ABSTRACT
BACKGROUND: Dutch hospitals are required to screen older patients for the risk of developing functional decline using the Safety Management System (VMS) which assesses four domains associated with functional decline; fall risk, risk of delirium, malnutrition, and physical impairment. PURPOSE: The aim is twofold, first to compare the VMS frailty instrument as a frailty screener with existing frailty instruments and second to provide an overview of the available evidence. METHODS: We performed a literature search to identify studies that used the VMS instrument as frailty screener to asses frailty or to predict adverse health outcomes in older hospitalized patients. Pubmed, Cinahl, and Embase were searched from January 1st 2008 to December 11th 2023. RESULTS: Our search yielded 603 articles, of which 17 studies with heterogenous populations and settings were included. Using the VMS, frailty was scored in six different ways. The agreement between VMS and other frailty instruments ranged from 57 to 87%. The highest sensitivity and specificity of VMS for frailty were 90% and 67%, respectively. The association of the VMS with outcomes was studied in 14 studies, VMS was predictive for complications, delirium, falls, length of stay, and adverse events. Conflicting results were found for hospital (re)admission, complications, change in living situation, functional decline, and mortality. CONCLUSION: The VMS frailty instrument were studied as a frailty screening instrument in various populations and settings. The value of the VMS instrument as a frailty screener looks promising. Our results suggest that the scoring method of the VMS could be adapted to specific requirements of settings or populations.
ABSTRACT
BACKGROUND: Healthcare professionals are sometimes forced to adjust their work to varying conditions leading to discrepancies between hospital protocols and daily practice. We will examine the discrepancies between protocols, 'Work As Imagined' (WAI), and daily practice 'Work As Done' (WAD) to determine whether these adjustments are deliberate or accidental. The discrepancies between WAI and WAD can be visualised using the Functional Resonance Analysis Method (FRAM). FRAM will be applied to three patient safety themes: risk screening of the frail older patients; the administration of high-risk medication; and performing medication reconciliation at discharge. METHODS: A stepped wedge design will be used to collect data over 16 months. The FRAM intervention consists of constructing WAI and WAD models by analysing hospital protocols and interviewing healthcare professionals, and a meeting with healthcare professionals in each ward to discuss the discrepancies between WAI and WAD. Safety indicators will be collected to monitor compliance rates. Additionally, the potential differences in resilience levels among nurses before and after the FRAM intervention will be measured using the Employee Resilience Scale (EmpRes) questionnaire. Lastly, we will monitor whether gaining insight into differences between WAI and WAD has led to behavioural and organisational change. DISCUSSION: This article will assess whether using FRAM to reveal possible discrepancies between hospital protocols (WAI) and daily practice (WAD) will improve compliance with safety indicators and employee resilience, and whether these insights will lead to behavioural and organisational change. TRIAL REGISTRATION: Netherlands Trial Register NL8778; https://www.trialregister.nl/trial/8778 . Registered 16 July 2020. Retrospectively registered.
