Readmissions In Cancer Patients Research Articles

Atrial flutter in a patient population with cancer: Comparison of incidence, mortality, and readmission rates.

e23079 Background: Cardiac tachyarrhythmias are common in cancer patients. Much has been studied regarding atrial fibrillation, but the impact of atrial flutter (AFL) in different malignancies is under-studied. We aim to compare the occurrence of atrial flutter (AFL), its mortality, and readmission rates in cancer patients stratified by different types. Methods: The National Readmission Database (2016-2020) was queried to identify all-cause admissions for patients with active malignancy of any origin. The study population was divided into six subgroups based on the type of cancer (colorectal, renal, lung, breast, prostate, and hematological). Multivariate regression analysis was utilized for adjusted odds of mortality. A propensity score matching (PSM) model matched malignancy of interest with other malignancies to obtain incidence rates. Results: Among 10.6 million all-cause cancer-related hospitalizations, about 0.4% developed AFL. After propensity matching, when compared to other malignancies, AFL had the highest incidence in hospitalizations associated with lung malignancies (0.75%), followed by hematological (0.66%), prostrate (0.57%), renal (0.49%), colorectal (0.38%) and breast (0.31%) malignancies [p < 0.05]. Moreover, cancer hospitalizations complicated by AFL were associated with higher mortality. AFL was associated with the highest odds of mortality in colorectal malignancies (aOR:2.80), followed by hematological (aOR:2.67), renal (aOR:2.66), lung (aOR:2.22), breast (aOR:2.12), & prostate (aOR:1.76) malignancies [p < 0.001]. AFL was also associated with frequent readmissions in cancer patients. The rates of 30-day AFL-related recurrent admission were highest in lung malignancies (18.3%), followed by hematological (18%), renal (16.6%), prostate (15.1%), colorectal (14.7%) & breast (14.2%) malignancies [p < 0.05]. Conclusions: The incidence of AFL in nationwide hospitalizations among cancer patients was ~ 0.4%. AFL was found to have the highest incidence and readmission rates in lung malignancies, while AFL-related mortality was highest in colorectal malignancies.

Hospitalization rates related to coordinated home healthcare services with a community oncology practice.

273 Background: Unplanned hospital admissions or hospital re-admissions in cancer patients after discharge cost in excess of 16 billion dollars. Oncology patients are a very high risk of hospitalization despite the involvement of a home healthcare agency. The 30-day medical oncology re-hospitalization rates are reported to be 21.6%. Unplanned hospitalization rates in selected oncology patients over a 12 month period have been reported to be as high as 58%. Methods: A large home health agency and a community based medical oncology practice created a delivery model referred to as the Advanced Community Care Model (ACCM). We are reporting our initial 14 month experience. The initial pilot involved three of the medical group’s six cancer centers. The ACCM created standing intervention orders regarding hydration, nausea/vomiting, central line management, antiemetic and diarrhea and a continuum of monthly management meetings with the agency and the practice. Navigation services by a designated RN were provided. Enhanced interventions with either telephone communication or home visits took place when deemed appropriate. Results: ACCM impacted 60-day hospitalization rates fell a baseline at 6 months into the program from 43% to 22% by the end of the 18 month pilot. Avoidable hospitalizations and re-hospitalizations related to N/V, pain, SOB and infection were less than 10%. The initial program has involved 310 unique patients. Conclusions: The reduction in the 60 day hospitalization rates and the low hospitalization and re-hospitalization rates related to pain control, infection, SOB and infection were below published national averages. The results were felt to be encouraging and the ACCM will be expanded to involve all 7 cancer centers in the practice.

ICU readmission of patients with cancer: Incidence, risk factors and mortality

PurposeFew studies evaluated ICU readmission in cancer patients. This study aimed to describe the incidence and risk factors for ICU readmission in cancer patients and the association with mortality. Materials and methodsA retrospective cohort study at a comprehensive cancer center, which included cancer patients who were discharged after their initial ICU admission over a 5-year period. The characteristics and outcomes of patients who required ICU readmission within 30 days of discharge were compared to those who did not require readmission during the study period. Multivariate analyses were performed to identify factors associated with readmission and to evaluate the association between readmission and mortality. ResultsAmong 1582 patients discharged from the ICU, 313(19.8%) were readmitted after a median of 6 days. The most common readmission diagnoses were respiratory failure and sepsis. Mechanical ventilation (OR 5.80; 95% CI 4.29–7.84) and thrombocytopenia (OR 1.66; 95% CI 1.16–2.38), on the first ICU admission were associated with readmission. Readmission was associated with a higher risk of 28-day and 90-day mortality, (OR 3.02; CI 2.3–4.00) and (OR 3.47; 95% CI 2.69–4.49), respectively. ConclusionsICU readmission was associated with increased mortality. Mechanical ventilation and thrombocytopenia at the first admission were associated with ICU readmission.

Using patient satisfaction to predict readmissions in cancer patients.

e18870Background: Thirty-day unplanned readmissions are a fundamental indicator of hospital quality. Current models used to predict readmissions perform poorly in cancer patients. We explored how p...

Development and prospective validation of a model estimating risk of readmission in cancer patients.

Hospital readmissions among cancer patients are common. While several models estimating readmission risk exist, models specific for cancer patients are lacking. A logistic regression model estimating risk of unplanned 30-day readmission was developed using inpatient admission data from a 2-year period (n = 18 782) at a tertiary cancer hospital. Readmission risk estimates derived from the model were then calculated prospectively over a 10-month period (n = 8616 admissions) and compared with actual incidence of readmission. There were 2478 (13.2%) unplanned readmissions. Model factors associated with readmission included: emergency department visit within 30 days, >1 admission within 60 days, non-surgical admission, solid malignancy, gastrointestinal cancer, emergency admission, length of stay >5 days, abnormal sodium, hemoglobin, or white blood cell count. The c-statistic for the model was 0.70. During the 10-month prospective evaluation, estimates of readmission from the model were associated with higher actual readmission incidence from 20.7% for the highest risk category to 9.6% for the lowest. An unplanned readmission risk model developed specifically for cancer patients performs well when validated prospectively. The specificity of the model for cancer patients, EMR incorporation, and prospective validation justify use of the model in future studies designed to reduce and prevent readmissions.

Palliative care utilization in oncology patients with 30-day hospital readmission.

110 Background: Reducing the rate of hospital readmissions is an important aspect of improving quality of life and cost of care for patients with advanced cancer. Early Palliative Care (PC) has been shown to improve quality of life and downstream healthcare utilization in patients with advanced cancer. The aim of this study was to examine palliative care (PC) utilization and factors associated with 30-day readmission in cancer patients. Methods: All patients with 30 day readmissions to the inpatient oncology service at the Wilmot Cancer Institute from July 2015-June 2016 were identified. Chart reviews were conducted to determine primary cancer stage and type; reason for, length of stay and discharge disposition (e.g. discharged on hospice, deceased) for index and readmission; potential preventability of readmission; and if and when the patient had met with PC. Results: A total of thirty-nine patients experienced a 30-day readmission, with 95% of patients having stage IV disease and 77% having a primary lung or GI malignancy. Most patients (74%) had not met with PC at the time of the index admission and 49% of patients had not met with PC by the time of readmission. Forty one percent (N = 17) of patients either died during readmission or were discharged on hospice. Forty one percent (N = 7) of those that died during readmission or were discharged on hospice did not meet with palliative care. Forty four percent of readmissions were classified as potentially preventable. Conclusions: Nearly half of all advanced cancer patients had not met with PC by the time of their readmission. Upon readmission, many patients were either discharged to hospice or died, suggesting that patients with advanced cancer could benefit from earlier PC. Increased and improved patient-oncologist PC communication, including referrals to PC specialists, may reduce readmission rates for patients with advanced cancer.

30 day readmissions in cancer patients in United States.

6577Background: National estimates of 30 day readmissions in cancer patients in US are unknown. Objective of our study was to identify 30 day readmission rates, predictors of readmissions and econo...

Readmissions in Cancer Patients After Receiving Inpatient Palliative Care in Taiwan: A 9-Year Nationwide Population-Based Cohort Study.

Few studies have reported on readmissions among cancer patients receiving inpatient palliative care (IPC). This study investigated readmissions in cancer patients after their first discharge from IPC in Taiwan from 2002 to 2010.This study was a secondary data analysis using information from the National Health Insurance Database in Taiwan from 2002 to 2010. We included subjects ≥20 years old diagnosed with malignant neoplasms who were listed in the registry of catastrophic illness. Patients diagnosed with cancer before January 1, 2002 or who had ever been admitted to an inpatient hospice palliative care unit before the study period were excluded. Readmission was defined as hospital readmission at least once after discharge from first admission to IPC until mortality or the end of the study period.A total of 42,022 patients who met the inclusion criteria were identified. The majority of these patients were male (60.4%). The mean age of cancer diagnosis was 64.0 ± 14.4 years for men and 64.5 ± 14.7 years for women. The mean age at first hospice ward admission was 65.2 ± 14.2 years for men and 65.9 ± 14.9 years for women. During their first admission to IPC, 59.2% patients died, and the median stay of first IPC admission was 8.0 days. Among those discharged alive from their first admission to IPC, 64.9% were readmitted, and 19.4% of these patients were readmitted on the same day of discharge. From first IPC discharge until mortality, 54.8% of patients were readmitted once, 23.9% were readmitted twice, 9.9% were readmitted 3 times, and 11.5% were readmitted 4 or more times. Being male, having a higher insurance premium level, having a longer length of stay during first IPC admission, being admitted to a teaching hospital, or being admitted to a tertiary hospital increased the adjusted hazard ratio for readmission.We found that terminal cancer patients in Taiwan received relatively late referrals for first admission to IPC and experienced a high rate of readmission after first discharge from IPC. Policies to improve hospice palliative care referrals and decrease readmissions should be considered.

Influence of language barriers on hospital readmissions in cancer patients.

e17583 Background: Patients with limited English proficiency (LEP) are increasing in number in the US. Language barriers make it difficult for patients to communicate their symptoms and may lead to...

Augmentation of cancer outcomes through safe transitions.

250 Background: Policymakers have identified 30-day readmissions as an important quality indicator of poor care or coordination of care. Among cancer centers, there is no benchmark data in terms of readmission rates or recommendations in terms of risk adjustment models. Methods: Retrospective data analysis to estimate baseline readmission rate and identify risk factors. Interventions: (1)admitting to single floor, (2) twice weekly interdisciplinary meetings with using risk assessment tool–Cancer Outcomes Augmented through Safe Transitions (COAST) tool, and (3) re-evaluate readmission rate post intervention at 6 months and 1 year. Results: Unplanned readmission rate on the Hospitalist Service at MD Anderson was 21.5% at baseline. After 6 months of interventions, our readmission rate over 6 months was 23.3%. Age 45-65, having Medicare insurance, and being discharged to hospice were protective of a readmission. Distant metastases and having more comorbidities were associated with increased risk for readmission. Readmitted patients have a greater length of stay (7 days) and a higher average cost of inpatient stay ($20.3K vs. 17.9K). The median days to readmission was 11 days. Top comorbidities: hypertension, fluid and electrolyte disorders, anemia, diabetes mellitus, and abnormal weight loss. Top reasons: metastatic disease, biliary tract disease, GI hemorrhage, intestinal obstruction, septicemia, renal failure. Conclusions: Our project has provided insight into the rates and risk factors for readmission in oncology hospitalist service in a tertiary cancer center. The development of web-based COAST risk assessment tool is expected to give an improved understanding of our patient population. Although our readmission rates have not shown decrease over the 6 months after our interventions, this means that more interventions and more time may be necessary to impact readmission rates of services dealing with complex cancer patients. Additionally, a proportion of these unplanned readmissions in cancer patients may not be preventable. Benchmark data we have presented and that we continue to collect will help inform recommendations for effective transitions of care, patient safety practices as well as strategies for reducing readmission rates in cancer centers.