RESUMO
BACKGROUND: Nursing care is a critical determinant of patient outcomes in the intensive care unit (ICU). Most studies of nursing care have focused on nursing characteristics aggregated across the ICU (eg, unit-wide nurse-to-patient ratios, education, and working environment). In contrast, relatively little work has focused on the influence of individual nurses and their characteristics on patient outcomes. Such research could provide granular information needed to create evidence-based nurse assignments, where a nurse's unique skills are matched to each patient's needs. To date, research in this area is hindered by an inability to link individual nurses to specific patients retrospectively and at scale. OBJECTIVE: This study aimed to determine the feasibility of using nurse metadata from the electronic health record (EHR) to retrospectively determine nurse-patient assignments in the ICU. METHODS: We used EHR data from 38 ICUs in 18 hospitals from 2018 to 2020. We abstracted data on the time and frequency of nurse charting of clinical assessments and medication administration; we then used those data to iteratively develop a deterministic algorithm to identify a single ICU nurse for each patient shift. We examined the accuracy and precision of the algorithm by performing manual chart review on a randomly selected subset of patient shifts. RESULTS: The analytic data set contained 5,479,034 unique nurse-patient charting times; 748,771 patient shifts; 87,466 hospitalizations; 70,002 patients; and 8,134 individual nurses. The final algorithm identified a single nurse for 97.3% (728,533/748,771) of patient shifts. In the remaining 2.7% (20,238/748,771) of patient shifts, the algorithm either identified multiple nurses (4,755/748,771, 0.6%), no nurse (14,689/748,771, 2%), or the same nurse as the prior shift (794/748,771, 0.1%). In 200 patient shifts selected for chart review, the algorithm had a 93% accuracy (ie, correctly identifying the primary nurse or correctly identifying that there was no primary nurse) and a 94.4% precision (ie, correctly identifying the primary nurse when a primary nurse was identified). Misclassification was most frequently due to patient transitions in care location, such as ICU transfers, discharges, and admissions. CONCLUSIONS: Metadata from the EHR can accurately identify individual nurse-patient assignments in the ICU. This information enables novel studies of ICU nurse staffing at the individual nurse-patient level, which may provide further insights into how nurse staffing can be leveraged to improve patient outcomes.
RESUMO
BACKGROUND: Despite impressive reductions in infectious disease burden within Sub-Saharan Africa (SSA), half of the top ten causes of poor health or death in SSA are communicable illnesses. With emerging and re-emerging infections affecting the region, the possibility of healthcare-acquired infections (HAIs) being transmitted to patients and healthcare workers, especially nurses, is a critical concern. Despite infection prevention and control (IPC) evidence-based practices (EBP) to minimize the transmission of HAIs, many healthcare systems in SSA are challenged to implement them. The purpose of this review is to synthesize and critique what is known about implementation strategies to promote IPC for nurses in SSA. METHODS: The databases, PubMed, Ovid/Medline, Embase, Cochrane, and CINHAL, were searched for articles with the following criteria: English language, peer-reviewed, published between 1998 and 2018, implemented in SSA, targeted nurses, and promoted IPC EBPs. Further, 6241 search results were produced and screened for eligibility to identify implementation strategies used to promote IPC for nurses in SSA. A total of 61 articles met the inclusion criteria for the final review. The articles were evaluated using the Joanna Briggs Institute's (JBI) quality appraisal tools. Results were reported using PRISMA guidelines. RESULTS: Most studies were conducted in South Africa (n = 18, 30%), within the last 18 years (n = 41, 67%), and utilized a quasi-experimental design (n = 22, 36%). Few studies (n = 14, 23%) had sample populations comprising nurses only. The majority of studies focused on administrative precautions (n = 36, 59%). The most frequent implementation strategies reported were education (n = 59, 97%), quality management (n = 39, 64%), planning (n = 33, 54%), and restructure (n = 32, 53%). Penetration and feasibility were the most common outcomes measured for both EBPs and implementation strategies used to implement the EBPs. The most common MAStARI and MMAT scores were 5 (n = 19, 31%) and 50% (n = 3, 4.9%) respectively. CONCLUSIONS: As infectious diseases, especially emerging and re-emerging infectious diseases, continue to challenge healthcare systems in SSA, nurses, the keystones to IPC practice, need to have a better understanding of which, in what combination, and in what context implementation strategies should be best utilized to ensure their safety and that of their patients. Based on the results of this review, it is clear that implementation of IPC EBPs in SSA requires additional research from an implementation science-specific perspective to promote IPC protocols for nurses in SSA.