Vanderboom, Catherine E.

Abstract Compared to urban caregivers, rural caregivers experience greater burdens accessing coordinated care for their loved ones during and after hospital discharge. The impact of technology-enhanced transitional palliative care (TPC) on patient and caregiver outcomes is currently being evaluated in a randomized control trial. This study evaluates resource use and health system costs of this caregiver-focused TPC intervention. Rural caregivers of hospitalized patients in Minnesota, Wisconsin, and Iowa were enrolled in an 8-week intervention consisting of video visits, conducted by a registered nurse, supplemented with phone calls and texts (n=207). Labor costs were estimated using the Bureau for Labor Statistics median hourly rate for a registered nurse and compared to a scenario analysis using a nurse practitioner or social worker wages. Hours spent conducting the visits and charting were calculated using study data. A one-way sensitivity analysis estimated resource use over a range of visits per caregiver and time per visit. Caregivers received 8.8 visits on average over the study period at 45 minutes per visit. In the base case, TPC cost $330 per caregiver facilitated by a registered nurse, compared to $281 and $489 if facilitated by a social worker or nurse practitioner, respectively. The number of visits had the greatest influence on total costs of the intervention (low of $198, high of $463). TPC is a feasible, low cost strategy to enhance caregiver support in rural areas. These results pose an opportunity to consider reimbursement mechanisms to evaluate the sustainability of transitional palliative care interventions to support caregivers.

Managing the complex care needs of seriously ill patients transitioning from hospital to home can have detrimental effects on family caregivers (FCG). Multi-component interventions tailored to FCG needs are most effective at reducing caregiver burden, distress, and depression. However, gaps exist in determining best methods to assess, document, and analyze intervention components for FCGs. Common methods used to capture patient data during transitions in care may not be appropriate or allowed for FCG needs. As such, we present a methodological approach for electronically capturing, reporting, and analyzing multiple intervention components. This approach uses a standardized terminology and pathway for tailoring intervention components in real time while evaluating intervention effects across time. We use examples from a randomized controlled trial to illustrate the benefits of the current approach for analyzing the effectiveness of multi-component interventions in the context of caregiving research.

16 Background: Family caregivers have been shown to have their own unique challenges when caring for someone with advanced cancer. These challenges may be more pronounced among rural caregivers. We present early lessons regarding caregiver needs from an intervention study that provides teaching, guidance, and counseling to rural family caregivers of individuals who received palliative care in the hospital and transitioned home. Methods: A randomized clinical trial is underway to test the efficacy of a care model that focuses on supporting rural family caregivers’ medical needs, self-care, and direct caregiving needs. We have developed a nurse-led, technology-enhanced intervention for family caregivers delivered over 8 weeks after hospital discharge of those receiving palliative care consults. The intervention includes video and phone visits between a palliative care nurse and caregiver. Caregiver needs and nurse strategies are documented using a standardized terminology in an electronic datafile. Results: Preliminary data from 21 family caregivers of individuals with advanced cancer who completed the intervention to date indicate caregivers personally had an average of 2.2 chronic conditions (up to 10) and were taking an average of 3.14 (up to 11) medications. In addition to challenges providing direct care, caregivers reported difficulty managing stress or depression (7/21; 33.3%); issues related to grief (6/21; 28.5%); inadequate sleep and rest (6/21; 28.5%), low or no income or uninsured medical expenses (5/21; 23.8%); and interpersonal challenges within families and with friends (5/21, 23.8%). Conclusions: Preliminary data from our study suggest that assessing the caregiver’s individual needs related to well being and self-care as well as direct caregiving is imperative to delivering caregiver support services that can improve the ability of family caregivers to provide care for their loved ones with advanced cancer. Clinical trial information: NCT03339271.

Abstract To date, nearly 40 U.S. states have passed the Caregiver Advise Record and Enable (CARE) Act to support family caregivers during transitions from hospital to home. These laws require hospitals to: 1) record designated family caregivers’ name in a patient medical records during a hospital stay; 2) inform the caregiver when the patient will be discharged; 3) provide education and instructions on care tasks needed for post-hospital discharge. Transitions from hospital to home are often fraught with adverse event risk and poor continuity of care, especially for rural patients with progressive life-limiting conditions. The CARE ACT has potential to address healthcare system factors that are sometimes attributable to poor transitions in care. Our presentation focuses on preliminary findings from an intervention that provides teaching, guidance, and counseling to caregivers caring for an individual receiving palliative care in the hospital and transitioning home to a rural setting. Findings suggest that the CARE ACT may be vital, but not fully sufficient, for successful transitions. Additional targets for caregiver interventions to improve transitions for this subset of very ill patients include: 1) attend to caregivers’ medical and non-medical needs which may impact their capacity to provide care; 2) advise clinical teams to communicate truthfully about prognosis and likely outcomes when creating post-hospital plans of care; 3) encourage caregivers to identify and engage services early in the transition; 4) urge caregivers to draw on multiple sources for social support. Findings can help optimize the CARE Act implementation, particularly in states with large rural populations.

To be effective, nurse care coordination must be targeted at individuals who will use the service. The purpose of this study was to identify variables that predicted use of care coordination by primary care patients. Data on the potential predictor variables were obtained from patient interviews, the electronic health record, and an administrative database of 178 adults eligible for care coordination. Use of care coordination was obtained from an administrative database. A multivariable logistic regression model was developed using a bootstrap sampling approach. Variables predicting use of care coordination were dependence in both activities of daily living (ADL) and instrumental activities of daily living (IADL; odds ratio [OR] = 5.30, p = .002), independent for ADL but dependent for IADL (OR = 2.68, p = .01), and number of prescription medications (OR = 1.12, p = .002). Consideration of these variables may improve identification of patients to target for care coordination.

Background: Electronic health records (EHRs) provide a clinical view of patient health. EHR data are becoming available in large data sets and enabling research that will transform the landscape of healthcare research. Methods are needed to incorporate wellbeing dimensions and strengths in large data sets. The purpose of this study was to examine the potential alignment of the Wellbeing Model with a clinical interface terminology standard, the Omaha System, for documenting wellbeing assessments. Objective: To map the Omaha System and Wellbeing Model for use in a clinical EHR wellbeing assessment and to evaluate the feasibility of describing strengths and needs of seniors generated through this assessment. Methods: The Wellbeing Model and Omaha System were mapped using concept mapping techniques. Based on this mapping, a wellbeing assessment was developed and implemented within a clinical EHR. Strengths indicators and signs/symptoms data for 5 seniors living in a residential community were abstracted from wellbeing assessments and analyzed using standard descriptive statistics and pattern visualization techniques. Results: Initial mapping agreement was 93.5%, with differences resolved by consensus. Wellbeing data analysis showed seniors had an average of 34.8 (range=22–49) strengths indicators for 22.8 concepts. They had an average of 6.4 (range=4–8) signs/symptoms for an average of 3.2 (range=2–5) concepts. The ratio of strengths indicators to signs/symptoms was 6:1 (range 2.8–9.6). Problem concepts with more signs/symptoms had fewer strengths. Conclusion: Together, the Wellbeing Model and the Omaha System have potential to enable a whole-person perspective and enhance the potential for a wellbeing perspective in big data research in healthcare.

Health care reform focuses on primary care and development of Health Care Homes to improve patient-centered chronic illness care. This pilot study evaluated a community care team intervention that linked chronically ill older patients, support persons, and nurse care coordinators from a Health Care Home with community resources using an adaptation of the Wraparound process. A pragmatic clinical trial design was used. Patient-centered chronic illness care; physical, mental, and social health; service use; and study feasibility were evaluated. Differences between groups were compared using two-sample t, Wilcoxon rank sum, chi-square, or Fisher’s exact tests. At 3 months, the intervention group reported higher patient-centered chronic illness care (mean total Patient Assessment of Chronic Illness Care change scores were 0.39 for the intervention group and −0.11 for the control group, p = .03). Results indicate that the integrated community care team intervention is a promising strategy to support patient-centered chronic illness care.