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Incidence and cost analysis of hospital admission and 30-day readmission among patients with cirrhosis.

ABSTRACT: We examined risks for first hospitalization and the rate, risk factors, costs, and 1-year outcome of 30-day readmission among patients admitted for complications of cirrhosis. Data were retrospectively analyzed for adult patients with cirrhosis residing in Minnesota, Iowa, or Wisconsin and admitted from 2010 through 2013 at both campuses of the Mayo Clinic Hospital in Rochester, MN. Readmission was captured at the two hospitals as well as at community hospitals in the tristate area within the Mayo Clinic Health System. The incidence of hospitalization for complications of cirrhosis was 100/100,000 population, with increasing age and male sex being the strongest risks for hospitalization. For the 2,048 hospitalized study patients, the overall 30-day readmission rate was 32%; 498 (24.3%) patients were readmitted to Mayo Clinic hospitals and 157 (7.7%) to community hospitals, mainly for complications of portal hypertension (52%) and infections (30%). Readmission could not be predicted accurately. There were 146 deaths during readmission and an additional 105 deaths up to 1 year of follow-up (50.4% total mortality). Annual postindex hospitalization costs for those with a 30-day readmission were substantially higher ($73,252) than those readmitted beyond 30 days ($62,053) or those not readmitted ($5,719). At 1-year follow-up, only 20.4% of patients readmitted within 30 days were at home. In conclusion, patients with cirrhosis have high rates of hospitalization, especially among men over 65 years, and of unscheduled 30-day readmission. Readmission cannot be accurately predicted. Postindex hospitalization costs are high; nationally, the annual costs are estimated to be more than $4.45 billion. Only 20% of patients readmitted within 30 days are home at 1 year. (Hepatology Communications 2018;2:188-198).

SUBMITTER: Chirapongsathorn S

PROVIDER: S-EPMC5796328 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Incidence and cost analysis of hospital admission and 30-day readmission among patients with cirrhosis.

Chirapongsathorn Sakkarin S Krittanawong Chayakrit C Enders Felicity T FT Pendegraft Richard R Mara Kristin C KC Borah Bijan J BJ Visscher Sue L SL Loftus Conor G CG Shah Vijay H VH Talwalkar Jayant A JA Kamath Patrick S PS

Hepatology communications 20180118 2

We examined risks for first hospitalization and the rate, risk factors, costs, and 1-year outcome of 30-day readmission among patients admitted for complications of cirrhosis. Data were retrospectively analyzed for adult patients with cirrhosis residing in Minnesota, Iowa, or Wisconsin and admitted from 2010 through 2013 at both campuses of the Mayo Clinic Hospital in Rochester, MN. Readmission was captured at the two hospitals as well as at community hospitals in the tristate area within the Ma ...[more]

PMID: 29404526

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Project description:BackgroundLowering hospital readmission rates has become a primary target for the Centers for Medicare & Medicaid Services, but studies of the relationship between adherence to the recommended hospital care processes and readmission rates have provided inconsistent and inconclusive results.ObjectiveTo examine the association between hospital performance on Medicare's Hospital Compare process quality measures and 30-day readmission rates for patients with acute myocardial infarction (AMI), heart failure and pneumonia, and for those undergoing major surgery.Design, setting and participantsWe assessed hospital performance on process measures using the 2007 Hospital Inpatient Quality Reporting Program. The process measures for each condition were aggregated in two separate measures: Overall Measure (OM) and Appropriate Care Measure (ACM) scores. Readmission rates were calculated using Medicare claims.Main outcome measureRisk-standardized 30-day all-cause readmission rate was calculated as the ratio of predicted to expected rate standardized by the overall mean readmission rate. We calculated predicted readmission rate using hierarchical generalized linear models and adjusting for patient-level factors.ResultsAmong patients aged ≥ 66 years, the median OM score ranged from 79.4 % for abdominal surgery to 95.7 % for AMI, and the median ACM scores ranged from 45.8 % for abdominal surgery to 87.9 % for AMI. We observed a statistically significant, but weak, correlation between performance scores and readmission rates for pneumonia (correlation coefficient R = 0.07), AMI (R = 0.10), and orthopedic surgery (R = 0.06). The difference in the mean readmission rate between hospitals in the 1st and 4th quartiles of process measure performance was statistically significant only for AMI (0.25 percentage points) and pneumonia (0.31 percentage points). Performance on process measures explained less than 1 % of hospital-level variation in readmission rates.ConclusionsHospitals with greater adherence to recommended care processes did not achieve meaningfully better 30-day hospital readmission rates compared to those with lower levels of performance.

Project description:BackgroundExisting readmission reduction solutions tend to focus on complementing inpatient care with enhanced care transition and postdischarge interventions. These solutions are initiated near or after discharge, when clinicians' impact on inpatient care is ending. Preventive intervention during hospitalization is an underexplored area that holds potential for reducing readmission risk. However, it is challenging to predict readmission risk at the early stage of hospitalization because few data are available.ObjectiveThe objective of this study was to build an early prediction model of unplanned 30-day hospital readmission using a large and diverse sample. We were also interested in identifying novel readmission risk factors and protective factors.MethodsWe extracted the medical records of 96,550 patients in 205 participating Cerner client hospitals across four US census regions in 2016 from the Health Facts database. The model was built with index admission data that can become available within 24 hours and data from previous encounters up to 1 year before the index admission. The candidate models were evaluated for performance, timeliness, and generalizability. Multivariate logistic regression analysis was used to identify readmission risk factors and protective factors.ResultsWe developed six candidate readmission models with different machine learning algorithms. The best performing model of extreme gradient boosting (XGBoost) achieved an area under the receiver operating characteristic curve of 0.753 on the development data set and 0.742 on the validation data set. By multivariate logistic regression analysis, we identified 14 risk factors and 2 protective factors of readmission that have never been reported.ConclusionsThe performance of our model is better than that of the most widely used models in US health care settings. This model can help clinicians identify readmission risk at the early stage of hospitalization so that they can pay extra attention during the care process of high-risk patients. The 14 novel risk factors and 2 novel protective factors can aid understanding of the factors associated with readmission.

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Incidence and cost analysis of hospital admission and 30-day readmission among patients with cirrhosis.

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Incidence and cost analysis of hospital admission and 30-day readmission among patients with cirrhosis.

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