A roadmap for comparing readmission policies with application to Denmark, England, Germany and the United States

Rapid systematic review of readmissions costs after stroke

BACKGROUND

Stroke readmissions are considered a marker of health quality and may pose a burden to healthcare systems. However, information on the costs of post-stroke readmissions has not been systematically reviewed.

OBJECTIVES

To systematically review information about the costs of hospital readmissions of patients whose primary diagnosis in the index admission was a stroke.

METHODS

A rapid systematic review was performed on studies reporting post-stroke readmission costs in EMBASE, MEDLINE, and Web of Science up to June 2021. Relevant data were extracted and presented by readmission and stroke type. The original study's currency values were converted to 2021 US dollars based on the purchasing power parity for gross domestic product. The reporting quality of each of the included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist.

RESULTS

Forty-four studies were identified. Considerable variability in readmission costs was observed among countries, readmissions, stroke types, and durations of the follow-up period. The UK and the USA were the countries reporting the highest readmission costs. In the first year of follow-up, stroke readmission costs accounted for 2.1-23.4%, of direct costs and 3.3-21% of total costs. Among the included studies, only one identified predictors of readmission costs.

CONCLUSION

Our review showed great variability in readmission costs, mainly due to differences in study design, countries and health services, follow-up duration, and reported readmission data. The results of this study can be used to inform policymakers and healthcare providers about the burden of stroke readmissions. Future studies should not solely focus on improving data standardization but should also prioritize the identification of stroke readmission cost predictors.

Patients with repeated acute admissions to somatic departments: sociodemographic characteristics, disease burden, and contact with primary healthcare sector - a retrospective register-based case-control study

BACKGROUND

Healthcare systems face escalating capacity challenges and patients with repeated acute admissions strain hospital resources disproportionately. However, studies investigating the characteristics of such patients across all public healthcare providers in a universal healthcare system are lacking.

OBJECTIVE

To investigate characteristics of patients with repeated acute admissions (three or more acute admissions within a calendar year) in regard to sociodemographic characteristics, disease burden, and contact with the primary healthcare sector.

METHODS

This matched register-based case-control study investigated repeated acute admissions from 1 January 2014 to 31 December 2018, among individuals, who resided in four Danish municipalities. The study included 6169 individuals with repeated acute admissions, matched 1:4 to individuals with no acute admissions and one to two acute admissions, respectively. Group comparisons were conducted using conditional logistic regression.

RESULTS

Receiving social benefits increased the odds of repeated acute admissions 9.5-fold compared with no acute admissions (odds ratio (OR) 9.5; 95% confidence interval (CI) 8.5; 10.6) and 3.4-fold compared with one to two acute admissions (OR 3.4; 95% CI 3.1; 3.7). The odds of repeated acute admissions increased with the number of used medications and chronic diseases. Having a mental illness increased the odds of repeated acute admissions 5.8-fold when compared with no acute admissions (OR 5.7; 95% CI 5.2; 6.4) and 2.3-fold compared with one to two acute admissions (OR 2.3; 95% CI 2.1; 2.5). Also, high use of primary sector services (e.g. nursing care) increased the odds of repeated acute admissions when compared with no acute admissions and one to two acute admissions.

CONCLUSIONS

This study pinpointed key factors encompassing social status, disease burden, and healthcare utilisation as pivotal markers of risk for repeated acute admissions, thus identifying high-risk patients and facilitating targeted intervention.

Evaluating a shared care pathway intervention for people receiving chemotherapy to reduce post-treatment unplanned hospital presentations: a randomised controlled trial

PURPOSE

The aim of this randomised controlled trial (RCT) was to explore whether a community nursing intervention for outpatients receiving systemic therapy reduced unplanned hospital presentations and improved physical and psychosocial health outcomes over the first three cycles of treatment compared to a control group receiving standard care.

METHODS

The number of and reasons for unplanned presentations were obtained for 170 intervention and 176 control group adult patients with solid tumours starting outpatient chemotherapy. Poisson regression was used to compare the number of presentations between the intervention and control groups. Patients self-completed the Hospital Anxiety and Depression Scale, the Cancer Behavior Inventory and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORTC QLQ-C30) at the start of the first four cycles. Linear regression techniques were used to compare quality of life outcomes.

RESULTS

The reduction in unplanned presentations in the intervention group relative to the control group was 12% (95% CI, - 25%, 37%; P = 0.48). At the start of cycle 4, there was no difference in anxiety (difference = 0.47 (95% CI, - 0.28, 1.22; P = 0.22)), depression (difference = 0.57 (95% CI, - 0.18, 1.31; P = 0.13)) or EORTC QLQ-C30 summary score (difference = 0.16 (95% CI, - 2.67, 3.00; P = 0.91)). Scores for self-efficacy as measured by the Cancer Behavior Inventory were higher in the intervention group (difference = 4.3 (95% CI, 0.7, 7.9; P = 0.02)).

CONCLUSION

This RCT did not demonstrate a benefit in reducing unplanned presentations to hospital. The trial identified improved cancer-based self-efficacy in patients receiving the intervention.

TRIAL REGISTRATION

Registered at Australian and New Zealand Clinical Trials Registry: ACTRN12614001113640, registered 21/10/2014.

Readmission is experienced as inevitable among older adults receiving homecare: A qualitative interview study

BACKGROUND

Older adults receiving homecare have an increased risk of readmission. The transition from hospital to home can be experienced as unsafe, and older adults describe themselves as vulnerable during the post-discharge period. Thus, the objective was to explore the experiences of unplanned readmissions among older adults who receive homecare.

METHODS

We conducted qualitative individual semi-structured interviews with older adults, 65 years or above, receiving homecare and being readmitted to an emergency department (ED) between August and October 2020. Data were analysed by systematic text condensation as described by Malterud.

FINDINGS

We included 12 adults aged 67-95 years, seven were male, and eight lived alone. The analysis derived three themes: (1) Responsibility and security at home, (2) the role of family, friends and homecare and (3) the importance of trust. The older adults felt that the hospital strived for too-early discharge, as they still did not feel well. They worried about how to manage their daily life. Active involvement of their family increased their sense of security, but those living alone described feeling anxious being at home by themselves after discharge. Although older adults did not wish to go to the hospital, inadequate treatment at home and the feeling of responsibility for their illness made them feel insecure. They expressed that earlier negative experiences affected their trust in the system and their inclination to ask for help.

CONCLUSIONS

The older adults were discharged from the hospital despite feeling ill. They described inadequate competencies from healthcare professionals in the home as a contributing factor to their readmission. The readmission increased a sense of security. Support from the family in the process was essential and provided a sense of security, whereas older adults living alone experienced feelings of insecurity in the home environment.

Identifying older adults at increased risk of medication-related readmission to hospital within 30 days of discharge: development and validation of a risk assessment tool

OBJECTIVE

Developing and validating a risk assessment tool aiming to identify older adults (≥65 years) at increased risk of possibly medication-related readmission to hospital within 30 days of discharge.

DESIGN

Retrospective cohort study.

SETTING

The risk score was developed using data from a hospital in southern Sweden and validated using data from four hospitals in the mid-eastern part of Sweden.

PARTICIPANTS

The development cohort (n=720) was admitted to hospital during 2017, whereas the validation cohort (n=892) was admitted during 2017-2018.

MEASURES

The risk assessment tool aims to predict possibly medication-related readmission to hospital within 30 days of discharge. Variables known at first admission and individually associated with possibly medication-related readmission were used in development. The included variables were assigned points, and Youden's index was used to decide a threshold score. The risk score was calculated for all individuals in both cohorts. Area under the receiver operating characteristic (ROC) curve (c-index) was used to measure the discrimination of the developed risk score. Sensitivity, specificity and positive and negative predictive values were calculated using cross-tabulation.

RESULTS

The developed risk assessment tool, the Hospitalisations, Own home, Medications, and Emergency admission (HOME) Score, had a c-index of 0.69 in the development cohort and 0.65 in the validation cohort. It showed sensitivity 76%, specificity 54%, positive predictive value 29% and negative predictive value 90% at the threshold score in the development cohort.

CONCLUSION

The HOME Score can be used to identify older adults at increased risk of possibly medication-related readmission within 30 days of discharge. The tool is easy to use and includes variables available in electronic health records at admission, thus making it possible to implement risk-reducing activities during the hospital stay as well as at discharge and in transitions of care. Further studies are needed to investigate the clinical usefulness of the HOME Score as well as the benefits of implemented activities.

Leveraging deep survival models to predict quality of care risk in diverse hospital readmissions

Hospital readmissions rate is reportedly high and has caused huge financial burden on health care systems in many countries. It is viewed as an important indicator of health care providers' quality of care. We examine the use of machine learning-based survival analysis to assess quality of care risk in hospital readmissions. This study applies various survival models to explore the risk of hospital readmissions given patient demographics and their respective hospital discharges extracted from a health care claims dataset. We explore advanced feature representation techniques such as BioBERT and Node2Vec to encode high-dimensional diagnosis code features. To our knowledge, this study is the first to apply deep-learning based survival-analysis models for predicting hospital readmission risk agnostic of specific medical conditions and a fixed window for readmission. We found that modeling the time from discharge date to readmission date as a Weibull distribution as in the SparseDeepWeiSurv model yields the best discriminative power and calibration. In addition, embedding representations of the diagnosis codes do not contribute to improvement in model performance. We find dependency of each model's performance on the time point at which it is evaluated. This time dependency of the models' performance on the health care claims data may necessitate a different choice of model in quality of care issue detection at different points in time. We show the effectiveness of deep-learning based survival-analysis models in estimating the quality of care risk in hospital readmissions.

Readmission and associated clinical factors among individuals admitted with bipolar affective disorder at a psychiatry facility in Uganda

BACKGROUND

Bipolar affective disorder (BAD) is a common severe mental health condition with a relapsing course that may include periods of hospital re-admissions. With recurrent relapses and admissions, the course, prognosis, and patient's overall quality of life can be affected negatively. This study aims to explore the rates and clinical factors associated with re-admission among individuals with BAD.

METHOD

This study used data from a retrospective chart review of all records of patients with BAD admitted in 2018 and followed up their hospital records for four years till 2021 at a large psychiatric unit in Uganda. Cox regression analysis was used to determine the clinical characteristics associated with readmission among patients diagnosed with BAD.

RESULTS

A total of 206 patients living with BAD were admitted in 2018 and followed up for four years. The average number of months to readmission was 9.4 (standard deviation = 8.6). The incidence of readmission was 23.8% (n = 49/206). Of those readmitted during the study period, 46.9% (n = 23/49) and 28.6% (n = 14/49) individuals were readmitted twice and three times or more, respectively. The readmission rate in the first 12 months following discharge was 69.4% (n = 34/49) at first readmission, 78.3% (n = 18/23) at second readmission, and 87.5% (n = 12/14) at third or more times. For the next 12 months, the readmission rate was 22.5% (n = 11/49) for the first, 21.7% (n = 5/23) for the second, and 7.1% (n = 1/14) for more than two readmissions. Between 25 and 36 months, the readmission rate was 4.1% (n = 2/49) for the first readmission and 7.1% (n = 1/14) for the third or more times. Between 37 and 48 months, the readmission rate was 4.1% (n = 2/49) for those readmitted the first time. Patients who presented with poor appetite and undressed in public before admission were at increased risk of being readmitted with time. However, the following symptoms/clinical presentations, were protective against having a readmission with time, increased number of days with symptoms before admission, mood lability, and high energy levels.

CONCLUSION

The incidence of readmission among individuals living with BAD is high, and readmission was associated with patients' symptoms presentation on previous admission. Future studies looking at BAD using a prospective design, standardized scales, and robust explanatory model are warranted to understand causal factors for hospital re-admission and inform management strategies.

Why do we evaluate 30-day readmissions in general medicine? A historical perspective and contemporary data

Reducing preventable readmissions is important to help manage current strains on healthcare systems. The metric of 30-day readmissions is commonly cited in discussions regarding this topic. While such thresholds have contemporary funding implications, the rationale for individual cut-off points is partially historical in nature. Through the examination of the basis for the analysis of 30-day readmissions, greater insight into the possible benefits and limitations of such a metric may be obtained.

Conceptual framework for acute community health care services - Illustrated by assessing the development of services in Denmark

Acute community health care services can support continuity of care by acting as a bridge between the primary and secondary health care sectors in the early detection of acute disease and provision of treatment and care. Although acute community health care services are a political priority in many countries, the literature on their organization and effect is limited. We present a conceptual framework for describing acute community health care services that can be used to support the policies and guidelines for such services. For illustrative purposes, we apply the framework to the Danish acute community health care services using implementation data from 2020 and identify gaps and opportunities for learning. The framework identifies two key pairs of dimensions: (1) capacity & capability, and (2) coordination & collaboration. These dimensions, together with the governance structure and quality assurance initiatives, are of key importance to the effect of acute community health care services. While all Danish municipalities have implemented acute community health care services, application of the framework indicates considerable variation in their approaches. The conceptual framework provides a systematic approach supporting the development, implementation, evaluation, and monitoring of acute community health care services and can assist policymakers at both national and local levels in this work.

Effectiveness of Transition Care Intervention Targeted to High-Risk Patients to Reduce Readmissions: Study Protocol for the TARGET-READ Multicenter Randomized-Controlled Trial

Hospital readmissions within 30 days represent a burden for the patients and the entire health care system. Improving the care around hospital discharge period could decrease the risk of avoidable readmissions. We describe the methods of a trial that aims to evaluate the effect of a structured multimodal transitional care intervention targeted to higher-risk medical patients on 30-day unplanned readmissions and death. The TARGET-READ study is an investigator-initiated, pragmatic single-blinded randomized multicenter controlled trial with two parallel groups. We include all adult patients at risk of hospital readmission based on a simplified HOSPITAL score of ≥4 who are discharged home or nursing home after a hospital stay of one day or more in the department of medicine of the four participating hospitals. The patients randomized to the intervention group will receive a pre-discharge intervention by a study nurse with patient education, medication reconciliation, and follow-up appointment with their referring physician. They will receive short follow-up phone calls at 3 and 14 days after discharge to ensure medication adherence and follow-up by the ambulatory care physician. A blind study nurse will collect outcomes at 1 month by phone call interview. The control group will receive usual care. The TARGET-READ study aims to increase the knowledge about the efficacy of a bundled intervention aimed at reducing 30-day hospital readmission or death in higher-risk medical patients.

Is long time to reimplantation a risk factor for reinfection in two-stage revision for periprosthetic infection? A systematic review of the literature

The two-stage revision arthroplasty is a common treatment option for chronic periprosthetic infection (PJI). The time to reimplantation (TTR) reported in the literature varies substantially from a few days to several hundred days. It is hypothesized that longer TTR could be associated with worse infection control after second stage. A systematic literature search was performed according to Preferred Reporting items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, in Pubmed, Cochrane Library and Web of Science Core Collection in clinical studies published until January 2023. Eleven studies investigating TTR as a potential risk factor for reinfection met the inclusion criteria (ten retrospective and one prospective study, published 2012-2022). Study design and outcome measures differed notably. The cutoff points above which TTR was regarded as "long" ranged from 4 to 18 weeks. No study observed a benefit for long TTR. In all studies, similar or even better infection control was observed for short TTR. The optimal TTR, however, is not yet defined. Larger clinical studies with homogeneous patient populations and adjustment for confounding factors are needed.

Accuracy of the Simplified HOSPITAL Score to Predict Nonelective Readmission in a Brazilian Tertiary Care Public Teaching Hospital

BACKGROUND AND OBJECTIVES

Predictive models to identify patients at high risk of readmission have gained the attention of health care teams, which have focused the strategies to reduce unnecessary readmissions on the "at-risk" patients. The HOSPITAL score includes 7 predictor variables with a C-statistic of 0.70 or more when applied to international datasets. Its simplified version retains a C-statistic at around the same level, but only incipient external validation has been attempted to date. The primary objective of this study was to evaluate the prognostic accuracy of the simplified HOSPITAL score to predict nonelective hospital readmissions in a tertiary care public teaching hospital in Brazil.

METHODS

We used a retrospective cohort that included all patients discharged from the internal medicine service of a Brazilian tertiary care public teaching hospital in 2018. We excluded patients who died before index discharge, were transferred to another institution, left against medical advice, or were readmitted electively. We calculated the simplified HOSPITAL score for each admission, and admissions were divided into low (0-4 points) or high risk (≥ 5 points) of nonelective 30-day readmission. We estimated accuracy, area under the receiver operating characteristic curve (AUC), and observed/expected (O/E) readmission ratio; the latter using the mid-P exact test with Miettinen's modification at a 95% confidence interval (CI). A P value < .05 was considered significant.

RESULTS

A total of 4472 hospital discharges were analyzed during the study period after application of the exclusion criteria. The nonelective 30-day readmission rate was 14.0% (n = 625). Of all patients discharged, 3173 (71.0%) were considered to be at low risk and 1299 (29.0%) at high risk of readmission according to the simplified HOSPITAL score. The AUC was 0.68 (95% CI: 0.66-0.71; P < .001). The nonelective 30-day readmission rate was 9.2% in the low-risk group (expected: 9.2%; O/E: 1.0 [95% CI: 0.89-1.12]) and 25.7% in the high-risk group (expected: 27.2%; O/E: 0.95 [95% CI: 0.85-1.05]) ( P < .001). At a cut-off of 5 points, the score had a sensitivity of 53.4%, specificity of 74.9%, positive predictive value of 25.7%, and negative predictive value (NPV) of 90.8%.

CONCLUSIONS

The parameters of the score were almost identical to the original study, with better applicability to exclude low-risk patients given its high NPV. Additional adjustments are still needed for better applicability in daily clinical practice.

Early prediction of 30- and 14-day all-cause unplanned readmissions

BACKGROUND

An unplanned readmission is a dual metric for both the cost and quality of medical care.

METHODS

We employed the random forest (RF) method to build a prediction model using a large dataset from patients' electronic health records (EHRs) from a medical center in Taiwan. The discrimination abilities between the RF and regression-based models were compared using the areas under the ROC curves (AUROC).

RESULTS

When compared with standardized risk prediction tools, the RF constructed using data readily available at admission had a marginally yet significantly better ability to identify high-risk readmissions within 30 and 14 days without compromising sensitivity and specificity. The most important predictor for 30-day readmissions was directly related to the representing factors of index hospitalization, whereas for 14-day readmissions the most important predictor was associated with a higher chronic illness burden.

CONCLUSIONS

Identifying dominant risk factors based on index admission and different readmission time intervals is crucial for healthcare planning.

Readmission trends before and after a national reconfiguration of emergency departments in Denmark

OBJECTIVE

In order to achieve better and more efficient emergency health care, the Danish public hospital system has been reconfigured, with hospital emergency care being centralised into extensive and specialised emergency departments. This article examines how this reconfiguration has affected patient readmission rates.

METHODS

We included all unplanned hospital admissions (aged ≥18 years) at public, non-psychiatric hospitals in four geographical regions in Denmark between 1 January 2007 and 24 December 2017. Using an interrupted time-series design, we examined trend changes in the readmission rates. In addition to analysing the overall effect, analyses stratified according to admission time of day and weekdays/weekends were conducted. The analyses were adjusted for patient characteristics and other system changes.

RESULTS

The seven-day readmission rate increased from 2.6% in 2007 to 3.8% in 2017, and the 30-day rate increased from 8.1% to 11.5%. However, the rates were less than what they would have been had the reconfiguration not been introduced. The reconfiguration reduced the seven-day readmission rate by 1.4% annually (hazard ratio [CI 95%] 0.986 [0.981-0.991]) and the 30-day rate by 1% annually (hazard ratio [CI 95%] 0.99 [0.987-0.993]).

CONCLUSIONS

Reconfiguration reduced the rate of increase in readmissions, but nevertheless readmissions still increased across the study period. It seems hospitals and policymakers will need to identify further ways to reduce patient loads.

Frequency and patient attributes associated with emergency department visits after discharge: Retrospective cohort study

BACKGROUND

The utilization of emergency department (ED) during the post-discharge period may provide relevant insights to reduce fragmentation of care, particularly in a context of general intense use. We aimed to describe frequency and patient attributes associated with emergency department (ED) visits within 30 days of inpatient discharge in a Portuguese health region-Algarve.

METHODS

Secondary data on inpatient and emergency care, for adult patients discharged in 2016. To analyse the association between outcome-ED visit within 30 days of discharge-and selected variables (admission type and groups of or individual illnesses/conditions), we used age- and sex-adjusted odds ratios (aOR). We included all adult patients (aged ≥18 years) discharged during 2016 from the region's public hospital inpatient departments. The period for ED visits also included January 2017.

RESULTS

For 21,744 adults discharged in 2016 (mean age: 58 years; 60% female), 23 percent visited ED at least once within 30 days of discharge. Seventy-five percent of those visits were triaged with high clinical priority. Patients with more comorbidities or specific groups of illnesses/conditions had a significant increased risk of returning ED (aOR and 95% confidence intervals-endocrine: 1.566; 1.256-1.951; mental illness: 1.421; 1.180-1.713; respiratory: 1.308; 1.136-1.505).

CONCLUSION

Patients returned ED after inpatient discharge frequently and for severe reasons. Patients with more comorbidities or specific groups of illnesses/conditions (endocrine, mental illness or respiratory) had an increased risk of returning ED, so these groups may be prioritized in further research and health system initiatives to improve care before and after discharge.

MEASURING PERFORMANCE FOR END-OF-LIFE CARE

Although not without controversy, readmission is entrenched as a hospital quality metric with statistical analyses generally based on fitting a logistic-Normal generalized linear mixed model. Such analyses, however, ignore death as a competing risk, although doing so for clinical conditions with high mortality can have profound effects; a hospital's seemingly good performance for readmission may be an artifact of it having poor performance for mortality. in this paper we propose novel multivariate hospital-level performance measures for readmission and mortality that derive from framing the analysis as one of cluster-correlated semi-competing risks data. We also consider a number of profiling-related goals, including the identification of extreme performers and a bivariate classification of whether the hospital has higher-/lower-than-expected readmission and mortality rates via a Bayesian decision-theoretic approach that characterizes hospitals on the basis of minimizing the posterior expected loss for an appropriate loss function. in some settings, particularly if the number of hospitals is large, the computational burden may be prohibitive. To resolve this, we propose a series of analysis strategies that will be useful in practice. Throughout, the methods are illustrated with data from CMS on N = 17,685 patients diagnosed with pancreatic cancer between 2000-2012 at one of J = 264 hospitals in California.

Analysis of the Application Effect of Multidisciplinary Team Cooperation Model in Chronic Heart Failure under WeChat Platform

Methods

From April 2020 to May 2021, 56 patients with CHF who were discharged from the cardiology department of our hospital after treatment were randomly divided into two groups: experimental group (n = 28) and control group (n = 28). The control group was given conventional nursing measures and health education and discharge instructions, while the experimental group received collaborative multidisciplinary team nursing care based on the WeChat platform on the basis of the control group, all for 3 months. All enrolled patients underwent the Self-Care of Heart Failure Index Version 6.2 (SCHFI v6.2), the Minnesota Living with Heart Failure Questionnaire (MLHFQ), and the 6-minute walking test (6MWT test). The SCHFI v6.2 and MLHFQ scores, 6 MWT test results, and readmission rates within 3 months were observed and compared between the two groups.

Results

There was no significant difference between the SCHFIv6.2 and MLHFQ scores of the two patients at admission and at discharge, and the scores of the experimental group were significantly higher than the scores of the control group at the end of 3 months after discharge. On the other hand, the SCHFIv6.2 and MLHFQ scores of the two groups were significantly higher at discharge compared to admission; the 6-minute walking distance of the experimental group was significantly higher than that of the control group at the end of 3 months. The readmission rate in the experimental group was significantly lower than that in the control group.

Conclusion

The multidisciplinary teamwork model based on the WeChat platform can significantly improve the self-care ability and quality of life of CHF patients and reduce the readmission rate.

LACE Index to Predict the High Risk of 30-Day Readmission in Patients With Acute Myocardial Infarction at a University Affiliated Hospital

Background

The LACE index (length of stay, acuity of admission, comorbidity index, and emergency room visit in the past 6 months) has been used to predict the risk of 30-day readmission after hospital discharge in both medical and surgical patients. This study aimed to utilize the LACE index to predict the risk of 30-day readmission in hospitalized patients with acute myocardial infraction (AMI).

Methods

This was a retrospective study. Data were extracted from the hospital's electronic medical records of patients admitted with AMI between 2015 and 2019. LACE index was built on admission patient demographic data, and clinical and laboratory findings during the index of admission. The multivariate logistic regression was performed to determine the association and the risk prediction ability of the LACE index, and 30-day readmission were analyzed by receiver operator characteristic curves with C-statistic.

Results

Of the 3,607 patients included in the study, 5.7% (205) were readmitted within 30 days of discharge from the hospital. The adjusted odds ratio based on logistic regression of all baseline variables showed a statistically significant association with the LACE score and revealed an increased risk of readmission within 30 days of hospital discharge. However, patients with high LACE scores (≥10) had a significantly higher rate of emergency revisits within 30 days from the index discharge than those with low LACE scores. Despite this, analysis of the receiver operating characteristic curve indicated that the LACE index had favorable discrimination ability C-statistic 0.78 (95%CI; 0.75–0.81). The Hosmer–Lemeshow goodness- of-fit test P value was p = 0.920, indicating that the model was well-calibrated to predict risk of the 30-day readmission.

Conclusion

The LACE index demonstrated the good discrimination power to predict the risk of 30-day readmissions for hospitalized patients with AMI. These results can help clinicians to predict the risk of 30-day readmission at the early stage of hospitalization and pay attention during the care of high-risk patients. Future work is to be focused on additional factors to predict the risk of 30-day readmissions; they should be considered to improve the model performance of the LACE index with other acute conditions by using administrative data.

Ability of the LACE Index to Predict 30-Day Readmissions in Patients with Acute Myocardial Infarction

Aims: This study aimed to utilize the existing LACE index (length of stay, acuity of admission, comorbidity index and emergency room visit in the past six months) to predict the risk of 30-day readmission and to find the associated factors in patients with AMI. Methods: This was a retrospective study and LACE index scores were calculated for patients admitted with AMI between 2015 and 2019. Data were utilized from the hospital’s electronic medical record. Multivariate logistic regression was performed to find the association between covariates and 30-day readmission. The risk prediction ability of the LACE index for 30-day readmission was analyzed by receiver operating characteristic curves with the C statistic. Results: A total of 205 (5.7%) patients were readmitted within 30 days. The odds ratio of older age group (OR = 1.78, 95% CI: 1.54–2.05), admission via emergency ward (OR = 1.45; 95% CI: 1.42–1.54) and LACE score ≥10 (OR = 2.71; 95% CI: 1.03–4.37) were highly associated with 30-day readmissions and statistically significant. The receiver operating characteristic curve C statistic of the LACE index for AMI patients was 0.78 (95% CI: 0.75–0.80) and showed favorable discrimination in the prediction of 30-day readmission. Conclusion: The LACE index showed a good discrimination to predict the risk of 30-day readmission for hospitalized patients with AMI. Further study would be recommended to focus on additional factors that can be used to predict the risk of 30-day readmission; this should be considered to improve the model performance of the LACE index for other acute conditions by using the national-based administrative data.

Young people with prior health service contacts have increased risk of repeated alcohol-related harm hospitalisations

INTRODUCTION

After a first alcohol-related hospitalisation in youth, subsequent hospitalisations may demonstrate an increased risk of further alcohol-related hospitalisations, but there is no existing data on this.

METHODS

A retrospective longitudinal study between July 1992 and June 2017 using linked hospital administrative data identified 23 464 Western Australian young people [9009 (38.4%) females and 14 455 (61.6%) males], aged 12-24 years hospitalised for at least one alcohol-related harm (ARH) episode of care. Cox regression was used to estimate hazard ratios (HR) between risk factors and repeated alcohol-related hospitalisation after the first discharge for ARH.

RESULTS

Of those admitted for an alcohol-related hospitalisation (n = 23 464), 21% (n = 4996) were readmitted for ARH. This high-risk sub-group comprised 46% (n = 16 017) of the total alcohol-related admissions (n = 34 485). After the first discharge for ARH, 16% (804) of people who experienced an alcohol-related readmission were readmitted within 1 month, and 51.8% (2589) were readmitted within 12 months. At increased risk of readmission were Aboriginal people and those with prior health service contacts occurring before their first alcohol-related hospitalisation, including illicit drug hospitalisations, mental health contacts and, in a sub-analysis, emergency department presentations.

DISCUSSION AND CONCLUSIONS

The probability of a repeated ARH hospitalisation was highest in the first month after initial discharge. There is a high-risk sub-group of young people more likely to have a repeat ARH hospitalisation. This represents an opportunity to provide interventions to those most at risk of repeated ARH.

Effectiveness of Hospital-Based Interventions by Occupational Therapy Practitioners on Reducing Readmissions: A Systematic Review With Meta-Analyses

IMPORTANCE

Readmission to the hospital can lead to poorer patient outcomes and increased health care costs. The effect of occupational therapy interventions for adult hospitalized patients on readmission rates has not been previously evaluated.

OBJECTIVE

To systematically examine the published literature to determine the effects of occupational therapy interventions for adult hospitalized patients on readmission rates.

DATA SOURCES

Systematic search of five electronic databases was performed from database inception until May 2020, supplemented by citation and reference list searches. Study Selection and Data Collection: This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered prospectively; methodological quality of the included studies was assessed using the Downs and Black checklist. Meta-analyses were conducted with clinically homogeneous data; the overall body of evidence was graded for quality.

FINDINGS

Meta-analysis of 7 studies with 16,718 participants provided low-quality evidence that 1-mo readmission rates were reduced when adult patients hospitalized for general medical and surgical care received additional occupational therapy interventions compared with standard care. Subgroup analysis of 4 studies provided moderate-quality evidence that interventions focusing on the transition from hospital to the community were effective in reducing 1-mo readmissions to hospitals compared with standard care.

CONCLUSIONS AND RELEVANCE

Occupational therapy interventions can be effective in reducing readmissions among some adult hospitalized patient populations, including those admitted for surgery or management of acute medical conditions, with stronger evidence to support transitional care interventions. What This Article Adds: Occupational therapy interventions can be effective in reducing readmissions among adult hospitalized patients. There is a continued need for occupational therapy practitioners to understand their value and contribution to reducing avoidable readmissions to hospitals.

External validation of EPIC's Risk of Unplanned Readmission model, the LACE+ index and SQLape as predictors of unplanned hospital readmissions: A monocentric, retrospective, diagnostic cohort study in Switzerland

Introduction

Readmissions after an acute care hospitalization are relatively common, costly to the health care system, and are associated with significant burden for patients. As one way to reduce costs and simultaneously improve quality of care, hospital readmissions receive increasing interest from policy makers. It is only relatively recently that strategies were developed with the specific aim of reducing unplanned readmissions using prediction models to identify patients at risk. EPIC’s Risk of Unplanned Readmission model promises superior performance. However, it has only been validated for the US setting. Therefore, the main objective of this study is to externally validate the EPIC’s Risk of Unplanned Readmission model and to compare it to the internationally, widely used LACE+ index, and the SQLAPE® tool, a Swiss national quality of care indicator.

Methods

A monocentric, retrospective, diagnostic cohort study was conducted. The study included inpatients, who were discharged between the 1^st of January 2018 and the 31^st of December 2019 from the Lucerne Cantonal Hospital, a tertiary-care provider in Central Switzerland. The study endpoint was an unplanned 30-day readmission. Models were replicated using the original intercept and beta coefficients as reported. Otherwise, score generator provided by the developers were used. For external validation, discrimination of the scores under investigation were assessed by calculating the area under the receiver operating characteristics curves (AUC). Calibration was assessed with the Hosmer-Lemeshow X² goodness-of-fit test This report adheres to the TRIPOD statement for reporting of prediction models.

Results

At least 23,116 records were included. For discrimination, the EPIC´s prediction model, the LACE+ index and the SQLape® had AUCs of 0.692 (95% CI 0.676–0.708), 0.703 (95% CI 0.687–0.719) and 0.705 (95% CI 0.690–0.720). The Hosmer-Lemeshow X² tests had values of p<0.001.

Conclusion

In summary, the EPIC´s model showed less favorable performance than its comparators. It may be assumed with caution that the EPIC´s model complexity has hampered its wide generalizability—model updating is warranted.

The impact of hospital support function centralization on patient outcomes: A before-after study

Objectives

Study design

Methods

Results

Conclusions

•

Integrated health systems including multiple hospitals are increasingly frequent and can lead to economies of scale.

•

We found a decrease in readmissions and average length of stay associated with the centralization of support functions.

•

Additional studies are needed to evaluate the effect of health systems integration on patient outcomes.

Factors associated with early 14-day unplanned hospital readmission: a matched case-control study

Background/Purpose

Early unplanned hospital readmissions are burdensome health care events and indicate low care quality. Identifying at-risk patients enables timely intervention. This study identified predictors for 14-day unplanned readmission.

Methods

We conducted a retrospective, matched, case–control study between September 1, 2018, and August 31, 2019, in an 1193-bed university hospital. Adult patients aged ≥ 20 years and readmitted for the same or related diagnosis within 14 days of discharge after initial admission (index admission) were included as cases. Cases were 1:1 matched for the disease-related group at index admission, age, and discharge date to controls. Variables were extracted from the hospital’s electronic health records.

Results

In total, 300 cases and 300 controls were analyzed. Six factors were independently associated with unplanned readmission within 14 days: previous admissions within 6 months (OR = 3.09; 95 % CI = 1.79–5.34, p < 0.001), number of diagnoses in the past year (OR = 1.07; 95 % CI = 1.01–1.13, p = 0.019), Malnutrition Universal Screening Tool score (OR = 1.46; 95 % CI = 1.04–2.05, p = 0.03), systolic blood pressure (OR = 0.98; 95 % CI = 0.97–0.99, p = 0.01) and ear temperature within 24 h before discharge (OR = 2.49; 95 % CI = 1.34–4.64, p = 0.004), and discharge with a nasogastric tube (OR = 0.13; 95 % CI = 0.03–0.60, p = 0.009).

Conclusions

Factors presented at admission (frequent prior hospitalizations, multimorbidity, and malnutrition) along with factors presented at discharge (clinical instability and the absence of a nasogastric tube) were associated with increased risk of early 14-day unplanned readmission.

Does geriatric follow-up visits reduce hospital readmission among older patients discharged to temporary care at a skilled nursing facility: a before-and-after cohort study

INTRODUCTION

Hospital readmission is a burden to patients, relatives and society. Older patients with frailty are at highest risk of readmission and its negative outcomes.

OBJECTIVE

We aimed at examining whether follow-up visits by an outgoing multidisciplinary geriatric team (OGT) reduces unplanned hospital readmission in patients discharged to a skilled nursing facility (SNF).

DESIGN

A retrospective single-centre before-and-after cohort study.

SETTING AND PARTICIPANTS

Study population included all hospitalised patients discharged from a Danish geriatric department to an SNF during 1 January 2016-25 February 2020. To address potential changes in discharge and readmission patterns during the study period, patients discharged from the same geriatric department to own home were also assessed.

INTERVENTION

OGT visits at SNF within 7 days following discharge. Patients discharged to SNF before 12 March 2018 did not receive OGT (-OGT). Patients discharged to SNF on or after 12 March 2018 received the intervention (+OGT).

MAIN OUTCOME MEASURES

Unplanned hospital readmission between 4 hours and 30 days following initial discharge.

RESULTS

Totally 847 patients were included (440 -OGT; 407 +OGT). No differences were seen between the two groups regarding age, sex, activities of daily living (ADLs), Charlson Comorbidity Index (CCI) or 30-day mortality. The cumulative incidence of readmission was 39.8% (95% CI 35.2% to 44.8%, n=162) in -OGT and 30.2% (95% CI 25.8% to 35.2%, n=113) in +OGT. The unadjusted risk (HR (95% CI)) of readmission was 0.68 (0.54 to 0.87, p=0.002) in +OGT compared with -OGT, and remained significantly lower (0.72 (0.57 to 0.93, p=0.011)) adjusting for age, length of stay, sex, ADL and CCI. For patients discharged to own home the risk of readmission remained unchanged during the study period.

CONCLUSION

Follow-up visits by OGT to patients discharged to temporary care at an SNF significantly reduced 30-day readmission in older patients.

Exploring experiences and perceptions of Aboriginal and Torres Strait Islander peoples readmitted to hospital with chronic disease in New South Wales, Australia: a qualitative study

Objective This study explored the experiences and perceptions of unplanned hospital readmissions from the perspective of Aboriginal and Torres Strait Islander peoples with chronic disease. Method We conducted semi-structured interviews with Aboriginal and Torres Strait Islander patients readmitted to hospital with chronic disease. Interviews covered perceptions of avoidable readmissions, experiences of health care, medications and carer support. Inductive thematic analysis was used to code and analyse the data. Results Fifteen patients with multiple chronic diseases were interviewed. Several participants believed their readmission was unavoidable due to their poor health, while others considered their readmission was avoidable due to perceived health professional and system failures. Enablers to chronic disease management included the importance of continuity of care and strong family networks, although a few participants struggled with isolation. Four themes emerged as barriers: poor communication from health professionals; low levels of health literacy and adherence to chronic disease management; poor access to community services; and health risk behaviours. Conclusions The participants in our study identified complex and interacting patient-, environmental-, encounter- and organisational-level factors as contributing to chronic disease management and unplanned readmissions. Our findings suggest systemic failures remain in access to basic services and access to culturally appropriate care. Family support and continuity of care were valued by participants. What is known about the topic? Aboriginal and Torres Strait Islander peoples with chronic diseases are more likely to be readmitted to hospital compared with non-Aboriginal people. Unplanned readmissions are associated with high health system costs, as well as poorer quality of life and psychological distress for the patient. What does this paper add? This paper describes the experiences and perceptions of unplanned readmissions by Aboriginal and Torres Strait Islander peoples with chronic disease. Our findings suggest systemic failures exist in access to basic services for a safe and secure living environment, and access to culturally appropriate care that is delivered in a manner which promotes health literacy and self-management capacity. What are the implications for practitioners? Practitioners and policy makers should consider involving family members in discharge planning and other medical care, and funding for Aboriginal and Torres Strait Islander health and community services to enhance transport, care coordination, culturally appropriate disability and housing services, and health promotion.

Trends in 30-day readmissions following hospitalisation for heart failure by sex, socioeconomic status and ethnicity

BACKGROUND

Reducing the high patient and economic burden of early readmissions after hospitalisation for heart failure (HF) has become a health policy priority of recent years.

METHODS

An observational study linking Hospital Episode Statistics to socioeconomic and death data in England (2002-2018). All first hospitalisations with a primary discharge code for HF were identified. Quasi-poisson models were used to investigate trends in 30-day readmissions by age, sex, socioeconomic status and ethnicity.

FINDINGS

There were 698,983 HF admissions, median age 81 years [IQR 14].In-hospital deaths reduced by 0.7% per annum (pa), whilst additional deaths at 30-days remained stable at 5%. Age adjusted 30-day readmissions (21% overall), increased by 1.4% pa (95% CI 1.3-1.5). Readmissions for HF (6%) and 'other cardiovascular disease (CVD)' (3%) remained stable, but readmissions for non-CVD causes (12%) increased at a rate of 2.6% (2.4-2.7) pa. Proportions were similar by sex but trends diverged by ethnicity. Black groups experienced an increase in readmissions for HF (1.8% pa, interaction-p 0.03) and South Asian groups had more rapidly increasing readmission rates for non-CVD causes (interaction-p 0.04). Non-CVD readmissions were also more prominent in the least (15%; 15-15) compared to the most affluent group (12%; 12-12). Strongest predictors for HF readmission were Black ethnicity and chronic kidney disease, whilst cardiac procedures were protective. For non-CVD readmissions, strongest predictors were non-CVD comorbidities, whilst cardiologist care was protective.

INTERPRETATION

In HF, despite readmission reduction policies, 30-day readmissions have increased, impacting the least affluent and ethnic minority groups the most.

FUNDING

NIHR.

Care Strategies for Reducing Hospital Readmissions Using Stochastic Programming

A hospital readmission occurs when a patient has an unplanned admission to a hospital within a specific time period of discharge from an earlier or initial hospital stay. Preventable readmissions have turned into a critical challenge for the healthcare system globally, and hospitals seek care strategies that reduce the readmission burden. Some countries have developed hospital readmission reduction policies, and in some cases, these policies impose financial penalties for hospitals with high readmission rates. Decision models are needed to help hospitals identify care strategies that avoid financial penalties, yet maintain balance among quality of care, the cost of care, and the hospital’s readmission reduction goals. We develop a multi-condition care strategy model to help hospitals prioritize treatment plans and allocate resources. The stochastic programming model has probabilistic constraints to control the expected readmission probability for a set of patients. The model determines which care strategies will be the most cost-effective and the extent to which resources should be allocated to those initiatives to reach the desired readmission reduction targets and maintain high quality of care. A sensitivity analysis was conducted to explore the value of the model for low- and high-performing hospitals and multiple health conditions. Model outputs are valuable to hospitals as they examine the expected cost of hitting its target and the expected improvement to its readmission rates.

Early hospital readmission increases short and long - term mortality in patients with interstitial lung disease

Objective:

To investigate the prognostic impact of early readmission (30 days) on hospitalized patients with Interstitial Lung Disease (ILD).

Methods:

Observational study analysing a cohort of patients hospitalized in a respiratory ward at a University Hospital. Demographic, clinical data and survival status were collected from patients’ records. Early readmission was defined as hospitalization within 30 days after patient’s discharge. The primary outcome was 90-day and 1-year all-cause mortality.

Results:

Between 2013 to 2016, a total of 2.238 patients were admitted to the respiratory ward and 98 (%) had a diagnosis of ILD. Among them, 74 patients were discharged (25% in-hospital mortality). Early readmission was observed in 15 cases (20.2%). Early readmitted patients were more frequently current smokers (20% vs. 2%, p=0.02). After a multivariate analysis, early readmission was found to be independently associated with 90-day and 1 year mortality (Odds Ratio (OR) 17.6, 95% Confidence Interval (CI) 4.5-69-2, p=0.001 and OR 4.5; 95CI 1.3-15.2, p=0.01, respectively).

Conclusion:

In patients with ILD, early readmission after hospitalization increases both short-term and long term mortality. Thus, preventing early readmission after discharge from hospital admission may have an impact in the clinical course of ILD patients. Further studies are required to identify factors contributing to early readmission.

Potential of community-based risk estimates for improving hospital performance measures and discharge planning

Background

Risk-adjusted rates of hospital readmission are a common indicator of hospital performance. There are concerns that current risk-adjustment methods do not account for the many factors outside the hospital setting that can affect readmission rates. Not accounting for these external factors could result in hospitals being unfairly penalized when they discharge patients to communities that are less able to support care transitions and disease management. While incorporating adjustments for the myriad of social and economic factors outside of the hospital setting could improve the accuracy of readmission rates as a performance measure, doing so has limited feasibility due to the number of potential variables and the paucity of data to measure them. This paper assesses a practical approach to addressing this problem: using mixed-effect regression models to estimate case-mix adjusted risk of readmission by community of patients’ residence (community risk of readmission) as a complementary performance indicator to hospital readmission rates.

Methods

Using hospital discharge data and mixed-effect regression models with a random intercept for community, we assess if case-mix adjusted community risk of readmission can be useful as a quality indicator for community-based care. Our outcome of interest was an unplanned repeat hospitalisation. Our primary exposure was community of residence.

Results

Community of residence is associated with case-mix adjusted risk of unplanned repeat hospitalisation. Community risk of readmission can be estimated and mapped as indicators of the ability of communities to support both care transitions and long-term disease management.

Conclusion

Contextualising readmission rates through a community lens has the potential to help hospitals and policymakers improve discharge planning, reduce penalties to hospitals, and most importantly, provide higher quality care to the people that they serve.

An integrated knowledge translation approach to address avoidable rehospitalisations and unplanned admissions for older people in South Australia: implementation and evaluation program plan

Background

Repeated admission to hospital can be stressful for older people and their families and puts additional pressure on the health care system. While there is some evidence about strategies to better integrate care, improve older patients’ experiences at transitions of care, and reduce preventable hospital readmissions, implementing these strategies at scale is challenging. This program of research comprises multiple, complementary research activities with an overall goal of improving the care for older people after discharge from hospital. The program leverages existing large datasets and an established collaborative network of clinicians, consumers, academics, and aged care providers.

Methods

The program of research will take place in South Australia focusing on people aged 65 and over. Three inter-linked research activities will be the following: (1) analyse existing registry data to profile individuals at high risk of emergency department encounters and hospital admissions; (2) evaluate the cost-effectiveness of existing ‘out-of-hospital’ programs provided within the state; and (3) implement a state-wide quality improvement collaborative to tackle key interventions likely to improve older people’s care at points of transitions. The research is underpinned by an integrated approach to knowledge translation, actively engaging a broad range of stakeholders to optimise the relevance and sustainability of the changes that are introduced.

Discussion

This project highlights the uniqueness and potential value of bringing together key stakeholders and using a multi-faceted approach (risk profiling; evaluation framework; implementation and evaluation) for improving health services. The program aims to develop a practical and scalable solution to a challenging health service problem for frail older people and service providers.

Uncaptured rates of postpartum venous thromboembolism: a US national analysis

OBJECTIVE

To quantify the proportion of postpartum venous thromboembolism (VTE) readmissions, including those that occur at different hospitals from index admission, and describe risk factors for this outcome.

DESIGN

Retrospective observational study.

SETTING

US hospitals included in the Nationwide Readmissions Database.

SAMPLE

A total of 3 719 238 patients >14 years of age with a delivery-associated hospitalisation in 2014.

METHODS

Univariate analysis was performed to identify patient and hospital factors associated with readmissions. Significant factors were included in multivariate logistic regression to identify independent risk factors. Results were weighted for national estimates.

MAIN OUTCOME MEASURES

Readmission with VTE to both index and different hospitals at 30, 60 and 90 days.

RESULTS

The VTE cumulative readmission rate was 0.053% (n = 1477), 0.063% (n = 1765) and 0.069% (n = 1938) at 30, 60 and 90 days, respectively. Patients were readmitted to different hospitals 31% of the time within 90 days. Risk factors for different hospital VTE readmission were unique and included younger age and initial admission to a small/medium-sized hospital. Initial admission to a for-profit hospital increased the likelihood of readmission to a different hospital.

CONCLUSIONS

Nearly one in three postpartum VTEs are missed by the current quality metrics, with significant implications for outcomes and quality. For-profit hospitals have a significant portion of their VTE readmissions hidden, falsely lowering their readmission rates relative to public hospitals.

TWEETABLE ABSTRACT

US analysis shows 1 in 3 readmissions for postpartum venous thromboembolism currently missed.

Effectiveness of using a simulation combined with online learning approach to develop discharge teaching skills

BACKGROUND

Despite evidence of the impact of discharge teaching on patient outcomes, nursing students are poorly prepared in the pedagogical skills necessary for their role as patient and family educators in clinical practice. This study evaluated the effectiveness of simulation combined with online learning to improve nursing students' discharge teaching skills.

METHODS

The module included simulations before and after an online module on patient/family teaching for hospital discharge. Evaluation measures were student and independent rater evaluations using the Quality of Discharge Teaching Scale- Evaluation form (QDTS-E).

RESULTS

Students (n = 153) improved their performance on both content and delivery subscales of the QDTS-E by 20% (student self-evaluations) and 18% (independent raters). However, correlations between student and rater scores were low (r = 0.08-0.22).

CONCLUSION

Use of simulation with online learning in a discharge teaching module can help students build patient education skills to improve post-discharge patient outcomes, contributing to national health priorities to reduce hospital readmissions. With further refinement and testing, the learning module and QDTS-E evaluation form may also be useful for evaluation and continuing education of clinical nursing staff.

Thirty-day readmission rate of COVID-19 patients discharged from a tertiary care university hospital in Turkey: an observational, single-center study

Background

The 30-day readmission rate is an important indicator of patient safety and hospital’s quality performance. In this study, we aimed to find out the 30-day readmission rate of mild and moderate severity COVID-19 patients discharged from a tertiary care university hospital and to demonstrate the possible factors associated with readmission.

Methods

This is an observational, single-center study. Epidemiological and clinical data of patients who were hospitalized with a diagnosis of COVID-19 were retrieved from a research database where patient information was recorded prospectively. Readmission data was sought from the hospital information management system and National Health Record System to detect if the patients were readmitted to any hospital within 30 days of discharge. Adult patients (≥18 years-old) hospitalized in COVID-19 wards with a diagnosis of mild or moderate COVID-19 between March 20, 2020 (when the first case was admitted to our hospital), and April 26, 2020 were included.

Results

From March 26 to May 1, there were 154 mild or moderate severity (non-critical) COVID-19 patients discharged from COVID-19 wards, of which 11 (7.1%) were readmitted The median time of readmission was 8.1 days (IQR=5.2). Two patients (18.1%) were categorized to have mild disease and the remaining 9 (81.9%) as moderate disease. Two patients who were over 65 years of age and had metastatic cancers and hypertension developed sepsis and died in the hospital during the readmission episode. Malignancy (18.7% vs 2.1%, P = 0.04) and hypertension (45.5% vs 14%, P = 0.02) were more common in those who were readmitted.

Conclusions

This is one of the first studies to report on 30-day readmission rate of COVID-19 in the literature. More comprehensive studies are needed to reveal the causes and predictors of COVID-19 readmissions.

Effectiveness of nurse-led peri-discharge interventions for reducing 30-day hospital readmissions: Network meta-analysis

BACKGROUND

Existing systematic reviews have compared the effectiveness of nurse-led peri-discharge interventions comprising different components with usual care on reducing all-cause 30-day hospital readmissions. However, conflicting results were reported.

OBJECTIVE

We conducted a network meta-analysis to evaluate the comparative effectiveness of different nurse-led peri-discharge interventions, compared with usual care, for reducing all-cause 30-day hospital readmissions.

DESIGN

Network meta-analysis.

METHODS

A total of five international databases were searched for systematic reviews of randomized controlled trials. Additional searches for most updated randomized controlled trials published between 2014 to 2019 were conducted. Data from included randomized controlled trials were extracted for random-effect pairwise meta-analyses. Pooled risk ratios with 95% confidence interval were used to quantify impact of nurse-led peri-discharge interventions on all-cause 30-day hospital readmissions. Network meta-analysis was used to evaluate the comparative effectiveness of different interventions.

RESULTS

From two systematic reviews and additional randomized controlled trial searches, 12 eligible randomized controlled trials (n=150,840) assessing 15 different nurse-led peri-discharge interventions were included. For reducing all-cause 30-day hospital readmissions, pairwise meta-analysis showed that there was no significant difference between nurse-led peri-discharge interventions and usual care (pooled risk ratios = 0.86, 95% confidence interval: 0.71-1.04, moderate quality of evidence). Network meta-analysis indicated no significant difference across different interventions despite variation in complexity.

CONCLUSIONS

Our results indicated that nurse-led peri-discharge interventions were not significantly different from usual care for reducing all-cause 30-day hospital readmissions. Simpler nurse-led peri-discharge interventions are on par with more complex interventions in terms of effectiveness. Benefits of nurse-led peri-discharge interventions may vary across health system context. Therefore, careful consideration is required prior to implementation.

REGISTRATION DETAILS

The protocol for this study has been registered in PROSPERO (Registration No. CRD42020186938). Tweetable abstract: This study suggested that nurse-led peri-discharge interventions do not differ from usual care for reducing all-cause 30-day hospital readmissions.

Patient factors associated with titration of medical therapy in patients with heart failure with reduced ejection fraction: data from the QUALIFY international registry

AIMS

Failure to prescribe key medicines at evidence-based doses is associated with increased mortality and hospitalization for patients with Heart Failure with reduced Ejection Fraction (HFrEF). We assessed titration patterns of guideline-recommended HFrEF medicines internationally and explored associations with patient characteristics in the global, prospective, observational, longitudinal registry.

METHODS AND RESULTS

Data were collected from September 2013 through December 2014, with 7095 patients from 36 countries [>18 years, previous HF hospitalization within 1-15 months, left ventricular ejection fraction (LVEF) ≤ 40%] enrolled, with dosage data at baseline and up to 18 months from 4368 patients. In 4368 patients (mean age 63 ± 17 years, 75% male) ≥ 100% target doses at baseline: 30.6% (ACEIs), 2.9% (ARBs), 13.9% (BBs), 53.8% (MRAs), 26.2% (ivabradine). At final follow-up, ≥100% target doses achieved in more patients for ACEI (34.8%), BB (18.0%), and ivabradine (30.5%) but unchanged for ARBs (3.2%) and MRAs (53.7%). Adjusting for baseline dosage, uptitration during follow-up was more likely with younger age, higher systolic blood pressure, and in absence of chronic kidney disease or diabetes for ACEIs/ARBs; younger age, higher body mass index, higher heart rate, lower LVEF, and absence of coronary artery disease for BBs. For ivabradine, uptitration was more likely with higher resting heart rate.

CONCLUSIONS

The international QUALIFY Registry suggests that few patients with HFrEF achieve target doses of disease-modifying medication, especially older patients and those with co-morbidity. Quality improvement initiatives are urgently required.

Diverse perspectives on hospitalisation events among people with dementia: protocol for a multisite qualitative study

INTRODUCTION

People living with dementia (PLWD) are more likely to experience hospitalisation events (hospitalisation, rehospitalisation) than those without dementia. Many hospitalisation events, particularly rehospitalisation within 30 days of discharge, are thought to be avoidable. Yet our understanding of dementia-specific risk and protective factors surrounding avoidable hospitalisation is limited to specific intersetting transitions and predominantly clinician perspectives. Broader insights are needed to design accessible and effective solutions for reducing avoidable hospitalisations. We have designed the Stakeholders Understanding of Prevention Protection and Opportunities to Reduce HospiTalizations (SUPPORT) Study to address these gaps. The objectives of the SUPPORT Study are to elicit and examine family caregiver, community and hospital providers' perspectives on avoidable hospitalisation events among PLWD, and to identify opportunities for effective prevention.

METHODS AND ANALYSIS

We will conduct a multisite, descriptive qualitative study to interview around 100 family caregivers, community and hospital providers. We will identify and sample from regions and communities with higher socio-contextual disadvantage and hospital utilisation, and will aim to recruit individuals representing diverse racial/ethnic backgrounds. Interviews will follow a descriptive qualitative design in conjunction with constant comparison techniques to sample divergent situations and events. We will employ a range of analytical approaches to address specific research questions including thematic (inductive and deductive), comparative and dimensional analysis. Interviews will be conducted individually or in focus groups and follow a semistructured interview guide.

ETHICS AND DISSEMINATION

The study is approved by the University of Wisconsin-Madison Institutional Review Board. Informed consent procedures will incorporate steps to evaluate capacity to provide informed consent in the event that participants express concerns with thinking or memory or demonstrate challenges recalling study details during the consent process to ensure capacity to consent to participation. A series of publicly available reports, seminars and symposia will be undertaken in collaboration with collaborating organisation partners.

Derivation and validation of a prediction model for neonate unplanned rehospitalization in a tertiary center in China

BACKGROUND

To construct and externally validate a prediction model for neonate unplanned rehospitalization within 31 days of discharge.

METHODS

A retrospective study was performed in the Department of Neonatology of the Children's Hospital of Fudan University. A binominal regression method was applied to construct and validate the prediction model. Analysis was performed on a total of 11,116 neonates with an index admission between 11/1/2016 and 12/31/2018. Neonates admitted from 11/1/2016 to 1/31/2018 were used for the selection of prognostic variables and construction of the model. Model validation was then performed with neonates admitted from 2/1/2018 to 12/31/2018.

RESULTS

The rehospitalization rate for neonates was 3.27% (373/11,116). A total of 512 neonates were enrolled for the construction of the prediction model. Gestational age (GA), NICU length of stay (LOS), nonmedical order discharge and younger maternal age were strongly correlated with rehospitalization. By incorporating these 4 strong risk factors, we constructed a model to predict neonate unplanned rehospitalization within 31 days of discharge. The formula was turned into a nomogram for use in clinical practice. The nomogram has a total score of 180, with a predicted risk from 0 to 100%. Neonates are at high risk for rehospitalization if they have a total score greater than 39 points, according to the cutoff point established by the Youden index. The model was shown to have good discriminatory ability, with area under the receiver operating characteristic curves of 0.68 and 0.65 in the model construction and validation datasets, respectively. A total of 39 points is the cutoff for follow-up.

CONCLUSIONS

The model is able to predict neonate unplanned rehospitalization well. A total score greater than 39 indicates that follow-up is necessary.

Patient-Related Risk Factors for Unplanned 30-Day Hospital Readmission Following Primary and Revision Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

Total knee arthroplasty (TKA) is a highly effective procedure for advanced osteoarthritis of the knee. Thirty-day hospital readmission is an adverse outcome related to complications, which can be mitigated by identifying associated risk factors. We aimed to identify patient-related characteristics associated with unplanned 30-day readmission following TKA, and to determine the effect size of the association between these risk factors and unplanned 30-day readmission. We searched MEDLINE and EMBASE from inception to 8 September 2020 for English language articles. Reference lists of included articles were searched for additional literature. Patients of interest were TKA recipients (primary and revision) compared for 30-day readmission to any institution, due to any cause, based on patient risk factors; case series were excluded. Two reviewers independently extracted data and carried out critical appraisal. In-hospital complications during the index admission were the strongest risk factors for 30-day readmission in both primary and revision TKA patients, suggesting discharge planning to include closer post-discharge monitoring to prevent avoidable readmission may be warranted. Further research could determine whether closer monitoring post-discharge would prevent unplanned but avoidable readmissions. Increased comorbidity burden correlated with increased risk, as did specific comorbidities. Body mass index was not strongly correlated with readmission risk. Demographic risk factors included low socioeconomic status, but the impact of age on readmission risk was less clear. These risk factors can also be included in predictive models for 30-day readmission in TKA patients to identify high-risk patients as part of risk reduction programs.

Reallocating Cancer Surgery Payments for Alternate Level of Care in Ontario: What Are the Options?

This article examines how alternate-level-of-care (ALC) days are funded through the cancer surgery funding model in Ontario and evaluates policy options to better address ALC days. The contribution of ALC days to hospital funding and the impact of removing or reallocating this funding from cancer surgery is measured. Though costs associated with ALC days in cancer surgery are low, this article highlights the need for policy options that would realign funding across the healthcare system in Ontario to better meet the needs of patients waiting for ALC, reduce pressure on inpatient bed capacity and improve value for money.

Cost-effectiveness analysis of Coblation versus mechanical shaver debridement in patients following knee chondroplasty

Background

To compare costs and outcomes following knee chondroplasty with Coblation versus mechanical shaver debridement (MSD) in patients with grade III articular cartilage lesions of the knee.

Methods

A decision-analytic model was developed to compare costs and outcomes of the two methods from a US payer perspective. We used published clinical data from a single-center randomized clinical trial (RCT) designed to compare outcomes between Coblation and MSD in patients with grade III articular cartilage lesions of the medial femoral condyle. Following primary knee chondroplasty, patients experienced either treatment success (no additional surgery required) or required a revision over the 4 year follow-up period. Costs associated with the initial chondroplasty, physical therapy sessions through the 6 week postoperative period, and revision rates at 4 years post-surgery were estimated using 2018 US Medicare Physician Fee Schedule. Sensitivity analyses including a 10 year time horizon and threshold analyses were performed to test the robustness of the model.

Results

The estimated total cost per patient was $4614 and $7886 for Coblation and MSD, respectively, resulting in cost-savings of $3272 in favor of Coblation, making it a dominant strategy because of lower costs and improved clinical outcomes. Threshold analysis showed that Coblation remained dominant even when revision rates were assumed to increase from the base case rate of 14–66%. Sensitivity analyses showed that cost-saving results were insensitive to variations in revision rates, number of physical therapy sessions and the time horizon used.

Conclusion

Coblation chondroplasty is a cost-saving procedure compared with MSD in the treatment of patients with grade III articular cartilage lesions of the knee.

In-hospital interventions for reducing readmissions to acute care for adults aged 65 and over: An umbrella review

PURPOSE

The aim of this umbrella review was to synthesize existing systematic review evidence on the effectiveness of in-hospital interventions to prevent or reduce avoidable hospital readmissions in older people (≥65 years old).

DATA SOURCES

A comprehensive database search was conducted in May 2019 through MEDLINE, EMBASE, CINAHL, the JBI Database of Systematic Reviews, DARE and Epistemonikos.

STUDY SELECTION

Systematic reviews and other research syntheses, including meta-analyses, exploring the effectiveness of hospital-based interventions to reduce readmissions for people aged 65 and older, irrespective of gender or clinical condition, were included for review. If a review did not exclusively focus on this age group, but data for this group could be extracted, then it was considered for inclusion. Only reviews in English were included.

DATA EXTRACTION

Data extracted for each review included the review objective, participant details, setting and context, type of studies, intervention type, comparator and findings.

RESULTS OF DATA SYNTHESIS

Twenty-nine reviews were included for analysis. Within these reviews, 11 intervention types were examined: in-hospital medication review, discharge planning, comprehensive geriatric assessment, early recovery after surgery, transitional care, interdisciplinary team care, in-hospital nutrition therapy, acute care geriatric units, in-hospital exercise, postfall interventions for people with dementia and emergency department-based palliative care. Except for discharge planning and transitional care, none of the interventions significantly reduced readmissions among older adults.

CONCLUSION

There is limited evidence to support the effectiveness of existing hospital-based interventions to reduce readmissions for people aged 65 and older.

Patient stratification for risk of readmission due to heart failure by using nationwide administrative data

BACKGROUND

Identifying patients with heart failure (HF) who are most at risk of readmission permits targeting adapted interventions. The use of administrative data enables regulators to support the implementation of such interventions.

METHODS AND RESULTS

In a French nationwide cohort of patients aged 65 years or older, surviving an index hospitalization for HF in 2015 (N = 70,657), we studied HF readmission predictors available in administrative data, distinguishing HF severity from overall morbidity and taking into account the competing mortality risk, over a 1-year follow-up period. We also computed cumulative incidences and daily rates of HF readmission for patient groups defined according to HF severity and overall morbidity. Of the patients, 31.8% (n = 22,475) were readmitted at least once for HF, and 17.6% (n = 12,416) died without any readmission for HF. HF severity and overall morbidity were the strongest readmission predictors were the strongest readmission predictors (subdistribution hazard ratios 2.66 [95% CI: 2.52-2.81] and 1.37 [1.30-1.45], respectively, when comparing extreme categories). Overall morbidity and age were more strongly associated with the rate of death without HF readmission (cause-specific hazard ratios). The difference in observed HF readmission between patient risk groups was approximately 40% (21.9%, n = 2144/9,786 vs 60.4%, n = 618/1023).

CONCLUSIONS

Segmentation of HF patients into readmission risk groups is possible by using administrative data, and it enables the targeting of preventive interventions.

Predicting non-elective hospital readmission or death using a composite assessment of cognitive and physical frailty in elderly inpatients with cardiovascular disease

Background

We aimed to assess the utility of the combination of the mini-mental state examination (MMSE) + clock drawing test (CDT) and the Fried phenotype for predicting non-elective hospital readmission or death within 6 months in elderly inpatients with cardiovascular disease (CVD).

Methods

A single-center prospective cohort was conducted from September 2018 to February 2019. Inpatients ≥65 years old were recruited. Predictive validity was tested using a Cox proportional hazards regression model analysis, and the discriminative ability was evaluated by the receiver operating characteristic (ROC) curve.

Results

A total of 542 patients were included. Overall, 12% (64/542) screened positive for cognitive impairment, 16% (86/542) were physically frail and 8% (44/542) had cognitive impairment combined with physical frailty, showing an older age (P < 0.001) and a lower education level (P < 0.001) than physically frail patients. A total of 113 patients (20.9%) died or were readmitted at 6 months. Frail participants with a normal (hazard ratio [HR]: 1.73, 95% confidence interval [CI]: 1.06–2.82, P = 0.028) or impaired cognition (HR: 2.50, 95% CI: 1.27–4.91, P = 0.008) had a higher risk of non-elective hospital readmission or death than robust patients after adjusting for the age, sex, education level, marital status, the presence of diabetes mellitus, heart failure, and history of stroke. The area under the ROC curve (AUC) showed that the discriminative ability in relation to 6 months readmission and death for the MMSE + CDT + Fried phenotype was 0.65 (95% CI: 0.60–0.71), and the AUC for men was 0.71 (95% CI: 0.63–0.78), while that for women was 0.60 (95% CI: 0.51–0.69).

Conclusions

Accounting for cognitive impairment in the frailty phenotype may allow for the better prediction of non-elective hospital readmission or death in elderly inpatients with CVD in the short term.

Trial registration

ChiCTR1800017204; date of registration: 07/18/2018.

Understanding the large heterogeneity in hospital readmissions and mortality for acute myocardial infarction

This study aims to investigate the variation in two acute myocardial infarction (AMI) outcomes across public hospitals in Portugal. In-hospital mortality and 30-day unplanned readmissions were studied using two distinct AMI cohorts of adults discharged from all acute care public hospital centers in Portugal from 2012-2015. Hierarchical generalized linear models were used to assess the association between patient and hospital characteristics and hospital variability in the two outcomes. Our findings indicate that hospitals are not performing homogeneously-the risk of adverse events tends to be consistently larger in some hospitals and consistently lower in other hospitals. While patient characteristics accounted for a larger share of the explained between-hospital variance, hospital characteristics explain an additional 8% and 10% of hospital heterogeneity in the mortality and the readmission cohorts respectively. Admissions to hospitals with low AMI caseloads or located in Alentejo/Algarve and Lisbon had a higher risk of mortality. Discharges from larger-sized hospitals were associated with increased risk of readmissions. Future health policies should incorporate these findings in order to incentivize more consistent health care outcomes across hospitals. Further investigation addressing geographical disparities, hospital caseload and practices is needed to direct actions of improvement to specific hospitals.

Risk factors for all-cause hospital readmission following exacerbation of COPD: a systematic review and meta-analysis

BACKGROUND

Readmission rates following hospitalisation for COPD exacerbations are unacceptably high, and the contributing factors are poorly understood. Our objective was to summarise and evaluate the factors associated with 30- and 90-day all-cause readmission following hospitalisation for an exacerbation of COPD.

METHODS

We systematically searched electronic databases from inception to 5 November 2019. Data were extracted by two independent authors in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Study quality was assessed using a modified version of the Newcastle-Ottawa Scale. We synthesised a narrative from eligible studies and conducted a meta-analysis where this was possible using a random-effects model.

RESULTS

In total, 3533 abstracts were screened and 208 full-text manuscripts were reviewed. A total of 32 papers met the inclusion criteria, and 14 studies were included in the meta-analysis. The readmission rate ranged from 8.8-26.0% at 30 days and from 17.5-39.0% at 90 days. Our narrative synthesis showed that comorbidities, previous exacerbations and hospitalisations, and increased length of initial hospital stay were the major risk factors for readmission at 30 and 90 days. Pooled adjusted odds ratios (95% confidence intervals) revealed that heart failure (1.29 (1.22-1.37)), renal failure (1.26 (1.19-1.33)), depression (1.19 (1.05-1.34)) and alcohol use (1.11 (1.07-1.16)) were all associated with an increased risk of 30-day all-cause readmission, whereas being female was a protective factor (0.91 (0.88-0.94)).

CONCLUSIONS

Comorbidities, previous exacerbations and hospitalisation, and increased length of stay were significant risk factors for 30- and 90-day all-cause readmission after an index hospitalisation with an exacerbation of COPD.

Thirty-Day Hospital Readmission After Acute Myocardial Infarction in China

Background Readmission after acute myocardial infarction in low- and middle-income countries like China is not well characterized. Methods and Results We approached consecutive patients with acute myocardial infarction hospitalized within 24 hours of symptom onset and discharged alive from 53 geographically diverse hospitals in China. We described rates of unplanned 30-day readmission, their timing and admitting diagnoses, and fit Cox proportional hazards models to identify factors associated with readmission. Among 3387 patients, median (interquartile range) age was 61 (52-69) years, and 76.9% were men. The index median length of stay was 11 (8-14) days. Unplanned 30-day readmission occurred in 6.3% of the cohort; most readmissions (77.7%) were for cardiovascular diagnoses. Nearly half (41.9% of all-cause readmissions; 44.3% of cardiovascular readmissions) occurred within 5 days of discharge. Mini-Global Registry of Acute Coronary Events scores at admission (hazard ratio [HR], 1.15 for every 10-point increase; 95% CI, 1.05-1.25), longer length of stay (HR, 1.03; 95% CI, 1.00-1.06 for each extra day), and in-hospital recurrent angina (HR, 1.40; 95% CI, 1.04-1.89) were associated with higher unplanned all-cause readmission. Revascularization during the index hospitalization (70.2% of the cohort) was associated with lower risks of all-cause readmission (HR, 0.27; 95% CI, 0.18-0.42). In addition, left ventricular ejection fraction <0.4 (HR, 1.79; 95% CI, 1.05-3.07) and in-hospital complication (HR, 1.20; 95% CI, 1.03-1.39) were associated with higher risk of unplanned cardiovascular readmission, and ST-segment-elevation myocardial infarction (HR, 0.60; 95% CI, 0.36-0.98) was associated with lower risk of unplanned cardiovascular readmission. Sex, family income, depression, stress level, lower social support, disease-specific health status, and medications were not associated with readmission. Conclusions In China, most readmissions are for cardiovascular events, and almost half occur within 5 days of discharge. Clinical factors identify patients at higher and lower unplanned readmissions. Clinical Trial Registration URL: https://www.clinicaltrials.gov . Unique identifier: NCT01624909.

Textbook Outcome: Nationwide Analysis of a Novel Quality Measure in Pancreatic Surgery

BACKGROUND

Textbook outcome (TO) is a multidimensional measure for quality assurance, reflecting the "ideal" surgical outcome.

METHODS

Post-hoc analysis of patients who underwent pancreatoduodenectomy (PD) or distal pancreatectomy (DP) for all indications between 2014 and 2017, queried from the nationwide prospective Dutch Pancreatic Cancer Audit. An international survey was conducted among 24 experts from 10 countries to reach consensus on the requirements for TO in pancreatic surgery. Univariable and multivariable logistic regression was performed to identify TO predictors. Between-hospital variation in TO rates was compared using observed-versus-expected rates.

RESULTS

Based on the survey (92% response rate), TO was defined by the absence of postoperative pancreatic fistula, bile leak, postpancreatectomy hemorrhage (all ISGPS grade B/C), severe complications (Clavien-Dindo ≥III), readmission, and in-hospital mortality. Overall, 3341 patients were included (2633 (79%) PD and 708 (21%) DP) of whom 60.3% achieved TO; 58.3% for PD and 67.4% for DP. On multivariable analysis, ASA class 3 predicted a worse TO rate after PD (ASA 3 OR 0.59 [0.44-0.80]), whereas a dilated pancreatic duct (>3 mm) and pancreatic ductal adenocarcinoma (PDAC) were associated with a better TO rate (OR 2.22 [2.05-3.57] and OR 1.36 [1.14-1.63], respectively). For DP, female sex and the absence of neoadjuvant therapy predicted better TO rates (OR 1.38 [1.01-1.90] and OR 2.53 [1.20-5.31], respectively). When comparing institutions, the observed-versus-expected rate for achieving TO varied from 0.71 to 1.46 per hospital after casemix-adjustment.

CONCLUSIONS

TO is a novel quality measure in pancreatic surgery. TO varies considerably between pancreatic centers, demonstrating the potential benefit of quality assurance programs.