Translating Data From an Electronic Prescribing and Medicines Administration System Into Knowledge: Application to Doctor-Nurse Time Discrepancy in Antibiotic Ordering and Administration.

BACKGROUND: Electronic Prescribing and Medicines Administration (EPMA) systems are being widely implemented to facilitate medication safety improvement. However, translating the resulting big data into actionable knowledge has received relatively little attention. OBJECTIVE: The objective of this study was to use routinely collected EPMA data in the study of exact time discrepancy between physicians' order and nurses' administration of systemic antibiotics. We evaluated first and follow-up dose administration and dose intervals and examined multifactorial determinants in ordering and administration explaining potential discrepancy. METHODS: We conducted an observational study of electronic health records for all medical patient stays with antibiotic treatment from January to June 2018 (n=4392) in a large Belgian tertiary care hospital. Using an EPMA system with Barcode Medication Administration, we calculated time discrepancy between order and administration of first doses (n=6233), follow-up doses (n=87 960), and dose intervals. Multiple logistic regression analysis estimated the association between time discrepancy and various determinants in ordering and administration. RESULTS: Time discrepancy between physician order and nurse administration was <30 minutes for 48.7% of first doses and 61.7% of follow-up doses, with large variation across primary diagnoses. Greater dose intervals, oral versus intravenous administration, and order diversion from regular nurse administration rounds showed strongest association with less timely administration. CONCLUSIONS: EPMA systems show huge potential to generate actionable knowledge. Concerning antibiotic treatment, having physicians' orders coincide with regular nurse administration rounds whenever clinically appropriate, further taking contextual factors into account, could potentially improve antibiotic administration timeliness.

Improving hospital nurse staffing during the pandemic: Implementation of the 2019 Fund for Health Care Staff in Belgium.

Chronic hospital nurse understaffing is a pre-existing condition of the COVID-19 pandemic. With nurses on the frontline against the pandemic, safe nurse staffing in hospitals is high on the political agenda of the responsible ministers of Health. This paper presents a recent Belgian policy reform to improve nurse staffing levels. Although the reform was initiated before the pandemic, its roll-out took place from 2020 onwards. Through a substantial increase of the hospital budget, policy makers envisaged to improve patient-to-nurse ratios. Yet, this ambition was considerably toned down during the implementation. Due to a shortage of nurses in the labour market, hospital associations successfully lobbied to allocate part of the budget to hire non-nursing staff. Moreover, other healthcare settings claimed their share of the pie. Elements of international best-practice examples such as ward managers supernumerary to the team and increasing the transparency on staffing decisions were adopted. Other measures, such as mandated patient-to-nurse ratios, nurse staffing committees, or the monitoring or public reporting of ratios, were not retained. Additional measures were taken to safeguard that bedside staffing levels would improve, such as the requirement to demonstrate a net increase in staff to obtain additional budget, staffing plan's approval by local work councils and recommendation to base staff allocation on patient acuity measures. This policy process makes clear that the engagement of budgets is only a first step towards safe staffing levels, which needs to be embedded in a comprehensive policy plan. Future evaluation of bedside nurse staffing levels and nurse wellbeing is needed to conclude about the effectiveness of these measures and the intended and unintended effects they provoked.