One-Year Hospital Readmission Rate in Elderly Patients Undergoing Percutaneous Coronary Intervention
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Background Over a quarter of Medicare patients admitted to the hospital are discharged to post‐acute care ( PAC ) facilities, but face high rates of readmission. Timing of readmission may be an important factor in identifying both risk for and preventability of future readmissions. This study aims to define factors associated with readmission within the first week of discharge to PAC facilities following hospitalization. Design and Measurements This was a secondary analysis of the 2011 Healthcare Cost and Utilization Project ( HCUP ) State Inpatient Databases ( SID ) for California, Massachusetts, and Florida. The primary outcome was all‐cause readmission within 7 days after hospital discharge, compared to readmission on days 8–30, for patients aged 65 and older who were discharged from the hospital to a PAC facility. Predictor variables included patient, index hospitalization, and hospital characteristics; multivariable logistic regression was used to identify significant predictors of readmission within 7 days. Results There were 81,173 hospital readmissions from PAC facilities in the first 30 days after hospital discharge. Patients readmitted within the first week were older, white, urban, had fewer comorbid illnesses, had a higher number of previous hospital admissions, and less commonly had Medicare as a payer. Longer index hospital length of stay (LOS) was associated with decreased risk of early readmission ( OR 0.74; 95% CI 0.70–0.74 for LOS 4–7 days and 0.60; 95% CI 0.56–0.64 for LOS ≥8 days). Conclusions Shorter length of index hospital stay is associated with earlier readmission and suggests that for this comorbid, older population, a shorter hospital stay may be detrimental. Readmission after 1 week is associated with increased chronic disease burden, suggesting they may be associated with factors that are less modifiable.
Hospital Readmission
Acute care
Hospital discharge
Patient discharge
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Hospitalization and readmission rates have decreased in recent years, with the possible consequence that hospitals are increasingly filled with high-risk patients.We studied whether readmission reduction has affected the risk profile of hospitalized patients and whether readmission reduction was similarly realized among hospitalizations with low, medium, and high risk of readmissions.Retrospective study of hospitalizations between January 2009 and June 2015.Hospitalized fee-for-service Medicare beneficiaries, categorized into 1 of 5 specialty cohorts used for the publicly reported hospital-wide readmission measure.Each hospitalization was assigned a predicted risk of 30-day, unplanned readmission using a risk-adjusted model similar to publicly reported measures. Trends in monthly mean predicted risk for each cohort and trends in monthly observed to expected readmission for hospitalizations in the lowest 20%, middle 60%, and highest 20% of risk of readmission were assessed using time series models.Of 47,288,961 hospitalizations, 16.2% (n = 7,642,161) were followed by an unplanned readmission within 30 days. We found that predicted risk of readmission increased by 0.24% (P = .03) and 0.13% (P = .004) per year for hospitalizations in the surgery/ gynecology and neurology cohorts, respectively. We found no significant increase in predicted risk for hospitalizations in the medicine (0.12%, P = .12), cardiovascular (0.32%, P = .07), or cardiorespiratory (0.03%, P = .55) cohorts. In each cohort, observed to expected readmission rates steadily declined, and at similar rates for patients at low, medium, and high risk of readmission.Hospitals have been effective at reducing readmissions across a range of patient risk strata and clinical conditions. The risk of readmission for hospitalized patients has increased for 2 of 5 clinical cohorts.
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Interquartile range
Hospital Readmission
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Increasing pediatric care regionalization may inadvertently fragment care if children are readmitted to a different (nonindex) hospital rather than the discharge (index) hospital. Therefore, this study aimed to assess trends in pediatric nonindex readmission rates, examine the risk factors, and determine if this destination difference affects readmission outcomes.In this retrospective cohort study, we use the Healthcare Cost and Utilization Project State Inpatient Database to include pediatric (0 to 18 years) admissions from 2010 to 2017 across Florida hospitals. Risk factors of nonindex readmissions were identified by using logistic regression analyses. The differences in outcomes between index versus nonindex readmissions were compared for in-hospital mortality, morbidity, hospital cost, length of stay, against medical advice discharges, and subsequent hospital visits by using generalized linear regression models.Among 41 107 total identified readmissions, 5585 (13.6%) were readmitted to nonindex hospitals. Adjusted nonindex readmission rate increased from 13.3% in 2010% to 15.4% in 2017. Patients in the nonindex readmissions group were more likely to be adolescents, live in poor neighborhoods, have higher comorbidity scores, travel longer distances, and be discharged at the postacute facility. After risk adjusting, no difference in in-hospital mortality was found, but morbidity was 13% higher, and following unplanned emergency department visits were 28% higher among patients with nonindex readmissions. Length of stay, hospital costs, and against medical advice discharges were also significantly higher for nonindex readmissions.A substantial proportion of children experienced nonindex readmissions and relatively poorer health outcomes compared with index readmission. Targeted strategies for improving continuity of care are necessary to improve readmission outcomes.
Hospital Readmission
Charlson comorbidity index
Pediatric hospital
Against medical advice
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It is widely believed that timely follow-up decreases hospital readmissions; however, the literature evaluating time to follow-up is limited. The authors conducted a retrospective analysis of patients discharged from a tertiary care academic medical center and evaluated the relationship between outpatient follow-up appointments made and 30-day unplanned readmissions. Of 1044 patients discharged home, 518 (49.6%) patients had scheduled follow-up ≤14 days after discharge, 52 (4.9%) patients were scheduled ≥15 days after discharge, and 474 (45.4%) had no scheduled follow-up. There was no statistical difference in 30-day readmissions between patients with follow-up within 14 days and those with follow-up 15 days or longer from discharge (P = .36) or between patients with follow-up within 14 days and those without scheduled follow-up (P = .75). The timing of postdischarge follow-up did not affect readmissions. Further research is needed to determine such factors and to prospectively study time to outpatient follow-up after discharge and the decrease in readmission rates.
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Patient discharge
Hospital discharge
Outpatient visits
Tertiary care
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Hospital Readmission
Charlson comorbidity index
Acute care
Nomogram
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Hospital Readmission
Charlson comorbidity index
Acute care
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The purpose of this study is to evaluate the role of HbA1C and its impact on hospital readmission. Despite widespread recognition of the burden of hospital readmissions, there are only a few studies focused on readmissions among patients with diabetes. We hypothesize that HbA1C values are associated with hospital readmission rates and would be an important indicator of risk of hospital readmission.
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Hospital admission
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A significant proportion of readmissions occurs at a different hospital than the index admission, and is thus missed by current quality metrics. No study has examined all-hospital adult 30-day readmission rates, including different hospitals, following burn injury across the United States. The purpose of this study was to evaluate nationwide readmission rates, potential risk factors, and ultimately the burden of burn injury readmission, including readmission to a different hospital. The 2010–2014 Nationwide Readmissions Database was queried for patients admitted for burn. Multivariate logistic regression identified risk factors and associated cost for 30-day readmission at index and different hospitals. There were 94,759 patients admitted during the study period, with 7.4% (n = 7000) readmitted and of those, 29.2% (n = 2047) readmitted to a different hospital. The most common reason for readmission was infection (29.4% [n = 1990]). Risk factors for unplanned 30-day readmission to any hospital included burn of lower limbs (odds ratio [OR] 1.29, [1.21–1.37], P < .01), third degree burns (OR 1.31, [1.22–1.41], P < .01), Charlson Comorbidity Index ≥2 (OR 1.48, [1.37–1.60], P < .01), depression (OR 1.30, [1.19–1.41], P < .01), and psychoses (OR 1.53, [1.40–1.67], P < .01). Risk factors unique to readmission to a different hospital included: length of stay greater than 7 days (OR 2.07, [1.78–2.40], P < 0.01), and initial admission to a metropolitan teaching hospital (OR 1.50, [1.26–1.78], P < .01). Previously unreported, one in three burn readmissions nationally occur at a different hospital, have unique risk factors, and are costlier. Current hospital benchmarking underestimates readmission by failing to capture this unique subpopulation.
Hospital Readmission
Charlson comorbidity index
Depression
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