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 \u3c 0.001), screened (68%–95%; p \u3c 0.001), screened within 24 h (51%–89%; p \u3c 0.001), assessed (72%–95%; p \u3c 0.001), assessed within 24 h (66%–93%; p \u3c 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