Limiting the number of open charts does not impact wrong patient order entry in the emergency department.

OBJECTIVE: We sought to examine the impact of limiting the number of open active charts on wrong patient order entry events among 13 emergency departments (EDs) in a large integrated health system. METHODS: A retrospective chart review of all orders placed between September 2017 and September 2019 was conducted. The rate of retract and reorder events was analyzed with no overlap in both the period pre- and post-intervention period. Secondary analysis of error rate by clinician type, clinician patient load, and time of day was performed. RESULTS: The order retraction rate was not improved pre- and post-intervention. Retraction rates varied by clinician type with residents retracting more often than physicians (odds ratio [OR] = 1.443 [1.349, 1.545]). Advanced practice providers also showed a slightly higher rate than physicians (OR = 1.114 [1.071, 1.160]). Pharmacists showed very low rates compared to physicians (OR = 0.191 [0.048, 0.764]). Time of day and staffing ratios appear to be a factor with wrong patient order entry rates slightly lower during the night (1900-0700) than the day (OR 0.958 [0.923, 0.995]), and increasing slightly with every additional patient per provider (OR 1.019 [1.005, 1.032]). The Academic Medical Center had more retractions that the other EDs. OR for the various ED types compared to the Academic Medical Center included Community (OR 0.908 [0.859, 0.959]), Teaching Hospitals (OR 0.850 [0.802, 0.900]), and Freestanding (OR 0.932 [0.864, 1.006]). CONCLUSIONS: Limiting the number of open active charts from 4 to 2 did not significantly reduce the incidence of wrong patient order entry. Further investigation into other factors contributing to order entry errors is warranted.

Telemedicine/Virtual ICU: Where Are We and Where Are We Going?

Intensive care unit telemedicine (tele-ICU) is technology enabled care delivered from off-site locations that was developed to address the increasing complexity of patients and insufficient supply of intensivists. Although tele-ICU deployment is increasing, it continues to cover only a small proportion of ICU patients. This is primarily due to expense, with first-year costs exceeding $50,000 per bed. Meta-analyses of outcomes indicate survival benefits and quality improvements, albeit with significant heterogeneity. Depending on the context, a wide range of estimated incremental cost-effectiveness ratios reflects variable effects on cost and outcomes, such as mortality or length of stay. Tele-ICUs may fit within a hybrid model of care to complement high-intensity ICU staff coverage. However, more research is required to foster consensus and determine best practices. This review summarizes data on tele-ICU structure, operations, outcomes, and costs. Evidence was extracted from meta-analyses, with secondary data from Cleveland Clinic's tele-ICU experience.