatic encephalopathy (HE), infections such as spontaneous bacterial peritonitis (SBP) and renal dysfunction.…”

Section: Introductionmentioning

confidence: 99%

Cost‐effectiveness of integrating gut microbiota analysis into hospitalisation prediction in cirrhosis

et al. 2020

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Summary Background Admissions in cirrhosis are expensive and often unpredictable based on purely clinical variables. Admissions could be related to complications associated with gut microbial changes, which can improve prognostication. However, the cost‐effectiveness remains unclear. Aims Determine cost‐effectiveness of adding gut microbiota analysis to clinical parameters in prediction and subsequent reduction of admissions in cirrhosis. Methods Using a Markov model of 1000 cirrhosis patients over 90 days, we modelled microbiota testing using 16srRNA ($250/sample), low‐depth ($350/sample) and high‐depth ($650/sample) metagenomics added to standard‐of‐care (SOC) for prevention of admissions using standard outcome costs and rates of development. We generated quality of life years (QALY) and Incremental cost‐effectiveness ratios (ICER) for the base scenarios and performed sensitivity analyses by varying costs for outcomes (transplant, death, admission) and admission rates (40%, range 25%‐60%). Results Using fixed costs of outcomes and outcome rates, microbiota analysis was cost‐saving ($47K‐$97K) at $250 and $350/sample if admissions were reduced by 5% over SOC and >10% with $650/sample. When costs of liver transplant, death and admissions were varied, these cost‐savings remained robust provided there was >2.1% reduction (range 1.3%‐3.2%) for $250/sample, >2.9% (range 1.8%‐4.4%) for $350/sample and >5.4% (range 3.3%‐8.2%) for $650/sample. These cost‐savings remained robust even when the assumed admission rate was varied for all sample cost values. Conclusions Gut microbiota analysis is cost‐effective for predicting and potentially preventing 90‐day admissions in cirrhosis over current SOC. This cost‐saving remained robust even after sensitivity analyses that varied the background admission rates.

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Validation of Risk Score in Predicting Early Readmissions in Decompensated Cirrhotic Patients: A Model Based on the Administrative Database

Cited by 24 publications

References 24 publications

Nationwide estimates and risk factors of hospital readmission in patients with cirrhosis in the United States

Nationwide estimates and risk factors of hospital readmission in patients with cirrhosis in the United States

Thirty‐Day Readmission and Cost Analysis in Patients With Cirrhosis: A Nationwide Population‐Based Data

Cost‐effectiveness of integrating gut microbiota analysis into hospitalisation prediction in cirrhosis

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