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Background: Germline cancer genetic testing has become a standard evidence-based practice, with established risk reduction and screening guidelines for genetic carriers. Access to genetic services is limited in many places, which leaves many genetic carriers unidentified and at risk for late diagnosis of cancers and poor outcomes. This poses a problem for childhood cancer survivors, as this is a population with an increased risk for subsequent malignant neoplasms (SMN) due to cancer therapy or inherited cancer predisposition. The ENGaging and Activating cancer survivors in Genetic services (ENGAGE) study evaluates the effectiveness of an in-home, collaborative PCP model of remote telegenetic services to increase uptake of cancer genetic testing in childhood cancer survivors compared to usual care options for genetic testing., Methods: The ENGAGE study is a 3-arm randomized hybrid type 1 effectiveness and implementation study within the Childhood Cancer Survivor Study population which tests a clinical intervention while gathering information on its delivery during the effectiveness trial and its potential for future implementation among 360 participants. Participants are randomized into three arms. Those randomized to Arm A receive genetic services via videoconferencing, those in Arm B receive these services by phone, and those randomized to Arm C will receive usual care services., Discussion: With many barriers to accessing genetic services, innovative delivery models are needed to address this gap and increase uptake of genetic services. The ENGAGE study evaluates the effectiveness of an adapted model of remote delivery of genetic services to increase the uptake of recommended genetic testing in childhood cancer survivors. This study assesses the uptake in remote genetic services and identify barriers to uptake to inform future recommendations and a theoretically-informed process evaluation which can inform modifications to enhance dissemination beyond this study population and to realize the benefits of precision medicine., Trial Registration: This protocol was registered at clinicaltrials.gov (NCT04455698) on July 2, 2020., (© 2024. The Author(s).)

Purpose: IBM Watson for Oncology trained by Memorial Sloan Kettering (WFO) is a clinical decision support tool designed to assist physicians in choosing therapies for patients with cancer. Although substantial technical and clinical expertise has guided the development of WFO, patients' perspectives of this technology have not been examined. To facilitate the optimal delivery and implementation of this tool, we solicited patients' perceptions and preferences about WFO., Methods: We conducted nine focus groups with 46 patients with breast, lung, or colorectal cancer with various treatment experiences: neoadjuvant/adjuvant chemotherapy, chemotherapy for metastatic disease, or systemic therapy through a clinical trial. In-depth qualitative and quantitative data were collected and analyzed to describe patients' attitudes and perspectives concerning WFO and how it may be used in clinical care., Results: Analysis of the qualitative data identified three main themes: patient acceptance of WFO, physician competence and the physician-patient relationship, and practical and logistic aspects of WFO. Overall, participant feedback suggested high levels of patient interest, perceived value, and acceptance of WFO, as long as it was used as a supplementary tool to inform their physicians' decision making. Participants also described important concerns, including the need for strict processes to guarantee the integrity and completeness of the data presented and the possibility of physician overreliance on WFO., Conclusion: Participants generally reacted favorably to the prospect of WFO being integrated into the cancer treatment decision-making process, but with caveats regarding the comprehensiveness and accuracy of the data powering the system and the potential for giving WFO excessive emphasis in the decision-making process. Addressing patients' perspectives will be critical to ensuring the smooth integration of WFO into cancer care.

Objective: Previous studies demonstrate differing treatment patterns between older and younger patients with breast cancer. To explore the reasons for these disparities we conducted a survey of 28 oncologists specializing in breast cancer., Design and Methods: Twenty-eight medical oncologists from Memorial Sloan-Kettering Cancer Center and the University of California Los Angeles who specialize in the treatment of breast cancer were asked to provide adjuvant treatment recommendations in hypothetical scenarios featuring older patients with high-risk breast cancer. For each of these hypothetical patients, the patient's age was varied over four possible values (70, 75, 80, or 85 years of age) and health and functional status varied across three possible states (perfect health, average health, or major health problems). Survey data were compiled and analyzed to determine the impact of theoretical patient age, baseline health, and functional status on their treatment recommendations., Results: The proportion of oncologists who recommended adjuvant chemotherapy decreased as the patient's age increased or as the patient's functional status and health status decreased. For 96% of physicians (95% CI, 82-100%), patient age influenced chemotherapy recommendations, controlling for health/functional status; the same proportion of respondents were influenced by health/functional status, controlling for patient age. There was increased variability in treatment recommendations as the patient's age increased or functional status and health status decreased., Conclusion: Among these medical oncologists who primarily treat breast cancer adjuvant treatment recommendations vary based on patient age, health, and functional status. Future studies are needed to correlate age, health, and functional status with the risks and benefits of adjuvant therapy so that consensus guidelines can be formed. A more comprehensive baseline assessment of the older patient, such as can be derived from a comprehensive geriatric assessment may be useful in this regard.

Background: Fragmentation across sites of care may impede efficient healthcare delivery., Objectives: The objectives of this study were to evaluate fragmentation of hospital care for chronically ill New York City (NYC) residents and its association with enrollment in the New York State (NYS) Medicaid program., Research Design: We conducted a cross-sectional study using the NYS Department of Health's Statewide Planning and Research Cooperative System discharge database. We identified 53,031 NYC residents admitted 3 or more times to acute care hospitals between 2000 and 2002 with the same principal diagnosis of a specific chronic illness (diabetes, sickle cell anemia, psychosis, substance abuse, cancer, gastrointestinal disease, chronic obstructive pulmonary disease/asthma, coronary artery disease, or congestive heart failure). We also evaluated a larger cohort of 225,421 patients with >or=3 admissions for a specific chronic illness coded as either the principal or a secondary diagnosis. A generalized logit model was used to examine the relationship between fragmentation and each patient's primary insurance adjusted for diagnosis and demographic characteristics., Measures: Fragmentation was characterized as high, moderate, or low based on the number of distinct hospitals a patient visited relative to the patient's total number of hospitalizations over the 3-year interval., Results: Among frequently hospitalized NYC residents with select chronic conditions, 17.1% experienced highly fragmented care. This rate was 9.9% for patients with commercial insurance, 24.4% for those with Medicaid, and 9.7% for those with Medicare. The unadjusted odds ratio describing high fragmentation of Medicaid enrollees compared with commercially insured patients was 3.82 (95% confidence interval [CI], 3.50-4.18) and, although attenuated, remained significant after adjustment for demographic characteristics (odds ratio, 1.33; 95% CI, 1.20-1.47). The strongest predictor of fragmentation was a diagnosis of psychosis (OR, 2.81; 95% CI, 2.43-3.25) or substance abuse (OR, 7.58; 95% CI, 6.55-8.77)., Conclusions: In NYC, Medicaid enrollment is associated with greater fragmentation of hospital care, but this is largely attributable to the preponderance of Medicaid enrollees with diagnoses of psychosis and substance abuse. Strategies to improve the efficiency of healthcare delivery should focus on patients with mental illness who are frequently admitted to general hospitals.