Socioeconomic status (SES) and 30-day hospital readmissions for chronic obstructive pulmonary (COPD) disease: A population-based cohort study

Hospital-Community Partnerships and 30-Day All-Cause Readmission Rates in High-Need and Low-Need Communities

This study examined hospital-community partnership effects on 30-day readmission rates across 2,484 U.S. hospitals. Fixed effect linear models analyzed the impact of three partnership types across community strata. In average-to-low need communities, healthcare system partnerships reduced hospital-wide, heart failure, pneumonia, and THA/TKA readmissions, while local agency partnerships reduced hospital-wide, heart failure, and pneumonia rates. In high-need communities, all partnership types significantly decreased COPD and pneumonia readmissions, with community-based partnerships also reducing hospital-wide rates. Healthcare system partnerships showed the strongest effect on COPD reduction (β = -0.56, p < 0.001). These findings suggest partnerships may reduce readmissions, with stronger effects in high-need communities.

Needs for discharge planning and facilitators-barriers to implementing discharge plans for patients with SLE: A qualitative study

OBJECTIVE

To investigate the needs of patients with SLE in terms of discharge planning, to outline the practical perspectives of clinical healthcare professionals regarding the enablers and impediments to SLE patients' discharge planning, and to establish a basis for the creation of SLE discharge plans for subsequently diagnosed patients.

METHODS

Descriptive qualitative research methodology was used in this study, with the researcher herself as the research instrument. Healthcare professionals formally employed in the rheumatology and immunology department, as well as SLE patients admitted to a tertiary-level hospital in Anhui Province between August and December 2023, were chosen for the study using a purposeful sample technique. In-person, semi-structured in-depth interviews were carried out, and used thematic analysis to analyze the interview data and distil themes.

RESULT

A total of 17 patients and 13 healthcare professionals were interviewed. Five themes and sixteen sub-themes in all were extracted: ①the needs of SLE patients for discharge planning; ②the present state of discharge planning implementation; ③factors conducive to the implementation of discharge planning; ④factors hindering the implementation of discharge planning; ⑤recommendations for implementing of discharge planning.

CONCLUSION

Planning for the discharge of SLE patients is essential, and in order to support patients' successful discharge, management should strengthen training, thoroughly evaluate the needs of SLE patients, and create customized discharge plans.

Timing of follow-up visits after hospital discharge for COPD: Application of a new method

RATIONALE

A common strategy to reduce COPD readmissions is to encourage patient follow-up with a physician within 1 to 2 weeks of discharge, yet evidence confirming its benefit is lacking. We used a new study design called target randomized trial emulation to determine the impact of follow-up visit timing on patient outcomes.

METHODS

All Ontario residents aged 35 or older discharged from a COPD hospitalization were identified using health administrative data and randomly assigned to those who received and did not receive physician visit follow-up by within seven days. They were followed to all-cause emergency department visits, readmissions or death. Targeted randomized trial emulation was used to adjust for differences between the groups. COPD emergency department visits, readmissions or death was also considered.

RESULTS

There were 94,034 patients hospitalized with COPD, of whom 73.5% had a physician visit within 30 days of discharge. Adjusted hazard ratio for all-cause readmission, emergency department visits or death for people with a visit within seven days post discharge was 1.03 (95% Confidence Interval [CI]: 1.01-1.05) and remained around 1 for subsequent days; adjusted hazard ratio for the composite COPD events was 0.97 (95% CI 0.95-1.00) and remained significantly lower than 1 for subsequent days.

CONCLUSION

While a physician visit after discharge was found to reduce COPD events, a specific time period when a physician visit was most beneficial was not found. This suggests that follow-up visits should not occur at a predetermined time but be based on factors such as anticipated medical need.

Risk of Cardiovascular Events Associated with Chronic Obstructive Pulmonary Disease and/or Metabolic Syndrome: A Large-Scale Nationwide Population-Based Cohort Study

Purpose

Chronic obstructive pulmonary disease (COPD) and metabolic syndrome (MetS) are among the most prevalent conditions that might predispose individuals to life-threatening events. We aimed to examine their associations with cardiovascular (CV) events and mortality using a large-scale population dataset from the National Health Information Database in Korea.

Patients and Methods

This population-based cohort study enrolled adults aged ≥40 years who had undergone more than two health examinations between 2009 and 2011. They were divided into four groups based on the presence of COPD and MetS. Analysis of the outcomes and CV events or deaths was performed from 2014 to 2019. We compared CV event incidence and mortality rates using a multivariate Cox proportional hazards model and Kaplan-Meier curves.

Results

Totally, 5,101,810 individuals were included, among whom 3,738,458 (73.3%) had neither COPD nor MetS, 1,193,014 (23.4%) had only MetS, 125,976 (2.5%) had only COPD, and 44,362 (0.9%) had both. The risk of CV events was significantly higher in individuals with both COPD and MetS than in those with either COPD or MetS alone (HRs: 2.4 vs 1.6 and 1.8, respectively; all P <0.001). Similarly, among those with both COPD and MetS, all-cause and CV mortality risks were also elevated (HRs, 2.9 and 3.0, respectively) compared to the risks in those with either COPD (HRs, 2.6 and 2.1, respectively) or MetS (HRs, 1.7 and 2.1, respectively; all P <0.001).

Conclusion

The comorbidity of MetS in patients with COPD increases the incidence of CV events and all-cause and cardiovascular mortality rates.

Evaluating Algorithmic Bias in 30-Day Hospital Readmission Models: Retrospective Analysis

BACKGROUND

The adoption of predictive algorithms in health care comes with the potential for algorithmic bias, which could exacerbate existing disparities. Fairness metrics have been proposed to measure algorithmic bias, but their application to real-world tasks is limited.

OBJECTIVE

This study aims to evaluate the algorithmic bias associated with the application of common 30-day hospital readmission models and assess the usefulness and interpretability of selected fairness metrics.

METHODS

We used 10.6 million adult inpatient discharges from Maryland and Florida from 2016 to 2019 in this retrospective study. Models predicting 30-day hospital readmissions were evaluated: LACE Index, modified HOSPITAL score, and modified Centers for Medicare & Medicaid Services (CMS) readmission measure, which were applied as-is (using existing coefficients) and retrained (recalibrated with 50% of the data). Predictive performances and bias measures were evaluated for all, between Black and White populations, and between low- and other-income groups. Bias measures included the parity of false negative rate (FNR), false positive rate (FPR), 0-1 loss, and generalized entropy index. Racial bias represented by FNR and FPR differences was stratified to explore shifts in algorithmic bias in different populations.

RESULTS

The retrained CMS model demonstrated the best predictive performance (area under the curve: 0.74 in Maryland and 0.68-0.70 in Florida), and the modified HOSPITAL score demonstrated the best calibration (Brier score: 0.16-0.19 in Maryland and 0.19-0.21 in Florida). Calibration was better in White (compared to Black) populations and other-income (compared to low-income) groups, and the area under the curve was higher or similar in the Black (compared to White) populations. The retrained CMS and modified HOSPITAL score had the lowest racial and income bias in Maryland. In Florida, both of these models overall had the lowest income bias and the modified HOSPITAL score showed the lowest racial bias. In both states, the White and higher-income populations showed a higher FNR, while the Black and low-income populations resulted in a higher FPR and a higher 0-1 loss. When stratified by hospital and population composition, these models demonstrated heterogeneous algorithmic bias in different contexts and populations.

CONCLUSIONS

Caution must be taken when interpreting fairness measures' face value. A higher FNR or FPR could potentially reflect missed opportunities or wasted resources, but these measures could also reflect health care use patterns and gaps in care. Simply relying on the statistical notions of bias could obscure or underplay the causes of health disparity. The imperfect health data, analytic frameworks, and the underlying health systems must be carefully considered. Fairness measures can serve as a useful routine assessment to detect disparate model performances but are insufficient to inform mechanisms or policy changes. However, such an assessment is an important first step toward data-driven improvement to address existing health disparities.

Thirty-day readmissions in children with complex chronic conditions

INTRODUCTION

The rate of hospital readmission within 30 days of discharge is a quality indicator in health care. Paediatric patients with complex chronic conditions have high readmission rates. Failure in the transition between hospital and home care could explain this phenomenon.

OBJECTIVES

To estimate the incidence rate of 30-day hospital readmission in paediatric patients with complex chronic conditions, estimate how many are potentially preventable and explore factors associated with readmission.

MATERIALS AND METHOD

Cohort study including hospitalised patients with complex chronic conditions aged 1 month to 18 years. Patients with cancer or with congenital heart disease requiring surgical correction were excluded. The outcomes assessed were 30-day readmission rate and potentially preventable readmissions. We analysed sociodemographic, geographic, clinical and transition to home care characteristics as factors potentially associated with readmission.

RESULTS

The study included 171 hospitalizations, and 28 patients were readmitted within 30 days (16.4%; 95% CI, 11.6%-22.7%). Of the 28 readmissions, 23 were potentially preventable (82.1%; 95% CI, 64.4%-92.1%). Respiratory disease was associated with a higher probability of readmission. There was no association between 30-day readmission and the characteristics of the transition to home care.

CONCLUSIONS

The 30-day readmission rate in patients with complex chronic disease was 16.4%, and 82.1% of readmissions were potentially preventable. Respiratory disease was the only identified risk factor for 30-day readmission.

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.

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.

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).

Hospital Readmission Due to Chronic Obstructive Pulmonary Disease: A Longitudinal Study

BACKGROUND

This study aimed to investigate the prevalence of hospital readmission for chronic obstructive pulmonary disease (COPD) at 30, 90 and 365 days, and to determine demographic and socioeconomic risk factors for 30-day and 90-day readmission and time to COPD-related readmission within 365 days in Tasmania.

METHODS

Patients ≥40 years admitted for COPD between 2011 and 2015 were identified using administrative data from all major public hospitals in Tasmania, Australia. Factors associated with readmission and time to readmission were identified using logistic and Cox regression, respectively.

RESULTS

The rates of COPD-related readmission were 6.7% within 30 days, 12.2% within 90 days and 23.7% within 365 days. Being male (odds ratio [OR]: 1.49, CI: 1.06-2.09), Indigenous (OR: 2.47, CI: 1.31-4.66) and living in the lower socioeconomic North-West region of Tasmania (OR: 1.80, CI: 1.20-2.69) were risk factors for 30-day readmission. Increased COPD-related (OR: 1.48, CI: 1.22-1.80; OR: 1.52, CI: 1.29-1.78) and non-COPD-related (OR: 1.12, CI: 1.03- 1.23; OR: 1.11, CI: 1.03-1.21) emergency department (ED) visits in the preceding six months were risk factors for both 30-day and 90-day readmissions. Being Indigenous (hazard ratio [HR]: 1.61, CI: 1.10-2.37) and previous COPD-related ED visits (HR: 1.30, CI: 1.21-1.39) decreased, while a higher Charlson Comorbidity Index (CCI) (OR: 0.91, CI: 0.83- 0.99) increased the time to readmission within 365 days.

CONCLUSION

Being male, Indigenous, living in the North-West region and previous ED visits were associated with increased risk of COPD readmission in Tasmania. Interventions to improve access to primary healthcare for these groups may reduce COPD-related readmissions.

Experiences of patients with chronic obstructive pulmonary disease receiving integrated telehealth nursing services during COVID-19 lockdown

Objective

Even though telemonitoring existed prior to COVID-19, the need was accelerated for patients with COPD due to the limited medical consultations and the anxiety for being infected. To our knowledge, no qualitative study has explored the experiences of COPD patients and the potential benefits of receiving integrated telehealth nursing services during the lockdown.

Methods

Ten participants were interviewed after receiving telehealth nursing services for 3 months; data was analyzed thematically.

Results

Irrespective of COPD severity, all participants expressed that the existing fragmented follow-up care was intensified during COVID. The telenursing services provided them with the comfort and reassurance that a clinician is available for support, advice, and care during the times of isolation. Despite diverse opinions regarding the respiratory-related questions for follow-up, all were enthusiastic about the use of the oximeter in their daily lives. None perceived sharing data as an issue, instead they encouraged the exchange across levels of care.

Conclusion

Despite an appreciation for the service, it is imperative for sustainability reasons that standardized protocols are developed to balance patient preferences in terms of response frequency and the clinical data needed for a telenurse to provide appropriate interventions.

Predictors of short-term COPD readmission

COPD readmissions have a great impact on patients' quality of life and mortality. Our goal was to identify factors related to 60-day readmission. We conducted a prospective observational cohort study with a nested case-control study, with 60 days of follow-up after the index admission. Patients readmitted were matched, by age, baseline forced expiratory volume in 1 s and month at admission, with patients admitted in the same period but not readmitted at 2 months. Data were collected on sociodemographic and clinical characteristics and health-related quality of life data at the index admission and events from discharge to readmission within 60 days. Conditional logistic (60-day readmission) and Cox (days to readmission) regression models were constructed. Both multivariable analyses identified the following as predictors: any admission in the preceding 2 months (OR: 2.366; HR: 1.918), hematocrit at ED arrival ≤ 35% (OR: 2.949; HR: 1.570), pre-existing cardiovascular disease (valvular disease or myocardial infarction) (OR: 1.878; HR: 1.490); NIMV at discharge (OR: 0.547; HR: 0.70); no appointment with a specialist after discharge (OR: 5.785; HR: 3.373) and patient-reported need for help at home (OR: 2.978; HR: 2.061). The AUC for the logistic model was 0.845 and the c-index for the Cox model was 0.707. EuroQol EQ-5D score before the admission was correlated with a lower risk of readmission (OR: 0.383; HR: 0.670). As conclusions, we have identified factors related to 60-day readmission and summarized the findings in easy-to-use scoring scales that could be incorporated into the daily clinical routine and may help establish preventive measures to reduce future readmissions.Registration: Clinical Trial Registration NCT03227211.

A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models

OBJECTIVE

Health care providers increasingly rely upon predictive algorithms when making important treatment decisions, however, evidence indicates that these tools can lead to inequitable outcomes across racial and socio-economic groups. In this study, we introduce a bias evaluation checklist that allows model developers and health care providers a means to systematically appraise a model's potential to introduce bias.

MATERIALS AND METHODS

Our methods include developing a bias evaluation checklist, a scoping literature review to identify 30-day hospital readmission prediction models, and assessing the selected models using the checklist.

RESULTS

We selected 4 models for evaluation: LACE, HOSPITAL, Johns Hopkins ACG, and HATRIX. Our assessment identified critical ways in which these algorithms can perpetuate health care inequalities. We found that LACE and HOSPITAL have the greatest potential for introducing bias, Johns Hopkins ACG has the most areas of uncertainty, and HATRIX has the fewest causes for concern.

DISCUSSION

Our approach gives model developers and health care providers a practical and systematic method for evaluating bias in predictive models. Traditional bias identification methods do not elucidate sources of bias and are thus insufficient for mitigation efforts. With our checklist, bias can be addressed and eliminated before a model is fully developed or deployed.

CONCLUSION

The potential for algorithms to perpetuate biased outcomes is not isolated to readmission prediction models; rather, we believe our results have implications for predictive models across health care. We offer a systematic method for evaluating potential bias with sufficient flexibility to be utilized across models and applications.

Hospice Enrollment, Future Hospitalization, and Future Costs Among Racially and Ethnically Diverse Patients Who Received Palliative Care Consultation

BACKGROUND

Palliative care consultation to discuss goals-of-care ("PCC") may mitigate end-of-life care disparities.

OBJECTIVE

To compare hospitalization and cost outcomes by race and ethnicity among PCC patients; identify predictors of hospice discharge and post-discharge hospitalization utilization and costs.

METHODS

This secondary analysis of a retrospective cohort study assessed hospice discharge, do-not-resuscitate status, 30-day readmissions, days hospitalized, ICU care, any hospitalization cost, and total costs for hospitalization with PCC and hospitalization(s) post-discharge among 1,306 Black/African American, Latinx, White, and Other race PCC patients at a United States academic hospital.

RESULTS

In adjusted analyses, hospice enrollment was less likely with Medicaid (AOR = 0.59, P = 0.02). Thirty-day readmission was less likely among age 75+ (AOR = 0.43, P = 0.02); more likely with Medicaid (AOR = 2.02, P = 0.004), 30-day prior admission (AOR = 2.42, P < 0.0001), and Black/African American race (AOR = 1.57, P = 0.02). Future days hospitalized was greater with Medicaid (Coefficient = 4.49, P = 0.001), 30-day prior admission (Coefficient = 2.08, P = 0.02), and Black/African American race (Coefficient = 2.16, P = 0.01). Any future hospitalization cost was less likely among patients ages 65-74 and 75+ (AOR = 0.54, P = 0.02; AOR = 0.53, P = 0.02); more likely with Medicaid (AOR = 1.67, P = 0.01), 30-day prior admission (AOR = 1.81, P = 0.0001), and Black/African American race (AOR = 1.40, P = 0.02). Total future hospitalization costs were lower for females (Coefficient = -3616.64, P = 0.03); greater with Medicaid (Coefficient = 7388.43, P = 0.01), 30-day prior admission (Coefficient = 3868.07, P = 0.04), and Black/African American race (Coefficient = 3856.90, P = 0.04). Do-not-resuscitate documentation (48%) differed by race.

CONCLUSIONS

Among PCC patients, Black/African American race and social determinants of health were risk factors for future hospitalization utilization and costs. Medicaid use predicted hospice discharge. Social support interventions are needed to reduce future hospitalization disparities.

A mixed methods study to inform and evaluate a longitudinal nurse practitioner/community health worker intervention to address social determinants of health and chronic obstructive pulmonary disease self-management

BACKGROUND

Individuals with low socioeconomic status experience higher prevalence and worse outcomes of chronic obstructive pulmonary disease (COPD). We undertook a quality improvement initiative at our safety net hospital in which a nurse practitioner (NP)/community health worker (CHW) team followed patients with COPD, frequent admissions, and unmet SDOH needs from hospitalization through one month post-discharge. We report our mixed methods approach to inform development and preliminary evaluation of this intervention.

METHODS

We first assessed characteristics of patients admitted with COPD in 2018 (n = 1811), performing multivariable logistic regression to identify factors associated with ≥ 2 admissions per year. We then tested a standardized tool to screen for unmet SDOH needs in a convenience sample of 51 frequently hospitalized patients with COPD. From January-July 2019, we pilot tested the NP/CHW intervention with 57 patients, reviewed NP/CHW logs, and conducted qualitative interviews with 16 patient participants to explore impressions of the intervention.

RESULTS

Patients with Medicaid insurance, mental health disorders, cardiac disease, and substance use disorder had increased odds of having ≥ 2 admissions. COPD severity, comorbidities, and unmet SDOH needs made COPD self-management challenging. Seventy-four percent of frequently admitted patients with COPD completing SDOH screening had unmet SDOH needs. Patients perceived that the NP/CHW intervention addressed these barriers by connecting them to resources and providing emotional support.

CONCLUSIONS

Many patients with COPD admitted at our safety-net hospital experience unmet SDOH needs that impede COPD self-management. A longitudinal NP/CHW intervention to address unmet SDOH needs following discharge appears feasible and acceptable.

Predicting 30-days Readmission Risk for COPD Patients Care through a Federated Machine Learning Architecture on FAIR Data: Development and Validation Study (Preprint)

Background

Owing to the nature of health data, their sharing and reuse for research are limited by legal, technical, and ethical implications. In this sense, to address that challenge and facilitate and promote the discovery of scientific knowledge, the Findable, Accessible, Interoperable, and Reusable (FAIR) principles help organizations to share research data in a secure, appropriate, and useful way for other researchers.

Objective

The objective of this study was the FAIRification of existing health research data sets and applying a federated machine learning architecture on top of the FAIRified data sets of different health research performing organizations. The entire FAIR4Health solution was validated through the assessment of a federated model for real-time prediction of 30-day readmission risk in patients with chronic obstructive pulmonary disease (COPD).

Methods

The application of the FAIR principles on health research data sets in 3 different health care settings enabled a retrospective multicenter study for the development of specific federated machine learning models for the early prediction of 30-day readmission risk in patients with COPD. This predictive model was generated upon the FAIR4Health platform. Finally, an observational prospective study with 30 days follow-up was conducted in 2 health care centers from different countries. The same inclusion and exclusion criteria were used in both retrospective and prospective studies.

Results

Clinical validation was demonstrated through the implementation of federated machine learning models on top of the FAIRified data sets from different health research performing organizations. The federated model for predicting the 30-day hospital readmission risk was trained using retrospective data from 4.944 patients with COPD. The assessment of the predictive model was performed using the data of 100 recruited (22 from Spain and 78 from Serbia) out of 2070 observed (records viewed) patients during the observational prospective study, which was executed from April 2021 to September 2021. Significant accuracy (0.98) and precision (0.25) of the predictive model generated upon the FAIR4Health platform were observed. Therefore, the generated prediction of 30-day readmission risk was confirmed in 87% (87/100) of cases.

Conclusions

Implementing a FAIR data policy in health research performing organizations to facilitate data sharing and reuse is relevant and needed, following the discovery, access, integration, and analysis of health research data. The FAIR4Health project proposes a technological solution in the health domain to facilitate alignment with the FAIR principles.

High fitness levels offset the increased risk of chronic obstructive pulmonary disease due to low socioeconomic status: A cohort study

OBJECTIVE

Evidence suggests that higher cardiorespiratory fitness (CRF) levels can offset the increased risk of adverse outcomes due to other risk factors. The impact of high CRF levels on the increased risk of chronic obstructive pulmonary disease (COPD) due to low socioeconomic status (SES) is unknown. We aimed to assess the combined effects of SES and CRF on the future risk of COPD.

METHODS

We employed a prospective cohort of 2312 Finnish men aged 42-61 years at study entry. Socioeconomic status was self-reported and CRF was objectively assessed using respiratory gas exchange analyzers. Both exposures were categorized as low and high based on median cutoffs. Multivariable-adjusted hazard ratios (HRs) with confidence intervals (CIs) were estimated.

RESULTS

During 26.0 years median follow-up, 120 COPD cases occurred. Low SES was associated with increased COPD risk and high CRF was associated with reduced COPD risk. Compared with high SES-low CRF, low SES-low CRF was associated with an increased COPD risk 2.36 (95% CI: 1.44-3.87), with no evidence of an association for low SES-high CRF and COPD risk 1.46 (95% CI:0.82-2.60).

CONCLUSION

In middle-aged Finnish men, SES and CRF are each independently associated with COPD risk. However, high CRF levels offset the increased COPD risk related to low SES.

Potentially modifiable risk factors for 30-day unplanned hospital readmission preventive intervention-A data mining and statistical analysis

Unplanned hospital readmissions have a high prevalence and substantial healthcare costs. Preventive intervention during hospitalization holds the potential for reducing readmission risk. However, it is challenging to develop individualized interventions during hospitalization because the causes of readmissions have not been clearly known and because patients are heterogeneous. This work aimed to identify potentially modifiable risk factors of readmission to help clinicians better plan and prioritize interventions for different patient subgroups during hospitalization. We performed the analysis of associations between the changes of potentially modifiable risk factors and the change of readmission status with association rule mining and statistical methods. Twenty-nine risk factors were identified from the association rules, and twenty-five of them were potentially modifiable. The association rules with potentially modifiable risk factors can be recommended to different patient subgroups to support the development of customized readmission preventive interventions.

Predicting Severe Chronic Obstructive Pulmonary Disease Exacerbations. Developing a Population Surveillance Approach with Administrative Data

Rationale: Automatic prediction algorithms based on routinely collected health data may be able to identify patients at high risk for hospitalizations related to acute exacerbations of chronic obstructive pulmonary disease (COPD).Objectives: To conduct a proof-of-concept study of a population surveillance approach for identifying individuals at high risk of severe COPD exacerbations.Methods: We used British Columbia's administrative health databases (1997-2016) to identify patients with diagnosed COPD. We used data from the previous 6 months to predict the risk of severe exacerbation in the next 2 months after a randomly selected index date. We applied statistical and machine-learning algorithms for risk prediction (logistic regression, random forest, neural network, and gradient boosting). We used calibration plots and receiver operating characteristic curves to evaluate model performance based on a randomly chosen future date at least 1 year later (temporal validation).Results: There were 108,433 patients in the development dataset and 113,786 in the validation dataset; of these, 1,126 and 1,136, respectively, were hospitalized for COPD within their outcome windows. The best prediction algorithm (gradient boosting) had an area under the receiver operating characteristic curve of 0.82 (95% confidence interval, 0.80-0.83), which was significantly higher than the corresponding value for the model with exacerbation history as the only predictor (current standard of care: 0.68). The predicted risk scores were well calibrated in the validation dataset.Conclusions: Imminent COPD-related hospitalizations can be predicted with good accuracy using administrative health data. This model may be used as a means to target high-risk patients for preventive exacerbation therapies.

Current status and preventive strategies of chronic obstructive pulmonary disease in China: a literature review

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease that seriously threatens human health and wellbeing, thereby representing an important public health problem. At present, it is the fourth leading cause of death worldwide, and is estimated to become the third greatest cause of death by 2030. In China, the prevalence of COPD is increasing, secondary to an increase in smoking, air pollution and an aging population, resulting in a current the mortality of COPD in China which is higher than the global average. Moreover, the disability-adjusted life year (DALY) rate of COPD in China is still relatively high, with an associated heavy economic burden to patients, their families and society. Unfortunately, current measures for treatment and prevention of COPD in China are not optimal. This primarily results from limited public awareness of COPD and pulmonary function tests amongst residents of China, and the generally poor disease-specific knowledge of primary care doctors. In recent years, a series of preventative strategies have been introduced in China across at the level of national policy, societies and associations, and scientific research. This review focuses upon both the epidemiology of COPD and the current status of preventative and treatment strategies in China.

Dynamic Increase of Red Cell Distribution Width Predicts Increased Risk of 30-Day Readmission in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Purpose

Studies have demonstrated that red blood cell distribution width (RDW) is closely associated with the prognosis of patients with chronic obstructive pulmonary disease (COPD). In addition, the dynamic changes in RDW appear to play an important role. Thus, we aimed to investigate the relationship between dynamic changes in RDW and 30-day all-cause readmission of patients with acute exacerbation of COPD (AECOPD).

Methods

In this retrospective cohort study, we enrolled patients with AECOPD hospitalized in the Department of Respiratory Medicine in Liyuan Hospital (Wuhan China), a tertiary, university-affiliated, public hospital. Patients with AECOPD were divided into three groups based on their RDW values after the first and fourth days of admission. The normal range for RDW is 10-15%. Patients with normal RDW values were included in the normal group. Patients with an RDW value >15% on the first day, which subsequently decreased by >2% on the fourth day was included in the decreased group. The increased group was comprised of patients with an RDW value >15% on the first day which continued to increase, or those with a normal RDW value on the first day which increased >15% on the fourth day.

Results

A total of 239 patients (age: 72 years [range: 64-81 years]; male: n=199 [83.3%]) were included. There were 108, 72, and 59 patients in the RDW normal, decreased, and increased groups, respectively; the 30-day all-cause readmission rate was 9.3%, 9.7%, 27.1%, respectively; (p=0.003), being noticeably higher in the RDW increased group. Dynamic increase of RDW (OR:3.45, 95% CI: 1.39-8.58, p= 0.008) was independently correlated with 30-day all-cause readmission of patients with AECOPD.

Conclusion

The dynamic increase of RDW is an independent prognostic factor of 30-day all-cause readmission of patients with AECOPD.

Risk factors and associated outcomes of hospital readmission in COPD: A systematic review

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a leading cause of unplanned readmission. There is need to identify risk factors for, and strategies to prevent readmission in patients with COPD.

AIM

To systematically review and summarise the prevalence, risk factors and outcomes associated with rehospitalisation due to COPD exacerbation.

METHOD

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Five databases were searched for relevant studies.

RESULTS

Fifty-seven studies from 30 countries met the inclusion criteria. The prevalence of COPD-related readmission varied from 2.6 to 82.2% at 30 days, 11.8-44.8% at 31-90 days, 17.9-63.0% at 6 months, and 25.0-87.0% at 12 months post-discharge. There were differences in the reported factors associated with readmissions, which may reflect variations in the local context, such as the availability of community-based services to care for exacerbations of COPD. Hospitalisation in the previous year prior to index admission was the key predictor of COPD-related readmission. Comorbidities (in particular asthma), living in a deprived area and living in or discharge to a nursing home were also associated with readmission. Relative to those without readmissions, readmitted patients had higher in-hospital mortality rates, shorter long-term survival, poorer quality of life, longer hospital stay, increased recurrence of subsequent readmissions, and accounted for greater healthcare costs.

CONCLUSIONS

Hospitalisation in the previous year was the principal risk factor for COPD-related readmissions. Variation in the prevalence and the reported factors associated with COPD-related readmission indicate that risk factors cannot be generalised, and interventions should be tailored to the local healthcare environment.

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.

Chronic Obstructive Pulmonary Disease: Proprioception Exercises as an Addition to the Rehabilitation Process

Respiratory rehabilitation in patients with chronic obstructive pulmonary disease (COPD) is recognized as a cornerstone for the therapeutic path. Physiotherapy involves physical activity with aerobic and anaerobic exercises, which can improve the patient's symptomatic picture, such as motor function, emotional status (depression and anxiety), and improve the pain perception. The training of proprioception is not included in the structure of the exercises proposed by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). The training of proprioception is a very useful strategy for stimulating the cerebellum, a neurological suffering area in patients with COPD. The cerebellum sorts information about pain and emotions, as well as motor stimuli. The article discusses the need to introduce proprioception in respiratory rehabilitation protocols, highlighting the neurological relationships with the management of comorbidities.

Risk factors for early readmission after acute exacerbation of chronic obstructive pulmonary disease

BACKGROUND AND AIMS

Patients discharged after treatment for acute exacerbation of chronic obstructive pulmonary disease (COPD) are at high risk for readmission. We aimed to identify the prevalence and risk factors for readmission.

METHODS

We included 16,105 patients who had claimed their medical expenses from 1 May 2014 to 1 May 2016 after discharge from any medical facility in Korea, following treatment for acute exacerbation of COPD. We analysed the potential risk factors for readmission within 30 days of discharge.

RESULTS

Readmission rate was 26.4% (3989 patients among 15,101 patients) and over 50% of readmissions occurred within 10 days of discharge. Approximately 57% of readmissions occurred due to respiratory causes. Major causes of readmission were COPD (27%), pneumonia (14.2%), and lung cancer (7.1%), in that order. Patients who were readmitted were male, had more comorbidities and were less frequently admitted to tertiary hospitals than those who were not readmitted. Risk factors for readmission within 30 days of discharge were male sex, medical aid coverage, longer hospital stay, longer duration of systemic steroid use during hospital stay, high comorbid condition index, and discharge to skilled nursing facility.

CONCLUSION

Readmission occurred in approximately one-quarter of patients, and was associated with patient-related and clinical factors. Using these results, we can identify high-risk patients for readmission and precautions are needed to be taken before deciding on a discharge plan. Further research is needed to develop accurate tools for predicting the risk of readmission before discharge, and development and evaluation of an effective care programme for COPD patients are necessary.The reviews of this paper are available via the supplemental material section.