Is Referral to Home Health Rehabilitation After Inpatient Rehabilitation Facility Associated With 90-Day Hospital Readmission for Adult Patients With Stroke?
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ABSTRACT: Objective
We examined the association between home health rehabilitation referral and 90-day risk-adjusted hospital readmission after discharge from inpatient rehabilitation facilities among adult patients recovering from stroke (N = 1219).Design
A secondary data analysis of the 2005-2006 Stroke Recovery in Underserved Population database. A logistic regression model, multilevel model, and the propensity score inverse probability weighting model were used to evaluate the risk of 90-day rehospitalization between patients with stroke who received a referral for home health rehabilitation and those who did not receive a home health rehabilitation referral at inpatient rehabilitation facility discharge.Results
The regression, multilevel, and propensity score inverse probability weighting models indicated that inpatient rehabilitation facility patients with stroke who received home health rehabilitation referral had substantially lower odds of 90-day rehospitalization after inpatient rehabilitation facility discharge compared with those who were not referred to home health (odds ratio = 0.325, 95% confidence interval = 0.138-0.764; odds ratio = 0.340, 95% confidence interval = 0.139-0.832; odds ratio = 0.407, 95% confidence interval = 0.183-0.906, respectively).Conclusions
Our findings suggest the importance of continuation of care (home health) after hospitalization and intense inpatient rehabilitation for stroke. Additional research is needed to establish appropriate use criteria and explore potential underuse of home health services as well as the benefits for follow-up outpatient services for those who do not qualify for home health at inpatient rehabilitation facility discharge.
SUBMITTER: Hong I
PROVIDER: S-EPMC7483954 | biostudies-literature |
REPOSITORIES: biostudies-literature
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| S-EPMC8827220 | biostudies-literature
Project description:OBJECTIVE:To investigate the effects of facility-level factors on 30-day unplanned risk-adjusted hospital readmission after discharge from inpatient rehabilitation facilities (IRFs). DESIGN:Study using 100% Medicare claims data, covering 269,306 discharges from 1094 IRFs between October 2010 and September 2011. SETTING:IRFs with at least 30 discharges. PARTICIPANTS:A total number of 1094 IRFs (N=269,306) serving Medicare fee-for-service beneficiaries. INTERVENTIONS:Not applicable. MAIN OUTCOME MEASURES:Risk-standardized readmission rate (RSRR) for 30-day hospital readmission. RESULTS:Profit status was the only provider-level IRF characteristic significantly associated with unplanned readmissions. For-profit IRFs had a significantly higher RSRR (13.26±0.51) than did nonprofit IRFs (13.15±0.47) (P<.001). After controlling for all other facility characteristics (except for accreditation status because of its collinearity with facility type), for-profit IRFs had a 0.1% point higher RSRR than did nonprofit IRFs, and census region was the only significant region-level characteristic, with the South showing the highest RSRR of all regions (type III test, P=.005 for both). CONCLUSIONS:Our findings support the inclusion of profit status on the IRF Compare website (a platform including IRF comparators to indicate quality of services). For-profit IRFs had a higher RSRR than did nonprofit IRFs for Medicare beneficiaries. The South had a higher RSRR than did other regions. The RSRR difference between for-profit and nonprofit IRFs could be due to the combined effects of organizational and regional factors.
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Project description:Determine patient and hospital-level risk factors associated with 30-day readmission for patients undergoing inpatient otolaryngologic surgery.Retrospective cohort study.We analyzed the State Inpatient Database (SID) from California for patients who underwent otolaryngologic surgery between 2008 and 2010. Readmission rates, readmission diagnoses, and patient- and hospital-level risk factors for 30-day readmission were determined. Hierarchical logistic regression modeling was performed to identify procedure-, patient-, and hospital-level risk factors for 30-day readmission.The 30-day readmission rate following an inpatient otolaryngology procedure was 8.1%. The most common readmission diagnoses were nutrition, metabolic, or electrolyte problems (44% of readmissions) and surgical complications (10% of readmissions). New complications after discharge were the major drivers of readmission. Variables associated with 30-day readmission in hierarchical logistic regression modeling were: type of otolaryngologic procedure, Medicare or Medicaid health insurance, chronic anemia, chronic lung disease, chronic renal failure, index admission via the emergency department, in-hospital complication during the index admission, and discharge destination other than home.Approximately one out of 12 patients undergoing otolaryngologic surgery had a 30-day readmission. Readmissions occur across a variety of types of procedures and hospitals. Most of the variability was driven by patient-specific factors, not structural hospital characteristics.4. Laryngoscope, 2016 127:337-345, 2017.
| S-EPMC5490655 | biostudies-literature
Project description:ObjectiveTo assess the incidence of, causes for, and factors associated with readmission to an acute care hospital (RTAC) during inpatient rehabilitation for traumatic brain injury (TBI).DesignProspective observational cohort.SettingInpatient rehabilitation.ParticipantsIndividuals with TBI admitted consecutively for inpatient rehabilitation (N=2130).InterventionsNot applicable.Main outcome measuresRTAC incidence, RTAC causes, rehabilitation length of stay (RLOS), and rehabilitation discharge location.ResultsA total of 183 participants (9%) experienced RTAC for a total of 210 episodes. Of 183 participants, 161 patients experienced 1 RTAC episode, 17 had 2, and 5 had 3. The mean time from rehabilitation admission to first RTAC was 22±22 days. The mean duration in acute care during RTAC was 7±8 days. Eighty-four participants (46%) had ≥1 RTAC episodes for medical reasons, 102 (56%) had ≥1 RTAC episodes for surgical reasons, and 6 (3%) participants had RTAC episodes for unknown reasons. Most common surgical RTAC reasons were neurosurgical (65%), pulmonary (9%), infection (5%), and orthopedic (5%); most common medical reasons were infection (26%), neurological (23%), and cardiac (12%). Any RTAC was predicted as more likely for patients with older age, history of coronary artery disease, history of congestive heart failure, acute care diagnosis of depression, craniotomy or craniectomy during acute care, and presence of dysphagia at rehabilitation admission. RTAC was less likely for patients with higher admission FIM motor scores and education less than high school diploma. RTAC occurrence during rehabilitation was significantly associated with longer RLOS and smaller likelihood of discharge home.ConclusionsApproximately 9% of patients with TBI experienced RTAC episodes during inpatient rehabilitation for various medical and surgical reasons. This information may help inform interventions aimed at reducing interruptions in rehabilitation for RTAC. RTACs were associated with longer RLOS and discharge to an institutional setting.
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Project description:IntroductionHospital readmission rates are an indicator of the health care quality provided by hospitals. Applying machine learning (ML) to a hospital readmission database offers the potential to identify patients at the highest risk for readmission. However, few studies applied ML methods to predict hospital readmission. This study sought to assess ML as a tool to develop prediction models for all-cause 90-day hospital readmission for dental patients.MethodsUsing the 2013 Nationwide Readmissions Database (NRD), the study identified 9260 cases for all-cause 90-day index admission for dental patients. Five ML classification algorithms including decision tree, logistic regression, support vector machine, k-nearest neighbors, and artificial neural network (ANN) were implemented to build predictive models. The model performance was estimated and compared by using area under the receiver operating characteristic curve (AUC), and accuracy, sensitivity, specificity, and precision.ResultsHospital readmission within 90 days occurred in 1746 cases (18.9%). Total charges, number of diagnosis, age, number of chronic conditions, length of hospital stays, number of procedures, primary expected payer, and severity of illness emerged as the top eight important features in all-cause 90-day hospital readmission. All models had similar performance with ANN (AUC = 0.743) slightly outperforming the rest.ConclusionThis study demonstrates a potential annual saving of over $500 million if all of the 90-day readmission cases could be prevented for 21 states represented in the NRD. Among the methods used, the prediction model built by ANN exhibited the best performance. Further testing using ANN and other methods can help to assess important readmission risk factors and to target interventions to those at the greatest risk.
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Project description:BackgroundUnplanned hospital readmissions are a major source of morbidity among dialysis patients, in whom the risk of hospital readmission is exceptionally high. The contribution of dialysis facility staffing to hospital readmission has been largely overlooked.MethodsUsing annual data of dialysis patients from the United States Renal Data System from 2010 to 2013, we assessed dialysis facilities with a significantly worse (SW) and facilities with a nonsignificant (NS) standardized readmission ratio (SRR). SRR estimates were risk adjusted for patient factors, past year comorbidities, and index hospitalization characteristics. Facility staffing variables were compared between 2 exposure groups: facilities with SW and NS SRRs. Four measures of staffing, including patient-to-staffing ratio, were compared between SW and matched NS facilities.ResultsAbout 136,000-148,000 dialysis patients with 269,000-319,000 index hospital discharges were used to identify facilities with SW and facilities with NS SRR annually. Approximately 3-4% of facilities were identified as having SW SRR among > 5,000 facilities annually. The percent of nurses-to-total staff was significantly lower in 2010 for SW facilities than in matched NS facilities (42.5 vs. 45.6%, p = 0.012), but this disparity was attenuated by 2013 (44.8 vs. 44.7%, p = 0.949). There was a higher patient-to-nurse ratio for SW facilities than for NS facilities (mean 16.4 vs. 15.2, p = 0.038) in 2010 as well, and the disparity was reduced by 2013. The trends were similar for patient-to-total staff and patient-to-registered nurse, but not statistically significant.ConclusionsThis study found that dialysis facilities with SW 30-day readmission rates had lower proportions of nurses-to-total staff and higher patient-to-nurse ratios, but this disparity improved in recent years. Additional research is warranted focusing on how evidence-based staffing at dialysis facilities can contribute to reduction of hospital readmission, and this knowledge is needed to inform clinical practice guidelines and policy decisions regarding optimal dialysis patient staffing.
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Project description:The Centers for Medicare & Medicaid Services recently identified 30-day readmission after discharge from inpatient rehabilitation facilities as a national quality indicator. Research is needed to determine the rates and factors related to readmission in this patient population.To determine 30-day readmission rates and factors related to readmission for patients receiving postacute inpatient rehabilitation.Retrospective cohort study of records for 736,536 Medicare fee-for-service beneficiaries (mean age, 78.0 [SD, 7.3] years) discharged from 1365 inpatient rehabilitation facilities to the community in 2006 through 2011. Sixty-three percent of patients were women, and 85.1% were non-Hispanic white.Thirty-day readmission rates for the 6 largest diagnostic impairment categories receiving inpatient rehabilitation. These included stroke, lower extremity fracture, lower extremity joint replacement, debility, neurologic disorders, and brain dysfunction.Mean rehabilitation length of stay was 12.4 (SD, 5.3) days. The overall 30-day readmission rate was 11.8% (95% CI, 11.7%-11.8%). Rates ranged from 5.8% (95% CI, 5.8%-5.9%) for patients with lower extremity joint replacement to 18.8% (95% CI, 18.8%-18.9%). for patients with debility. Rates were highest in men (13.0% [ 95% CI, 12.8%-13.1%], vs 11.0% [95% CI, 11.0%-11.1%] in women), non-Hispanic blacks (13.8% [95% CI, 13.5%-14.1%], vs 11.5% [95% CI, 11.5%-11.6%] in whites, 12.5% [95% CI, 12.1%-12.8%] in Hispanics, and 11.9% [95% CI, 11.4%-12.4%] in other races/ethnicities), beneficiaries with dual eligibility (15.1% [95% CI, 14.9%-15.4%], vs 11.1% [95% CI, 11.0%-11.2%] for no dual eligibility), and in patients with tier 1 comorbidities (25.6% [95% CI, 24.9%-26.3%], vs 18.9% [95% CI, 18.5%-19.3%] for tier 2, 15.1% [95% CI, 14.9%-15.3%] for tier 3, and 9.9% [95% CI, 9.9%-10.0%] for no tier comorbidities). Higher motor and cognitive functional status were associated with lower hospital readmission rates across the 6 impairment categories. Adjusted readmission rates by state ranged from 9.2% to 13.6%. Approximately 50% of patients rehospitalized within the 30-day period were readmitted within 11 days of discharge. Medicare Severity Diagnosis-Related Group codes for heart failure, urinary tract infection, pneumonia, septicemia, nutritional and metabolic disorders, esophagitis, gastroenteritis, and digestive disorders were common reasons for readmission.Among postacute rehabilitation facilities providing services to Medicare fee-for-service beneficiaries, 30-day readmission rates ranged from 5.8% to 18.8% for selected impairment groups. Further research is needed to understand the causes of readmission.
| S-EPMC4085109 | biostudies-literature
Project description:OBJECTIVE:To examine the association between hospital-based rehabilitation service use and all-cause 30-day hospital readmission among patients with ischemic stroke. DESIGN:Secondary analysis of inpatient Medicare claims data using Standard Analytical Files. SETTING:Acute hospitals across the United States. PARTICIPANTS:From nationwide data, Medicare fee-for-service beneficiaries (N=88,826) aged 66 years or older hospitalized for ischemic stroke between January to November 2010. INTERVENTIONS:Hospital-based rehabilitation services were quantified using Medicare inpatient claims revenue center codes for evaluation (occupational therapy [OT] and physical therapy [PT]), as well as the number of therapy units delivered. Therapy minutes for both OT and PT services were categorized into none, low, medium, and high. MAIN OUTCOME MEASURES:All-cause 30-day hospital readmission. A generalized linear mixed model was used to examine the effect of hospital-based rehabilitation services on 30-day hospital readmission, after adjusting for patient and hospital characteristics. RESULTS:In fully adjusted models, compared to patients who received no PT, we observed a monotonic inverse relationship between the amount of PT and hospital readmission. For low PT (30 minutes), the odds ratio (OR) was 0.90 (95% confidence interval [CI], 0.83-0.96). For medium PT (>30 to ≤75 minutes), the OR was 0.89 (95% CI, 0.82-0.95). For high PT (>75 minutes), the OR was 0.86 (95% CI, 0.80-0.93). CONCLUSION:Hospital-based PT services were associated with lower risk of 30-day hospital readmission in patients with ischemic stroke.
| S-EPMC6599551 | biostudies-literature
Project description:IntroductionWe aimed to validate and compare two clinical prognostic models for mortality which include the National Institutes of Health Stroke Scale (NIHSS); the Age and NIHSS Score (ANS) and case mix model (CMM) of the Sentinel Stroke National Audit Program (SSNAP). The NIHSS on admission was also tested as a prognostic score.Patients and methodsProspectively collected data from the SSNAP register for a cohort of patients (ischaemic and haemorrhagic stroke) admitted over 1 year to Gloucestershire Royal Hospital, England were accessed. The ANS and CMM were calculated and tested for in hospital, 30-day and 90-day mortality using calibration plots with Hosmer-Lemeshow tests, receiver operating characteristics curves and other measures of prognostic accuracy.ResultsOf 848 patients, 110 (12.9%) died in hospital, 112 (13.2%) at 30 days and 164 (19.2%) at 90 days. Calibration for all three scores was good, although Hosmer-Lemeshow test p values were <0.05 with the NIHSS alone for in hospital and 30-day deaths, suggesting deviation from good fit. The c-statistics for in hospital, 30-day and 90-day mortality were ANS (0.783, 0.782, 0.779) and CMM (0.783, 0.774, 0.758), respectively. The NIHSS alone showed fair discrimination but performed less well. A NIHSS score ?6 was associated with significant mortality (p?<?0.0001) in comparison to a score <6.ConclusionA simple prognostic model containing age and admission NIHSS only, performed as well as a more complex score at predicting in hospital, 30-day and 90-day mortality. Admission NIHSS recording should be encouraged for stroke registries.
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