Readmissions Following Hospitalization for Infection in Children With or Without Medical Complexity

OBJECTIVE: To describe the prevalence and characteristics of infection-related readmissions in children and to identify opportunities for readmission reduction and estimate associated cost savings. STUDY DESIGN: Retrospective analysis of 380,067 nationally representative index hospitalizations for children using the 2014 Nationwide Readmissions Database. We compared 30-day, all-cause unplanned readmissions and costs across 22 infection categories. We used the Inpatient Essentials database to measure hospital-level readmission rates and to establish readmission benchmarks for individual infections. We then estimated the number of readmissions avoided and costs saved if hospitals achieved the 10th percentile of hospitals’ readmission rates (ie, readmission benchmark). All analyses were stratified by the presence/absence of a complex chronic condition (CCC). RESULTS: The overall 30-day readmission rate was 4.9%. Readmission rates varied substantially across infections and by presence/absence of a CCC (CCC: range, 0%-21.6%; no CCC: range, 1.5%-8.6%). Approximately 42.6% of readmissions (n = 3,576) for children with a CCC and 54.7% of readmissions (n = 5,507) for children without a CCC could have been potentially avoided if hospitals achieved infection-specific benchmark readmission rates, which could result in an estimated savings of $70.8 million and $44.5 million, respectively. Bronchiolitis, pneumonia, and upper respiratory tract infections were among infections with the greatest number of potentially avoidable readmissions and cost savings for children with and without a CCC. CONCLUSION: Readmissions following hospitalizations for infection in children vary significantly by infection type. To improve hospital resource use for infections, future preventative measures may prioritize children with complex chronic conditions and those with specific diagnoses (eg, respiratory illnesses).

Identifying Actionable Causes of Potentially Avoidable Readmissions to an Oncology Service at a Safety Net Hospital

PURPOSE: Hospital readmissions occur commonly in those receiving cancer care and result in impaired quality of life and increased costs. Causes of readmission in safety net hospitals that serve vulnerable populations are not well understood. The primary goal of this project was to identify potentially avoidable and intervenable causes of readmissions to an urban safety net hospital. METHODS: A retrospective chart review was performed on patients who were readmitted within 30 days of discharge from the hematology and oncology service at Boston Medical Center over the 6-month period between October 2018 and March 2019. Charts were reviewed by three internal medicine residents and discussed under the supervision of an attending oncologist. RESULTS: Two hundred ninety-one patient encounters involving 203 unique patients were identified in the 6-month study period. Of these 291 encounters, 80 encounters (27.5%) were followed by a readmission within 30 days and occurred in 61 (30.0%) unique patients. Nineteen (31.1%) of these 61 patients experienced two readmissions within 30 days of discharge. Twenty-five readmissions (31.3%) were classified as potentially avoidable, with the most common cause of potentially avoidable readmissions attributed to ascitic or pleural fluid reaccumulation (8, 32%). The majority of presumed nonpreventable readmissions were due to expected complications of cancer progression and treatment-related side effects. DISCUSSION: In conclusion, readmissions were common, and a modifiable reason for 30-day readmissions was identified. Addressing recurrent ascitic and pleural fluid reaccumulation in the outpatient setting could help to reduce inpatient hospital readmission on an inpatient oncology service.

Transition of Care for Discharged Patients

Practice Problem: The 30-day readmission rate for patients discharged from the hospital and returned to their primary care in a clinical office setting (21%) was higher than the national average readmission rate (17%). The high readmission rate suggested patients were receiving transitional care that was fragmented and non-standardized. Therefore, the implementation of a collaborative transition of care practice was vital to reduce avoidable readmissions. PICOT: The PICOT question that guided this project was, “In adult patients with chronic conditions, what is the effect of a transition of care practice, versus a non-standardized practice, on reducing 30-day readmissions, within a 30-day period?” Evidence: Evidence suggests that implementing a multidisciplinary Transition of Care practice for patients who are discharged from the hospital to home decreases the 30-day readmission rate. Intervention: Using a multidisciplinary approach, the registered nurse implemented a Transition of Care practice, consisting of 10 evidence-based interventions, applied to help the patient transition from hospital to home. Outcome: The results of this project revealed a decrease in the 30-day readmission rate from 23% to 15%. Also, seven of the 10 interventions were successfully implemented at a rate of higher than 85%. Conclusion: The reduction in the percent of 30-day readmissions was statistically and clinically significant between the pre-transition of care and the post-transition of care participants. In addition, the transition of care interventions were successfully implemented to standardize an evidence-based practice for patients transitioning from the hospital to their home.

Dementia Severity Is Associated With Early Potentially Avoidable Readmissions in an Acute Care Hospital

Understanding the association of dementia severity with early potentially avoidable readmissions (PAR) could encourage the identification of the target patients for the health care providers to provide transitional care (i.e. follow-up and coordination care) to prevent early readmissions. This study examined whether dementia severity before admission was associated with PAR within 90 days (90-day PAR). This retrospective cohort study was conducted using a Diagnosis Procedure Combination database linked with routinely collected dementia assessment data from a large acute general hospital in Tokyo, Japan. Patients aged 65 or older who were discharged to home or facilities (n=8,910; mean age: 79.8 years, standard deviation: 7.4 years) between July 2016 and September 2018. The dementia severity was classified as normal, slight, moderate, severe dementia based on the Dementia Assessment Sheet for Community-based Integrated Care System 21-items (DASC-21) from the patient or their family at admission. We conducted a multivariable logistic regression adjusted for covariates (sex, age, insurance copayment rate, diagnosis at admission, Charlson Comorbidity Index, unscheduled admission, ICU utilization, surgical treatment, length of hospital stay, discharge place) to examine the association of severity of dementia with 90-day PAR. Among the patients, 225 (2.5%) experienced 90-day PAR. The adjusted odds of 90-day PAR among patients with moderate dementia were 1.571 times (95% confidence interval [CI]: 1.102-2.240) and patients with severe dementia were 2.386 times (95% CI: 1.294-4.398) higher than the odds among patients without dementia. Patients with moderate and severe dementia before admission would be the target with high priority for providing transitional care.

Development of a risk prediction model of potentially avoidable readmission for patients hospitalised with community-acquired pneumonia: study protocol and population

Introduction30-day readmission rate is considered an adverse outcome reflecting suboptimal quality of care during index hospitalisation for community-acquired pneumonia (CAP). However, potentially avoidable readmission would be a more relevant metric than all-cause readmission for tracking quality of hospital care for CAP. The objectives of this study are (1) to estimate potentially avoidable 30-day readmission rate and (2) to develop a risk prediction model intended to identify potentially avoidable readmissions for CAP.Methods and analysisThe study population consists of consecutive patients admitted in two hospitals from the community or nursing home setting with pneumonia. To qualify for inclusion, patients must have a primary or secondary discharge diagnosis code of pneumonia. Data sources include routinely collected administrative claims data as part of diagnosis-related group prospective payment system and structured chart reviews. The main outcome measure is potentially avoidable readmission within 30 days of discharge from index hospitalisation. The likelihood that a readmission is potentially avoidable will be quantified using latent class analysis based on independent structured reviews performed by four panellists. We will use a two-stage approach to develop a claims data-based model intended to identify potentially avoidable readmissions. The first stage implies deriving a clinical model based on data collected through retrospective chart review only. In the second stage, the predictors comprising the medical record model will be translated into International Classification of Diseases, 10th revision discharge diagnosis codes in order to obtain a claim data-based risk model.The study sample consists of 1150 hospital stays with a diagnosis of CAP. 30-day index hospital readmission rate is 17.5%.Ethics and disseminationThe protocol was reviewed by the Comité de Protection des Personnes Sud Est V (IRB#6705). Efforts will be made to release the primary study results within 6 months of data collection completion.Trial registration numberClinicalTrials.gov Registry (NCT02833259).

Assessing 30-day avoidable readmission rates: Is it an appropriate tool to manage emergency department quality of care?

Objective: Quality indicators, based on administrative data, are being increasingly used to assess avoidable hospital readmission rates. Their potential to identify areas for improvement at low cost is attractive, but their performance in emergency departments (EDs) has been criticised.Methods: Hospital readmissions were categorised as potentially avoidable or non-avoidable, by a computerised algorithm (SQLape®, version 2016 - Striving for Quality Level and analysing of patient expenditures). Half-yearly rates were reported between July 2015 and June 2016. Two senior physicians conducted a medical record review on 100 randomly selected cases from an ED, flagged as potentially avoidable readmissions (PAR). Results were then discussed with the algorithm’s designer.Results: The algorithm screened 2,182 eligible emergency visits - 105 cases (4.8%), were deemed potentially avoidable by the algorithm. Among 100 randomly selected cases, nine exclusions were due to coding issues and four due to false positives. Overall (N = 87), 20/87 (23%) of readmissions were directly related to sole emergency care, 31/87 (36%) related to healthcare providers other than the ED, and 23/87 (26%) were of mixed provision, while 13/87 (15%) were attributed to the course of the disease.Conclusions: The study confirms the need for a better understanding of the algorithm’s measurement and of its reported results. Careful interpretation is required before a sound conclusion can be made. Indeed, it is apparent that the 30-day PAR quality indicator rate reflects a wider parameter of care than hospitals alone, who understandably tend to concentrate on their own, direct liability of care. In particular the 30-day PAR quality indicator is not well-suited to evaluate ED performance.