Preventing COPD Readmissions Under the Hospital Readmissions Reduction Program: How Far Have We Come?

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.

Rationale and Design of Healthy at Home for COPD: an Integrated Remote Patient Monitoring and Virtual Pulmonary Rehabilitation Pilot Study

Chronic Obstructive Pulmonary Disease (COPD) is a common, costly, and morbid condition. Pulmonary rehabilitation, close monitoring, and early intervention during acute exacerbations of symptoms represent a comprehensive approach to improve outcomes, but the optimal means of delivering these services is uncertain. Logistical, financial, and social barriers to providing healthcare through face-to-face encounters, paired with recent developments in technology, have stimulated interest in exploring alternative models of care. The Healthy at Home study seeks to determine the feasibility of a multimodal, digitally enhanced intervention provided to participants with COPD longitudinally over six months. This paper details the recruitment, methods, and analysis plan for the study, which is recruiting 100 participants in its pilot phase. Participants were provided with several integrated services including a smartwatch to track physiological data, a study app to track symptoms and study instruments, access to a mobile integrated health program for acute clinical needs, and a virtual comprehensive pulmonary support service. Participants shared physiologic, demographic, and symptom reports, electronic health records, and claims data with the study team, facilitating a better understanding of their symptoms and potential care needs longitudinally. The Healthy at Home study seeks to develop a comprehensive digital phenotype of COPD by tracking and responding to multiple indices of disease behavior and facilitating early and nuanced responses to changes in participants' health status. This study is registered at Clinicaltrials.gov (NCT06000696).

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.

Development of Multivariable Prediction Models for the Identification of Patients Admitted to Hospital with an Exacerbation of COPD and the Prediction of Risk of Readmission: A Retrospective Cohort Study using Electronic Medical Record Data

BACKGROUND

Approximately 20% of patients who are discharged from hospital for an acute exacerbation of COPD (AECOPD) are readmitted within 30 days. To reduce this, it is important both to identify all individuals admitted with AECOPD and to predict those who are at higher risk for readmission.

OBJECTIVES

To develop two clinical prediction models using data available in electronic medical records: 1) identifying patients admitted with AECOPD and 2) predicting 30-day readmission in patients discharged after AECOPD.

METHODS

Two datasets were created using all admissions to General Internal Medicine from 2012 to 2018 at two hospitals: one cohort to identify AECOPD and a second cohort to predict 30-day readmissions. We fit and internally validated models with four algorithms.

RESULTS

Of the 64,609 admissions, 3,620 (5.6%) were diagnosed with an AECOPD. Of those discharged, 518 (15.4%) had a readmission to hospital within 30 days. For identification of patients with a diagnosis of an AECOPD, the top-performing models were LASSO and a four-variable regression model that consisted of specific medications ordered within the first 72 hours of admission. For 30-day readmission prediction, a two-variable regression model was the top performing model consisting of number of COPD admissions in the previous year and the number of non-COPD admissions in the previous year.

CONCLUSION

We generated clinical prediction models to identify AECOPDs during hospitalization and to predict 30-day readmissions after an acute exacerbation from a dataset derived from available EMR data. Further work is needed to improve and externally validate these models.

Motivational Interviewing and Chronic Care Management Using the Transtheoretical Model of Change

The number of Americans living with chronic health conditions has steadily increased. Chronic diseases are the leading causes of death and disability in the United States and cost the healthcare system an estimated $4.1 trillion dollars a year. The role of social workers in assisting patients in the management of their chronic diseases is vital. The behavioral health changes often required of chronic care management (CCM) patients require support and intervention by professionals to help the patient improve self-management of their chronic health conditions. Motivational interviewing (MI) is an evidence-based practice that helps people change by paying attention to the language patients use as they discuss their change goals and behaviors. Applying the principles and strategies of MI within the stages of change model (transtheoretical model of change) can help social workers better understand and assist patients receiving CCM. This article outlines specific strategies the social worker can use to address motivation at different stages of change.

Effectiveness of a Bundled Payments for Care Improvement Program for Chronic Obstructive Pulmonary Disease

BACKGROUND

The Medicare Bundled Payments for Care Improvement (BPCI) program reimburses 90-day care episodes post-hospitalization. COPD is a leading cause of early readmissions making it a target for value-based payment reform.

OBJECTIVE

Evaluate the financial impact of a COPD BPCI program.

DESIGN, PARTICIPANTS, INTERVENTIONS

A single-site retrospective observational study evaluated the impact of an evidence-based transitions of care program on episode costs and readmission rates, comparing patients hospitalized for COPD exacerbations who received versus those who did not receive the intervention.

MAIN MEASURES

Mean episode costs and readmissions.

KEY RESULTS

Between October 2015 and September 2018, 132 received and 161 did not receive the program, respectively. Mean episode costs were below target for six out of eleven quarters for the intervention group, as opposed to only one out of twelve quarters for the control group. Overall, there were non-significant mean savings of $2551 (95% CI: - $811 to $5795) in episode costs relative to target costs for the intervention group, though results varied by index admission diagnosis-related group (DRG); there were additional costs of $4184 per episode for the least-complicated cohort (DRG 192), but savings of $1897 and $1753 for the most complicated index admissions (DRGs 191 and 190, respectively). A significant mean decrease of 0.24 readmissions per episode was observed in 90-day readmission rates for intervention relative to control. Readmissions and hospital discharges to skilled nursing facilities were factors of higher costs (mean increases of $9098 and $17,095 per episode respectively).

CONCLUSIONS

Our COPD BPCI program had a non-significant cost-saving effect, although sample size limited study power. The differential impact of the intervention by DRG suggests that targeting interventions to more clinically complex patients could increase the financial impact of the program. Further evaluations are needed to determine if our BPCI program decreased care variation and improved quality of care.

PRIMARY SOURCE OF FUNDING

This research was supported by NIH NIA grant #5T35AG029795-12.

Care Quality for Patients with Chronic Obstructive Pulmonary Disease in the Readmission Penalty Era

Rationale: Chronic obstructive pulmonary disease (COPD) is the fifth-leading cause of admissions and third-leading cause of readmissions among U.S. adults. Recent policies instituted financial penalties for excessive COPD readmissions. Objectives: To evaluate changes in the quality of care for patients hospitalized for COPD after implementation of the Hospital Readmissions Reduction Program (HRRP). Methods: We conducted a retrospective cohort study of patients older than 40 years of age hospitalized for COPD across 995 U.S. hospitals (Premier Healthcare Database). Measurements and Main Results: Quality of care before and after HRRP implementation was measured via adherence to recommended inpatient care treatments for acute exacerbations of COPD (recommended care, nonrecommended care, "ideal care" [all recommended and no nonrecommended care]). We included 662,842 pre-HRRP (January 2010-September 2014) and 285,508 post-HRRP (October 2014-December 2018) admissions. Recommended care increased at a rate of 0.16% per month pre-HRRP and 0.01% per month post-HRRP (P < 0.001). Nonrecommended care decreased at a rate of 0.15% per month pre-HRRP and 0.13% per month post-HRRP. Ideal care increased at a rate of 0.24% per month pre-HRRP and 0.11% per month post-HRRP (P < 0.001). Conclusions: The pre-HRRP trends toward improving care quality for inpatient COPD care slowed after HRRP implementation. This suggests that financial penalties for readmissions did not stimulate higher quality of care for patients hospitalized with COPD. It remains unclear what policies or approaches will be effective to ensure high care quality for patients hospitalized with COPD exacerbations.

Using Machine Learning to Predict Likelihood and Cause of Readmission After Hospitalization for Chronic Obstructive Pulmonary Disease Exacerbation

Background

Chronic obstructive pulmonary disease (COPD) is a leading cause of hospital readmissions. Few existing tools use electronic health record (EHR) data to forecast patients’ readmission risk during index hospitalizations.

Objective

We used machine learning and in-hospital data to model 90-day risk for and cause of readmission among inpatients with acute exacerbations of COPD (AE-COPD).

Design

Retrospective cohort study.

Participants

Adult patients admitted for AE-COPD at the University of Chicago Medicine between November 7, 2008 and December 31, 2018 meeting International Classification of Diseases (ICD)-9 or −10 criteria consistent with AE-COPD were included.

Methods

Random forest models were fit to predict readmission risk and respiratory-related readmission cause. Predictor variables included demographics, comorbidities, and EHR data from patients’ index hospital stays. Models were derived on 70% of observations and validated on a 30% holdout set. Performance of the readmission risk model was compared to that of the HOSPITAL score.

Results

Among 3238 patients admitted for AE-COPD, 1103 patients were readmitted within 90 days. Of the readmission causes, 61% (n = 672) were respiratory-related and COPD (n = 452) was the most common. Our readmission risk model had a significantly higher area under the receiver operating characteristic curve (AUROC) (0.69 [0.66, 0.73]) compared to the HOSPITAL score (0.63 [0.59, 0.67]; p = 0.002). The respiratory-related readmission cause model had an AUROC of 0.73 [0.68, 0.79].

Conclusion

Our models improve on current tools by predicting 90-day readmission risk and cause at the time of discharge from index admissions for AE-COPD. These models could be used to identify patients at higher risk of readmission and direct tailored post-discharge transition of care interventions that lower readmission risk.

Evaluation of COPD Chronic Care Management Collaborative to Reduce Emergency Department and Hospital Revisits Across U.S. Hospitals

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is the third-leading cause of early readmissions. The Centers for Medicare and Medicaid instituted a financial penalty for excessive COPD readmissions galvanizing hospitals to implement effective strategies to reduce readmissions. We evaluated a 6-month COPD Chronic Care Management Collaborative to support hospitals to reduce preventable COPD-related revisits.

METHODS

Sites were recruited among nearly 300 Vizient, Inc., members. The Collaborative used performance improvement initiatives to assist with implementation of effective strategies. Participants submitted performance data for 2 outcome measures: emergency department (ED) and hospital revisits.

RESULTS

Forty-seven members enrolled (Part I+II: n=33; Part I: n=3; Part II: n=11) of which 23 submitted data (n=23/47). The majority (n=19/23, 83%) reduced rates of COPD-related ED and/or hospital revisits. Among all 23 sites, the change in ED visits went from 11.05% to 10.87%; among 7 sites with reductions in ED visits, the reduction was 12.7% to 9%. Among all 23 sites, there were not reductions in hospital readmissions (18.53% to 18.64%); among 7 sites with reductions, the readmission rate went from 20.1% to 15.6%. The mean reach across 17 hospitals reporting reach for their most successful measure at baseline was 35.2% (SD=26.7%) and for the other 6, reporting reach at follow-up was 73.8%% (SD=18.3%); of note, only 3 sites submitted both baseline and follow-up data.

CONCLUSIONS

The Collaborative successfully supported the majority of sites in reducing COPD-related ED and/or hospital revisits using subject matter experts and coaching strategies to support hospitals' implementation of COPD quality improvement interventions.

Weak Handgrip at Index Admission for Acute Exacerbation of COPD Predicts All-Cause 30-Day Readmission

Rationale: Identifying patients hospitalized for acute exacerbations of COPD (AECOPD) who are at high risk for readmission is challenging. Traditional markers of disease severity such as pulmonary function have limited utility in predicting readmission. Handgrip strength, a component of the physical frailty phenotype, may be a simple tool to help predict readmission. Objective(s): To investigate if handgrip strength, a component of the physical frailty phenotype and surrogate for weakness, is a predictive biomarker of COPD readmission. Methods: This was a prospective, observational study of patients admitted to the inpatient general medicine unit at the University of Chicago Medicine, US. This study evaluated age, sex, ethnicity, degree of obstructive lung disease by spirometry (FEV1 percent predicted), and physical frailty phenotype (components include handgrip strength and walk speed). The primary outcome was all-cause hospital readmission within 30 days of discharge. Results: Of 381 eligible patients with AECOPD, 70 participants agreed to consent to participate in this study. Twelve participants (17%) were readmitted within 30 days of discharge. Weak grip at index hospitalization, defined as grip strength lower than previously established cut-points for sex and body mass index (BMI), was predictive of readmission (OR 11.2, 95% CI 1.3, 93.2, p = 0.03). Degree of airway obstruction (FEV1 percent predicted) did not predict readmission (OR 1.0, 95% CI 0.95, 1.1, p = 0.7). No non-frail patients were readmitted. Conclusions: At a single academic center weak grip strength was associated with increased 30-day readmission. Future studies should investigate whether geriatric measures can help risk-stratify patients for likelihood of readmission after admission for AECOPD.