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Age-related differences in the rate and diagnosis of 30-day readmission after hospitalization for acute ischemic stroke.

ABSTRACT: Background Little is known about the association between age and readmission within 30 days after hospitalization for acute ischemic stroke. Aim To examine the age-related differences in rate and principal reason of 30-day readmissions in patients hospitalized for acute ischemic stroke. Methods In this retrospective, population-based cohort study using State Inpatient Databases from eight US states, we identified all adults hospitalized for acute ischemic stroke. We grouped the patients into four age categories: < 65, 65-74, 75-84, and ≥85 years. Outcomes were any-cause readmission within 30 days of discharge from the index hospitalization for acute ischemic stroke and the principal diagnosis of 30-day readmission. Results We identified 620,788 hospitalizations for acute ischemic stroke. The overall 30-day readmission rate was 16.6% with an increase with advanced age. Compared to patients aged <65 years, the readmission rate was significantly higher in age 65-74 years (OR 1.19; 95% CI 1.16-1.21), in age 75-84 years (OR 1.29; 95% CI 1.27-1.31), and in ≥ 85 years (OR 1.24; 95% CI 1.22-1.27; all P<0.001). There was heterogeneity in the age-readmission rate association between men and women (P_interaction < 0.001). Overall, 45.8% of readmissions were assigned stroke-related conditions or rehabilitation care. Compared to younger adults, older adults were more likely to present with non-stroke-related conditions (46.1% in < 65 years, 50.6% in 65-74 years, 57.1% in 75-84 years, and 62.9% in ≥ 85 years; P<0.001). Conclusions Advanced age was associated with a higher 30-day readmission rate after acute ischemic stroke. Compared with younger adults, older adults were more likely to be readmitted for non-stroke-related conditions.

SUBMITTER: Hirayama A

PROVIDER: S-EPMC7718769 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Age-related differences in the rate and diagnosis of 30-day readmission after hospitalization for acute ischemic stroke.

Hirayama Atsushi A Goto Tadahiro T Faridi Mohammad K MK Camargo Carlos A CA Hasegawa Kohei K

International journal of stroke : official journal of the International Stroke Society 20180425 7

Background Little is known about the association between age and readmission within 30 days after hospitalization for acute ischemic stroke. Aim To examine the age-related differences in rate and principal reason of 30-day readmissions in patients hospitalized for acute ischemic stroke. Methods In this retrospective, population-based cohort study using State Inpatient Databases from eight US states, we identified all adults hospitalized for acute ischemic stroke. We grouped the patients into fou ...[more]

PMID: 29693505

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Project description:Background and Purpose: Hospital readmissions impose a substantial burden on the healthcare system. Reducing readmissions after stroke could lead to improved quality of care especially since stroke is associated with a high rate of readmission. The goal of this study is to enhance our understanding of the predictors of 30-day readmission after ischemic stroke and develop models to identify high-risk individuals for targeted interventions. Methods: We used patient-level data from electronic health records (EHR), five machine learning algorithms (random forest, gradient boosting machine, extreme gradient boosting-XGBoost, support vector machine, and logistic regression-LR), data-driven feature selection strategy, and adaptive sampling to develop 15 models of 30-day readmission after ischemic stroke. We further identified important clinical variables. Results: We included 3,184 patients with ischemic stroke (mean age: 71 ± 13.90 years, men: 51.06%). Among the 61 clinical variables included in the model, the National Institutes of Health Stroke Scale score above 24, insert indwelling urinary catheter, hypercoagulable state, and percutaneous gastrostomy had the highest importance score. The Model's AUC (area under the curve) for predicting 30-day readmission was 0.74 (95%CI: 0.64-0.78) with PPV of 0.43 when the XGBoost algorithm was used with ROSE-sampling. The balance between specificity and sensitivity improved through the sampling strategy. The best sensitivity was achieved with LR when optimized with feature selection and ROSE-sampling (AUC: 0.64, sensitivity: 0.53, specificity: 0.69). Conclusions: Machine learning-based models can be designed to predict 30-day readmission after stroke using structured data from EHR. Among the algorithms analyzed, XGBoost with ROSE-sampling had the best performance in terms of AUC while LR with ROSE-sampling and feature selection had the best sensitivity. Clinical variables highly associated with 30-day readmission could be targeted for personalized interventions. Depending on healthcare systems' resources and criteria, models with optimized performance metrics can be implemented to improve outcomes.

Project description:ImportanceReadmission reduction is linked to improved quality of care, saves cost, and is a desirable patient-centered outcome. Nationally representative readmission metrics for patients with stroke are unavailable to date. Such estimates are necessary for benchmarking performance.ObjectivesTo provide US nationwide estimates and a temporal trend for overall, planned, and potentially preventable 30-day hospital readmission among patients with ischemic and hemorrhagic stroke; to investigate the association between hospitals' stroke discharge volume, teaching status, and 30-day readmission; and to highlight reasons for 30-day readmission and explore the association of 30-day readmission in terms of mortality, length of stay, and cost of care among patients with stroke.Design, setting, and participantsCohort, year-wise analysis of the Nationwide Readmissions Database between January 1, 2010, and September 30, 2015. The setting was a population-based cohort study providing national estimates of 30-day readmission. The database represents 50% of all US hospitalizations from 22 geographically dispersed states. Participants were adult (≥18 years) patients with a primary discharge diagnosis of intracerebral hemorrhage, acute ischemic stroke, or subarachnoid hemorrhage. Hospitals were categorized by their annual stroke discharge volume and were classified as teaching hospitals if they had an American Medical Association-approved residency program or had a ratio of full-time equivalent interns and residents to beds of 0.25 or higher.Main outcomes and measuresReadmission was defined as any admission within 30 days of index hospitalization discharge. Using Centers for Medicare & Medicaid Services-defined algorithms, events were classified as planned or unplanned and as potentially preventable.ResultsBased on study criteria, 2 078 854 eligible patients were included (mean [SE] age, 70.02 [0.07] years; 51.9% female). Thirty-day readmission was highest for patients with intracerebral hemorrhage (13.70%; 95% CI, 13.40%-13.99%), followed by patients with acute ischemic stroke (12.44%; 95% CI, 12.33%-12.55%) and patients with subarachnoid hemorrhage (11.48%; 95% CI, 11.01%-11.96%). On average, there was a 3.3% annual decline in readmission between 2010 and 2014, which was statistically significant for the period of investigation (odds ratio, 0.96; 95% CI, 0.95-0.97). Patients discharged from nonteaching hospitals with high stroke discharge volume were at a significantly higher risk of 30-day readmission, and the top 2 reasons for readmission were acute cerebrovascular disease and septicemia.Conclusions and relevanceThis study suggests that nationally representative readmission metrics can be used to benchmark hospitals' performance, and a temporal trend of 3.3% may be used to evaluate the effectiveness of readmission reduction strategies.

Project description:ImportanceTrauma of hospitalization refers to the depersonalizing and stressful experience of a hospital admission and is hypothesized to increase the risk of readmission after discharge.ObjectivesTo characterize the trauma of hospitalization by measuring patient-reported disturbances in sleep, mobility, nutrition, and mood among medical inpatients, and to examine the association between these disturbances and the risk of unplanned return to hospital after discharge.Design, setting, and participantsThis prospective cohort study enrolled participants between September 1, 2016, and September 1, 2017, at 2 academic hospitals in Toronto, Canada. Participants were adults admitted to the internal medicine ward for more than 48 hours. Participants were interviewed before discharge using a standardized questionnaire to assess sleep, mobility, nutrition, and mood. Responses for each domain were dichotomized as disturbance or no disturbance. Disturbance in 3 or 4 domains (the upper tertile) was considered high trauma of hospitalization, and disturbance in 0 to 2 domains (the lower 2 tertiles) was considered low trauma.Main outcome and measuresThe primary outcome was readmission or emergency department visit within 30 days of discharge. The association between trauma of hospitalization and the primary outcome was examined using logistic regression, adjusted for age; sex; length of stay; Charlson Comorbidity Index Score; Laboratory-Based Acute Physiology Score; and baseline disturbances in sleep, mobility, nutrition, and mood.ResultsA total of 207 patients participated, of whom 82 (39.6%) were women and 125 (60.4%) were men, with a mean (SD) age of 60.3 (16.8) years. Among the 207 participants, 75 (36.2%) reported sleep disturbance, 162 (78.3%) reported mobility disturbance, 114 (55.1%) reported nutrition disturbance, and 48 (23.2%) reported mood disturbance. Nearly all participants (192 [92.8%]) described a disturbance in at least 1 domain, and 61 participants (29.5%) had high trauma exposure. A statistically significant 15.8% greater absolute risk of readmission or emergency department visit was found in participants with high trauma (37.7%; 95% CI, 25.9%-51.1%) compared with those with low trauma (21.9%; 95% CI, 15.7%-29.7%), which remained statistically significant after adjusting for baseline characteristics (adjusted odds ratio, 2.52; 95% CI, 1.24-5.17; P = .01) and propensity score matching (odds ratio, 2.47; 95% CI, 1.11-5.73; P = .03).Conclusions and relevanceDisturbances in sleep, mobility, nutrition, and mood were common in medical inpatients; such trauma of hospitalization may be associated with a greater risk of 30-day readmission or emergency department visit after hospital discharge.

Dataset Information

Age-related differences in the rate and diagnosis of 30-day readmission after hospitalization for acute ischemic stroke.

Publications

Age-related differences in the rate and diagnosis of 30-day readmission after hospitalization for acute ischemic stroke.

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