Is meal order timing and flexibility key to improving patient satisfaction with hospital foodservice?

AIM: The aim of this study was to retrospectively evaluate and compare patient foodservice (FS) satisfaction using a validated tool and consistent methodology in an acute health service for four different FS models as the organisation transitioned through traditional model (TM), choice at point of service (CaPOS), bedside menu ordering systems (BMOS) and room service (RS) from 2013 to 2016. METHODS: Patient satisfaction data were collected using the Acute Care Hospital Foodservice Patient Satisfaction Questionnaire. For the purposes of this study, patients' rating of their overall experience with FS (very good, good, okay, poor or very poor) was compared for each site and model. RESULTS: Satisfaction was significantly higher in the CaPOS and RS models compared with TM. BMOS, although somewhat higher, was not shown to be significantly higher than TM. The RS model was significantly higher than BMOS, but there was no significant difference observed between RS and CaPOS. CONCLUSION: FS models that support patient flexibility and meal ordering closer to the meal delivery time (as seen with RS and CaPOS) show higher patient satisfaction among hospital patients. It is recommended that sites consistently opt to include patient satisfaction as part of routine auditing. This would enable clear conclusions to be drawn regarding best practice FS models, based on specific and individual hospital requirements.

Implementation of an electronic solution to improve malnutrition identification and support clinical best practice.

BACKGROUND: Routine malnutrition risk screening of patients is critical for optimal care and comprises part of the National Australian Hospital Standards. Identification of malnutrition also ensures reimbursement for hospitals to adequately treat these high-risk patients. However, timely, accurate screening, assessment and coding of malnutrition remains suboptimal. The present study aimed to investigate manual and digital interventions to overcome barriers to malnutrition identification for improvements in the hospital setting. METHODS: Retrospective reporting on malnutrition identification processes was conducted through two stages: (1) manual auditing intervention and (2) development of a digital solution - the electronic malnutrition management solution (eMS). Repeated process audits were completed at approximately 6-monthly intervals through both stages between 2016 and 2019 and the results were analysed. In Stage 2, time investment and staff adoption of the digital solution were measured. RESULTS: Overall, the combined effect of both regular auditing and use of the eMS resulted in statistically significant improvements across all six key measures: patients identified (97%-100%; p < 0.001), screened (68%-95%; p < 0.001), screened within 24 h (51%-89%; p < 0.001), assessed (72%-95%; p < 0.001), assessed within 24 h (66%-93%; p < 0.001) and coded (81%-100%; p = 0.017). The eMS demonstrated a reduction in screening time by over 60% with user adoption 100%. Data analytics enabled automated, real-time auditing with a 95% reduction in time taken to audit. CONCLUSIONS: A single digital solution for management of malnutrition and automation of auditing demonstrated significant improvements where manual or combinations of manual and electronic systems continue to fall short.