Evaluating the Impact of Smartphones on Nursing Workflow: Lessons Learned.

ABSTRACT: Although smartphone use in the workplace by physicians has been well documented, such use by nurses warrants further examination. In particular, there is a lack of research regarding the effects of smartphone use on nursing efficiency and workflow satisfaction. Our organization developed a pilot program to introduce the use of hospital-issued smartphones by direct care nurses in the pediatric ICU (PICU) and a satellite ED and created an implementation team to carry this out. Our research team thought it important to measure and evaluate nursing efficiency and workflow both before and after these phones were issued. The original plan included three primary measures: pre- and postimplementation surveys (both units), time-on-task studies (both units), and interruption observations (PICU only). Because of technical difficulties, the PICU pilot arm was abandoned after the smartphones were introduced. The ED arm completed the postimplementation time-on-task studies and the postimplementation survey nine months after implementation. The postimplementation survey results showed that nurses preferred other methods of communication over smartphones, and smartphones were scored lower than all other forms of communication for ease of integration into the workflow. Time-on-task results indicated texting was faster with smartphones than it was when using T9 texting (predictive texting) with the wireless Ascom phones in the PICU. Making calls with the smartphone took ED nurses significantly longer, and many preferred their traditional communication methods. Further research is needed to determine whether smartphones can be optimized to enhance nursing workflow, increase efficiency, and improve patient outcomes. This article provides vital information for nurses and others considering a transition to the use of smartphones or similar devices in the workplace.

Utilization and effects of mobile electronic clinical decision support on pediatric asthma care quality in the emergency department and inpatient setting.

OBJECTIVE: To determine utilization and impacts of a mobile electronic clinical decision support (mECDS) on pediatric asthma care quality in emergency department and inpatient settings. METHODS: We conducted an observational study of a mECDS tool that was deployed as part of a multi-dimensional, national quality improvement (QI) project focused on pediatric asthma. We quantified mECDS utilization using cumulative screen views over the study period in the city in which each participating site was located. We determined associations between mECDS utilization and pediatric asthma quality metrics using mixed-effect logistic regression models (adjusted for time, site characteristics, site-level QI project engagement, and patient characteristics). RESULTS: The tool was offered to clinicians at 75 sites and used on 286 devices; cumulative screen views were 4191. Children's hospitals and sites with greater QI project engagement had higher cumulative mECDS utilization. Cumulative mECDS utilization was associated with significantly reduced odds of hospital admission (OR: 0.95, 95% CI: 0.92-0.98) and higher odds of caregiver referral to smoking cessation resources (OR: 1.08, 95% CI: 1.01-1.16). DISCUSSION: We linked mECDS utilization to clinical outcomes using a national sample and controlling for important confounders (secular trends, patient case mix, and concomitant QI efforts). We found mECDS utilization was associated with improvements in multiple measures of pediatric asthma care quality. CONCLUSION: mECDS has the potential to overcome barriers to dissemination and improve care on a broad scale. Important areas of future work include improving mECDS uptake/utilization, linking clinicians' mECDS usage to clinical practice, and studying mECDS's impacts on other common pediatric conditions.

Frontiers in human factors: embedding specialists in multi-disciplinary efforts to improve healthcare.

Despite the application of a huge range of human factors (HF) principles in a growing range of care contexts, there is much more that could be done to realize this expertise for patient benefit, staff well-being and organizational performance. Healthcare has struggled to embrace system safety approaches, misapplied or misinterpreted others, and has stuck to a range of outdated and potentially counter-productive myths even has safety science has developed. One consequence of these persistent misunderstandings is that few opportunities exist in clinical settings for qualified HF professionals. Instead, HF has been applied by clinicians and others, to highly variable degrees-sometimes great success, but frequently in limited and sometimes counter-productive ways. Meanwhile, HF professionals have struggled to make a meaningful impact on frontline care and have had little career structure or support. However, in the last few years, embedded clinical HF practitioners have begun to have considerable success that are now being supported and amplified by professional networks. The recent coronavirus disease of 2019 (COVID-19) experiences confirm this. Closer collaboration between healthcare and HF professionals will result in significant and ultimately beneficial changes to both professions and clinical care.

Doctors documenting: an ethnographic and informatics approach to understanding attending physician documentation in the pediatric emergency department.

OBJECTIVE: The pediatric emergency department is a highly complex and evolving environment. Despite the fact that physicians spend a majority of their time on documentation, little research has examined the role of documentation in provider workflow. The aim of this study is to examine the task of attending physician documentation workflow using a mixed-methods approach including focused ethnography, informatics, and the Systems Engineering Initiative for Patient Safety (SEIPS) model as a theoretical framework. MATERIALS AND METHODS: In a 2-part study, we conducted a hierarchical task analysis of patient flow, followed by a survey of documenting ED providers. The second phase of the study included focused ethnographic observations of ED attendings which included measuring interruptions, time and motion, documentation locations, and qualitative field notes. This was followed by analysis of documentation data from the electronic medical record system. RESULTS: Overall attending physicians reported low ratings of documentation satisfaction; satisfaction after each shift was associated with busyness and resident completion. Documentation occurred primarily in the provider workrooms, however strategies such as bedside documentation, dictation, and multitasking with residents were observed. Residents interrupted attendings more often but also completed more documentation actions in the electronic medical record. DISCUSSION: Our findings demonstrate that complex work processes such as documentation, cannot be measured with 1 single data point or statistical analysis but rather a combination of data gathered from observations, surveys, comments, and thematic analyses. CONCLUSION: Utilizing a sociotechnical systems framework and a mixed-methods approach, this study provides a holistic picture of documentation workflow. This approach provides a valuable foundation not only for researchers approaching complex healthcare systems but also for hospitals who are considering implementing large health information technology projects.

Asking the Right Questions-Human Factors Considerations for Telemedicine Design.

PURPOSE OF REVIEW: The goal of this paper was to provide a narrative review of human factors considerations for telemedicine. It also sought to provide readers a foundation of human factors thinking and methods that could be employed within their own practice. RECENT FINDINGS: There are only a handful of articles that discuss the importance of user-centered design and human factors principles in relation to telemedicine systems. Most articles come to the conclusion that design flaws could have been avoided by involving stakeholders in the design and implementation of telemedicine. However, many of them lack the guidance for those who find themselves having to choose, implement, or use unwieldy systems. With this in mind, this paper provides a series of human factors principles, real-world questions, methods, and resources for those who may find themselves considering, implementing, sustaining, or using telemedicine in their own healthcare settings.

Safeuristics! Do Heuristic Evaluation Violation Severity Ratings Correlate with Patient Safety Severity Ratings for a Native Electronic Health Record Mobile Application?

OBJECTIVE: Usability of electronic health records (EHRs) remains challenging, and poor EHR design has patient safety implications. Heuristic evaluation detects usability issues that can be classified by severity. The National Institute of Standards and Technology provides a safety scale for EHR usability. Our objectives were to investigate the relationship between heuristic severity ratings and safety scale ratings in an effort to analyze EHR safety. MATERIALS AND METHODS: Heuristic evaluation was conducted on seven common mobile EHR tasks, revealing 58 heuristic violations and 28 unique usability issues. Each usability issue was independently scored for severity by trained hospitalists and a Human Factors researcher and for safety severity by two physician informaticists and two clinical safety professionals. RESULTS: Results demonstrated a positive correlation between heuristic severity and safety severity ratings. Regression analysis demonstrated that 49% of safety risk variability by clinical safety professionals (r = 0.70; n = 28) and 42% of safety risk variability by clinical informatics specialists (r = 0.65; n = 28) was explained by usability severity scoring of problems outlined by heuristic evaluation. Higher severity ratings of the usability issues were associated with increased perceptions of patient safety risk. DISCUSSION: This study demonstrated the use of heuristic evaluation as a technique to quickly identify usability problems in an EHR that could lead to safety issues. Detection of higher severity ratings could help prioritize failures in EHR design that more urgently require design changes. This approach is a cost-effective technique for improving usability while impacting patient safety. CONCLUSION: Results from this study demonstrate the efficacy of the heuristic evaluation technique to identify usability problems that impact safety of the EHR. Also, the use of interdisciplinary teams for evaluation should be considered for severity assessment.

Estimating the impact of deploying an electronic clinical decision support tool as part of a national practice improvement project.

OBJECTIVE: Estimate the impact on clinical practice of using a mobile device-based electronic clinical decision support (mECDS) tool within a national standardization project. MATERIALS AND METHODS: An mECDS tool (app) was released as part of a change package to provide febrile infant management guidance to clinicians. App usage was analyzed using 2 measures: metric hits per case (metric-related screen view count divided by site-reported febrile infant cases in each designated market area [DMA] monthly) and cumulative prior metric hits per site (DMA metric hits summed from study month 1 until the month preceding the index, divided by sites in the DMA). For each metric, a mixed logistic regression model was fit to model site performance as a function of app usage. RESULTS: An increase of 200 cumulative prior metric hits per site was associated with increased odds of adherence to 3 metrics: appropriate admission (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.06-1.18), appropriate length of stay (OR, 1.20; 95% CI, 1.12-1.28), and inappropriate chest x-ray (OR, 0.82; 95% CI, 0.75-0.91). Ten additional metric hits per case were also associated: OR were 1.18 (95% CI, 1.02-1.36), 1.36 (95% CI, 1.14-1.62), and 0.74 (95% CI, 0.62-0.89). DISCUSSION: mECDS tools are increasingly being implemented, but their impact on clinical practice is poorly described. To our knowledge, although ecologic in nature, this report is the first to link clinical practice to mECDS use on a national scale and outside of an electronic health record. CONCLUSIONS: mECDS use was associated with changes in adherence to targeted metrics. Future studies should seek to link mECDS usage more directly to clinical practice and assess other site-level factors.

Impact of Mobile Device-Based Clinical Decision Support Tool on Guideline Adherence and Mental Workload.

OBJECTIVE: To evaluate the individual-level impact of an electronic clinical decision support (ECDS) tool, PedsGuide, on febrile infant clinical decision making and cognitive load. METHODS: A counterbalanced, prospective, crossover simulation study was performed among attending and trainee physicians. Participants performed simulated febrile infant cases with use of PedsGuide and with standard reference text. Cognitive load was assessed using the NASA-Task Load Index (NASA-TLX), which determines mental, physical, temporal demand, effort, frustration, and performance. Usability was assessed with the System Usability Scale (SUS). Scores on cases and NASA-TLX scores were compared between condition states. RESULTS: A total of 32 participants completed the study. Scores on febrile infant cases using PedsGuide were greater compared with standard reference text (89% vs 72%, P = .001). NASA-TLX scores were lower (ie, more optimal) with use of PedsGuide versus control (mental 6.34 vs 11.8, P < .001; physical 2.6 vs 6.1, P = .001; temporal demand 4.6 vs 8.0, P = .003; performance 4.5 vs 8.3, P < .001; effort 5.8 vs 10.7, P < .001; frustration 3.9 vs 10, P < .001). The SUS had an overall score of 88 of 100 with rating of acceptable on the acceptability scale. CONCLUSIONS: Use of PedsGuide led to increased adherence to guidelines and decreased cognitive load in febrile infant management when compared with the use of a standard reference tool. This study employs a rarely used method of assessing ECDS tools using a multifaceted approach (medical decision-making, assessing usability, and cognitive workload,) that may be used to assess other ECDS tools in the future.

Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project.

Objective: Implementing evidence-based practices requires a multi-faceted approach. Electronic clinical decision support (ECDS) tools may encourage evidence-based practice adoption. However, data regarding the role of mobile ECDS tools in pediatrics is scant. Our objective is to describe the development, distribution, and usage patterns of a smartphone-based ECDS tool within a national practice standardization project. Materials and Methods: We developed a smartphone-based ECDS tool for use in the American Academy of Pediatrics, Value in Inpatient Pediatrics Network project entitled "Reducing Excessive Variation in the Infant Sepsis Evaluation (REVISE)." The mobile application (app), PedsGuide, was developed using evidence-based recommendations created by an interdisciplinary panel. App workflow and content were aligned with clinical benchmarks; app interface was adjusted after usability heuristic review. Usage patterns were measured using Google Analytics. Results: Overall, 3805 users across the United States downloaded PedsGuide from December 1, 2016, to July 31, 2017, leading to 14 256 use sessions (average 3.75 sessions per user). Users engaged in 60 442 screen views, including 37 424 (61.8%) screen views that displayed content related to the REVISE clinical practice benchmarks, including hospital admission appropriateness (26.8%), length of hospitalization (14.6%), and diagnostic testing recommendations (17.0%). Median user touch depth was 5 [IQR 5]. Discussion: We observed rapid dissemination and in-depth engagement with PedsGuide, demonstrating feasibility for using smartphone-based ECDS tools within national practice improvement projects. Conclusions: ECDS tools may prove valuable in future national practice standardization initiatives. Work should next focus on developing robust analytics to determine ECDS tools' impact on medical decision making, clinical practice, and health outcomes.

Meta-Analyses of the Effects of Standardized Handoff Protocols on Patient, Provider, and Organizational Outcomes.

OBJECTIVE: The overall purpose was to understand the effects of handoff protocols using meta-analytic approaches. BACKGROUND: Standardized protocols have been required by the Joint Commission, but meta-analytic integration of handoff protocol research has not been conducted. METHOD: The primary outcomes investigated were handoff information passed during transitions of care, patient outcomes, provider outcomes, and organizational outcomes. Sources included Medline, SAGE, Embase, PsycINFO, and PubMed, searched from the earliest date available through March 30th, 2015. Initially 4,556 articles were identified, with 4,520 removed. This process left a final set of 36 articles, all which included pre-/postintervention designs implemented in live clinical/hospital settings. We also conducted a moderation analysis based on the number of items contained in each protocol to understand if the length of a protocol led to systematic changes in effect sizes of the outcome variables. RESULTS: Meta-analyses were conducted on 34,527 pre- and 30,072 postintervention data points. Results indicate positive effects on all four outcomes: handoff information (g = .71, 95% confidence interval [CI] [.63, .79]), patient outcomes (g = .53, 95% CI [.41, .65]), provider outcomes (g = .51, 95% CI [.41, .60]), and organizational outcomes (g = .29, 95% CI [.23, .35]). We found protocols to be effective, but there is significant publication bias and heterogeneity in the literature. Due to publication bias, we further searched the gray literature through greylit.org and found another 347 articles, although none were relevant to this research. Our moderation analysis demonstrates that for handoff information, protocols using 12 or more items led to a significantly higher proportion of information passed compared with protocols using 11 or fewer items. Further, there were numerous negative outcomes found throughout this meta-analysis, with trends demonstrating that protocols can increase the time for handover and the rate of errors of omission. CONCLUSIONS: These results demonstrate that handoff protocols tend to improve results on multiple levels, including handoff information passed and patient, provider, and organizational outcomes. These findings come with the caveat that publication bias exists in the literature on handoffs. Instances where protocols can lead to negative outcomes are also discussed. APPLICATION: Significant effects were found for protocols across provider types, regardless of expertise or area of clinical focus. It also appears that more thorough protocols lead to more information being passed, especially when those protocols consist of 12 or more items. Given these findings, publication bias is an apparent feature of this literature base. Recommendations to reduce the apparent publication bias in the field include changing the way articles are screened and published.

Directly Comparing Handoff Protocols for Pediatric Hospitalists.

BACKGROUND AND OBJECTIVES: Handoff protocols are often developed by brainstorming and consensus, and few are directly compared. We hypothesized that a handoff protocol (Flex 11) developed using a rigorous methodology would be more favorable in terms of clinicians' attitudes, behaviors, cognitions, or time-on-task when performing handoffs compared with a prevalent protocol (Situation Background Assessment Recommendation [SBAR]). METHODS: Using a between-groups, randomized control trial design (Flex 11 versus SBAR) during a pilot study in a simulated environment, 20 clinicians (13 attending physicians and 7 residents) received 3 patient handoffs from a standardized physician, managed the patients, and handed off the patients to the same standardized physician. Participants completed surveys assessing their attitudes and cognitions, and behaviors and handoff duration were assessed through observations. RESULTS: All data were analyzed using independent samples t tests. For attitudes, "ease of use" ratings were lower for SBAR participants than Flex 11 participants (P < .01), and "being helpful" ratings were lower for SBAR participants than Flex 11 participants (P = .02). For behaviors, results indicate no significant difference in the information acquired between the SBAR and Flex 11 protocols. However, SBAR participants gave significantly less information than Flex 11 participants (P < .01). For cognitions, SBAR and Flex 11 participants reported similar workload except for frustration. For handoff duration, there were no significant differences between the protocols (P = .36). CONCLUSIONS: The results suggest that Flex 11 is an efficient, beneficial tool in a simulated environment with pediatric clinicians. Future studies should evaluate this protocol in the inpatient setting.