Reducing excess readmissions: promising effect of hospital readmissions reduction program in US hospitals

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 6 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).

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).

Risk of 30-Day All-Cause Readmission in Interstitial Lung Disease Patients after COVID-19: National-Level Data

Rationale: Hospital readmission within 30 days poses challenges for healthcare providers, policymakers, and patients because of its impact on care quality, costs, and outcomes. Patients with interstitial lung disease (ILD) are particularly affected by readmission, which is associated with increased morbidity and mortality and reduced quality of life. Because small sample sizes have hindered previous studies, this study seeks to address this gap in knowledge by examining a large-scale dataset. Objective: To determine the rate and probability of 30-day all-cause readmission and secondary outcomes in patients with coronavirus disease (COVID-19) or ILD admitted to the hospital. Methods: This study is a nested cohort study that used the PearlDiver patient records database. Adult patients (age ⩾18 yr) who were admitted to hospitals in 28 states in the United States with COVID-19 or ILD diagnoses were included. We defined and analyzed two separate cohorts in this study. The first cohort consisted of patients with COVID-19 and was later divided into two groups with or without a history of ILD. The second cohort consisted of patients with ILD and was later divided into groups with COVID-19 or with a non-COVID-19 pneumonia diagnosis at admission. We also studied two other subcohorts of patients with and without idiopathic pulmonary fibrosis within the second cohort. Propensity score matching was employed to match confounders between groups. The Kaplan-Meier log rank test was applied to compare the probabilities of outcomes. Results: We assessed the data of 2,286,775 patients with COVID-19 and 118,892 patients with ILD. We found that patients with COVID-19 with preexisting ILD had an odds ratio of 1.6 for 30-day all-cause readmission. Similarly, an odds ratio of 2.42 in readmission rates was observed among hospitalized individuals with ILD who contracted COVID-19 compared with those who were hospitalized for non-COVID-19 pneumonia. Our study also found a significantly higher probability of intensive care admission among patients in both cohorts. Conclusions: Patients with ILD face heightened rates of hospital readmissions, particularly when ILD is combined with COVID-19, resulting in adverse outcomes such as decreased quality of life and increased healthcare expenses. It is imperative to prioritize preventive measures against COVID-19 and establish effective postdischarge care strategies for patients with ILD.

Hypothyroidism as an Independent Predictor of 30-day Readmission in Head and Neck Cancer Patients

OBJECTIVES

To define the role of hypothyroidism and other risk factors for unplanned readmissions after surgery for head and neck cancer.

STUDY DESIGN

Retrospective cohort study.

METHODS

The Nationwide Readmission Database (NRD) was used to identify patients who underwent surgery for mucosal head and neck cancer (oral cavity, oropharynx, larynx, and hypopharynx) between 2010 and 2017. Univariate and multivariate logistic regression were performed to determine patient, tumor, and hospital related risk factors for 30-day readmission. Readmitted patients were stratified by preoperative diagnosis of hypothyroidism to compare readmission characteristics.

RESULTS

For the 131,013 patients who met inclusion criteria, the readmission rate was 15.9%. Overall, 11.91% of patients had a preoperative diagnosis of hypothyroidism. After controlling for other variables, patients with a preoperative diagnosis of hypothyroidism had 12.2% higher odds of readmission compared to those without hypothyroidism (OR: 1.12, 1.03-1.22, p = 0.008). Patients with hypothyroidism had different reasons for readmission, including higher rates of wound dehiscence, fistula, infection, and electrolyte imbalance. Among readmitted patients, the length of stay for index admission (mean 10.5 days vs. 9.2 days, p < 0.001), readmission (mean 7.0 vs. 6.6 days, p = 0.05), and total hospital charge were higher for hypothyroid patients ($137,742 vs. $119,831, p < 0.001).

CONCLUSION

Hypothyroidism is an independent risk factor for 30-day readmission following head and neck cancer resection. Furthermore, hypothyroid patients are more likely to be readmitted for wound complications, infection, and electrolyte imbalance. Targeted interventions should be considered for hypothyroid patients to decrease readmission rates and associated patient morbidity, potentially leading to earlier initiation of adjuvant treatment.

LEVEL OF EVIDENCE

3 Laryngoscope, 133:2988-2998, 2023.

Machine Learning on Medicare Claims Poorly Predicts the Individual Risk of 30-Day Unplanned Readmission After Total Joint Arthroplasty, Yet Uncovers Interesting Population-level Associations With Annual Procedure Volumes

BACKGROUND

Unplanned hospital readmissions after total joint arthroplasty (TJA) represent potentially serious adverse events and remain a critical measure of hospital quality. Predicting the risk of readmission after TJA may provide patients and clinicians with valuable information for preoperative decision-making.

QUESTIONS/PURPOSES

(1) Can nonlinear machine-learning models integrating preoperatively available patient, surgeon, hospital, and county-level information predict 30-day unplanned hospital readmissions in a large cohort of nationwide Medicare beneficiaries undergoing TJA? (2) Which predictors are the most important in predicting 30-day unplanned hospital readmissions? (3) What specific information regarding population-level associations can we obtain from interpreting partial dependency plots (plots describing, given our modeling choice, the potentially nonlinear shape of associations between predictors and readmissions) of the most important predictors of 30-day readmission?

METHODS

National Medicare claims data (chosen because this database represents a large proportion of patients undergoing TJA annually) were analyzed for patients undergoing inpatient TJA between October 2016 and September 2018. A total of 679,041 TJAs (239,391 THAs [61.3% women, 91.9% White, 52.6% between 70 and 79 years old] and 439,650 TKAs [63.3% women, 90% White, 55.2% between 70 and 79 years old]) were included. Model features included demographics, county-level social determinants of health, prior-year (365-day) hospital and surgeon TJA procedure volumes, and clinical classification software-refined diagnosis and procedure categories summarizing each patient's Medicare claims 365 days before TJA. Machine-learning models, namely generalized additive models with pairwise interactions (prediction models consisting of both univariate predictions and pairwise interaction terms that allow for nonlinear effects), were trained and evaluated for predictive performance using area under the receiver operating characteristic (AUROC; 1.0 = perfect discrimination, 0.5 = no better than random chance) and precision-recall curves (AUPRC; equivalent to the average positive predictive value, which does not give credit for guessing "no readmission" when this is true most of the time, interpretable relative to the base rate of readmissions) on two holdout samples. All admissions (except the last 2 months' worth) were collected and split randomly 80%/20%. The training cohort was formed with the random 80% sample, which was downsampled (so it included all readmissions and a random, equal number of nonreadmissions). The random 20% sample served as the first test cohort ("random holdout"). The last 2 months of admissions (originally held aside) served as the second test cohort ("2-month holdout"). Finally, feature importances (the degree to which each variable contributed to the predictions) and partial dependency plots were investigated to answer the second and third research questions.

RESULTS

For the random holdout sample, model performance values in terms of AUROC and AUPRC were 0.65 and 0.087, respectively, for THA and 0.66 and 0.077, respectively, for TKA. For the 2-month holdout sample, these numbers were 0.66 and 0.087 and 0.65 and 0.075. Thus, our nonlinear models incorporating a wide variety of preoperative features from Medicare claims data could not well-predict the individual likelihood of readmissions (that is, the models performed poorly and are not appropriate for clinical use). The most predictive features (in terms of mean absolute scores) and their partial dependency graphs still confer information about population-level associations with increased risk of readmission, namely with older patient age, low prior 365-day surgeon and hospital TJA procedure volumes, being a man, patient history of cardiac diagnoses and lack of oncologic diagnoses, and higher county-level rates of hospitalizations for ambulatory-care sensitive conditions. Further inspection of partial dependency plots revealed nonlinear population-level associations specifically for surgeon and hospital procedure volumes. The readmission risk for THA and TKA decreased as surgeons performed more procedures in the prior 365 days, up to approximately 75 TJAs (odds ratio [OR] = 1.2 for TKA and 1.3 for THA), but no further risk reduction was observed for higher annual surgeon procedure volumes. For THA, the readmission risk decreased as hospitals performed more procedures, up to approximately 600 TJAs (OR = 1.2), but no further risk reduction was observed for higher annual hospital procedure volumes.

CONCLUSION

A large dataset of Medicare claims and machine learning were inadequate to provide a clinically useful individual prediction model for 30-day unplanned readmissions after TKA or THA, suggesting that other factors that are not routinely collected in claims databases are needed for predicting readmissions. Nonlinear population-level associations between low surgeon and hospital procedure volumes and increased readmission risk were identified, including specific volume thresholds above which the readmission risk no longer decreases, which may still be indirectly clinically useful in guiding policy as well as patient decision-making when selecting a hospital or surgeon for treatment.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Impact of HRRP Policy on 30-day and 90-day Readmissions in Patients with Acute Myocardial Infarction: A Ten-Year Trend from the National readmissions database

BACKGROUND

Hospital readmissions following acute myocardial infarction (AMI) pose a significant economic burden on health care utilization. The hospital readmission reduction program (HRRP) enacted in 2012 focused on reducing readmissions by penalizing CMS Medicare hospitals. We aim to assess the trend of readmissions after AMI hospitalization between 2010-2019 and assess the impact of HRRP.

METHODS

The NRD was queried to identify AMI hospitalizations between 2010 and 2019. In the primary analysis, trends of 30-day and 90-day all-cause and AMI specific readmissions were assessed from 2010-2019. In the secondary analysis, trend of readmission mean length of stay (LOS) and mean adjusted total cost were calculated.

RESULTS

There were a total of 592,015 30-day readmissions and 787,008 90-day readmissions after an index hospitalization for AMI between 2010-2019. The rates of 30-day and 90-day all-cause readmissions decreased significantly from 12.8% to 11.6%, (p=0.0001) and 20.6 to 18.8, p(=0.0001) respectively in the decade under study. With regards to HRRP policy intervals, the pre-HRRP period from 2010-2012 showed a downward trend in all-cause readmission (12.8% to 11.6%) and similarly a downward trend was also seen in the post HRRP period (2013-2015:11.0%-8.2%, 2016-2019-12.3-11.7%). Secondary analysis showed a trend towards increase in mean LOS (4.54 to 4.96 days, P=0.0001) and adjusted total cost ($13,449 to $16,938) in 30-day all-cause readmission for AMI in the decade under review.

CONCLUSION

In our NRD-based analysis of patients readmitted to hospitals within 30-days and 90-days after AMI, the rate of all-cause readmissions down trended from 2010 to 2019.

Analysis of Rates, Causes, and Risk Factors for 90-Day Readmission After Surgery for Large Hiatal Hernia: A Two-Center Study

Background: Hospital readmissions have become a more examined indicator of surgical care delivery and quality. There is scarcity of data in the literature on the rate, risk factors, and most common reasons of readmission following major hiatal hernia surgery. The primary endpoint was 90-day readmission after surgery for large hiatal hernia. Secondary endpoint was to examine which characteristics related with a higher risk of readmission. Methods: A retrospective review of two distinct institutional databases was performed for patients who had surgery for a large hiatal hernia between January 2012 and December 2019. Demographic, perioperative, and outpatient data were collected from the medical record. Results: A total of 71 patients met the inclusion criteria, most of them suffering from a type III hernia (66.2%). Mean operative time was 146 (±56.5) minutes and median length of stay (LOS) was 6 days (interquartile range = 3). The overall morbidity was 21.1% and the in-hospital mortality was 1.4%. The 30- and 90-day readmission rates were 7% and 8.5%, respectively. The mean time to readmission was 14.3 (±15.6) days. The reasons for 90-day hospital readmission were dysphagia (50%), pneumonia (16.7%), congestive heart failure (16.7%), and bowel obstruction (16.7%). Grade of esophagitis ≥2, presence of Barrett's esophagus, and LOS longer than 8 days were significant risk factors for unplanned readmission within 90 days. Conclusion: We observed that about 6 out of 71 patients who had surgery readmitted within 90 days (8.5%). Readmissions were most often linked to esophagitis ≥2, presence of Barrett's esophagus, and LOS longer than 8 days. These findings point to the necessity for focused treatments before, during, and after hospitalization to decrease morbidity and extra costs in this high-risk population.

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

IMPORTANCE

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

OBJECTIVE

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

DATA SOURCES

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

FINDINGS

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

CONCLUSIONS AND RELEVANCE

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

Characteristics and Outcomes of Pediatric Nonindex Readmission: Evidence From Florida Hospitals

OBJECTIVES

Increasing pediatric care regionalization may inadvertently fragment care if children are readmitted to a different (nonindex) hospital rather than the discharge (index) hospital. Therefore, this study aimed to assess trends in pediatric nonindex readmission rates, examine the risk factors, and determine if this destination difference affects readmission outcomes.

METHODS

In this retrospective cohort study, we use the Healthcare Cost and Utilization Project State Inpatient Database to include pediatric (0 to 18 years) admissions from 2010 to 2017 across Florida hospitals. Risk factors of nonindex readmissions were identified by using logistic regression analyses. The differences in outcomes between index versus nonindex readmissions were compared for in-hospital mortality, morbidity, hospital cost, length of stay, against medical advice discharges, and subsequent hospital visits by using generalized linear regression models.

RESULTS

Among 41 107 total identified readmissions, 5585 (13.6%) were readmitted to nonindex hospitals. Adjusted nonindex readmission rate increased from 13.3% in 2010% to 15.4% in 2017. Patients in the nonindex readmissions group were more likely to be adolescents, live in poor neighborhoods, have higher comorbidity scores, travel longer distances, and be discharged at the postacute facility. After risk adjusting, no difference in in-hospital mortality was found, but morbidity was 13% higher, and following unplanned emergency department visits were 28% higher among patients with nonindex readmissions. Length of stay, hospital costs, and against medical advice discharges were also significantly higher for nonindex readmissions.

CONCLUSIONS

A substantial proportion of children experienced nonindex readmissions and relatively poorer health outcomes compared with index readmission. Targeted strategies for improving continuity of care are necessary to improve readmission outcomes.

Thirty-day unplanned readmission in hospitalised asthma patients in the USA

INTRODUCTION

Hospital quality improvement and hospital performance are commonly evaluated using parameters such as average length of stay (LOS), patient safety measures and rates of hospital readmission. Thirty-day readmission (30-DR) rates are widely used as a quality indicator and a quantifiable metric for hospitals since patients are often readmitted for the exacerbation of conditions from index admission. The quality of patient education and postdischarge care can influence readmission rates. We report the 30-DR rates of patients with asthma using a national dataset for the year 2013.

OBJECTIVES

The aim of our study was to assess the 30- day readmission (30-DR) rate as well as, the causes and predictors of readmissions.

STUDY DESIGNS/METHODS

Using the Nationwide Readmission Database (NRD) (2013), we identified primary discharge diagnoses of asthma by using International Classification of Diseases, Ninth Revision, Clinical Modification code '493'. Categorical and continuous variables were assessed by a χ² test and a Student's t-test, respectively. The independent predictors of unplanned 30-DR were detected by multivariate analysis. We used sampling weights, which are provided in the NRD, to generate the national estimates.

RESULTS

There were 130 490 (weighted N=311 173) inpatient asthma admissions during 2013. The overall 30-DR for asthma was 11.9%. The associated factors for 30-DR were age 45-84 years (40.32% vs 29.05%; p<0.001), enrolment in Medicare (49.33% vs 30.61% p<0.001), extended LOS (mean, 4.40±0.06 vs 3.25±0.04 days; p<0.001), higher mean cost (US$8593.91 vs US$6741.31; p<0.001) and higher disposition against medical advice (DAMA) (4.14% vs 1.51%; p<0.001). The factors that increased the chance of 30-DR were advanced age (≥45-64 vs ≤17 years; OR 4.61, 95% CI 4.04 to 5.27, p<0.0001), male sex (OR 1.19, 95% CI 1.13 to 1.26, p<0.0001), a higher Charlson Comorbidity Index (CCI) (OR 1.16, 95% CI 1.14 to 1.18, p<0.0001), DAMA (OR 2.32, 95% CI 2.08 to 2.59, p<0.0001), non-compliance with medication (OR 1.34, 95% CI 1.24 to 1.46, p<0.0001), post-traumatic stress disorder (OR 1.48, 95% CI 1.22 to 1.79, p<0.0001), alcohol use (OR 1.45, 95% CI 1.27 to 1.65, p<0.0001), gastro-oesophageal reflux disease (OR 1.20, 95% CI 1.14 to 1.27, p<0.0001), obstructive sleep apnoea (OR 1.11, 95% CI 1.03 to 1.18, p<0.0042) and hypertension (OR 1.11, 95% CI 1.06 to 1.17, p<0.0001).

CONCLUSIONS

We found that the overall 30-DR rate for asthma was 11.9% all-cause readmission. Major causes of 30-DR were asthma exacerbation (36.74%), chronic obstructive pulmonary disease (11.47%), respiratory failure (6.46%), non-specific pneumonia (6.19%), septicaemia (3.61%) and congestive heart failure (3.32%). One-fourth of the revisits occurred in the first week, while half of the revisits took place in the first 2 weeks. Education regarding illness and the importance of medicine compliance could play a significant role in preventing asthma-related readmission.

Rehospitalization for pneumonia after first pneumonia admission: Incidence and predictors in a population-based cohort study

Background and objectives

Hospital readmissions are a frequent complication of pneumonia. Most data regarding readmissions are obtained from the United States, whereas few data are available from the European healthcare utilization (HCU) systems. In a large cohort of Italian patients with a previous hospitalization for pneumonia, our aim was to evaluate the incidence and predictors of early readmissions due to pneumonia.

Methods

This is a observational retrospective, population based, cohort study. Data were retrieved from the HCU databases of the Italian Lombardy region. 203,768 patients were hospitalized for pneumonia between 2003 and 2012. The outcome was the first rehospitalization for pneumonia. The patients were followed up after the index hospital admission to estimate the hazard ratio, and relative 95% confidence interval, of the outcome associated with the risk factors that we had identified.

Results

7,275 patients (3.6%) had an early pneumonia readmission. Male gender, age ≥70 years, length of stay of the first admission and a higher burden of comorbidities were significantly associated with the outcome. Chronic use of antidepressants, antiarrhythmics, glucocorticoids and drugs for obstructive airway diseases were also more frequently prescribed in patients requiring rehospitalization. Previous use of inhaled broncodilators, including both beta2-agonists and anticholinergics, but not inhaled steroids, were associated with an increased risk of hospital readmission.

Conclusions

Frail elderly patients with multiple comorbidities and complex drug regimens were at higher risk of early rehospitalization and, thus, may require closer follow-up and prevention strategies.

Composite Outcomes of Mortality and Readmission in Patients with Heart Failure: Retrospective Review of Administrative Datasets

Background

Controlling the quality of care through readmissions and mortality for patients with heart failure (HF) is a national priority for healthcare regulators in developed countries. In this longitudinal cohort study, using administrative data such as hospital discharge forms (HDFs), emergency departments (EDs) accesses, and vital statistics, we test new covariates for predicting mortality and readmissions of patients hospitalized for HF and discuss the use of combined outcome as an alternative.

Methods

Logistic models, with a stepwise selection method, were estimated on 70% of the sample and validated on the remaining 30% to evaluate 30-day mortality, 30-day readmissions, and the combined outcome. We followed an extraction method for any-cause mortality and unplanned readmission within 30 days after incident HF hospitalization. Data on patient admission and previous history were extracted by HDFs and ED dataset.

Results

Our principal findings demonstrate that the model’s discriminant ability is consistent with literature both for mortality (AUC=0.738, CI (0.729–0.748)) and readmissions (AUC=0.578, CI (0.562–0.594)). Additionally, the discriminant ability of the composite outcome model is satisfactory (AUC=0.675, CI (0.666–0.684)).

Conclusion

Hospitalization characteristics and patient history introduced in the logistic models do not improve their discriminant ability. The composite outcome prediction is led more by mortality than readmission, without improvements for the comprehension of the readmission phenomenon.

Improving clinical outcomes and patient satisfaction among patients with coronary artery disease: an example of enhancing regional integration between a cardiac centre and a referring hospital

BACKGROUND

Value-based healthcare (VBHC) is a promising strategy to increase patient value. For a successful implementation of VBHC, intensive collaborations between organizations and integrated care delivery systems are key conditions. Our aim was to evaluate the effects of a pilot study regarding enhancing regional integration between a cardiac centre and a referring hospital on patient-relevant clinical outcomes and patient satisfaction.

METHODS

The study population consisted of a sample of patients treated for coronary artery disease by use of a coronary artery bypass graft (CABG) or a percutaneous coronary intervention between 2011 and 2016. Since 2013, the two hospitals have implemented different interventions to improve clinical outcomes and the degree of patient satisfaction, e.g. improvement of communication, increased consultant capacity, introduction of outpatient clinic for complex patients, and improved guideline adherence. To identify intervention effects, logistic regression analyses were conducted. Patients' initial conditions, like demographics and health status, were included in the model as predictors. Clinical data extracted from the electronic health records and the hospitals' cardiac databases as well as survey-based data were used.

RESULTS

Our findings indicate a non-significant increase of event-free survival of patients treated for coronary artery disease between 2014 and 2016 compared to patients treated between 2011 and 2013 (97.4% vs. 96.7% respectively). This non-significant improvement over time has led to significant better outcomes for patients referred from the study referring hospital compared to patients referred from other hospitals. The level of patient satisfaction (response rate 32.2%; 216 out of 669) was improved and reached statistically significant higher scores regarding patient information and education (p = .013), quality of care (p = .007), hospital admission and stay (p = .032), personal contact with the physician (p = .024), and total impression (p = .007).

CONCLUSIONS

This study shows a promising effect of regional integration. An intensified collaboration in the care chain, organized in a structured manner between a cardiac centre and a referring hospital and aiming at high quality, resulted in successful improvement of clinical outcomes and degree of patient satisfaction. The applied method may be used as a starting point of regional integration with other referring hospitals. We encourage others to organize the whole care chain to continuously improve patient-relevant outcomes and patient satisfaction.

TRIAL REGISTRATION

ISRCTN11311830. Registered 01 October 2018 (retrospectively registered).

Doing well by doing good: Evaluating the influence of patient safety performance on hospital financial outcomes

BACKGROUND

As financial pressures on hospitals increase because of changing reimbursement structures and heightened focus on quality and value, the association between patient safety performance and financial outcomes remains unclear.

PURPOSE

The purpose of this study is to investigate if hospitals with higher patient safety performance are associated with higher levels of profitability than those with lower safety performance.

METHODOLOGY/APPROACH

Using multinomial logistic regression, we analyzed data from the spring 2014 Leapfrog Hospital Safety Score and the 2014 American Hospital Association to determine the association between Leapfrog Hospital Safety Score performance and three dimensions of organizational profitability: operating margin, net patient revenue, and operating income.

RESULTS

Our findings suggest that improved hospital safety scores are associated with a relative risk of being in the top versus bottom quartile of financial performance: 5.41 times greater (p < .001) for operating margin, 10.98 times greater (p < .001) for net patient revenue, and 4.03 times greater (p < .001) for operating income.

PRACTICE IMPLICATIONS

Our findings suggest that improved patient safety performance, as evaluated within the Leapfrog Hospital Safety Score, is associated with improved financial performance at the hospital level. Targeted focus on patient safety may allow hospitals to improve financial performance, maximize scarce resources, and generate additional capital to continue to positively evolve care.

Evaluation of discharge instructions among hospitalized Lebanese patients

Background:

Hospital readmissions are considered as the primary indicator of insufficient quality of care and are responsible of increasing annual medical costs by billions of dollars. Different factors tend to reduce readmissions, particularly instructions at discharge.

Objectives:

Our study objective was to evaluate discharge instructions given to hospitalized Lebanese patients and associated factors.

Methods:

Two hundred patients, aged between 21 and 79 years and admitted to the emergency department, were recruited from a Lebanese university hospital. Discharge instructions were evaluated by a face-to-face interview to fill a questionnaire with the patients immediately after their final contact with the physician or nurse in charge. We mainly focused on medications instructions and created two scores related to “instructions given” and “instructions appropriate” to later conduct bivariate analysis.

Results:

We found that discharge instructions were not completely given to all our study population. The degree of appropriateness fluctuated between 25% and 100%. The instructor in charge of giving discharge instructions had its significant influence on medication instructions given (p=0.014). In addition, the instructor and his experience influenced the degree of “appropriate instructions”. In fact, our study showed that despite being capable of giving good medication advice, nurses’ instructions were significantly less effective in comparison with physicians, fellows and residents. However, nurses gave 52% of the instructions, which questions the quality of those instructions.

Conclusions:

In conclusion, our observational study showed that in a Lebanese university hospital, patients’ understanding of discharge instructions is poor. Careful attention should be drawn to other hospitals as well and interventions should be considered to improve instructions quality and limit later complications and readmissions. The intervention of clinical pharmacists and their medication-related advice might be crucial in order to improve instructions’ quality.

Quality Measures in Postmastectomy Breast Reconstruction: Identifying Metrics to Improve Care

BACKGROUND

Specific measures tailored to the properties of individual procedures will ensure the appropriate evaluation of quality. Because postmastectomy breast reconstruction (PMBR) is becoming increasingly common, a review of the literature is timely to identify potential breast reconstruction-specific measures that can be applied by institutions and national healthcare organizations to improve quality.

METHODS

We searched PubMed and Embase for studies examining the quality of care for patients undergoing PMBR. Data extracted from the articles include basic study characteristics, the number of quality metrics, type of quality metric (defined by Donabedian model), and the domain of quality (defined by the National Academy of Medicine).

RESULTS

A total of 2,158 articles were identified in the initial search, and 440 studies were included for data extraction. The most common type of quality measure was outcome measures (91%), and the least common measure was structure measures (1%). The most common metrics were operative time (41%), hospital type (28%), and aspects of the patient-provider interactions (20%). Additionally, we found that timeliness and equity were least common among the 6 National Academy of Medicine domains.

CONCLUSIONS

We identified metrics utilized in the PMBR, some of which can be further investigated through high-level evidence studies and incorporated into policy. Because many factors influence surgical outcomes and breast reconstruction is driven by patient preferences, an inclusion of structure, process, and outcome metrics will help improve care for this patient population. Moreover, nonpunitive initiatives, specifically quality collaboratives, may provide an avenue to improve care quality without compromising patient safety.

Hospital physicians' views on discharge and readmission processes: a qualitative study from Norway

OBJECTIVES

To explore hospital physicians' views on readmission and discharge processes in the interface between hospitals and municipalities.

DESIGN

Qualitative case study.

SETTING

The Norwegian healthcare system.

PARTICIPANTS

Fifteen hospital physicians (residents and consultants) from one hospital, involved in the treatment and discharge of patients.

RESULTS

The results of this study showed that patients were being discharged earlier, with more complex medical conditions, than they had been previously, and that discharges sometimes were perceived as premature. Insufficient capacity at the hospital resulted in pressure to discharge patients, but the primary healthcare service of the area was not always able to assume care of these patients. Communication between levels of the healthcare service was limited. The hospital stay summary was the most important, and sometimes only, form of communication between levels. The discharge process was described as complicated and was affected by healthcare personnel, by patients themselves and by aspects of the primary healthcare service. Early hospital discharges, poor communication between healthcare services and inadequacies in the discharge process were perceived to affect hospital readmissions.

CONCLUSION

The results of this study provide a better understanding of hospital physicians' views on the discharge and hospital readmission processes in the interface between the hospital and the primary healthcare service. The study also identifies discrepancies in governmental requirements, reform regulations and current practices in municipalities and hospitals.

Thirty-day readmissions in aneurysmal subarachnoid hemorrhage: A good metric for hospital quality?

Thirty-day readmission rates has been increasingly used by clinicians, hospital administrators, and policy makers as a metric for the quality of care. However, the 30-day readmission rates may be affected by other factors intrinsic to the patient and may not be a good measure of the quality of care provided by the hospital. In this review, we examined the quality of the 30-day readmissions rate as a quality metric for the quality of care provided to patients with aneurysmal subarachnoid hemorrhage (SAH). It has been shown that in this patient population, 30-day readmission rate primarily captures values, such as the number of comorbidities, disease severity, and discharge dispositions. There is little association between SAH 30-day readmission rates and mortality. However, 30-day readmissions may be reduced by increasing early discharge surveillance, providing readmission reduction programs to patients discharged to medical facilities as well as to home, and identifying patients most at risk for readmission.

Predictors of 30-Day Readmission After Total Knee Arthroplasty: Analysis of 566,323 Procedures in the United Kingdom

BACKGROUND

All-cause 30-day readmission after total knee arthroplasty (TKA) is currently used as a measure of hospital performance in the United States and elsewhere. Readmissions from surgical causes may more accurately reflect preventability and costs. However, little is known about whether predictors of each type of readmission differ.

METHODS

All primary TKAs recorded in England's National Health Service administrative database from 2006 to 2015 were included. Multilevel logistic regression analysis was used to describe the effects of patient-related factors on 30-day readmission risk using 3 different readmission metrics: all-cause, surgical (defined using International Classification of Disease-10 primary admission diagnoses), and those resulting in return to theater (RTT).

RESULTS

In total, 566,323 procedures were recorded. The comorbidity with the highest odds ratio (OR) for all types of readmission was psychoses (RTT OR 2.52, P < .001). Obesity was a strong independent predictor of RTT (OR 1.36, P < .001) and had the highest population attributable fraction of any comorbidity (4.7%). Unicompartmental arthroplasty was associated with a significantly lower risk of all types of readmission when compared with TKA, with the effect being most pronounced for surgical readmission (OR 0.66, P < .001). RTT in the index episode increased the risk of RTT readmission (OR 2.80, P < .001), as did any emergency admission to hospital in the preceding 12 months (for >2 emergency admissions, all-cause OR 2.38, P < .001). Length of stay either more than or less than 2 days was associated with an increased risk of all-cause and surgical readmission but not RTT readmission.

CONCLUSION

Patient-related predictors of surgical and RTT readmission following TKA differ from those for all-cause readmission, but only the latter metric is in widespread use.

Nursing home leaders' and nurses' experiences of resources, staffing and competence levels and the relation to hospital readmissions - a case study

Background

Thirty-day hospital readmissions represent an international challenge leading to increased prevalence of adverse events, reduced quality of care and pressure on healthcare service’s resources and finances. There is a need for a broader understanding of hospital readmissions, how they manifest, and how resources in the primary healthcare service may affect hospital readmissions. The aim of the study was to examine how nurses and nursing home leaders experienced the resource situation, staffing and competence level in municipal healthcare services, and if and how they experienced these factors to influence hospital readmissions.

Method

The study was conducted as a comparative case study of two municipalities affiliated with the same hospital, chosen for historical differences in readmission rates. Nurses and leaders from four nursing homes participated in focus groups and interviews. Data were analyzed within and across cases.

Results

The analysis resulted in four common themes, with some variation in each municipality, describing nurses’ and leaders’ experience of the nursing home resource situation, staffing level and competence and their perception of factors affecting hospital readmissions. The nursing home patients were described as becoming increasingly complex with a subsequent need for increased nurse competence. There was variation in competence and staffing between nursing homes, but capacity building was an overall focus. Economic limitations and attempts at saving through cost-cutting were present, but not perceived as affecting patient care and the availability of medical equipment. Several factors such as nurse competence and staffing, physician coverage, and adequate communication and documentation, were recognized as factors affecting hospital readmissions across the municipalities.

Conclusion

Several factors related to nurses’ and leaders’ experience of the resource situation, staffing and competence level were suggested to affect hospital readmissions and the municipalities were similar in their answers regarding these factors. Patients were perceived as more complex with higher patient mortality forcing long-term nursing homes to shift towards an acute care or palliative function, and short-term nursing homes to function as “small hospitals”, requiring higher nurse competence. Staffing, competence and physician coverage did not seem to have adjusted to the new patient group in some nursing homes.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3769-3) contains supplementary material, which is available to authorized users.

Determining 30-day readmission risk for heart failure patients: the Readmission After Heart Failure scale

Background

Chronic heart failure (CHF), which affects >5 million Americans, accounts for >1 million hospitalizations annually. As a part of the Hospital Readmission Reduction Program, the Affordable Care Act requires that the Centers for Medicare and Medicaid Services reduce payments to hospitals with excess readmissions. This study sought to develop a scale that reliably predicts readmission rates among patients with CHF.

Methods

The State Inpatient Database (2006–2011) was utilized, and discharge data including demographic and clinical characteristics on 642,448 patients with CHF from California and New York (derivation cohort) and 365,359 patients with CHF from Florida and Washington (validation cohort) were extracted. The Readmission After Heart Failure (RAHF) scale was developed to predict readmission risk.

Results

The 30-day readmission rates were 9.42 and 9.17% (derivation and validation cohorts, respectively). Age <65 years, male gender, first income quartile, African American race, race other than African American or Caucasian, Medicare, Medicaid, self-pay/no insurance, drug abuse, renal failure, chronic pulmonary disorder, diabetes, depression, and fluid and electrolyte disorder were associated with higher readmission risk after hospitalization for CHF. The RAHF scale was created and explained the 95% of readmission variability within the validation cohort. The RAHF scale was then used to define the following three levels of risk for readmission: low (RAHF score <12; 7.58% readmission rate), moderate (RAHF score 12–15; 9.78% readmission rate), and high (RAHF score >15; 12.04% readmission rate). The relative risk of readmission was 1.67 for the high-risk group compared with the low-risk group.

Conclusion

The RAHF scale reliably predicts a patient’s 30-day CHF readmission risk based on demographic and clinical factors present upon initial admission. By risk-stratifying patients, using models such as the RAHF scale, strategies tailored to each patient can be implemented to improve patient outcomes and reduce health care costs.

Reducing excess hospital readmissions: Does destination matter?

Reducing excess hospital readmissions has become a high policy priority to lower health care spending and improve quality. The Affordable Care Act (ACA) penalizes hospitals with higher-than-expected readmission rates. This study tracks patient-level admissions and readmissions to Florida hospitals from 2006 to 2014 to examine whether the ACA has reduced readmission effectively. We compare not only the change in readmissions in targeted conditions to that in non-targeted conditions, but also changes in sites of readmission over time and differences in outcomes based on destination of readmission. We find that the drop in readmissions is largely owing to the decline in readmissions to the original hospital where they received operations or treatments (i.e., the index hospital). Patients readmitted into a different hospital experienced longer hospital stays. The results suggest that the reduction in readmission is likely achieved via both quality improvement and strategic admission behavior.

Did case-based payment influence surgical readmission rates in France? A retrospective study

OBJECTIVES

To determine whether implementation of a case-based payment system changed all-cause readmission rates in the 30 days following discharge after surgery, we analysed all surgical procedures performed in all hospitals in France before (2002-2004), during (2005-2008) and after (2009-2012) its implementation.

SETTING

Our study is based on claims data for all surgical procedures performed in all acute care hospitals with >300 surgical admissions per year (740 hospitals) in France over 11 years (2002-2012; n=51.6 million admissions).

INTERVENTIONS

We analysed all-cause 30-day readmission rates after surgery using a logistic regression model and an interrupted time series analysis.

RESULTS

The overall 30-day all-cause readmission rate following discharge after surgery increased from 8.8% to 10.0% (P<0.001) for the public sector and from 5.9% to 8.6% (P<0.001) for the private sector. Interrupted time series models revealed a significant linear increase in readmission rates over the study period in all types of hospitals. However, the implementation of case-based payment was only associated with a significant increase in rehospitalisation rates for private hospitals (P<0.001).

CONCLUSION

In France, the increase in the readmission rate appears to be relatively steady in both the private and public sector but appears not to have been affected by the introduction of a case-based payment system after accounting for changes in care practices in the public sector.

Predicting the Risk of Readmission in Pneumonia. A Systematic Review of Model Performance

RATIONALE

Predicting which patients are at highest risk for readmission after hospitalization for pneumonia could enable hospitals to proactively reallocate scarce resources to reduce 30-day readmissions.

OBJECTIVES

To synthesize the available literature on readmission risk prediction models for adults who are hospitalized because of pneumonia and describe their performance.

METHODS

We systematically searched Ovid MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature databases from inception through July 2015. We included studies of adults discharged with pneumonia that developed or validated a model that predicted hospital readmission. Two independent reviewers abstracted data and assessed the risk of bias.

MEASUREMENTS AND MAIN RESULTS

Of 992 citations reviewed, 7 studies met inclusion criteria, which included 11 unique risk prediction models. All-cause 30-day readmission rates ranged from 11.8 to 20.8% (median, 17.3%). Model discrimination (C statistic) ranged from 0.59 to 0.77 (median, 0.63) with the highest-quality, best-validated model, the Centers for Medicare and Medicaid Services Pneumonia Administrative Model performing modestly (C Statistic of 0.63 in 4 separate multicenter cohorts). The best performing model (C statistic of 0.77) was a single-site study that lacked internal validation. The models had adequate calibration, with patients predicted as high risk for readmission having a higher average observed readmission rate than those predicted to be low risk. None of the studies included pneumonia illness severity scores, and only one included measures of in-hospital clinical trajectory and stability on discharge, robust predictors of readmission.

CONCLUSIONS

We found a limited number of validated pneumonia-specific readmission models, and their predictive ability was modest. To improve predictive accuracy, future models should include measures of pneumonia illness severity, hospital complications, and stability on discharge.

Factors Associated With 30-Day Readmission After Primary Total Hip Arthroplasty: Analysis of 514 455 Procedures in the UK National Health Service

Importance

Thirty-day readmission to hospital after total hip arthroplasty (THA) has significant direct costs and is used as a marker of hospital performance. All-cause readmission is the only metric in current use, and risk factors for surgical readmission and those resulting in return to theater (RTT) are poorly understood.

Objective

To determine whether patient-related predictors of all-cause, surgical, and RTT readmission after THA differ and which predictors are most significant.

Design, Setting, and Participants

Analysis of all primary THAs recorded in the National Health Service (NHS) Hospital Episode Statistics database from 2006 to 2015. The effect of patient-related factors on 30-day readmission risk was evaluated by multilevel logistic regression analysis. The analysis comprised all acute NHS hospitals in England and all patients receiving primary THA.

Main Outcomes and Measures

Thirty-day readmission rate for all-cause, surgical (defined using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision primary admission diagnoses), and readmissions resulting in RTT.

Results

Across all hospitals, 514 455 procedures were recorded. Seventy-nine percent of patients were older than 60 years, 40.3% were men, and 59.7% were women. There were 30 489 all-cause readmissions (5.9%), 16 499 surgical readmissions (3.2%), and 4286 RTT readmissions (0.8%); 54.1% of readmissions were for surgical causes. Comorbidities with the highest odds ratios (ORs) of RTT included those likely to affect patient behavior: drug abuse (OR, 2.22; 95% CI, 1.34-3.67; P = .002), psychoses (OR, 1.83; 95% CI, 1.16-2.87; P = .009), dementia (OR, 1.57; 95% CI, 1.11-2.22; P = .01), and depression (OR, 1.52; 95% CI, 1.31-1.76; P < .001). Obesity had a strong independent association with RTT (OR, 1.46; 95% CI, 4.45-6.43; P < .001), with one of the highest population attributable fractions of the comorbidities (3.4%). Return to theater in the index episode was associated with a significantly increased risk of RTT readmission (OR, 5.35; 95% CI, 4.45-6.43; P < .001). Emergency readmission to the hospital in the preceding 12 months increased the risk of readmission significantly, with the association being most pronounced for all-cause readmission (for >2 emergency readmissions, OR, 2.33; 95% CI, 2.11-2.57; P < .001). Hip resurfacing was associated with a lower risk of RTT when compared with cemented implants (OR, 0.69; 95% CI, 0.54-0.88; P = .002) but for other types of readmission, implant type had no significant association with readmission risk. Increasing age and length of stay were strongly associated with all-cause readmission.

Conclusions and Relevance

Many patient-related risk factors for surgical and RTT readmission differ from those for all-cause readmission despite the latter being the only measure in widespread use. Clinicians and policy makers should consider these alternative readmission metrics in strategies for risk reduction and cost savings.

National estimates of 30-day readmissions among children hospitalized for asthma in the United States

OBJECTIVE

Previous single-center studies have reported that up to 40% of children hospitalized for asthma will be readmitted. The study objectives are to investigate the prevalence and timing of 30-day readmissions in children hospitalized with asthma, and to identify factors associated with 30-day readmissions.

METHODS

Data (n = 12,842) for children aged 6-18 years hospitalized for asthma were obtained from the 2013 Nationwide Readmission Database (NRD). The primary study outcome was time to readmission within 30 days after discharge attributable to any cause. Several predictors associated with the risk of admission were included: patient (age, sex, median household income, insurance type, county location, and pediatric chronic complex condition), admission (type, day, emergency services utilization, length of stay (LOS), and discharge disposition), and hospital (ownership, bed size, and teaching status). Cox's proportional hazards model was used to identify predictors.

RESULTS

Of 12,842 asthma-related index hospitalizations, 2.5% were readmitted within 30-days post-discharge. Time to event models identified significantly higher risk of readmission among asthmatic children aged 12-18 years, those who resided in micropolitan counties, those with >4-days LOS during index hospitalization, those who were hospitalized in an urban hospital, who had unfavorable discharge (hazard ratio 2.53, 95% confidence interval 1.33-4.79), and those who were diagnosed with a pediatric complex chronic condition, respectively, than children in respective referent categories.

CONCLUSION

A multi-dimensional approach including effective asthma discharge action plans and follow-up processes, home-based asthma education, and neighborhood/community-level efforts to address disparities should be integrated into the routine clinical care of asthma children.

How to identify potentially preventable readmissions by classifying them using a national administrative database

Importance

Hospital readmissions are being used increasingly as an indicator of quality of care. However, it remains difficult to identify potentially preventable readmissions.

Objectives

To evaluate the identification of potentially preventable hospital readmissions by using a classification of readmissions based on administrative data.

Design and setting

We classified a random sample of 455 readmissions to a Dutch university hospital in 2014 using administrative data. We compared these results to a classification based on reviewing the medical records of these readmissions to evaluate the accuracy of classification by administrative data.

Main outcome measures

Frequencies of categories of readmissions based on reviewing records versus those based on administrative data. Cohen's kappa for the agreement between both methods. The sensitivity and specificity of the identification of potentially preventable readmissions with classification by administrative data.

Results

Reviewing the medical records of acute readmissions resulted in 28.5% of the records being classified as potentially preventable. With administrative data this was 44.1%. There was slight agreement between both methods: ƙ 0.08 (95% CI: 0.02-0.15, P < 0.05). The sensitivity of the classification of potentially preventable readmissions by administrative data was 63.1% and the specificity was 63.5%.

Conclusions

This explorative study demonstrated differences between categorizing readmissions based on reviewing records compared to using administrative data. Therefore, this tool can only be used in practice with great caution. It is not suitable for penalizing hospitals based on their number of potentially preventable readmissions. However, hospitals might use this classification as a screening tool to identify potentially preventable readmissions more efficiently.

Cardiology Consultation in the Emergency Department Reduces Re-hospitalizations for Low-Socioeconomic Patients with Acute Decompensated Heart Failure

BACKGROUND

Re-hospitalization after discharge for acute decompensated heart failure is a common problem. Low-socioeconomic urban patients suffer high rates of re-hospitalization and often over-utilize the emergency department (ED) for their care. We hypothesized that early consultation with a cardiologist in the ED can reduce re-hospitalization and health care costs for low-socioeconomic urban patients with acute decompensated heart failure.

METHODS

There were 392 patients treated at our center for acute decompensated heart failure who received standardized education and follow-up. Patients who returned to the ED received early consultation with a cardiologist; 392 patients who received usual care served as controls. Thirty- and 90-day re-hospitalization, ED re-visits, heart failure symptoms, mortality, and health care costs were recorded.

RESULTS

Despite guideline-based education and follow-up, the rate of ED re-visits was not different between the groups. However, the rate of re-hospitalization was significantly lower in patients receiving the intervention compared with controls (odds ratio 0.592), driven by a reduction in the risk of readmission from the ED (0.56 vs 0.79, respectively). Patients receiving the intervention accumulated 14% fewer re-hospitalized days than controls and 57% lower 30-day total health care cost. Despite the reduction in health care resource consumption, mortality was unchanged. After accounting for the total cost of intervention delivery, the health care cost savings was substantially greater than the cost of intervention delivery.

CONCLUSION

Early consultation with a cardiologist in the ED as an adjunct to guideline-based follow-up is associated with reduced re-hospitalization and health care cost for low-socioeconomic urban patients with acute decompensated heart failure.

Short-term Complication Rates Following Anterior Urethroplasty: An Analysis of National Surgical Quality Improvement Program Data

OBJECTIVE

To determine the characteristics and predictors of perioperative complications after male anterior urethroplasty.

MATERIALS AND METHODS

The American College of Surgeons-National Surgical Quality Improvement Program is a validated outcomes-based program comprising academic and community hospitals in the United States and Canada. Data from 2007 to 2015 were queried for single-stage anterior urethroplasty using Current Procedure Terminology codes. The primary outcome was frequency of complications within the 30-day postoperative period. Preoperative and intraoperative parameters were correlated with morbidity measures, and univariate and multivariate regression analyses were used.

RESULTS

A total of 555 patients underwent anterior urethroplasty, of whom 180 (32.4%) had graft or flap placement. Of the patients, 127 (22.9%) went home the same day after surgery, 255 (45.9%) stayed for 1 night, and 173 (31.2%) stayed for 2 or more nights. No deaths, cardiovascular complications, or sepsis were noted. Forty-seven patients (8.5%) had complications in the 30-day period. The most common complications were infection (57.4%), readmission (42.9%), and return to the operating room (17%). On univariate analysis, patients who had substitution urethroplasty (P = .04) and longer operative times (P = .002) were more likely to have complications, but only longer operative time showed significance on multivariate analysis (P = .006). Age, American Society of Anesthesiologists score, and length of stay were not predictive of complication frequency.

CONCLUSION

Anterior urethroplasty has low postoperative morbidity. Longer operative times were associated with increased rate of complications. Longer hospital stay after surgery is not protective against perioperative complications.

Chronic Obstructive Pulmonary Disease Readmissions and Other Measures of Hospital Quality

RATIONALE

The Centers for Medicare and Medicaid Services recently implemented financial penalties to reduce hospital readmissions for select conditions, including chronic obstructive pulmonary disease (COPD). Despite growing pressure to reduce COPD readmissions, it is unclear how COPD readmission rates are related to other measures of quality, which could inform efforts on common organizational factors that affect high-quality care.

OBJECTIVES

To examine the association between COPD readmissions and other quality measures.

METHODS

We analyzed data from the 2015 Centers for Medicare and Medicaid Services annual files, downloaded from the Hospital Compare website. We included 3,705 hospitals nationwide that had publically reported data on COPD readmissions. We compared COPD readmission rates to other risk-adjusted measures of quality, including readmission and mortality rates for other conditions, and patient reports about care experiences.

MEASUREMENTS AND MAIN RESULTS

There were modest correlations between COPD readmission rates and readmission rates for other medical conditions, including heart failure (r = 0.39; P < 0.01), acute myocardial infarction (r = 0.30; P < 0.01), pneumonia (r = 0.38; P < 0.01), and stroke (r = 0.29; P < 0.01). In contrast, we found low correlations between COPD readmission rates and readmission rates for surgical conditions, as well as mortality rates for all measured conditions. There were significant correlations between COPD readmission rates and all patient experience measures.

CONCLUSIONS

These findings suggest there may be common organizational factors that influence multiple disease-specific outcomes. As pay-for-performance programs focus attention on individual disease outcomes, hospitals may benefit from in-depth assessments of organizational factors that affect multiple aspects of hospital quality.

Readmission After COPD Exacerbation Scale: determining 30-day readmission risk for COPD patients

BACKGROUND

COPD affects over 13 million Americans, and accounts for over half a million hospitalizations annually. The Hospital Readmission Reduction Program, established by the Affordable Care Act requires the Centers for Medicare and Medicaid Services to reduce payments to hospitals with excess readmissions for COPD as of 2015. This study sought to develop a predictive readmission scale to identify COPD patients at higher readmission risk.

METHODS

Demographic and clinical data on 339,389 patients from New York and California (derivation cohort) and 258,113 patients from Washington and Florida (validation cohort) were abstracted from the State Inpatient Database (2006-2011), and the Readmission After COPD Exacerbation (RACE) Scale was developed to predict 30-day readmission risk.

RESULTS

Thirty-day COPD readmission rates were 7.54% for the derivation cohort and 6.70% for the validation cohort. Factors including age 40-65 years (odds ratio [OR] 1.17; 95% CI, 1.12-1.21), male gender (OR 1.16; 95% CI, 1.13-1.19), African American (OR 1.11; 95% CI, 1.06-1.16), 1st income quartile (OR 1.10; 95% CI, 1.06-1.15), 2nd income quartile (OR 1.06; 95% CI, 1.02-1.10), Medicaid insured (OR 1.83; 95% CI, 1.73-1.93), Medicare insured (OR 1.45; 95% CI, 1.38-1.52), anemia (OR 1.05; 95% CI, 1.02-1.09), congestive heart failure (OR 1.06; 95% CI, 1.02-1.09), depression (OR 1.18; 95% CI, 1.14-1.23), drug abuse (OR 1.17; 95% CI, 1.09-1.25), and psychoses (OR 1.19; 95% CI, 1.13-1.25) were independently associated with increased readmission rates, P<0.01. When the devised RACE scale was applied to both cohorts together, it explained 92.3% of readmission variability.

CONCLUSION

The RACE Scale reliably predicts an individual patient's 30-day COPD readmission risk based on specific factors present at initial admission. By identifying these patients at high risk of readmission with the RACE Scale, patient-specific readmission-reduction strategies can be implemented to improve patient care as well as reduce readmissions and health care expenditures.

Predictors of 30-day hospital readmission after hip fracture: a systematic review

BACKGROUND

Early readmission to hospital after hip fracture is associated with increased mortality and significant costs to the healthcare system. There is growing interest in the use of 30-day readmission rates as a metric of hospital performance. Identifying patients at increased risk of readmission after hip fracture may enable pre-emptive action to mitigate this risk and the development of effective methods of risk-adjustment to allow readmission to be used as a reliable measure of hospital performance.

METHODS

We conducted a systematic review of bibliographic databases and reference lists up to July 2016 to identify primary research papers assessing the effect of patient- and hospital-related risk factors for 30-day readmission to hospital after hip fracture.

RESULTS

495 papers were found through electronic and reference search. 65 full papers were assessed for eligibility. 22 met inclusion criteria and were included in the final review. Medical causes of readmission were significantly more common than surgical causes, with pneumonia consistently being cited as the most common readmission diagnosis. Age, pre-existing pulmonary disease and neurological disorders were strong independent predictors of readmission. ASA grade and functional status were more robust predictors of readmission than the Charlson score or individual co-morbidities. Hospital-related risk factors including initial length of stay, hospital size and volume, time to surgery and type of anaesthesia did not have a consistent effect on readmission risk. Discharge location and the strength of hospital-discharge facility linkage were important determinants of risk.

CONCLUSIONS

Patient-related risk factors such as age, co-morbidities and functional status are stronger predictors of 30-day readmission risk after hip fracture than hospital-related factors. Rates of 30-day readmission may not be a valid reflection of hospital performance unless a clear distinction can be made between modifiable and non-modifiable risk factors. We identify a number of deficiencies in the existing literature and highlight key areas for future research.

Guiding Principles for the Use of Nebulized Long-Acting Beta2-Agonists in Patients with COPD: An Expert Panel Consensus

Determining which patients with COPD may benefit from a nebulized long-acting beta2-agonist (LABA) is a challenge in current practice. In the absence of strong clinical guidelines addressing this issue, an expert panel convened to develop guiding principles for the use of nebulized LABA therapy in patients with COPD. This article summarizes these guiding principles and other practical issues discussed during a roundtable meeting.