Background: Frailty is characterized by loss of biological reserves and is associated with an increased risk of adverse health outcomes. Frailty can be operationalized using a Frailty Index (FI) based on the accumulation of health deficits; items under health evaluation in the well-established Comprehensive Geriatric Assessment (CGA) have been used to generate an FI-CGA. Traditionally, constructing the FI-CGA has relied on paper-based recording and manual data processing. As this can be time-consuming and error-prone, it limits widespread uptake of this proven type of frailty assessment. Here, we report the development of an electronic tool, the eFI-CGA, for use on personal computers by frontline healthcare providers, to collect CGA data and automate FI-CFA calculation. The ultimate goal is to support early identification and management of frailty at points-of-care, and make uptake in Electronic Medical Records (EMR) feasible and transparent. Methods: An electronic CGA (eCGA) form was implemented to operate on Microsoft's WinForms platform and coded using C# programming language. Users complete the eCGA form, from which items under the CGA evaluation are automatically retrieved and processed to output an eFI-CGA score. A user-friendly interface and secured data saving methods were implemented. The software was debugged and tested using systematically designed simulation data, addressing different logic, syntax, and application errors, and then tested with clinical assessment. The user manual and manual scoring were used as ground truth to compare eFI-CGA input and automated eFI score calculations. Frontline health-provider user feedback was incorporated to improve the end-user experience. Sepehri et al. Standalone eFI-CGA Results: The Standalone eFI-CGA software tool was developed and optimized for use on personal computers. The user interface adapted the design of paper-based CGA form to facilitate familiarity for clinical users. Compared to known scores, the software tool generated eFI-CGA scores with 100% accuracy to four decimal places. The eFI-CGA allowed secure data storage and retrieval of multiple types, including user input, completed eCGA form, coded items, and calculated eFI-CGA scores. It also permitted recording of actions requiring clinical follow-up, facilitating care planning. Application bugs were identified and resolved at various stages of the implementation, resulting in efficient system performance. Discussion: Accurate, robust, and reliable computerized frailty assessments are needed to promote effective frailty assessment and management, as a key tool in health care systems facing up to frailty. Our research has enabled the delivery of the standalone eFI-CGA software technology to empower effective frailty assessment and management by various healthcare providers at points-of-care, facilitating integrated care of older adults.
Frailty is characterized by loss of biological reserves across multiple systems and associated with increased risks of adverse outcomes. A Frailty Index (FI) constructed using items from the Comprehensive Geriatric Assessment (CGA) has been validated in geriatric medicine settings to estimate the level of frailty. Traditionally, the CGA used a paper form and the CGA-based FI calculation was a manual process. Here, we reported building of an electronic version of the assessment on personal computers (PC), i.e., standalone eFI-CGA, to benefit frailty assessment at points of care. The eFI-CGA was implemented as a software tool on the WinForms platform. It automated the FI calculation by counting deficits accumulation across multiple domains assessing medical conditions, cognition, balance, and dependency of activities of daily living. Debugging, testing, and optimization were performed to enhance the software performance with respect to automation accuracy (processing algorithm), friendly user interface (user manual and feedback), and data quality control (missing data and value constraints). Systematically-designed simulation dataset and anonymous real-world cases were both applied. The optimized assessment tool resulted in fast and convenient conductance of the CGA, and a 100% accuracy rate of the eFI-CGA automation for up to four decimals. The stand-alone eFI-CGA implementation has provided a PC-based software tool for use by geriatricians and primary and acute care providers, benefiting early detection and management of frailty at points of care for older adults.
Frailty Index (FI), polypharmacy and cognition status are significant health concerns in older adults. We conducted this study to investigate the interplay of frailty, polypharmacy, and cognition, in determining health outcomes. InterRAI Residential Care (RAI-RC MDS2.0) data were retrieved from residential care homes in Surrey, BC, Canada. Older residents (65+ years) who had RAI-RC records between 2016 and 2018 were used in the analysis (n=976). A deficit accumulation-based FI was generated using 36 variables. Information on polypharmacy and cognition were obtained by accounting the total number of medications and the cognitive performance scale. Information on falls, emergency visits, and mortality were followed. Multivariate Cox proportional hazard models were used to examine the effects of these variables on different outcomes. The FI showed a near Gaussian distribution (median= 0.370 mean= 0.372 SD= 0.143), and increased linearly with age on a logarithm scale (R=0.75, p<0.001). Residents with cognitive impairment showed a higher level of the FI (KW= 863.3, p<0.001). A higher FI was associated with an increased risk of death (HR=15.2 p=0.006) and emergency visits (HR=2.72 p=0.048), adjusting for age, sex, medications, and education levels. Frailty, polypharmacy, and cognition levels are associated and have interactive effects on health outcomes. Ongoing research is to validate the findings with large samples in different health settings, and to understand the underlying processes of the effect. The close relationships between frailty, polypharmacy, and cognition with health outcomes call for effective integrated strategies for healthcare of older adults with multiple complex health problems.
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