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Background
The complex work of public health nurses (PHNs) specifically related to mental health assessment, intervention, and outcomes makes it difficult to quantify and evaluate the improvement in client outcomes attributable to their interventions.
Objectives
We examined heterogeneity across parents of infants served by PHNs receiving different interventions, compared the ability of traditional propensity scoring methods versus energy-balancing weight (EBW) techniques to adjust for the complex and stark differences in baseline characteristics among those receiving different interventions, and evaluated the causal effects of the quantity and variety of PHN interventions on client health and social outcomes.
Methods
This retrospective study of 4,109 clients used existing Omaha System data generated during the routine documentation of PHN home visit data. We estimated the effects of intervention by computing and comparing weighted averages of the outcomes within the different treatment groups using two weighting methods: (a) inverse probability of treatment (propensity score) weighting and (b) EBWs.
Results
Clients served by PHNs differed in baseline characteristics with clients with more signs/symptoms. Both weighting methods reduced heterogeneity in the sample. EBWs were more effective than inverse probability of treatment weighting in adjusting for multifaceted confounding and resulted in close balance of 105 baseline characteristics. Weighting the sample changed outcome patterns, especially when using EBWs. Clients who received more PHN interventions and a wider variety of them had improved knowledge, behavior, and status outcomes with no plateau over time, whereas the unweighted sample showed plateaus in outcomes over the course of home-visiting services.
Discussion
Causal analysis of PHN-generated data demonstrated PHN intervention effectiveness for clients with mental health signs/symptoms. EBWs are a promising tool for evaluating the true causal effect of PHN home-visiting interventions.
The poor usability of electronic health records contributes to increased nurses' workload, workarounds, and potential threats to patient safety. Understanding nurses' perceptions of electronic health record usability and incorporating human factors engineering principles are essential for improving electronic health records and aligning them with nursing workflows. This review aimed to synthesize studies focused on nurses' perceived electronic health record usability and categorize the findings in alignment with three human factor goals: satisfaction, performance, and safety. This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Five hundred forty-nine studies were identified from January 2009 to June 2023. Twenty-one studies were included in this review. The majority of the studies utilized reliable and validated questionnaires (n = 15) to capture the viewpoints of hospital-based nurses (n = 20). When categorizing usability-related findings according to the goals of good human factor design, namely, improving satisfaction, performance, and safety, studies used performance-related measures most. Only four studies measured safety-related aspects of electronic health record usability. Electronic health record redesign is necessary to improve nurses' perceptions of electronic health record usability, but future efforts should systematically address all three goals of good human factor design. 
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