Variation in 30-Day Readmission Rates from Inpatient Rehabilitation Facilities to Acute Care Hospitals

2021 ◽  
Author(s):  
Cristina A. Shea ◽  
Razvan Turcu ◽  
Bonny S. Wong ◽  
Michelle E. Brassil ◽  
Chloe S. Slocum ◽  
...  
Keyword(s):  
Acute Care ◽  
Inpatient Rehabilitation ◽  
Acute Care Hospitals ◽  
Readmission Rates ◽  
Rehabilitation Facilities

Poster 475 Predicting Readmissions to Acute Care Hospitals From Inpatient Rehabilitation Facilities in Medicare Fee-for-Service Stroke Patients

PM&R ◽  
2011 ◽  
Vol 3 ◽  
pp. S340-S341
Author(s):  
Margaret A. DiVita ◽  
Carl V. Granger ◽  
Samuel Markello ◽  
Paulette Niewczyk
Keyword(s):  
Acute Care ◽  
Inpatient Rehabilitation ◽  
Acute Care Hospitals ◽  
Fee For Service ◽  
Stroke Patients ◽  
Rehabilitation Facilities

Abstract 17161: Type and Intensity of Strategies to Reduce Readmissions Under the Hospital Readmissions Reduction Were Not Associated With Improvements in Readmission Rates

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
J Gmerice Hammond ◽  
Jonathan Yu ◽  
Jose Figueroa ◽  
Karen E Joynt Maddox
Keyword(s):  
Acute Care ◽  
High Intensity ◽  
Hospital Readmissions ◽  
Acute Care Hospitals ◽  
Transitions Of Care ◽  
Patient Centered ◽  
Readmission Rates ◽  
Hospital Size ◽  
Reduction Strategies ◽  
Individual Strategies

Background: Little is known about what strategies are associated with improvements in hospital readmissions under the Hospital Readmissions Reduction Program. Objective: To determine whether the type or intensity of readmission reduction strategies were associated with changes in readmission rates for heart failure, acute myocardial infarction, and pneumonia among acute care hospitals participating in the HRRP. Methods: We surveyed leaders of 1,600 U.S. acute care hospitals participating in the HRRP about their use of 13 specific strategies to reduce readmissions. Strategies were grouped into three domains: transitions of care (TOC, e.g. discharge checklist), quality improvement (QLT, e.g. medication reconciliation), and patient-centered (PC, e.g. patient engagement programs). Intensity of each domain was scored as high or low according to how many strategies were implemented. We calculated hospital-level readmission rates prior to (2011-12) and following (2014-15) HRRP implementation. We used linear regression to determine if there were associations between individual strategies, domains, or overall scope of strategies and a reduction in readmission rates. Results: Of the 1,600 hospitals surveyed, 926 participated (58% response rate). Hospitals reported using 6.1 (SD 2.5) strategies on average. TOC was the most commonly used domain: 69% of hospitals scored high intensity in TOC, compared to only 22% and 14% of hospitals scoring high intensity in QLT and PC domains, respectively. After adjusting for hospital size, type, teaching status, and location, there were no statistically significant associations between any individual strategy and changes in readmission rates, nor between domain intensity and changes in readmission rates. Nearly half of all hospitals, 49%, scored high in only one domain; only 22% scored high in two domains and 5% scored high in all three domains. In fully adjusted models, there was no association between scoring high in multiple domains and reducing readmission rates. Conclusions: Under the HRRP, hospitals focused most on transitions of care strategies. There was no evidence that any of the most commonly employed strategies for reducing readmissions were associated with differential changes in readmission rates.

scholarly journals 1153. National Trend of Urinary Catheter Device Utilization by Hospital Type, National Healthcare Safety Network (2015–2019)

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S411-S412
Author(s):  
Minn M Soe
Keyword(s):  
Acute Care ◽  
Negative Binomial ◽  
Urinary Catheter ◽  
Inpatient Rehabilitation ◽  
Acute Care Hospitals ◽  
Equation Modeling ◽  
Quality Reporting ◽  
Factors Associated ◽  
National Healthcare ◽  
National Healthcare Safety Network

Abstract Background Reducing unnecessary urinary catheter use and optimizing insertion techniques and catheter maintenance and care practices are the most important urinary tract infection (CAUTI) prevention strategies. To monitor device use (DU) as quality improvement activity, the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN) developed the risk adjusted, standardized urinary catheter device utilization ratio in 2015. This study aims to assess national trends of DU from the baseline year 2015 through 2019. Methods For our trend analysis, we analyzed DU data (catheter days per 100 inpatient-days) that acute care hospitals (ACHs), long-term acute care hospitals (LTACHs), inpatient rehabilitation facilities (IRFs), and critical access hospitals (CAHs) reported to NHSN from 2015Q1 through 2019Q1. The ward and intensive care unit patient care locations included in our analysis are those that ACHs, LTACHs, IRFs and CAHs are required to report to CMS to comply with CMS Inpatient Quality Reporting program requirements. We regressed DU by quarterly period using generalized estimating equation modeling with the negative-binomial distribution, after adjusting for factors associated with corresponding SUR models of 2015 baseline and accounting for autocorrelation of error terms within a location. For graphic display, we also computed quarterly DU using marginal predictive models. Results The DU decreased over time (P ≤ 0.05, average percent change per quarter (%change): −0.54 [95% CI: −0.54, −0.53]) among ACHs (Table 1, Figure 1), and −0.54 [95% CI: −0.58, −0.49] among LTACHs (Table 1, Figure 2). Among IRFs, quarterly DU in 2015Q2–2016Q3 were similar relative to 2015Q1, but decreased from 2016Q4 onward (P ≤ 0.05, % change: −0.51 [95% CI: −0.61, −0.40]) (Table 1, Figure 3). Among CAHs, quarterly DU in 2015Q2–2016Q4 were similar relative to 2015Q1, but decreased from 2017Q1 onward (P ≤ 0.05, % change: −0.22 [95% CI: −0.39, −0.04]) (Table 1, Figure 4). Conclusion There was a statistically significant decrease in National DU of urinary catheter during 2015–2019 across NHSN, although the magnitude of change per quarter was not large. Further research is needed to explore causal factors associated with such reduction. Disclosures All authors: No reported disclosures.

Abstract 142: Which Hospitals Fail to Improve Readmission Rates?

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Karen E Joynt ◽  
Sidney T Le ◽  
Matthew Inada-Kim ◽  
Ashish K Jha
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Acute Care ◽  
Odds Ratio ◽  
Readmission Rate ◽  
Medical Intensive Care Unit ◽  
Acute Care Hospitals ◽  
Teaching Hospitals ◽  
Readmission Rates ◽  
Medical Intensive Care

Objective: The 30-day readmission rate in the Medicare population is near 18%, with an associated cost of $16 billion dollars annually. Policy makers have become focused on trying to identify successful strategies to reduce both the clinical and economic burden of rehospitalizations, and to this end, the Affordable Care Act sets up penalties for hospitals with high readmission rates. Despite the national attention to readmissions, there are many hospitals that have failed to improve their readmission rates. Understanding who these persistently poor-performing hospitals are is key to helping them improve. Methods: We used national Medicare data from 2007 through 2009 to calculate mean readmission rates across six common conditions (heart failure, acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, stroke and gastrointestinal bleeding) for all acute-care hospitals in the U.S. We identified poor baseline performers as those hospitals with performance in the worst quartile of readmission rates in 2007. We then categorized these hospitals into two groups: those who improved by 2009 and those who did not. We compared the characteristics of hospitals and markets in each of these groups. Results: Our sample was comprised of 869 poor-performing acute-care hospitals. Baseline median composite readmission rates were 27.8% (IQR 25.8%-32.5%). Of these, 214 (24.6%) hospitals failed to improve their readmission rates by 2009; the median 2009 readmission rate for persistently poor performers was 32.0% (IQR 27.1%-38.0%) while the rate fo hospitals that improved was 20.9% (IQR 18.5%-23.6%). Persistently poor performers were more likely to be small hospitals (71% versus 32%, p<0.001), publicly owned (32% versus 21%, p=0.003), rural (43% versus 18%, p=0.02), non-teaching hospitals (86% versus 74%, p<0.001). They were less likely to have a medical intensive care unit (20% versus 52%, p=0.001). Persistently poor performers were located in areas with fewer specialist physicians (7 per 100,000 population versus 9 per 100,000 population, p<0.001) and lower median income ($33,299 versus $34,523, p<0.001). In multivariate logistic regression analyses, the strongest predictors of being a persistently poor performer were being a small hospital (odds ratio 13.3, p<0.001) and lacking a medical intensive care unit (odds ratio 2.9, p<0.001). Conclusions and Implications: Between 2007 and 2009, small, public, non-teaching hospitals were far less likely to improve their readmission rates than others; in general, persistently poor performers were hospitals with lower resource levels and more socioeconomically disadvantaged populations. As hospitals face looming penalties for high readmission rates, our findings raise concern about the ability of the small, worst-performing hospitals and those with poor resource bases to improve their outcomes, and thus raise concerns about the potential of readmissions penalties to widen disparities in care. Policymakers may need to consider coupling readmission penalties with programs and resources to help these vulnerable hospitals improve in order to avoid unintended consequences of this policy initiative.

Inpatient rehabilitation facilities’ hospital readmission rates for medicare beneficiaries treated following a stroke

2020 ◽  
Vol 28 (1) ◽  
pp. 61-71
Author(s):  
Laura Coots Daras ◽  
Anne Deutsch ◽  
Melvin J. Ingber ◽  
Jennifer Gaudet Hefele ◽  
Jennifer Perloff
Keyword(s):  
Hospital Readmission ◽  
Inpatient Rehabilitation ◽  
Medicare Beneficiaries ◽  
Readmission Rates ◽  
Hospital Readmission Rates ◽  
Rehabilitation Facilities
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