Skilled Nursing Facility Differences in Readmission Rates by the Diagnosis-Related Group Category of the Initial Hospitalization

2020 ◽  
Vol 21 (8) ◽  
pp. 1175-1177
Author(s):  
John Oruongo ◽  
Katie Ronk ◽  
Oguzhan Alagoz ◽  
Jonathan Jaffery ◽  
Maureen Smith
Keyword(s):  
Skilled Nursing Facility ◽  
Diagnosis Related Group ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Related Group ◽  
Initial Hospitalization

The Association Between Skilled Nursing Facility Care Quality and 30-Day Readmission Rates After Hospitalization for Heart Failure

2014 ◽  
Vol 30 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Owolabi Ogunneye ◽  
Michael B. Rothberg ◽  
Jennifer Friderici ◽  
Mara T. Slawsky ◽  
Vijay T. Gadiraju ◽  
...  
Keyword(s):  
Heart Failure ◽  
Skilled Nursing Facility ◽  
Care Quality ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing

Disease management partnership with skilled nursing facility improves heart failure 30-day readmission rates

Heart & Lung ◽  
2015 ◽  
Vol 44 (6) ◽  
pp. 556
Author(s):  
Tasha Beck Freitag ◽  
Sandra Young ◽  
Macall Perez ◽  
Dan Altland ◽  
Tamela Sterner
Keyword(s):  
Heart Failure ◽  
Disease Management ◽  
Skilled Nursing Facility ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing

scholarly journals RACIAL DISPARITIES IN 30-DAY READMISSION RATES AMONG MEDICARE PATIENTS DISCHARGED TO SKILLED NURSING FACILITIES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S780-S780
Author(s):  
Maricruz Rivera-Hernandez ◽  
Maricruz Rivera-Hernandez ◽  
Momotazur Rahman ◽  
Vincent Mor ◽  
Amal N Trivedi
Keyword(s):  
Skilled Nursing Facility ◽  
Ethnic Disparities ◽  
Fee For Service ◽  
Nursing Facilities ◽  
Readmission Rates ◽  
Value Based Purchasing ◽  
Nursing Facility ◽  
Data Set ◽  
Skilled Nursing ◽  
American Health Care

Abstract The 30-Day All-Cause Readmission Measure is part of the Skilled Nursing Facility Value-Based Purchasing (SNFVBP) beginning 2019. The objective of the study was to characterize racial and ethnic disparities in 30-day rehospitalization rates from SNF among fee-for-service (FFS) and Medicare Advantage (MA) patients using the Minimum Data Set. The American Health Care Association risk-adjusted model was used. The primary independent variables were race/ethnicity and enrollment in FFS and MA. The sample included 1,813,963 patients from 15,412 SNFs across the US in 2015. Readmission rates were lower for whites. However, MA patients had readmission rates that were ~1 to 2 percentage points lower. In addition, we also found that African-Americans had higher readmission rates than whites, even when they received care within the same SNF. The inclusion of MA patients could change SNF penalties. Successful efforts to reduce rehospitalizations in SNF settings often require improving care coordination and care planning.

scholarly journals Reduction in Hospitals’ Readmission Rates: Role of Hospital-Based Skilled Nursing Facilities

2019 ◽  
Vol 56 ◽  
pp. 004695801881799
Author(s):  
Shivani Gupta ◽  
Ferhat D. Zengul ◽  
Ganisher K. Davlyatov ◽  
Robert Weech-Maldonado
Keyword(s):  
Hospital Readmission ◽  
Fixed Effects ◽  
Skilled Nursing Facility ◽  
Health Resources ◽  
Estimating Equation ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
American Hospital ◽  
American Hospital Association

Hospital readmission within 30 days of discharge is an important quality measure given that it represents a potentially preventable adverse outcome. Approximately, 20% of Medicare beneficiaries are readmitted within 30 days of discharge. Many strategies such as the hospital readmission reduction program have been proposed and implemented to reduce readmission rates. Prior research has shown that coordination of care could play a significant role in lowering readmissions. Although having a hospital-based skilled nursing facility (HBSNF) in a hospital could help in improving care for patients needing short-term skilled nursing or rehabilitation services, little is known about HBSNFs’ association with hospitals’ readmission rates. This study seeks to examine the association between HBSNFs and hospitals’ readmission rates. Data sources included 2007-2012 American Hospital Association Annual Survey, Area Health Resources Files, the Centers for Medicare and Medicaid Services (CMS) Medicare cost reports, and CMS Hospital Compare. The dependent variables were 30-day risk-adjusted readmission rates for acute myocardial infarction (AMI), congestive heart failure, and pneumonia. The independent variable was the presence of HBSNF in a hospital (1 = yes, 0 = no). Control variables included organizational and market factors that could affect hospitals’ readmission rates. Data were analyzed using generalized estimating equation (GEE) models with state and year fixed effects and standard errors corrected for clustering of hospitals over time. Propensity score weights were used to control for potential selection bias of hospitals having a skilled nursing facility (SNF). GEE models showed that the presence of HBSNFs was associated with lower readmission rates for AMI and pneumonia. Moreover, higher SNFs to hospitals ratio in the county were associated with lower readmission rates. These findings can inform policy makers and hospital administrators in evaluating HBSNFs as a potential strategy to lower hospitals’ readmission rates.

Discharge to a skilled nursing facility as the strongest modifiable risk factor for readmissions following pancreaticoduodenectomy.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 435-435
Author(s):  
Katelin Anne Mirkin ◽  
Christopher S Hollenbeak ◽  
Amanda Beth Cooper ◽  
Niraj Jaysukh Gusani
Keyword(s):  
Health Care Cost ◽  
Skilled Nursing Facility ◽  
Home Healthcare ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Black Race ◽  
Anastomotic Complications ◽  
Common Causes ◽  
Initial Hospital

435 Background: Pancreaticoduodenectomy is a technically difficult and notoriously morbid procedure. As payers begin to link reimbursement to readmission rates, there is growing interest in understanding and preventing readmissions. The objective of this study was to evaluate factors contributing to 30-day readmission rates for patients undergoing pancreaticoduodenectomy. Methods: Data from the Pennsylvania Health Care Cost Containment Council (PHC4) were reviewed for patients undergoing pancreaticoduodenectomy from 2011-2014 (n = 1,552). Outcomes included 30-day readmission and length of stay (LOS). Univariate comparisons were performed between characteristics of those readmitted (n = 404) and not readmitted (n = 1,148). Readmission and LOS were modeled using multivariate logistic regression and linear regression, respectively. Results: Of the 404 (26.0%) patients who were readmitted, the most common causes for readmission were post-operative infection (26.2%), anastomotic complications (8.0%), and dehydration (5.7%). Patients who were readmitted were more likely to be discharged to a skilled nursing facility (SNF) and were associated with a longer LOS of index admission (p < 0.001, both). In multivariate analysis, black race (HR 1.96, p = 0.001), discharge to a SNF (HR 1.73, p = 0.006) and increased LOS (HR 1.36, p = 0.019), were associated with increased odds of readmission. After controlling for patient, admission, and facility characteristics, black race, urgent and emergent admissions, and discharge to a SNF or home with home healthcare, were predictive of a longer LOS (p < 0.05). High surgeon volume, and high hospital volume were associated with a shorter LOS (p < 0.05). Conclusions: The most common causes of readmission following pancreaticoduodenectomy in Pennsylvania from 2011-2014 were post-operative infection, anastomotic complications, and dehydration. Patients with a longer initial hospital stay and those discharged to a SNF were associated with higher odds of readmission. Understanding the interplay of these factors may result in opportunities to prevent readmissions, and improve outcomes in patients undergoing this complex surgery.

scholarly journals Hospital-skilled nursing facility referral linkage reduces readmission rates among Medicare patients receiving major surgery

Surgery ◽  
2016 ◽  
Vol 159 (5) ◽  
pp. 1461-1468 ◽  
Author(s):  
Andrew J. Schoenfeld ◽  
Xuan Zhang ◽  
David C. Grabowski ◽  
Vincent Mor ◽  
Joel S. Weissman ◽  
...  
Keyword(s):  
Skilled Nursing Facility ◽  
Major Surgery ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Medicare Patients

scholarly journals Skilled Nursing Facility Referral and Hospital Readmission Rates after Heart Failure or Myocardial Infarction

2012 ◽  
Vol 125 (1) ◽  
pp. 100.e1-100.e9 ◽  
Author(s):  
Jersey Chen ◽  
Joseph S. Ross ◽  
Melissa D.A. Carlson ◽  
Zhenqiu Lin ◽  
Sharon-Lise T. Normand ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Hospital Readmission ◽  
Skilled Nursing Facility ◽  
Readmission Rates ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Hospital Readmission Rates

scholarly journals Developing a Predictive Tool for Hospital Discharge Disposition of Patients Poststroke with 30-Day Readmission Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jin Cho ◽  
Krystal Place ◽  
Rebecca Salstrand ◽  
Monireh Rahmat ◽  
Misagh Mansouri ◽  
...  
Keyword(s):  
Medicare Beneficiary ◽  
Skilled Nursing Facility ◽  
Risk Scores ◽  
Healthcare Team ◽  
Readmission Rates ◽  
Predictive Tool ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Discharge Disposition ◽  
Complex Decision

After short-term, acute-care hospitalization for stroke, patients may be discharged home or other facilities for continued medical or rehabilitative management. The site of postacute care affects overall mortality and functional outcomes. Determining discharge disposition is a complex decision by the healthcare team. Early prediction of discharge destination can optimize poststroke care and improve outcomes. Previous attempts to predict discharge disposition outcome after stroke have limited clinical validations. In this study, readmission status was used as a measure of the clinical significance and effectiveness of a discharge disposition prediction. Low readmission rates indicate proper and thorough care with appropriate discharge disposition. We used Medicare beneficiary data taken from a subset of base claims in the years of 2014 and 2015 in our analyses. A predictive tool was created to determine discharge disposition based on risk scores derived from the coefficients of multivariable logistic regression related to an adjusted odds ratio. The top five risk scores were admission from a skilled nursing facility, acute heart attack, intracerebral hemorrhage, admission from “other” source, and an age of 75 or older. Validation of the predictive tool was accomplished using the readmission rates. A 75% probability for facility discharge corresponded with a risk score of greater than 9. The prediction was then compared to actual discharge disposition. Each cohort was further analyzed to determine how many readmissions occurred in each group. Of the actual home discharges, 95.7% were predicted to be there. However, only 47.8% of predictions for home discharge were actually discharged home. Predicted discharge to facility had 15.9% match to the actual facility discharge. The scenario of actual discharge home and predicted discharge to facility showed that 186 patients were readmitted. Following the algorithm in this scenario would have recommended continued medical management of these patients, potentially preventing these readmissions.

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