Jeffrey S. Farroni

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.

Cancer Care Ethics in the Emergency Center

The emergency center (EC) is a technical, specialized, fast-paced environment where time is of the essence. Falling into a process by which the need for immediate response overshadows the need for ethical examination of important aspects of patient care is easy. Our purpose is to provide clinicians with some ethical considerations that can be made and reduce challenges to caring for the cancer patient in the EC. Cancer patients are often seen in ECs because of issues at the end of life, uncontrolled physical pain, and psychosocial or coping issues. This chapter deals with some of these and other common issues, including delirium, quickly changing condition, and possible drug-seeking behaviors for coping. Also considered are clinician responses to these as well as issues to recognize when assisting patients and their surrogates with decision-making during these difficult times. Case examples, discussion of the ethical challenges, and suggestions for the clinician and health care team are used to highlight and examine some of the ethical dilemmas faced in the EC.

Chapter 14 – A Perspective on the Cost of Cancer Care

Cancer, like many chronic diseases, imposes a heavy cost on the health-care enterprise. Although the most common calculation of this cost is in monetary units, the most salient toll may be in terms of the vulnerability of disease, caregiver burdens, loss of personhood, death, grief, etc. These are the costs hidden from the ledger of health-care expenditures and impose a moral agency upon the machinations that contribute to the high cost of care. This chapter explores ways to change institutional structures and achieve a more equitable health-care system with regard to the cost of chemotherapy.

An Ethical Framework for Disclosing Individual Genetic Findings to Patients, Research Participants, and Relatives

Abstract Current advances in genetic screening, biomarker development, personalized medicine, and targeted therapeutics have generated unprecedented quantities of patient data. These data are becoming increasingly vital as instruments of patient care and research. However, the nature of genetic information is such that it has clinically actionable implications for the patient’s relatives. This chapter focuses on a practical framework for the disclosure of genetic information to not only the patient but also to the family members who may be impacted by these findings. The potential benefit and utility of this information is carefully balanced with reducing the possible risks and informational harms by the use of policy, institutional safeguards, and empowering patient autonomy through rigorous informed consent standards.

I Don't Know Why I Called You

This case study details a request from a patient family member who calls our service without an articulated ethical dilemma. The issue that arose involved the conflict between continuing further medical interventions versus transitioning to supportive or palliative care and transferring the patient home. Beyond the resolution of the ethical dilemma, this narrative illustrates an approach to ethics consultation that seeks practical resolution of ethical dilemmas in alignment with patient goals and values. Importantly, the family’s suffering is addressed through a relationship driven, humanistic approach that incorporates elements of compassion, empathy and dialog.

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 (

Extrinsic factors regulate partial agonist efficacy of strychnine-sensitive glycine receptors

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.