Social and clinical predictors of short- and long-term readmission after a severe exacerbation of copd

[Medico-economic evaluation of the PRADO-BPCO post-exacerbation support program]

INTRODUCTION

The "Programme d'Accompagnement du retour à Domicile" (PRADO) COPD is a home discharge support program dedicated to organizing care pathways following hospitalization for COPD exacerbation. This study aimed at assessing its medico-economic impact.

METHODS

This was a retrospective database study of patients included in the PRADO BPCO between 2017 and 2019. Data were extracted from the National Health Data System. A control group was built using propensity score matching. Morbi-mortality and costs (national health insurance perspective) were measured during the year following hospitalization.

RESULTS

While the proportion of patients with a care pathway complying with recommendations from the National Health Authority was higher in the PRADO group, there was no significant effect on mortality and 12-month rehospitalization. In the PRADO group, the rehospitalization rate was lower when the care pathway was optimal. Healthcare costs per patient were 670 € higher in the PRADO group.

CONCLUSIONS

The PRADO COPD improves quality of care but without decreasing rehospitalizations and mortality, although rehospitalizations did decrease among PRADO group patients benefiting from an optimal care pathway.

Nursing diagnoses and hospital readmission of patients with respiratory diseases: Findings from a case-control study

AIM

The rate of readmission after hospitalisation for respiratory diseases has become a common and challenging clinical problem. Social and functional patient variables could help identify cases at high risk of readmission. The aim was to identify the nursing diagnoses that were associated with readmission after hospitalisation for respiratory disease in Spain.

DESIGN

Case-control study within the cohort of patients admitted for respiratory disease during 2016-19 in a tertiary public hospital in Spain (n = 3781).

METHODS

Cases were patients who were readmitted within the first 30 days of discharge, and their controls were the remaining patients. All nursing diagnoses (n = 130) were collected from the electronic health record. They were then grouped into 29 informative diagnostic categories. Clinical confounder-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression models.

RESULTS

The readmission rate was 13.1%. The nursing diagnoses categories 'knowledge deficit' (OR: 1.61; 95%CI: 1.13-2.31), 'impaired skin integrity and risk of ulcer infection' (OR: 1.45; 95%CI: 1.06-1.97) and 'activity intolerance associated with fatigue' (OR: 1.56; 95%CI: 1.21-2.01) were associated with an increased risk of suffering an episode of hospital readmission rate at 30% after hospital discharge, and this was independent of sociodemographic background, care variables and comorbidity.

PATIENT OR PUBLIC CONTRIBUTION

The nursing diagnoses assigned as part of the care plan of patients during hospital admission may be useful for predicting readmissions.

Predicting Hospital Readmission in Medicaid Patients With COPD Using Administrative and Claims Data

BACKGROUND

The goals of this study were to develop a model that predicts the risk of 30-d all-cause readmission in hospitalized Medicaid patients diagnosed with COPD and to create a predictive model in a retrospective study of a population cohort.

METHODS

We analyzed 2016-2019 Medicaid claims data from 7 United States states. A COPD admission was one in which either the admission diagnosis or the first or second clinical (discharge) diagnosis bore an International Classification of Diseases, Tenth Revision code for COPD. A readmission was an admission for any condition (not necessarily COPD) that occurred within 30 d of a COPD discharge. We estimated a mixed-effects logistic model to predict 30-d readmission from patient demographic data, comorbidities, past health care utilization, and features of the index hospitalization. We evaluated model fit graphically and measured predictive accuracy by the area under the receiver operating characteristic (ROC) curve.

RESULTS

Among 12,283 COPD hospitalizations contributed by 9,437 subjects, 2,534 (20.6%) were 30-d readmissions. The final model included demographics, comorbidities, claims history, admission and discharge variables, length of stay, and seasons of admission and discharge. The observed versus predicted plot showed reasonable fit, and the estimated area under the ROC curve of 0.702 was robust in sensitivity analyses.

CONCLUSIONS

Our model identified with acceptable accuracy hospitalized Medicaid patients with a diagnosis of COPD who are at high risk of readmission. One can use the model to develop post-discharge management interventions for reducing readmissions, for adjusting comparisons of readmission rates between sites/providers or over time, and to guide a patient-centered approach to patient care.

The impact on thirty day readmissions for patients hospitalized for acute exacerbations of chronic obstructive pulmonary disease admitted to an observation unit versus an inpatient medical unit: A retrospective observational study

OBJECTIVES

We aimed to evaluate the utility of an Observation Unit (OU) in management of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and to identify the clinical characteristics of patients readmitted within 30-days for AECOPD following index admission to the OU or inpatient floor from the OU.

METHODS

This is a retrospective observational study of patients admitted from January to December 2017 for AECOPD to an OU in an urban-based tertiary care hospital. Primary outcome was rate of 30-day readmission after admission for AECOPD for patients discharged from the OU versus inpatient service after failing OU management. Regression analyses were used to define risk factors.

RESULTS

163 OU encounters from 92 unique patients were included. There was a lower readmission rate (33%) for patients converted from OU to inpatient care versus patients readmitted after direct discharge from the OU (44%). Patients with 30-day readmissions were more likely to be undomiciled, with history of congestive heart failure (CHF), pulmonary embolism (PE), or had previous admissions for AECOPD. Patients with >6 annual OU visits for AECOPD had higher rates of substance abuse, psychiatric diagnosis, and prior PE; when these patients were excluded, the 30-day readmission rate decreased to 13.5%.

CONCLUSION

Patients admitted for AECOPD with a history of PE, CHF, prior AECOPD admissions, and socioeconomic deprivation are at higher risk of readmission and should be prioritized for direct inpatient admission. Further prospective studies should be conducted to determine the clinical impact of this approach on readmission rates.

Predictors of Readmission, for Patients with Chronic Obstructive Pulmonary Disease (COPD) - A Systematic Review

Introduction

Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death globally and is responsible for over 3 million deaths annually. One of the factors contributing to the significant healthcare burden for these patients is readmission. The aim of this review is to describe significant predictors and prediction scores for all-cause and COPD-related readmission among patients with COPD.

Methods

A search was conducted in Ovid MEDLINE, Ovid Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials, from database inception to June 7, 2022. Studies were included if they reported on patients at least 40 years old with COPD, readmission data within 1 year, and predictors of readmission. Study quality was assessed. Significant predictors of readmission and the degree of significance, as noted by the p-value, were extracted for each study. This review was registered on PROSPERO (CRD42022337035).

Results

In total, 242 articles reporting on 16,471,096 patients were included. There was a low risk of bias across the literature. Of these, 153 studies were observational, reporting on predictors; 57 studies were observational studies reporting on interventions; and 32 were randomized controlled trials of interventions. Sixty-four significant predictors for all-cause readmission and 23 for COPD-related readmission were reported across the literature. Significant predictors included 1) pre-admission patient characteristics, such as male sex, prior hospitalization, poor performance status, number and type of comorbidities, and use of long-term oxygen; 2) hospitalization details, such as length of stay, use of corticosteroids, and use of ventilatory support; 3) results of investigations, including anemia, lower FEV1, and higher eosinophil count; and 4) discharge characteristics, including use of home oxygen and discharge to long-term care or a skilled nursing facility.

Conclusion

The findings from this review may enable better predictive modeling and can be used by clinicians to better inform their clinical gestalt of readmission risk.

Readmission rate for acute exacerbation of chronic obstructive pulmonary disease: A systematic review and meta-analysis

BACKGROUND

The readmission rate following hospitalization for chronic obstructive pulmonary disease (COPD) exacerbations is extremely high and has become a common and challenging clinical problem. This study aimed to systematically summarize COPD readmission rates for acute exacerbations and their underlying risk factors.

METHODS

A comprehensive search was performed using PubMed, Embase, Cochrane Library, and Web of Science, published from database inception to April 2, 2022. Methodological quality was evaluated using the Newcastle-Ottawa Scale (NOS). We used a random-effects model or a fixed-effects model to estimate the pooled COPD readmission rate for acute exacerbations and underlying risk factors.

RESULTS

A total of 46 studies were included, of which 24, 7, 17, 7, and 20 summarized the COPD readmission rates for acute exacerbations within 30, 60, 90, 180, and 365 days, respectively. The pooled 30-, 60-, 90-, 180-, and 365-day readmission rates were 11%, 17%, 17%, 30%, and 37%, respectively. The study design type, age stage, WHO region, and length of stay (LOS) were initially considered to be sources of heterogeneity. We also identified potential risk factors for COPD readmission, including male sex, number of hospitalizations in the previous year, LOS, and comorbidities such as heart failure, tumor or cancer, and diabetes, whereas obesity was a protective factor.

CONCLUSIONS

Patients with COPD had a high readmission rate for acute exacerbations, and potential risk factors were identified. Therefore, we should propose clinical interventions and adjust or targeted the control of avoidable risk factors to prevent and reduce the negative impact of COPD readmission.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, identifier CRD42022333581.

Taking Charge After Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Randomized Controlled Feasibility Trial of a Psychologically Informed Self-Management Intervention

Purpose

Few interventions improve outcomes for people with Chronic Obstructive Pulmonary Disease (COPD), particularly higher risk groups such as those admitted to hospital with an acute exacerbation of COPD (AECOPD). The aim of the study was to test the feasibility and acceptability of a modified version of the Take Charge program in people after AECOPD and to determine the potential to improve self-reported limitations, health-related quality of life and reduce future hospitalizations.

Patients and Methods

A prospective, parallel group randomized trial with blinded endpoint assessment. Participants had been discharged from hospital with a diagnosis of AECOPD and were randomized to receive either a single 60-90 minute session of "Take Charge for COPD" from a trained facilitator in their own home or usual care. Take Charge is a "talking therapy" that encourages a sense of purpose, autonomy, mastery, and connectedness with others. The primary outcome was the rate of moderate or severe episodes of AECOPD in the subsequent 12 months.

Results

Fifty-six people were randomized (study target 60): predominantly European (71%), female (61%), older (mean [SD] age 70 [11] years), and non-smokers (89%). Charlson Comorbidity Index mean (SD) score was 2.3 (1.6) indicating mild to moderate comorbidity severity. There were 85 moderate or severe AECOPD episodes in the 12 months after the index admission for the Take Charge participants and 84 episodes in the control group (relative rate 0.93; 95% confidence interval (CI) 0.69 to 1.26). COPD Clinical Questionnaire (CCQ) scores were significantly lower (better) in the Take Charge group (mean difference -1.26; 95% CI -2.06 to -0.45).

Conclusion

The Take Charge intervention proved feasible with a population of people recently discharged from hospital with AECOPD. The direction of change in the primary outcome and some secondary outcomes suggest that an adequately powered study is justified.

All-cause readmission rate and risk factors of 30- and 90-day after discharge in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis

BACKGROUND

The readmission rate following hospitalization for chronic obstructive pulmonary disease (COPD) is surprisingly high, and frequent readmissions represent a higher risk of mortality and a heavy economic burden. However, information on all-cause readmissions in patients with COPD is limited.

OBJECTIVE

This study aimed to systematically summarize all-cause COPD readmission rates within 30 and 90 days after discharge and their underlying risk factors.

METHODS

Eight electronic databases were searched to identify relevant observational studies about COPD readmission from inception to 1 August 2022. Newcastle-Ottawa Scale was used for methodological quality assessment. We adopt a random effects model or a fixed effects model to estimate pooled all-cause COPD readmission rates and potential risk factors.

RESULTS

A total of 28 studies were included, of which 27 and 8 studies summarized 30- and 90-day all-cause readmissions, respectively. The pooled all-cause COPD readmission rates within 30 and 90 days were 18% and 31%, respectively. The World Health Organization region was initially considered to be the source of heterogeneity. We identified alcohol use, discharge destination, two or more hospitalizations in the previous year, and comorbidities such as heart failure, diabetes, chronic kidney disease, anemia, cancer, or tumor as potential risk factors for all-cause readmission, whereas female and obesity were protective factors.

CONCLUSIONS

Patients with COPD had a high all-cause readmission rate, and we also identified some potential risk factors. Therefore, it is urgent to strengthen early follow-up and targeted interventions, and adjust or avoid risk factors after discharge, so as to reduce the major health economic burden caused by frequent readmissions.

TRIAL REGISTRATION

This systematic review and meta-analysis protocol was prospectively registered with PROSPERO (no. CRD42022369894).

Social disparities in unplanned 30-day readmission rates after hospital discharge in patients with chronic health conditions: A retrospective cohort study using patient level hospital administrative data linked to the population census in Switzerland

Unplanned readmissions shortly after discharge from hospital are common in chronic diseases. The risk of readmission has been shown to be related both to hospital care, e.g., medical complications, and to patients’ resources and abilities to manage the chronic disease at home and to make appropriate use of outpatient medical care. Despite a growing body of evidence on social determinants of health and health behaviour, little is known about the impact of social and contextual factors on readmission rates. The objective of this study was to analyse possible effects of educational, financial and social resources of patients with different chronic health conditions on unplanned 30 day-readmission risks. The study made use of nationwide inpatient hospital data that was linked with Swiss census data. The sample included n = 62,109 patients aged 25 and older, hospitalized between 2012 and 2016 for one of 12 selected chronic conditions. Multivariate logistic regressions analysis was performed. Our results point to a significant association between social factors and readmission rates for patients with chronic conditions. Patients with upper secondary education (OR = 1.26, 95% CI: 1.11, 1.44) and compulsory education (OR = 1.51, 95% CI: 1.31, 1.74) had higher readmission rates than those with tertiary education when taking into account demographic, social and health status factors. Having private or semi-private hospital insurance was associated with a lower risk for 30-day readmission compared to patients with mandatory insurance (OR = 0.81, 95% CI: 0.73, 0.90). We did not find a general effect of social resources, measured by living with others in a household, on readmission rates. The risk of readmission for patients with chronic conditions was also strongly predicted by type of chronic condition and by factors related to health status, such as previous hospitalizations before the index hospitalization (+77%), number of comorbidities (+15% higher probability per additional comorbidity) as well as particularly long hospitalizations (+64%). Stratified analysis by type of chronic condition revealed differential effects of social factors on readmissions risks. Compulsory education was most strongly associated with higher odds for readmission among patients with lung cancer (+142%), congestive heart failure (+63%) and back problems (+53%). We assume that low socioeconomic status among patients with chronic conditions increases the risk of unplanned 30-day readmission after hospitalisation due to factors related to their social situation (e.g., low health literacy, material deprivation, high social burden), which may negatively affect cooperation with care providers and adherence to recommended therapies as well as hamper active participation in the medical process and the development of a shared understanding of the disease and its cure. Higher levels of comorbidity in socially disadvantaged patients can also make appropriate self-management and use of outpatient care more difficult. Our findings suggest a need for increased preventive measures for disadvantaged populations groups to promote early detection of diseases and to remove financial or knowledge-based barriers to medical care. Socially disadvantaged patients should also be strengthened more in their individual and social resources for coping with illness.

Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions

BACKGROUND

Emergency readmission poses an additional burden on both patients and healthcare systems. Risk stratification is the first step of transitional care interventions targeted at reducing readmission. To accurately predict the short- and intermediate-term risks of readmission and provide information for further temporal risk stratification, we developed and validated an interpretable machine learning risk scoring system.

METHODS

In this retrospective study, all emergency admission episodes from January 1st 2009 to December 31st 2016 at a tertiary hospital in Singapore were assessed. The primary outcome was time to emergency readmission within 90 days post discharge. The Score for Emergency ReAdmission Prediction (SERAP) tool was derived via an interpretable machine learning-based system for time-to-event outcomes. SERAP is six-variable survival score, and takes the number of emergency admissions last year, age, history of malignancy, history of renal diseases, serum creatinine level, and serum albumin level during index admission into consideration.

FINDINGS

A total of 293,589 ED admission episodes were finally included in the whole cohort. Among them, 203,748 episodes were included in the training cohort, 50,937 episodes in the validation cohort, and 38,904 in the testing cohort. Readmission within 90 days was documented in 80,213 (27.3%) episodes, with a median time to emergency readmission of 22 days (Interquartile range: 8-47). For different time points, the readmission rates observed in the whole cohort were 6.7% at 7 days, 10.6% at 14 days, 13.6% at 21 days, 16.4% at 30 days, and 23.0% at 60 days. In the testing cohort, the SERAP achieved an integrated area under the curve of 0.737 (95% confidence interval: 0.730-0.743). For a specific 30-day readmission prediction, SERAP outperformed the LACE index (Length of stay, Acuity of admission, Charlson comorbidity index, and Emergency department visits in past six months) and the HOSPITAL score (Hemoglobin at discharge, discharge from an Oncology service, Sodium level at discharge, Procedure during the index admission, Index Type of admission, number of Admissions during the last 12 months, and Length of stay). Besides 30-day readmission, SERAP can predict readmission rates at any time point during the 90-day period.

INTERPRETATION

Better performance in risk prediction was achieved by the SERAP than other existing scores, and accurate information about time to emergency readmission was generated for further temporal risk stratification and clinical decision-making. In the future, external validation studies are needed to evaluate the SERAP at different settings and assess their real-world performance.

FUNDING

This study was supported by the Singapore National Medical Research Council under the PULSES Center Grant, and Duke-NUS Medical School.

Sociodemographic and Clinical Variables Related to the Overburden of the Informal Caregivers of Patients Hospitalized for Chronic Obstructive Pulmonary Disease Exacerbations

Objective

To increase our knowledge of the patient variables related to the overburden of the caregivers of patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPDs).

Methodology

This was a cross-sectional study of patients with severe COPD who have informal caregivers. We performed a multivariate analysis of sociodemographic (economic situation, care, dependence, social risk, and use of social services) and clinical (degree of dyspnea, previous hospitalizations, disease impact, pulmonary function, and comorbidity) factors and related these to the burden of informal caregivers, as evaluated using the Zarit scale.

Results

The study included 91 patients, age 72.6±8.7 years and 80 were male (89.7%); the mean modified Medical Research Council dyspnea scale (mMRC) score was 2.5±0.8; mean FEV₁ was 39.5 ± 13.2%; and 70 patients (76.9%) were dependent for basic activities. Of the informal caregivers, 90 (90.9%) were women, 49 (49.4%) were partners or spouses, and 29 (29.6%) were daughters. The mean Zarit questionnaire score was 51.4±14.2, with 63 of carers (69.2%) perceiving some overburden, and 34 (37.4%) describing the overburden as mild–moderate. The variables related to informal caregiver overburden in the multivariate study were the previous use of social resources [OR = 8.1 (95% CI = 1.03–69.9); p = 0.04], degree of mMRC dyspnea 3–4 [OR =4.7 (95% CI = 1.7–13.2); p = 0.003], and two or more admissions for AEPOC in the previous year [OR = 4.5 (95% CI = 1.7–13.2); p = 0.003]. Of the informal caregivers of patients who had presented two or more of these variables, 92.3% perceived an overburden.

Conclusion

The variables associated with overburden are easily accessible in patient medical records, or can be obtained by interviewing patients or their relatives. This information would allow to detect and assess the overburden of informal caregivers to provide an early warning of this problem.

Four Decades of COPD Mortality Trends: Analysis of Trends and Multiple Causes of Death

There is little information on chronic obstructive pulmonary disease (COPD) mortality trends, age of death, or male:female ratio. This study therefore sought to analyze time trends in mortality with COPD recorded as the underlying cause of death from 1980 through 2017, and with COPD recorded other than as the underlying cause of death. We conducted an analysis of COPD deaths in Galicia (Spain) from 1980 through 2017, including those in which COPD was recorded other than as the underlying cause of death from 2015 through 2017. We calculated the crude and standardized rates, and analyzed mortality trends using joinpoint regression models. There were 43,234 COPD deaths, with a male:female ratio of 2.4. Median age of death was 82 years. A change point in the mortality trend was detected in 1996 with a significant decrease across the sexes, reflected by an annual percentage change of −3.8%. Taking deaths into account in which COPD participated or contributed without being the underlying cause led to an overall 42% increase in the mortality burden. The most frequent causes of death when COPD was not considered to be the underlying cause were bronchopulmonary neoplasms and cardiovascular diseases. COPD mortality has decreased steadily across the sexes in Galicia since 1996, and age of death has also gradually increased. Multiple-cause death analysis may help prevent the underestimation of COPD mortality.

Changes in symptoms and health-related quality of life in patients with exacerbated chronic obstructive pulmonary disease

AIMS

To describe changes in symptoms and identify distinct subgroups of symptoms, to determine whether the sample's characteristics predicted changes in symptoms, and to examine how changes in symptoms predicted changes in health-related quality of life (HRQOL) over 6 months in patients with exacerbated chronic obstructive pulmonary disease (COPD).

BACKGROUND

Different patterns of changes in symptoms and their relationship to changes in HRQOL in patients with exacerbated COPD over long periods of time have been understudied.

METHODS

In this longitudinal study, participants with COPD (N = 42) had been admitted to a medical ward or had visited a pulmonary medicine clinic for treatment of exacerbation. Descriptive and inferential statistics were used to analyze data from questionnaires that assessed symptoms and HRQOL at baseline, daily symptoms over 6 months, and HRQOL at 6 months after exacerbation.

RESULTS

Not all participants experienced improved symptoms over time. Two sets of subgroups (improving &worsening; constantly better &constantly worse) emerged, based on 6-month changes in symptoms. Sample characteristics of the improving and worsening subgroups were similar, whereas usual dyspnea and HRQOL were significantly different in the constantly better and constantly worse subgroups. Little change in HRQOL was found in the total sample, but HRQOL deteriorated in the worsening subgroup, although deterioration was not meaningful. Changes in symptoms significantly predicted changes in HRQOL over 6 months.

CONCLUSION

Assessing patients' symptoms after exacerbations of COPD may enable health care providers to identify those at risk of future exacerbations and poorer HRQOL.0.