Vital Sign Abnormalities on Discharge Do Not Predict 30-Day Readmission

Deviating vital signs in continuous monitoring prior to discharge and risk of readmission: an observational study

Premature discharge may result in readmission while longer hospitalization may increase risk of complications such as immobilization and reduce hospital capacity. Continuous monitoring detects more deviating vital signs than intermittent measurements and may help identify patients at risk of deterioration after discharge. We aimed to investigate the association between deviating vital signs detected by continuous monitoring prior to discharge and risk of readmission within 30 days. Patients undergoing elective major abdominal surgery or admitted with acute exacerbation of chronic obstructive pulmonary disease were included in this study. Eligible patients had vital signs monitored continuously within the last 24 h prior to discharge. The association between sustained deviated vital signs and readmission risk was analyzed by using Mann-Whitney's U test and Chi-square test. A total of 51 out of 265 patients (19%) were readmitted within 30 days. Deviated respiratory vital signs occurred frequently in both groups: desaturation < 88% for at least ten minutes was seen in 66% of patients who were readmitted and in 62% of those who were not (p = 0.62) while desaturation < 85% for at least five minutes was seen in 58% of readmitted and 52% of non-readmitted patients (p = 0.5). At least one sustained deviated vital sign was detected in 90% and 85% of readmitted patients and non-readmitted patients, respectively (p = 0.2). Deviating vital signs prior to hospital discharge were frequent but not associated with increased risk of readmission within 30 days. Further exploration of deviating vital signs using continuous monitoring is needed.

Active clinical issues at discharge predict readmission within 30 days and one year following hip fracture surgery

AIM

To investigate the impact of delay in surgery for medical causes and active clinical issues (ACIs) on 30-day readmission for medical causes after hip fracture surgery.

FINDINGS

ACIs were associated with readmissions following hip fracture surgery; however, no association between readmissions and reasons for delaying surgery was found.

MESSAGE

Further studies into ACIs and reasons for delaying surgery are warranted to make more tailor-made treatment plans for patients with hip fracture.

Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes: The 2019 Literature Year in Review

Data science continues to be recognized and used within healthcare due to the increased availability of large data sets and advanced analytics. It can be challenging for nurse leaders to remain apprised of this rapidly changing landscape. In this article, we describe our findings from a scoping literature review of papers published in 2019 that use data science to explore, explain, and/or predict 15 phenomena of interest to nurses. Fourteen of the 15 phenomena were associated with at least one paper published in 2019. We identified the use of many contemporary data science methods (eg, natural language processing, neural networks) for many of the outcomes. We found many studies exploring Readmissions and Pressure Injuries. The topics of Artificial Intelligence/Machine Learning Acceptance, Burnout, Patient Safety, and Unit Culture were poorly represented. We hope that the studies described in this article help readers: (1) understand the breadth and depth of data science's ability to improve clinical processes and patient outcomes that are relevant to nurses and (2) identify gaps in the literature that are in need of exploration.

The LACE Index: A Predictor of Mortality and Readmission in Patients With Acute Myocardial Infarction

INTRODUCTION

Improving patient outcomes after acute myocardial infarction (AMI) may be facilitated by identifying patients at a high risk of adverse events before hospital discharge. We aimed to determine the accuracy of the LACE (Length of stay, Acuity, Comorbidities, Emergency presentations within prior 6 months) index score (a prediction tool) for predicting 30-day all-cause mortality and readmission rates (independently and combined) in South Australian AMI patients who had an angiogram.

METHODS

All consecutive AMI patients enrolled in the Coronary Angiogram Database of South Australia Registry at two major tertiary hospitals and discharged alive between July 2016 to June 2017. A LACE score was calculated for each patient, and receiver operating characteristic curve analysis was performed.

RESULTS

Analysis of registry patients found a 30-day unplanned readmission rate of 11.8% and mortality rate of 0.7%. Moreover, the LACE index was a moderate predictor (C-statistic = 0.62) of readmissions in this cohort, and a score ≥10 indicated moderate discriminatory capacity to predict 30-day readmissions.

CONCLUSION

The LACE index shows moderate discriminatory capacity to predict 30-day readmissions and mortality. A cut-off score of nine to optimize sensitivity may assist clinicians in identifying patients at a high risk of adverse outcomes.

HOSPITAL Score, LACE Index and LACE+ Index as predictors of 30-day readmission in patients with heart failure

This study aimed to evaluate the accuracy of the HOSPITAL Score (Haemoglobin level at discharge, Oncology at discharge, Sodium level at discharge, Procedure during hospitalization, Index admission, number of hospital admissions, Length of stay) LACE index (Length of stay, Acute/emergent admission, Charlson comorbidy index score, Emerency department visits in previous 6 months) and LACE+ index in predicting 30-day readmission in patients with diastolic dysfunction. Heart failure remains one of the most common hospital readmissions in adults, leading to significant morbidity and mortality. Different models have been used to predict 30-day hospital readmissions. All adult medical patients discharged from the SIU School of Medicine Hospitalist service from 12 June 2016 to 12 June 2018 with an International Classification of Disease, 10th Revision, Clinical Modification diagnosis of diastolic heart failure were studied retrospectively to evaluate the performance of the HOSPITAL Score, LACE index and LACE+ index readmission risk prediction tools in this patient population. Of the 730 patient discharges with a diagnosis of heart failure with preserved ejection fraction (HFpEF), 692 discharges met the inclusion criteria. Of these discharges, 189 (27%) were readmitted to the same hospital within 30 days. A receiver operating characteristic evaluation showed C-statistic values to be 0.595 (95% CI 0.549 to 0.641) for the HOSPITAL Score, 0.551 (95% CI 0.503 to 0.598) for the LACE index and 0.568 (95% CI 0.522 to 0.615) for the LACE+ index, indicating poor specificity in predicting 30-day readmission. The result of this study demonstrates that the HOSPITAL Score, LACE index and LACE+ index are not effective predictors of 30-day readmission for patients with HFpEF. Further analysis and development of new prediction models are needed to better estimate the 30-day readmission rates in this patient population.

Vital sign abnormalities as predictors of clinical deterioration in subacute care patients: A prospective case-time-control study

BACKGROUND

Emergency interhospital transfers from inpatient subacute care to acute care occur in 8% to 17.4% of admitted patients and are associated with high rates of acute care readmission and in-hospital mortality. Serious adverse events in subacute care (rapid response team or cardiac arrest team calls) and increased nursing surveillance are the strongest known predictors of emergency interhospital transfer from subacute to acute care hospitals. However, the epidemiology of clinical deterioration across sectors of care, and specifically in subacute care is not well understood.

OBJECTIVES

To explore the trajectory of clinical deterioration in patients who did and did not have an emergency interhospital transfer from subacute to acute care; and develop an internally validated predictive model to identify the role of vital sign abnormalities in predicting these emergency interhospital transfers.

DESIGN

This prospective, exploratory cohort study is a subanalysis of data derived from a larger case-time-control study.

SETTING

Twenty-two wards of eight subacute care hospitals in five major health services in Victoria, Australia. All subacute care hospitals were geographically separate from their health services' acute care hospitals.

PARTICIPANTS

All patients with an emergency transfer from inpatient rehabilitation or geriatric evaluation and management unit to an acute care hospital within the same health service were included. Patients receiving palliative care were excluded.

METHODS

Study data were collected between 22 August 2015 and 30 October 2016 by medical record audit. The Cochran-Mantel-Haenszel test and bivariate logistic regression analysis were used to compare cases with controls and to account for health service clustering effect.

RESULTS

Data were collected on 603 transfers (557 patients) and 1160 controls. Adjusted for health service, ≥2 vital sign abnormalities in subacute care (adjusted odds ratio=8.81, 95% confidence intervals:6.36-12.19, p<0.001) and serious adverse events during the first acute care admission (adjusted odds ratio=1.28, 95% confidence intervals:1.08-1.99, p=0.015) were the clinical factors associated with increased risk of emergency interhospital transfer. An internally validated predictive model showed that vital sign abnormalities can fairly predict emergency interhospital transfers from subacute to acute care hospitals.

CONCLUSION

Serious adverse events in acute care should be a key consideration in decisions about the location of subacute care delivery. During subacute care, 15.7% of cases had vital signs fulfilling organisational rapid response team activation criteria, yet missed rapid response team activations were common suggesting that further consideration of the criteria and strategies to optimise recognition and response to clinical deterioration in subacute care are needed.

Heart Failure Drug Class Effects on 30-Day Readmission Rates in Patients with Heart Failure with Preserved Ejection Fraction: A Retrospective Single Center Study

Background: The pharmacologic management of heart failure with preserved ejection fraction (HFpEF) involves far fewer options with demonstrated additional benefit. Therefore, we examined the effect of combination of multiple classes of HF medication in the 30-day hospital readmission in patients with HFpEF. Methods: All adult patients discharged with a diagnosis of HFpEF and a left ventricular ejection fraction (LVEF) of ≥ 50% reported during the admission or within the previous six months from our institution were retrospectively studied for a 30-day hospital readmission risk. Individual as well as combination drug therapy at the time of hospital discharge were evaluated using Pearson chi2 test and multivariate logistic regression. Results: The overall 30-day readmission rate in this HFpEF cohort of 445 discharges was 29%. Therapy with loop diuretics (p = 0.011), loop diuretics and angiotensin receptor blocker (p = 0.043) and loop diuretics and beta blockers (p = 0.049) were associated with a lower risk of 30-day hospital readmission. Multivariate logistic regression revealed only loop diuretics to be associated with a lower risk of hospital readmission in patients with HFpEF (OR 0.59; 95% CI, 0.39-0.90; p = 0.013). Conclusions: Our study revealed that loop diuretics at discharge decreases early readmission in patients with HFpEF. Further, our study highlights the implication of a lack of guidelines and treatment challenges in HFpEF patients and emphasizes the importance of a conservative approach in preventing early readmission in patients with HFpEF.

Predictors of 30-day hospital readmission: The direct comparison of number of discharge medications to the HOSPITAL score and LACE index

Effective hospital readmission risk prediction tools exist, but do not identify actionable items that could be modified to reduce the risk of readmission. Polypharmacy has attracted attention as a potentially modifiable risk factor for readmission, showing promise in a retrospective study. Polypharmacy is a very complex issue, reflecting comorbidities and healthcare resource utilisation patterns. This investigation compares the predictive ability of polypharmacy alone to the validated HOSPITAL score and LACE index readmission risk assessment tools for all adult admissions to an academic hospitalist service at a moderate sized university-affiliated hospital in the American Midwest over a 2-year period. These results indicate that the number of discharge medications alone is not a useful tool in identifying patients at high risk of hospital readmission within 30 days of discharge. Further research is needed to explore the impact of polypharmacy as a risk predictor for hospital readmission.