Evaluation of prediction strategy and care coordination for COPD readmissions

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.

Modelling 30-day hospital readmission after discharge for COPD patients based on electronic health records

Chronic Obstructive Pulmonary Disease (COPD) is the third most common chronic disease in China with frequent exacerbations, resulting in increased hospitalization and readmission rate. COPD readmission within 30 days after discharge is an important indicator of care transitions, patient's quality of life and disease management. Identifying risk factors and improving 30-day readmission prediction help inform appropriate interventions, reducing readmissions and financial burden. This study aimed to develop a 30-day readmission prediction model using decision tree by learning from the data extracted from the electronic health record of COPD patients in Macao. Health records data of COPD inpatients from Kiang Wu Hospital, Macao, from January 1, 2018, to December 31, 2019 were reviewed and analyzed. A total of 782 hospitalizations for AECOPD were enrolled, where the 30-day readmission rate was 26.5% (207). A balanced dataset was randomly generated, where male accounted for 69.1% and mean age was 80.73 years old. Age, length of stay, history of tobacco smoking, hemoglobin, systemic steroids use, antibiotics use and number of hospital admission due to COPD in last 12 months were found to be significant risk factors for 30-day readmission of CODP patients (P < 0.01). A data-driven decision tree-based modelling approach with Bayesian hyperparameter optimization was developed. The mean precision-recall and AUC value for the classifier were 73.85, 73.7 and 0.7506, showing a satisfying prediction performance. The number of hospital admission due to AECOPD in last 12 months, smoke status and patients' age were the top factors for 30-day readmission in Macao population.

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).

An AI-driven clinical care pathway to reduce 30-day readmission for chronic obstructive pulmonary disease (COPD) patients

Healthcare regulatory agencies have mandated a reduction in 30-day hospital readmission rates and have targeted COPD as a major contributor to 30-day readmissions. We aimed to develop and validate a simple tool deploying an artificial neural network (ANN) for early identification of COPD patients with high readmission risk. Using COPD patient data from eight hospitals within a large urban hospital system, four variables were identified, weighted and validated. These included the number of in-patient admissions in the previous 6 months, the number of medications administered on the first day, insurance status, and the Rothman Index on hospital day one. An ANN model was trained to provide a predictive algorithm and validated on an additional dataset from a separate time period. The model was implemented in a smartphone app (Re-Admit) incorporating four input risk factors, and a clinical care plan focused on high-risk readmission candidates was then implemented. Subsequent readmission data was analyzed to assess impact. The areas under the curve of receiver operating characteristics predicting readmission with ANN is 0.77, with sensitivity 0.75 and specificity 0.67 on the separate validation data. Readmission rates in the COPD high-risk subgroup after app and clinical intervention implementation saw a significant 48% decline. Our studies show the efficacy of ANN model on predicting readmission risks for COPD patients. The AI enabled Re-Admit smartphone app predicts readmission risk on day one of the patient's admission, allowing for early implementation of medical, hospital, and community resources to optimize and improve clinical care pathways.

Predicting hospital readmission risk: A prospective observational study to compare primary care providers' assessments with the LACE readmission risk index

Purpose

This study aims to determine if the primary care provider (PCP) assessment of readmission risk is comparable to the validated LACE tool at predicting readmission to hospital.

Methods

A prospective observational study of recently discharged adult patients clustered by PCPs in the primary care setting. Physician readmission risk assessment was determined via a questionnaire after the PCP reviewed the hospital discharge summary. LACE scores were calculated using administrative data and the discharge summary. The sensitivity and specificity of the physician assessment and the LACE tool in predicting readmission risk, agreement between the 2 assessments and the area under receiver operating characteristic (AUROC) curves were calculated.

Results

217 patient readmission encounters were included in this study from September 2017 till June 2018. The rate of readmission within 30 days was 14.7%, and 217 discharge summaries were used for analysis. The weighted kappa coefficient was 0.41 (95% CI: 0.30–0.51) demonstrating a moderate level of agreement. Sensitivity of physician assessment was 0.31 (95% CI: 0.22–0.40) and specificity was 0.80 (95% CI: 0.77–0.83). The sensitivity of the LACE assessment was 0.42 (95% CI: 0.25–0.59) and specificity was 0.79 (95% CI: 0.73–0.85). The AUROC for the LACE readmission risk was 0.65 (95% C.I. 0.55–0.76) demonstrating modest predictive power and was 0.57 (95% C.I. 0.46–0.68) for physician assessment, demonstrating low predictive power.

Conclusion

The LACE index shows moderate discriminatory power in identifying high-risk patients for readmission when compared to the PCP’s assessment. If this score can be provided to the PCP, it may help identify patients who requires more intensive follow-up after discharge.

Strategies to Prevent Readmissions to Hospital for COPD: A Systematic Review

Patients with chronic obstructive pulmonary disease (COPD) experience high rates of hospital readmissions, placing substantial clinical and economic strain on the healthcare system. Therefore, it is essential to implement evidence-based strategies for preventing these readmissions. The primary objective of our systematic review was to identify and describe the domains of existing primary research on strategies aimed at reducing hospital readmissions among adult patients with COPD. We also aimed to identify existing gaps in the literature to facilitate future research efforts. A total of 843 studies were captured by the initial search and 96 were included in the final review (25 randomized controlled trials, 37 observational studies, and 34 non-randomized interventional studies). Of the included studies, 72% (n = 69) were considered low risk of bias. The majority of included studies (n = 76) evaluated patient-level readmission prevention strategies (medication and other treatments (n = 25), multi-modal (n = 19), follow-up (n = 16), telehealth (n = 8), education and coaching (n = 8)). Fewer assessed broader system- (n = 13) and policy-level (n = 7) strategies. We observed a trend toward reduced all-cause readmissions with the use of medication and other treatments, as well as a trend toward reduced COPD-related readmissions with the use of multi-modal and broader scale system-level interventions. Notably, much of this evidence supported shorter-term (30-day) readmission outcomes, while little evidence was available for longer-term outcomes. These findings should be interpreted with caution, as considerable between-study heterogeneity was also identified. Overall, this review identified several evidence-based interventions for reducing readmissions among patients with COPD that should be targeted for future research.Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2021.1955338 .

Frequency and predictors of 30-day readmission after an index hospitalization for generalized convulsive status epilepticus: A nationwide study

OBJECTIVE

The objective of the study was to assess the frequency and factors associated with all-cause 30-day readmission among patients hospitalized with generalized convulsive status epilepticus (GCSE) in a nationwide sample in the United States.

METHODS

We used The 2014 Nationwide Readmission Database (NRD) as the data source. We included adults (age ≥18 years) with a primary discharge diagnosis of GCSE, identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 345.3. We excluded patients who died during hospitalization and those who had missing information on the length of stay (LOS). We also excluded those discharged in December 2014. We computed the overall 30-day readmission rate and compared prespecified groups by their 30-day readmission status. We applied a multiple logistic regression analysis to identify independent predictors of all-cause 30-day readmission adjusting for potential confounders.

RESULTS

Among 14,562 (weighted 31,062) adults discharged with a diagnosis of GCSE, 2520 (17.3%) were readmitted within 30 days. In multivariate analysis, patients with comorbid conditions (odds ratio (OR) for Charlson Comorbidities Index (CCI) = 1 and ≥2 was 1.12, 95% confidence interval (CI): 1.0-1.36 and 1.32, 95% CI: 1.17-1.48, respectively), LOS >6 days (OR: 1.42; 95% CI: 1.05-192), discharged against medical advice (OR: 1.45; 95% CI: 1.09-1.92), or discharged to a short-term hospital (OR: 1.39; 95% CI: 1.0-1.88), had higher odds of 30-day readmission, while there was an inverse association for those aged ≥45 years or with high income. Seizures were the most common cause associated with readmission, followed by sepsis and cerebrovascular diseases, respectively.

SIGNIFICANCE

Little is known about the frequency and predictors of early readmission after GCSE. This study showed that more than one in six patients with GCSE was readmitted within 30 days after discharge. More considerable attention to high-risk subgroups may identify opportunities to ameliorate the clinical outcome and lessen the economic burden of early readmission after GCSE.

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.

Multi-morbidities are Not a Driving Factor for an Increase of COPD-Related 30-Day Readmission Risk

Background and Objective

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States. COPD is expensive to treat, whereas the quality of care is difficult to evaluate due to the high prevalence of multi-morbidity among COPD patients. In the US, the Hospital Readmissions Reduction Program (HRRP) was initiated by the Centers for Medicare and Medicaid Services to penalize hospitals for excessive 30-day readmission rates for six diseases, including COPD. This study examines the difference in 30-day readmission risk between COPD patients with and without comorbidities.

Methods

In this retrospective cohort study, we used Cox regression to estimate the hazard ratio of 30-day readmission rates for COPD patients who had no comorbidity and those who had one, two or three, or four or more comorbidities. We controlled for individual, hospital and geographic factors. Data came from three sources: Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID), Area Health Resources Files (AHRF) and the American Hospital Association’s (AHA's) annual survey database for the year of 2013.

Results

COPD patients with comorbidities were less likely to be readmitted within 30 days relative to patients without comorbidities (aHR from 0.84 to 0.87, p < 0.05). In a stratified analysis, female patients with one comorbidity had a lower risk of 30-day readmission compared to female patients without comorbidity (aHR = 0.80, p < 0.05). Patients with public insurance who had comorbidities were less likely to be readmitted within 30 days in comparison with those who had no comorbidity (aHR from 0.79 to 0.84, p < 0.05).

Conclusion

COPD patients with comorbidities had a lower risk of 30-day readmission compared with patients without comorbidity. Future research could use a different study design to identify the effectiveness of the HRRP.

Incidence and Risk Factors Associated With 30-Day Readmission for Alcoholic Hepatitis

BACKGROUND

Alcohol abuse and liver disease are associated with high rates of 30-day hospital readmission, but factors linking alcoholic hepatitis (AH) to readmission are not well understood. We aimed to determine the incidence rate of 30-day readmission for patients with AH and to evaluate potential predictors of readmission.

METHODS

We used the Nationwide Readmissions Database to determine the 30-day readmission rate for recurrent AH between 2010 and 2014 and examined trends in readmissions during the study period. We also identified the 20 most frequent reasons for readmission. Multivariate survey logistic regression analysis was used to identify factors associated with 30-day readmission.

RESULTS

Of the 61,750 index admissions for AH, 23.9% were readmitted within 30-days. The rate of readmission did not change significantly during the study period. AH, alcoholic cirrhosis, and hepatic encephalopathy were the most frequent reasons for readmission. In multivariate analysis female sex, leaving against medical advice, higher Charlson comorbidity index, ascites, and history of bariatric surgery were associated with earlier readmissions, whereas older age, payer type (private or self-pay/other), and discharge to skilled nursing-facility reduced this risk.

CONCLUSIONS

The 30-day readmission rate in patients with AH was high and stable during the study period. Factors associated with readmission may be helpful for development of consensus-based expert guidelines, treatment algorithms, and policy changes to help decrease readmission in AH.

Effects of Pharmacist-Conducted Medication Reconciliation at Discharge on 30-Day Readmission Rates of Patients With Chronic Obstructive Pulmonary Disease

PURPOSE

To analyze effect of pharmacist-conducted medication reconciliation on 30-day readmission rates in chronic obstructive pulmonary disease (COPD) and identify common medication errors among patient with readmissions.

METHODS

Pharmacists were educated on discharge medication reconciliation for patients with COPD. A retrospective chart review was conducted on patients who underwent pharmacist-conducted discharge medication reconciliation to determine 30-day readmissions. Medication errors analyzed included medication omissions and dose or frequency errors. Previously collected internal research without pharmacist-conducted medication reconciliation served as the control.

RESULTS

There were 65 patients in the control group and 50 in the intervention group. About 25% of patients in the control group and 26% of patients in the intervention group had any cause readmissions within 30 days of discharge (P = .87). Both the control and the intervention group had similar COPD-related readmissions of 12.3% and 12.6%, respectively. Medication dose or frequency errors consisted of 68.9% and 46.7% of total errors in the control and the intervention groups, respectively. Long-acting muscarinic antagonist (LAMA) or long-acting beta 2-agonist (LABA) were the most common drug classes to be incorrectly dosed or omitted at discharge. In the intervention group, 30 errors were identified. Due to inability to coordinate discharges, pharmacists intervened on 13 errors, 7 of which were accepted by the prescriber.

CONCLUSION

Pharmacist-conducted medication reconciliation at discharge did not affect 30-day readmission rates of patients with COPD. Confounding factors included a small sample size, passive pharmacist education, and discharge issues. The most common medication errors at discharge were dosing or frequency errors of LABAs or LAMAs.

Predicting 30-Day Readmission Rate in Inflammatory Bowel Disease Patients: Performance of LACE Index

Background and Aims

Readmission within 30 days in inflammatory bowel disease (IBD) patients increases treatment costs and serves as a quality indicator. The LACE (Length of stay, Acuity of admission, Charlson comorbidity index, Emergency Department visits in past 6 months) index is used to predict the risk of unplanned readmission within 30 days. The aim of this study was to evaluate the accuracy of using the LACE index in IBD.

Methods

Calculation of LACE index was done prospectively for IBD patients admitted to a single tertiary care center. Patient, disease, and treatment characteristics, as well as index hospitalization characteristics including indication for admission and disease activity measures were retrospectively recorded. Descriptive statistics and univariable exact logistic regression analyses were performed.

Results

In total, 64 IBD patients were admitted during the study period. The 30-day readmission rate of IBD patients was 19% and overall median LACE index was 6, with IQR 6–7. LACE index categorized 16% of IBD patients in low-risk group, 82% in moderate risk group, and 2% in high-risk group. LACE index did not predict 30-day readmission (OR 1.35, CI: 0.88–2.18, P = 0.19). There was no significant difference in 30-day readmission rates with inpatient antibiotic or narcotic use, admission C-reactive protein (CRP), anemia, IBD duration, maintenance therapy, or prior IBD operation. For every 1 day increase in length of stay (LOS), patients were 8% more likely (OR: 1.08, 95% CI: 1.00–1.16) to be readmitted within 30 days (P = .05).

Conclusions

LACE index does not accurately identify 30-day readmission risk in the IBD population. As increased LOS is associated with higher risk, there may be benefit for targeted strategic resource allocation via specialized services.

Effectiveness of Healthcare Coordination in Patients with Chronic Respiratory Diseases

Coordination of healthcare effectively prevents exacerbations and reduces the number of hospitalizations, emergency visits, and the mortality rate in patients with chronic respiratory diseases. The purpose of this study was to determine clinical effectiveness of ambulatory healthcare coordination in chronic respiratory patients and its effect on the level of healthcare services as an indicator of direct medical costs. We conducted a retrospective health record survey, using an online database of 550 patients with chronic respiratory diseases. There were decreases in breathing rate, heart rate, and the number of cigarettes smoked per day, and forced vital capacity (FVC) and forced expired volume in 1 s (FEV1) increased after the implementation of the coordinated healthcare structure. These benefits were accompanied by increases in the number of visits to the pulmonary outpatient clinic (p < 0.001), diagnostic costs (p < 0.001), and referrals to other outpatient clinics (p < 0.003) and hospitals (p < 0.001). The advantageous effects of healthcare coordination on clinical status of respiratory patients above outlined persisted over a 3-year period being reviewed.

Performance of the LACE index to predict 30-day hospital readmissions in patients with chronic obstructive pulmonary disease

Background and objective

Patients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (COPD) have a high 30-day hospital readmission rate, which has a large impact on the health care system and patients’ quality of life. The use of a prediction model to quantify a patient’s risk of readmission may assist in directing interventions to patients who will benefit most. The objective of this study was to calculate the rate of 30-day readmissions and evaluate the accuracy of the LACE index (length of stay, acuity of admission, co-morbidities, and emergency department visits within the last 6 months) for 30-day readmissions in a general hospital population of COPD patients.

Methods

All patients admitted with a principal diagnosis of COPD to Liverpool Hospital, a tertiary hospital in Sydney, Australia, between 2006 and 2016 were included in the study. A LACE index score was calculated for each patient and assessed using receiver operator characteristic curves.

Results

During the study period, 2,662 patients had 5,979 hospitalizations for COPD. Four percent of patients died in hospital and 25% were readmitted within 30 days; 56% of all 30-day readmissions were again due to COPD. The most common reasons for readmission, following COPD, were heart failure, pneumonia, and chest pain. The LACE index had moderate discriminative ability to predict 30-day readmission (C-statistic =0.63).

Conclusion

The 30-day hospital readmission rate was 25% following hospitalization for COPD in an Australian tertiary hospital and as such comparable to international published rates. The LACE index only had moderate discriminative ability to predict 30-day readmission in patients hospitalized for COPD.

Evaluating the predictive strength of the LACE index in identifying patients at high risk of hospital readmission following an inpatient episode: a retrospective cohort study

OBJECTIVE

To assess how well the LACE index and its constituent elements predict 30-day hospital readmission, and to determine whether other combinations of clinical or sociodemographic variables may enhance prognostic capability.

DESIGN

Retrospective cohort study with split sample design for model validation.

SETTING

One large hospital Trust in the West Midlands.

PARTICIPANTS

All alive-discharge adult inpatient episodes between 1 January 2013 and 31 December 2014.

DATA SOURCES

Anonymised data for each inpatient episode were obtained from the hospital information system. These included age at index admission, gender, ethnicity, admission/discharge date, length of stay, treatment specialty, admission type and source, discharge destination, comorbidities, number of accident and emergency (A&E) visits in the 6 months before the index admission and whether a patient was readmitted within 30 days of index discharge.

OUTCOME MEASURES

Clinical and patient characteristics of readmission versus non-readmission episodes, proportion of readmission episodes at each LACE score, regression modelling of variables associated with readmission to assess the effectiveness of LACE and other variable combinations to predict 30-day readmission.

RESULTS

The training cohort included data on 91 922 patient episodes. Increasing LACE score and each of its individual components were independent predictors of readmission (area under the receiver operating characteristic curve (AUC) 0.773; 95% CI 0.768 to 0.779 for LACE; AUC 0.806; 95% CI 0.801 to 0.812 for the four LACE components). A LACE score of 11 was most effective at distinguishing between higher and lower risk patients. However, only 25% of readmission episodes occurred in the higher scoring group. A model combining A&E visits and hospital episodes per patient in the previous year was more effective at predicting readmission (AUC 0.815; 95% CI 0.810 to 0.819).

CONCLUSIONS

Although LACE shows good discriminatory power in statistical terms, it may have little added value over and above clinical judgement in predicting a patient's risk of hospital readmission.