Predictors of Hospital Length of Stay and Readmissions in Ischemic Stroke Patients and the Impact of Inpatient Medication Management

Okere, Arinze Nkemdirim; Renier, Colleen M.; Frye, Angela

doi:10.1016/j.jstrokecerebrovasdis.2016.04.011

Cited by 13 publications

(7 citation statements)

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“…This study found that patients with Medicare insurance and severity of illness were important predictors for increased LOS in their stroke patients. While the data from our study did not find a statistically significant relationship in those patients insured by Medicare versus private insurance, the fact that severity of illness was a predictor in the Okere study,[ 8 ] supports the findings in this study which found that there is a significant relationship between admission to the intensive care unit and prolonged length of stay.…”

Section: Discussionsupporting

confidence: 75%

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Predictive model of length of stay and discharge destination in neuroscience admissions

Stecker

Falotico

2017

Surg Neurol Int

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Background:The purpose of this study was to try and determine the best predictors of hospital length of stay and discharge destination in patients admitted to a neuroscience service.Methods:Valid data was collected for 170 patients. Variables included age, gender, location prior to admission, principle diagnosis, various physiological measurements upon admission, comorbidity, independence in various activities of daily living prior to admission, length of stay, and disposition upon discharge. Study design was a correlational descriptive study performed through the analysis of data and the development and validation of statistically significant factors in determining the length of stay.Results:All factors with a strong (P < 0.05) relationship with the length of stay were entered into a forward stepwise linear regression with length of stay as the dependent variable. The three most significant variables in predicting length of stay in this study were admission from an outpatient setting, modified Rankin score on admission, and systolic blood pressure on admission.Conclusions:Functional status at admission, specifically, a higher modified Rankin score and a lower systolic blood pressure along with the acquisition of deep vein thrombosis, catheter associated urinary tract infections, intubation, and admission to an intensive care unit all have a statistically significant effect on the hospital length of stay.

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Section: Discussionsupporting

confidence: 75%

“…Okere et al . [ 8 ] studied predictors for increased LOS in patients with nonsurgical ischemic stroke. This study found that patients with Medicare insurance and severity of illness were important predictors for increased LOS in their stroke patients.…”

Section: Discussionmentioning

confidence: 99%

Predictive model of length of stay and discharge destination in neuroscience admissions

Stecker

Falotico

2017

Surg Neurol Int

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“…Factors associated with stroke readmission have been characterized in five domains: patient characteristics, social circumstances, clinical processes of care, health outcomes, and health system determinants (including hospital location and treating physician) ( 11 ). Although treating physician (neurology vs. non-neurology service) was investigated in our analysis, location of the hospital proximity of patients ( 12 ) and insurance type ( 13 , 14 ) were not analyzed and have been previously demonstrated to influence readmission.…”

Section: Discussionmentioning

confidence: 99%

High Mortality among 30-Day Readmission after Stroke: Predictors and Etiologies of Readmission

et al. 2017

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BackgroundAlthough some risk factors for stroke readmission have been reported, the mortality risk is unclear. We sought to evaluate etiologies and predictors of 30-day readmissions and determine the associated mortality risk.MethodsThis is a retrospective case–control study evaluating 1,544 patients admitted for stroke (hemorrhagic, ischemic, or TIA) from January 2013 to December 2014. Of these, 134 patients readmitted within 30 days were identified as cases; 1,418 other patients, with no readmissions were identified as controls. Patients readmitted for hospice or elective surgery were excluded. An additional 248 patients deceased on index admission were included for only a comparison of mortality rates. Factors explored included socio-demographic characteristics, clinical comorbidities, stroke characteristics, and length of stay. Chi-square test of proportions and multivariable logistic regression were used to identify independent predictors of 30-day stroke readmissions. Mortality rates were compared for index admission and readmission and among readmission diagnoses.ResultsAmong the 1,544 patients in the main analysis, 67% of index stroke admissions were ischemic, 22% hemorrhagic, and 11% TIA. The 30-day readmission rate was 8.7%. The most common etiologies for readmission were infection (30%), recurrent stroke and TIA (20%), and cardiac complications (14%). Significantly higher proportion of those readmitted for recurrent strokes and TIAs presented within the first week (p = 0.039) and had a shorter index admission length of stay (p = 0.027). Risk factors for 30-day readmission included age >75 (p = 0.02), living in a facility prior to index stroke (p = 0.01), history of prior stroke (p = 0.03), diabetes (p = 0.03), chronic heart failure (p ≤ 0.001), atrial fibrillation (p = 0.03), index admission to non-neurology service (p < 0.01), and discharge to other than home (p < 0.01). On multivariate analysis, index admission to a non-neurology service was an independent predictor of 30-day readmission (p ≤ 0.01). The mortality after a within 30-day readmission after stroke was higher than index admission (36.6 vs. 13.8% p ≤ 0.001) (OR 3.6 95% CI 2.5–5.3). Among those readmitted, mortality was significantly higher for those admitted for a recurrent stroke (p = 0.006).ConclusionApproximately one-third of 30-day readmissions were infection related and one-fifth returned with recurrent stroke or TIA. Index admission to non-neurology service was an independent risk factor of 30-day readmissions. The mortality rate for 30-day readmission after stroke is more than 2.5 times greater than index admissions and highest among those readmitted for recurrent stroke. Identifying high-risk patients for readmission, ensuring appropriate level of service, and early outpatient follow-up may help reduce 30-day readmission and the high associated risk of mortality.

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“…In a recent report, the Centers for Disease Control called for further evaluation of system-level factors that may result in variation in stroke outcomes (Adeoye et al, 2019; Centers for Disease Control and Prevention, 2018). In the few studies examining system-level factors, investigators have focused on the availability of stroke physician specialists and stroke center status (Doyle et al, 2013;Okere et al, 2016;Shkirkova et al, 2020;Thompson et al, 2017). Nurses are an integral part of health care systems and provide around the clock monitoring and management to stroke patients, though few investigators have examined nursing's influence on stroke outcomes (Camicia & Lutz, 2016;Summers et al, 2009).…”

mentioning

confidence: 99%

Better nurse work environments associated with fewer readmissions and shorter length of stay among adults with ischemic stroke: A cross‐sectional analysis of United States hospitals

Brom

Carthon

Sloane

et al. 2021

Research in Nursing & Health

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Stroke is among the most common reasons for disability and death. Avoiding readmissions and long lengths of stay among ischemic stroke patients has benefits for patients and health care systems alike. Although reduced readmission rates among a variety of medical patients have been associated with better nurse work environments, it is unknown how the work environment might influence readmissions and length of stay for ischemic stroke patients. Using linked data sources, we conducted a cross-sectional analysis of 543 hospitals to evaluate the association between the nurse work environment and readmissions and length of stay for 175,467 hospitalized adult ischemic stroke patients. We utilized logistic regression models for readmission to estimate odds ratios (OR) and zero-truncated negative binomial models for length of stay to estimate the incident-rate ratio (IRR). Final models accounted for hospital and patient characteristics. Seven and 30-day readmission rates were 3.9% and 10.1% respectively and the average length of stay was 4.9 days. In hospitals with better nurse work environments ischemic stroke patients experienced lower odds of 7-and 30-day readmission (7-day OR, 0.96; 95% confidence interval [CI]: 0.93-0.99 and 30-day OR, 0.97; 95% CI: 0.94-0.99) and lower length of stay (IRR, 0.97; 95% CI: 0.95-0.99). The work environment is a modifiable feature of hospitals that should be considered when providing comprehensive stroke care and improving post-stroke outcomes.ischemic stroke, length of stay, nurse work environment, readmissionGlobally, stroke is the second highest cause of death and third highest reason for disability (Benjamin et al., 2017;Gorelick, 2019). Despite acute stroke management being highly protocolized, variation still exists with regard to patient outcomes (Kaufman et al., 2019;Messé et al., 2016). For example, readmission rates among stroke patients are as high as 13% with most readmissions being unplanned and many avoidable (Bambhroliya et al., 2018;Vahidy et al., 2017).Variations in outcomes, including readmissions and length of stay, have been attributed to patient factors, including age and underlying general health (

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Predictors of Hospital Length of Stay and Readmissions in Ischemic Stroke Patients and the Impact of Inpatient Medication Management

Cited by 13 publications

References 24 publications

Predictive model of length of stay and discharge destination in neuroscience admissions

Predictive model of length of stay and discharge destination in neuroscience admissions

High Mortality among 30-Day Readmission after Stroke: Predictors and Etiologies of Readmission

Better nurse work environments associated with fewer readmissions and shorter length of stay among adults with ischemic stroke: A cross‐sectional analysis of United States hospitals

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