Development and preliminary usability testing of an electronic conversation guide incorporating patient values and prognostic information in preparation for older people's decision-making near the end of life.

Initiating end-of-life conversations can be daunting for clinicians and overwhelming for patients and families. This leads to delays in communicating prognosis and preparing for the inevitable in old age, often generating potentially harmful overtreatment and poor-quality deaths. We aimed to develop an electronic resource, called Communicating Health Alternatives Tool (CHAT) that was compatible with hospital medical records software to facilitate preparation for shared decision-making across health settings with older adults deemed to be in the last year of life. The project used mixed methods including: literature review, user-directed specifications, web-based interface development with authentication and authorization; clinician and consumer co-design, iterative consultation for user testing; and ongoing developer integration of user feedback. An internet-based conversation guide to facilitate clinician-led advance care planning was co-developed covering screening for short-term risk of death, patient values and preferences, and treatment choices for chronic kidney disease and dementia. Printed summary of such discussion could be used to begin the process in hospital or community health services. Clinicians, patients, and caregivers agreed with its ease of use and were generally accepting of its contents and format. CHAT is available to health services for implementation in effectiveness trials to determine whether the interaction and documentation leads to formal decision-making, goal-concordant care, and subsequent reduction of unwanted treatments at the end of life.

The Feasibility of Deriving the Electronic Frailty Index from Australian General Practice Records.

Purpose: Frailty is a prevalent condition in older adults. Identification of frailty using an electronic Frailty Index (eFI) has been successfully implemented across general practices in the United Kingdom. However, in Australia, the eFI remains understudied. Therefore, we aimed to (i) examine the feasibility of deriving an eFI from Australian general practice records and (ii) describe the prevalence of frailty as measured by the eFI and the prevalence with socioeconomic status and geographic remoteness. Participants and Methods: This retrospective analysis included patients (≥70 years) attending any one of >700 general practices utilizing the Australian MedicineInsight data platform, 2017-2018. A 36-item eFI was derived using standard methodology, with frailty classified as mild (scores 0.13-0.24); moderate (0.25-0.36) or severe (≥0.37). Socioeconomic status (Socio-Economic Indexes for Areas (SEIFA) index)) and geographic remoteness (Australian Statistical Geography Standard (ASGC) remoteness areas) were also examined. Results: In total, 79,251 patients (56% female) were included, mean age 80.0 years (SD 6.5); 37.4% (95% CI 37.0-37.7) were mildly frail, 16.7% (95% CI 16.4-16.9) moderately frail, 4.8% (95% CI 4.7-5.0) severely frail. Median eFI score was 0.14 (IQR 0.08 to 0.22); maximum eFI score was 0.69. Across all age groups, moderate and severe frailty was significantly more prevalent in females (P < 0.001). Frailty severity increased with increasing age (P < 0.001) and was strongly associated with socioeconomic disadvantage (P < 0.001) but not with geographic remoteness. Conclusion: Frailty was identifiable from routinely collected general practice data. Frailty was more prevalent in socioeconomically disadvantaged groups, women and older patients and existed in all levels of remoteness. Routine implementation of an eFI could inform interventions to prevent or reduce frailty in all older adults, regardless of location.

How Do Patients with Life-Limiting Illness and Caregivers Want End-Of-Life Prognostic Information Delivered? A Pilot Study.

We aimed to identify the level of prognostic disclosure, type of prognostic information and delivery format of prognostic communication that older adults diagnosed with a life-limiting illness or caregivers prefer to receive. We developed and pilot tested an open-ended survey to 15 older patients and caregivers who had experience in health services for life-limiting illness either for a relative, friend or themselves. Five hypothetical clinical scenarios of prognostic options were presented to ascertain preferences. The preferred format to receive prognostic information was verbal delivery by the clinician with a written summary. Photos and videos were less favoured, and a table with numbers/percentages was least preferred. Distress levels to the prognostic scenarios were low, with the exception of a photo. We conclude that older patients/caregivers want end-of-life prognostic information delivered the traditional way, verbally by clinicians. Options to deliver prognostic information may vary across patient groups but empower clinicians in introducing end-of-life discussions with patients/caregivers. Our study illustrates the feasibility of involving terminal patients and caregivers in research that contributes to eliciting prognostic preferences. Further research is needed to understand whether the prognostic preferences of hospitalized patients with life-limiting illness differ.

Which frailty scale for patients admitted via Emergency Department? A cohort study.

OBJECTIVES: To determine the prevalence of frailty in Emergency Departments (EDs); examine the ability of frailty to predict poor outcomes post-discharge; and identify the most appropriate instrument for routine ED use. METHODS: In this prospective study we simultaneously assessed adults 65+yrs admitted and/or spent one night in the ED using Fried, the Clinical Frailty Scale (CFS), and SUHB (Stable, Unstable, Help to walk, Bedbound) scales in four Australian EDs for rapid recognition of frailty between June 2015 and March 2016. RESULTS: 899 adults with complete follow-up data (mean (SD) age 80.0 (8.3) years; female 51.4%) were screened for frailty. Although different scales yielded vastly different frailty prevalence (SUHB 9.7%, Fried 30.4%, CFS 43.7%), predictive discrimination of poor discharge outcomes (death, poor self-reported health/quality of life, need for community services post-discharge, or reattendance to ED after the index hospitalization) for all identical final models was equivalent across all scales (AUROC 0.735 for Fried, 0.730 for CFS and 0.720 for SUHB). CONCLUSION: This study confirms that screening for frailty in older ED patients can inform prognosis and target discharge planning including community services required. The CFS was as accurate as the Fried and SUHB in predicting poor outcomes, but more practical for use in busy clinical environments with lower level of disruption. Given the limitations of objectively measuring frailty parameters, self-report and clinical judgment can reliably substitute the assessment in EDs. We propose that in a busy ED environment, frailty scores could be used as a red flag for poor follow-up outcome.