Use of Telephone- and Internet-Based Support to Elicit and Address Financial Abuse and Mismanagement in Dementia: Experiences from the Care Ecosystem Study

Background: Financial mismanagement and abuse in dementia have serious consequences for patients and their families. Vulnerability to these outcomes reflects both patient and contextual factors. Objective: Our study aimed to assess how multidisciplinary care coordination programs assist families in addressing psychosocial vulnerabilities and accessing needed resources. Methods: Our study was embedded in a clinical trial of the Care Ecosystem, a telephone- and internet-based supportive care intervention for patients with dementia and caregivers. This program is built around the role of the Care Team Navigator (CTN), an unlicensed dementia care guide who serves as the patient and caregiver’s primary point of contact, screening for common problems and providing support. We conducted a qualitative analysis of case summaries from a subset of 19 patient/caregiver dyads identified as having increased risk for financial mismanagement and abuse, to examine how Care Ecosystem staff identified vulnerabilities and provided support to patients and families. Results: CTNs elicited patient and caregiver needs using templated conversations to address common financial and legal planning issues in dementia. Sources of financial vulnerability included changes in patients’ behavior, caregiver burden, intrafamily tension, and confusion about resources to facilitate end-of-life planning. The Care Ecosystem staff’s rapport with their dyads helped them address these issues by providing emotional support, information on how to access financial, medical, and legal resources, and improving intra-familial communication. Conclusion: The Care Ecosystem offers a scalable way to address vulnerabilities to financial mismanagement and abuse in patients and caregivers through coordinated care by unlicensed care guides supported by a multidisciplinary team.

Early palliative/supportive care in acute myeloid leukaemia allows low aggression end-of-life interventions: observational outpatient study

ObjectivesEarly palliative supportive care has been associated with many advantages in patients with advanced cancer. However, this model is underutilised in patients with haematological malignancies. We investigated the presence and described the frequency of quality indicators for palliative care and end-of-life care in a cohort of patients with acute myeloid leukaemia receiving early palliative supportive care.MethodsThis is an observational, retrospective study based on 215 patients consecutively enrolled at a haematology early palliative supportive care clinic in Modena, Italy. Comprehensive hospital chart reviews were performed to abstract the presence of well-established quality indicators for palliative care and for aggressiveness of care near the end of life.Results131 patients received a full early palliative supportive care intervention. All patients had at least one and 67 (51%) patients had four or more quality indicators for palliative care. Only 2.7% of them received chemotherapy in the last 14 days of life. None underwent intubation or cardiopulmonary resuscitation and was admitted to intensive care unit during the last month of life. Only 4% had either multiple hospitalisations or two or more emergency department access. Approximately half of them died at home or in a hospice. More than 40% did not receive transfusions within 7 days of death. The remaining 84 patients, considered late referrals to palliative care, demonstrated sensibly lower frequencies of the same indicators.ConclusionsPatients with acute myeloid leukaemia receiving early palliative supportive care demonstrated high frequency of quality indicators for palliative care and low rates of treatment aggressiveness at the end of life.

Center-Specific Modeling Predicts Cancer Trial Accrual More Accurately Than Investigators and Random Effects Modeling at 16 Cancer Centers

PURPOSE Clinical trials often exceed their anticipated enrollment periods, and study sites often do not meet accrual goals. We previously reported the development and validation of a single-site accrual prediction model. Here, we describe the expansion of this methodology at 16 cancer centers (CCs) and compare an overall model versus site-specific models. METHODS This retrospective cohort study used data from treatment and supportive care intervention studies permanently closed to accrual between 2009 and 2015 at 16 United States–based CCs. Center and ClinicalTrials.gov data were used to generate both site-specific and random effects mixed models (random effect: institution). Accrual predictions were generated from each model and compared with the accrual prediction of the disease team (DT). RESULTS Sixteen institutions submitted 5,787 eligible trials (range, 93 to 697 trials per institution). Local accrual ranged from 363 to 6,716 participants; 1,053 studies (18%) accrued no participants. Actual average accrual was 8.5 participants (median, four participants). Site-specific models predicted accrual at 99% of actual and correctly predicted whether a study would accrue four or more participants 73% of the time versus DT prediction of 58%. Correlation at the category level was 30%; model sensitivity and specificity were 83% and 62%, respectively. The overall model predicted accrual 93% of actual and correctly predicted accrual of four or more participants 66% of the time, with a correlation at the category level of 28%. CONCLUSION Both regression models predicted clinical trial accrual at least as or more accurately than DT at all but one center. Site-specific models generally performed slightly better than the random effects model. This study confirms the previous finding that this method is an accurate and objective metric that can be easily implemented to improve clinical research resource allocation across multiple centers.