A multicenter observational study investigating care errors, staffing levels, and workload in small animal intensive care units. Issue 5 (12th September 2020)

• Record Type: Journal Article
• Authors: Hayes, Galina M.; Bersenas, Alexa M.; Mathews, Karol; Lane, William G.; LaLonde‐Paul, Denise F.; Steele, Andrea; Avellaneda, Ana
• Is Part Of: Journal of veterinary emergency and critical care. Volume 30:Issue 5(2020)
• Page Start: 517
• Page End: 524
• Publication Date: 2020-09-12
• Subjects: ICU -- medical errors -- staffing -- veterinary; Veterinary emergencies -- Periodicals; Veterinary critical care -- Periodicals; 636.089
• DOI: 10.1111/vec.12991
• Languages: English
• ISSNs: 1479-3261

Abstract

Abstract: Objective: To investigate associations among care errors, staffing, and workload in small animal ICUs. Design: Multicenter observational cohort study conducted between January 2017 and September 2018. Setting: Three small animal teaching hospital ICUs. Animals: None. Interventions: None. Measurements and main results: Data on patient numbers, illness severity (assesed via the acute patient physiologic and laboratory evaluation [APPLE] score), care burden, staffing levels, technician experience/education level, and care errors were collected at each study site. Care errors were categorized as major (unanticipated arrest or death; patient endangerment through IV line, arterial catheter, chest tube or other invasive device mismanagement, or errors in drug calculation/administration) or minor. Median patient:technician ratio was 4.3 (range: 1–18). Median patient illness severity was 15.1 (4.7–27.1) APPLE score units. A total of 221 major and 3, 317 minor errors were observed over the study period. The odds of a major error increased by an average of 11% (odds ratio [OR] = 1.11; 95% confidence interval [CI], 1.02–1.20; P = 0.012) for each 1 patient increase in the patient:technician ratio after averaging by ICU location. The major error incident rate ratio was 2.53 (95% CI, 1.84–3.54; P < 0.001) for patient:technician ratios of >4.0 compared with ≤4.0. The odds of a major error increased by 0.5% per total unit APPLE score increase (OR = 1.005; 95% CI, 1.002–1.007; P < 0.001). The major error incident rate ratio was 1.71 (95% CI, 1.30–2.25; P < 0.001) for APPLEfast :technician ratios of >73 compared with ≤73. The odds of a major error decreased by 2% (OR = 0.98; 95% CI, 0.97–0.99; P = 0.01) for each year increase in total technician years of ICU work experience. Conclusions: Substantial reductions in major care errors may be achieved by maintaining ICU patient:technician ratios at ≤4. Technician experience and total unit burden of patient illness severity are also associated with error incidence, and should be taken into consideration when scheduling staff.