Optimizing Inpatient Care for Lung Cancer Patients with Immune Checkpoint Inhibitor- Related Pneumonitis Using a Clinical Care Pathway Algorithm.

Purpose: Immune checkpoint inhibitor-related pneumonitis (ICI-P) is a condition associated with high mortality, necessitating prompt recognition and treatment initiation. This study aimed to assess the impact of implementing a clinical care pathway algorithm on reducing the time to treatment for ICI-P. Methods: Patients with lung cancer and suspected ICI-P were enrolled, and a multi-modal intervention promoting algorithm use was implemented in two phases. Pre- and post-intervention analyses were conducted to evaluate the primary outcome of time from ICI-P diagnosis to treatment initiation. Results: Of the 82 patients admitted with suspected ICI-P, 73.17% were confirmed to have ICI-P, predominantly associated with non-small cell lung cancer (91.67%) and stage IV disease (95%). Pembrolizumab was the most commonly used immune checkpoint inhibitor (55%). The mean times to treatment were 2.37 days in the pre-intervention phase and, 3.07 days (p=0.46), and 1.27 days (p=0.40) in the post-intervention phases 1 and 2, respectively. Utilization of the immunotoxicity order set significantly increased from 0% to 27.27% (p = 0.04) after phase 2. While there were no significant changes in ICU admissions or inpatient mortality, outpatient pulmonology follow-ups increased statistically significantly, demonstrating enhanced continuity of care. The overall mortality for patients with ICI-P was 22%, underscoring the urgency of optimizing management strategies. Notably, all patients discharged on high-dose corticosteroids received appropriate gastrointestinal prophylaxis and prophylaxis against Pneumocystis jirovecii pneumonia infections at the end of phase 2. Conclusion: Implementing a clinical care pathway algorithm for ICI-P management standardizes care practices and enhances patient outcomes, underscoring the importance of structured approaches.

Treatment patterns and outcomes of high-grade immune checkpoint inhibitor-related pneumonitis in an oncology hospitalist service.

PURPOSE: Immune checkpoint inhibitors (ICI) have become standard of care for some types of lung cancer. Along with expanding usage comes the emergence of immune-related adverse events (irAEs), including ICI-related pneumonitis (ICI-P). Treatment guidelines for managing irAEs have been developed; however, how clinicians manage irAEs in the real-world setting is less well known. We aimed to describe the outcomes and care patterns of grade ≥ 3 ICI-P in an onco-hospitalist service. PATIENTS AND METHODS: We included patients with lung cancer treated with ICI who were admitted to an oncology hospitalist service with a suspicion of ICI-P. We described the hospitalization characteristics, treatment patterns, discharge practices, and clinical outcomes of patients with confirmed ICI-P. The primary outcome was time to start treatment for ICI-P. RESULTS: Among 49 patients admitted with a suspicion of ICI-P, 31 patients were confirmed to have ICI-P and subsequently received ICI-P directed treatment. Pulmonology was consulted in 97% of patients. Median time to start treatment for ICI-P was 1 day (IQR 0-3.5 days). All 31 patients received corticosteroids. Inpatient mortality was 32%. Majority of patients discharged with steroids were prescribed prophylaxis for gastritis and opportunistic infections. Thirty-eight percent of patients were seen by pulmonology and 86% were seen by the oncology team post-discharge. CONCLUSION: Our study confirms prior findings of high mortality among patients with high-grade ICI-P. Early diagnosis and treatment are key to improving clinical outcomes. Understanding the care patterns and adherence to treatment guidelines of clinicians caring for this patient population may help identify ways to further standardize management practices and improve patient outcomes.

Understanding Potentially Preventable 7-day Readmission Rates in Hospital Medicine Patients at a Comprehensive Cancer Center.

This study aimed to describe the potentially preventable 7-day unplanned readmission (PPR) rate in medical oncology patients. A retrospective analysis of all unplanned 7-day readmissions within Hospital Medicine at MD Anderson Cancer Center from September 1, 2020 to February 28, 2021, was performed. Readmissions were independently analyzed by 2 randomly selected individuals to determine preventability. Discordant reviews were resolved by a third reviewer to reach a consensus. Statistical analysis included 138 unplanned readmissions. The estimated PPR rate was 15.94%. The median age was 62.50 years; 52.90% were female. The most common type of cancer was noncolon GI malignancy (34.06%). Most patients had stage 4 cancer (69.57%) and were discharged home (64.93%). Premature discharge followed by missed opportunities for goals of care discussions were the most cited reasons for potential preventability. These findings highlight areas where care delivery can be improved to mitigate the risk of readmission within the medical oncology population.

Interstitial lung abnormalities after hospitalization for COVID-19 in patients with cancer: A prospective cohort study.

INTRODUCTION: Survivors of SARS-CoV-2 pneumonia often develop persistent respiratory symptom and interstitial lung abnormalities (ILAs) after infection. Risk factors for ILA development and duration of ILA persistence after SARS-CoV-2 infection are not well described in immunocompromised hosts, such as cancer patients. METHODS: We conducted a prospective cohort study of 95 patients at a major cancer center and 45 patients at a tertiary referral center. We collected clinical and radiographic data during the index hospitalization for COVID-19 pneumonia and measured pneumonia severity using a semi-quantitative radiographic score, the Radiologic Severity Index (RSI). Patients were evaluated in post-COVID-19 clinics at 3 and 6 months after discharge and underwent comprehensive pulmonary evaluations (symptom assessment, chest computed tomography, pulmonary function tests, 6-min walk test). The association of clinical and radiological factors with ILAs at 3 and 6 months post-discharge was measured using univariable and multivariable logistic regression. RESULTS: Sixty-six (70%) patients of cancer cohort had ILAs at 3 months, of whom 39 had persistent respiratory symptoms. Twenty-four (26%) patients had persistent ILA at 6 months after hospital discharge. In adjusted models, higher peak RSI at admission was associated with ILAs at 3 (OR 1.5 per 5-point increase, 95% CI 1.1-1.9) and 6 months (OR 1.3 per 5-point increase, 95% CI 1.1-1.6) post-discharge. Fibrotic ILAs (reticulation, traction bronchiectasis, and architectural distortion) were more common at 6 months post-discharge. CONCLUSIONS: Post-COVID-19 ILAs are common in cancer patients 3 months after hospital discharge, and peak RSI and older age are strong predictors of persistent ILAs.

Sclerosing mesenteritis following immune checkpoint inhibitor therapy.

PURPOSE: Sclerosing mesenteritis (SM), a fibroinflammatory process of the mesentery, can rarely occur after immune checkpoint inhibitor (ICI) therapy; however, its clinical significance and optimal management are unclear. We aimed to assess the characteristics and disease course of patients who developed SM following ICI therapy at a single tertiary cancer center. METHODS: We retrospectively identified 12 eligible adult cancer patients between 05/2011 and 05/2022. Patients' clinical data were evaluated and summarized. RESULTS: The median patient age was 71.5 years. The most common cancer types were gastrointestinal, hematologic, and skin. Eight patients (67%) received anti-PD-1/L1 monotherapy, 2 (17%) received anti-CTLA-4 monotherapy, and 2 (17%) received combination therapy. SM occurred after a median duration of 8.6 months from the first ICI dose. Most patients (75%) were asymptomatic on diagnosis. Three patients (25%) reported abdominal pain, nausea, and fever and received inpatient care and corticosteroid treatment with symptom resolution. No patients experienced SM recurrence after the completion of corticosteroids. Seven patients (58%) experienced resolution of SM on imaging. Seven patients (58%) resumed ICI therapy after the diagnosis of SM. CONCLUSIONS: SM represents an immune-related adverse event that may occur after initiation of ICI therapy. The clinical significance and optimal management of SM following ICI therapy remains uncertain. While most cases were asymptomatic and did not require active management or ICI termination, medical intervention was needed in select symptomatic cases. Further large-scale studies are needed to clarify the association of SM with ICI therapy.

Hospitalization characteristics and outcomes of patients with cancer and COVID-19 at a comprehensive cancer center.

PURPOSE: Several studies have confirmed increased mortality among patients with both COVID-19 and cancer. It remains important to continue to report observations of morbidity and mortality from COVID-19 in this vulnerable population. The purpose of this study is to describe the hospitalization characteristics and outcomes of patients with both cancer and COVID-19 admitted to our comprehensive cancer center. METHODS: This was a descriptive study of the first COVID-19-related hospitalization among adult patients with cancer admitted to our institution. Descriptive statistics were used to summarize patient demographics, clinical as well as hospitalization characteristics. Overall survival (OS) was estimated using the Kaplan-Meier method. RESULTS: A total of 212 patients were included in our cohort with a mean age of 59 years. Fifty-four percent of patients had history of solid tumor malignancy and 46% had hematologic malignancies. Eighty-five percent of our cohort had active malignancy. The mean length of stay (LOS) for hospitalization was 11.2 days (median LOS of 6 days). Twenty-five percent had severe disease and 10.8% died during their initial hospitalization. Those who had severe disease had worse survival at the end of the observation period. CONCLUSIONS: COVID-19 among cancer patients causes significant morbidity and mortality as well as repeat hospitalizations. Continued study of COVID-19 in this vulnerable population is essential in order to better inform evolving treatment algorithms, public health policies, and infection control protocols, especially for institutions caring for patients with cancer.

A modified emergency severity index level is associated with outcomes in cancer patients with COVID-19.

OBJECTIVE: To evaluate a modified emergency severity index (mESI)-based triage of cancer patients with coronavirus disease 2019 (COVID-19) in the emergency department (ED) and determine the associations between mESI level and ED disposition, hospital length of stay, and overall survival. METHODS: Medical records were retrospectively reviewed for all patients who presented to our institution's ED between March 22, 2020, and March 12, 2021, and tested positive for SARS-CoV-2. RESULTS: A total of 306 cancer patients tested positive for SARS-CoV-2, with 45% of patients triaged to level 2 (emergent) and 55% to level 3 (urgent). Among all patients, 61.8% were admitted to the hospital, 15.7% were admitted to the intensive care unit, 2.9% were sent for observation, and 19.6% were discharged. Although demographic and clinical characteristics did not significantly vary by triage level, we observed significant differences in ED length of stay (urgent = 6.67 h, emergent = 5.97 h; p < 0.01). Hospital and intensive care unit admission rates were also significantly higher among emergent patients than among urgent patients (p < 0.05). There were 75 deaths (urgent = 32; emergent = 43), and the 30-day mortality rate was significantly higher among emergent patients (urgent = 8%, emergent = 15%; p < 0.05). The mESI level persisted as a significant factor associated with overall survival (hazard ratio = 1.7, 95% confidence interval = 1.09-2.81) in multivariable analysis. CONCLUSION: The mESI level is associated with ED disposition, ED length of stay, and overall survival in cancer patients presenting with COVID-19. These results indicate that the mESI triage tool can be effectively used in cancer patients with COVID-19, whose condition can rapidly deteriorate.

Derivation and Validation of the Cancer READMIT Score: A Readmission Risk Scoring System for Patients With Solid Tumor Malignancies.

PURPOSE: Readmissions for the medical treatment of cancer have traditionally been excluded from readmission measures under the Hospital Readmissions Reduction Program. Patients with cancer often have higher readmission rates and may need heightened support to ensure effective care transitions after hospitalization. Estimating readmission risk before discharge may assist in discharge planning efforts and help promote care coordination at time of discharge. PATIENTS AND METHODS: We developed and validated a readmission risk scoring system among a cohort of adult cancer patients with solid tumor admitted at a comprehensive cancer center. Multivariate logistic regression analysis was used to develop the model. The model's discriminative capacity was evaluated through a receiver operating characteristic curve analysis. We further compared the performance of the developed score with existing risk scores for 30-day readmission. RESULTS: The 30-day unplanned readmission rate in the total cohort was 16.0% (n = 1,078 of 6,720). After multivariate analysis, Cancer site, Recent emergency room visit within 30 days, non-English primary language, Anemia defined as hemoglobin < 10 g/dL, > 4 Days length of stay during the index admission, unmarried Marital status, Increased white blood cell count > 11 × 109/L, and distant Tumor spread were significantly associated with risk of unplanned 30-day readmission. The derived score, which we call the Cancer READMIT score, had modest discriminatory performance in predicting readmissions (area under the curve for the model receiver operating characteristic curve = 0.647). CONCLUSION: The Cancer READMIT score was able to predict 30-day unplanned readmissions to our institution with fairly modest performance. External validation of our derived risk scoring system is recommended.

Comparison of LACE and HOSPITAL Readmission Risk Scores for CMS Target and Nontarget Conditions.

This study evaluated the utility and performance of the LACE index and HOSPITAL score with consideration of the type of diagnoses and assessed the accuracy of these models for predicting readmission risks in patient cohorts from 2 large academic medical centers. Admissions to 2 hospitals from 2011 to 2015, derived from the Vizient Clinical Data Base and regional health information exchange, were included in this study (291 886 encounters). Models were assessed using Bayesian information criterion and area under the receiver operating characteristic curve. They were compared in CMS diagnosis-based cohorts and in 2 non-CMS cancer diagnosis-based cohorts. Overall, both models for readmission risk performed well, with LACE performing slightly better (area under the receiver operating characteristic curve 0.73 versus 0.69; P ≤ 0.001). HOSPITAL consistently outperformed LACE among 4 CMS target diagnoses, lung cancer, and colon cancer. Both LACE and HOSPITAL predict readmission risks well in the overall population, but performance varies by salient, diagnosis-based risk factors.

Renal Replacement Therapy in Patients With Stage IV Cancer Admitted to the Intensive Care Unit With Acute Kidney Injury at a Comprehensive Cancer Center Was Not Associated With Survival.

INTRODUCTION: In patients with advanced cancer, prolongation of life with treatment often incurs substantial emotional and financial expense. Among hospitalized patients with cancer since acute kidney injury (AKI) is known to be associated with much higher odds for hospital mortality, we investigated whether renal replacement therapy (RRT) use in the intensive care unit (ICU) was a significant independent predictor of worse outcomes. METHODS: We retrospectively reviewed patients admitted in 2005 to 2014 who were diagnosed with stage IV solid tumors, had AKI, and a nephrology consult. The main outcomes were survival times from the landmark time points, inpatient mortality, and longer term survival after hospital discharge. Logistic regression and Cox proportional regression were used to compare inpatient mortality and longer term survival between RRT and non-RRT groups. Propensity score-matched landmark survival analyses were performed with 2 landmark time points chosen at day 2 and at day 7 from ICU admission. RESULTS: Of the 465 patients with stage IV cancer admitted to the ICU with AKI, 176 needed RRT. In the multivariate logistic regression model after adjusting for baseline serum albumin and baseline maximum Sequential Organ Failure Assessment (SOFA), the patients who received RRT were not significantly different from non-RRT patients in inpatient mortality (odds ratio: 1.004 [95% confidence interval: 0.598-1.684], P = .9892). In total, 189 patients were evaluated for the impact of RRT on long-term survival and concluded that RRT was not significantly associated with long-term survival after discharge for patients who discharged alive. Landmark analyses at day 2 and day 7 confirmed the same findings. CONCLUSIONS: Our study found that receiving RRT in the ICU was not significantly associated with inpatient mortality, survival times from the landmark time points, and long-term survival after discharge for patients with stage IV cancer with AKI.

Demonstrating value: association of cost and quality outcomes with implementation of a value-driven oncology-hospitalist inpatient collaboration for patients with lung cancer.

The hospitalist model of care has gained favour in many hospital systems for the value, cost-effectiveness and quality of care that hospitalists provide. Hospitalists are experts in high-acuity medical problems of patients and they are intimately knowledgeable about hospital operations that enable efficiency of patient care. This results in tremendous cost-savings for institutions especially since hospitalists are also obligated to be involved in quality and practice improvement initiatives. The University of Texas MD Anderson Cancer Center employs oncology-hospitalists for many of their patients with cancer needing inpatient services. This physician team has expertise in both cancer-related and comorbidity-related reasons for hospitalisation. In September 2015, the thoracic and head and neck medical oncology team started a collaboration with the Oncology Hospitalist team whereby a proportion of patients with thoracic malignancies were directly admitted to hospitalists for inpatient care. To determine the value of this collaboration, a pre- and post- implementation study was done to compare quality outcomes such as readmission rates and length of stay (LOS) between the two groups. Adjusted outcomes showed that readmission rates were similar for both physician groups both at baseline and after implementation of the collaborative (p=0.680 and p=0.840, respectively). Median LOS was similar for both groups at baseline (4 days) and was not significantly different post-implementation (4vs5 days, p=0.07). The adjusted cost of a hospitalisation was also similar for hospitalist encounters and thoracic oncology encounters. This initial study showed that quality of care remained comparable for patients with lung cancer who were admitted to either service. With possibly shorter LOS but comparable readmission outcomes and adjusted cost for patients discharged from the hospitalist service, there is a strong value benefit for the implemented Thoracic Oncology-Hospitalist inpatient collaborative.

How Leading Hospitals Operationalize Evidence-Based Readmission Reduction Strategies: A Mixed-Methods Comparative Study Using Systematic Review and Survey Design.

Although various interventions targeted at reducing hospital readmissions have been identified in the literature, little is known about actual operationalization of such evidence-based interventions. This study conducted a systematic review and a survey of key informants in 2 leading hospitals, Houston Methodist (HM) and MD Anderson Cancer Center (MDACC), to compare and contrast the most cited evidence-based interventions in the current literature with interventions reported by those hospitals. The authors found that both hospitals followed evidence-based practices reported as successful in the literature. Both hospitals have implemented interventions for inpatient settings, and the timing of interventions was very similar. Major implementation differences observed for post-discharge interventions focused on collaboration. It also was found that HM was more likely than MDACC to use medication reconciliation in outpatient (P = .018) and discharge planning for community/home patients (P = .032). Results will provide hospital professionals with insights for implementing the most effective interventions to reduce readmissions.

Readmission Patterns After GI Cancer Hospitalizations: The Medical Versus Surgical Patient.

PURPOSE: Readmission within 30 days has been used as a metric for quality of care received at hospitals for certain diagnoses. In the era of accountability, value-based care, and increasing cancer costs, policymakers are looking into cancer readmissions as well. It is important to describe the readmission profile of patients with cancer in the most clinically relevant approach to inform policy and health care delivery that can positively impact patient outcomes. PATIENTS AND METHODS: We conducted a retrospective cohort study using linked Texas Cancer Registry and Medicare claims data. We included elderly Texas residents diagnosed with GI cancer and identified risk factors for unplanned readmission using generalized estimating equations, comparing medical with surgical cancer-related hospitalizations. RESULTS: We analyzed 69,693 hospitalizations from 31,736 patients. The unplanned readmission rate was higher after medical hospitalizations than after surgical hospitalizations (21.6% v 13.4%, respectively). Shared risk factors for readmission after medical and surgical hospitalizations included advanced disease stage, high comorbidity index, and emergency room visit and radiation therapy within 30 days before index hospitalization. Several other associated factors and reasons for readmission were noted to be unique to medical or surgical hospitalizations alone. CONCLUSION: Unplanned readmissions among elderly patients with GI cancer are more common after medical hospitalizations compared with surgical hospitalizations. There are shared risk factors and unique risk factors for these hospitalizations that can inform policy, health care delivery, and interventions to reduce readmissions. Other findings underscore the importance of care coordination and comorbidity management in this patient population.

Unplanned 30-Day Readmissions in a General Internal Medicine Hospitalist Service at a Comprehensive Cancer Center.

PURPOSE: Hospital readmissions are considered by the Centers for Medicare and Medicaid as a metric for quality of health care delivery. Robust data on the readmission profile of patients with cancer are currently insufficient to determine whether this measure is applicable to cancer hospitals as well. To address this knowledge gap, we estimated the unplanned readmission rate and identified factors influencing unplanned readmissions in a hospitalist service at a comprehensive cancer center. METHODS: We retrospectively analyzed unplanned 30-day readmission of patients discharged from the General Internal Medicine Hospitalist Service at a comprehensive cancer center between April 1, 2012, and September 30, 2012. Multiple independent variables were studied using univariable and multivariable logistic regression models, with generalized estimating equations to identify risk factors associated with readmissions. RESULTS: We observed a readmission rate of 22.6% in our cohort. The median time to unplanned readmission was 10 days. Unplanned readmission was more likely in patients with metastatic cancer and those with three or more comorbidities. Patients discharged to hospice were less likely to be readmitted (all P values < .01). CONCLUSION: We observed a high unplanned readmission rate among our population of patients with cancer. The risk factors identified appear to be related to severity of illness and open up opportunities for improving coordination with primary care physicians, oncologists, and other specialists to manage comorbidities, or perhaps transition appropriate patients to palliative care. Our findings will be instrumental for developing targeted interventions to help reduce readmissions at our hospital. Our data also provide direction for appropriate application of readmission quality measures in cancer hospitals.

Patterns and predictors of unplanned hospitalization in a population-based cohort of elderly patients with GI cancer.

PURPOSE: Hospitalizations among patients with cancer are common and costly and, if unplanned, may interrupt oncologic treatment. The rate of unplanned hospitalizations in the population of elderly patients with cancer is unknown. We sought to describe and quantify patterns and risk factors for early unplanned hospitalization among elderly patients with GI cancer. PATIENTS AND METHODS: We conducted a retrospective cohort study using linked Texas Cancer Registry and Medicare claims data from 2001 to 2009. Texas residents age 66 years or older initially diagnosed with GI cancer between 2001 and 2007 were included in the study. The unplanned hospitalization rate was estimated, and reasons for unplanned hospitalization were evaluated. Risk factors were identified using adjusted Cox proportional hazards modeling. RESULTS: Thirty thousand one hundred ninety-nine patients were included in our study, 59% of whom had one or more unplanned hospitalizations. Of 60,837 inpatient claims, 58% were unplanned. The rate of unplanned hospitalization was 93 events per 100 person-years. The most common reasons for unplanned hospitalization were fluid and electrolyte disorders, intestinal obstruction, and pneumonia. Multivariable analysis showed that black race; residing in census tracts with poverty levels greater than 13.3%; esophageal, gastric, and pancreatic cancer; advanced disease stage; high Charlson comorbidity index score; and dual eligibility for Medicare and Medicaid increased the risk for unplanned hospitalization (all P values < .05). CONCLUSION: Unplanned hospitalizations among elderly patients with GI cancer are common. Some of the top reasons for unplanned hospitalization are potentially preventable, suggesting that comorbidity management and close coordination among involved health care providers should be promoted.