Elizabeth H. Lazzara

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.

Understanding multiteam systems in emergency care: one case at a time

Abstract Purpose Although adverse events are less studied in the prehospital setting, the evidence is beginning to paint an alarming picture. Consequently, improvements in Emergency Medical Services (EMS) demand a paradigm shift regarding the way care is conceptualized. The chapter aims to (1) support the dialogue on near-misses and adverse events as a learning opportunity and (2) to provide insights on applications of multiteam systems (MTSs). Approach To offer discussion on near-misses and adverse events and knowledge on how MTSs are applicable to emergency medical care, we review and dissect a complex patient case. Findings Throughout this case discussion, we uncover seven pertinent issues specific to this particular MTS: (1) misunderstanding with number of patients and their locations, (2a) lack of context to build a mental model, (2b) no time or resources to think, (3) expertise-facilitated diagnosis, (4) lack of communication contributing to a medication error, (5) treatment plan selection, (6) extended time on scene, and (7) organizational culture impacting treatment plan decisions. Originality/value By dissecting a patient case within the prehospital setting, we can highlight the value in engaging in dialogue regarding near-misses and adverse events. Further, we can demonstrate the need to expand the focus from simply teams to MTSs.

Measuring shared mental models in healthcare

Objective To review common qualitative and quantitative methods of measuring shared mental models appropriate for use in the healthcare setting. Background Shared mental models are the overlap of individuals’ set of knowledge and/or assumptions that act as the basis for understanding and decision making between individuals. Within healthcare, shared mental models facilitate effective teamwork and theorized to influence clinical decision making and performance. With the current rapid growth and expansion of healthcare teams, it is critical that we understand and correctly use shared mental model measurement methods assess optimal team performance. Unfortunately, agreement on the proper measurement of shared mental models within healthcare remains diffuse. Method This paper presents methods appropriate to measure shared mental models within healthcare. Results Multiple shared mental model measurement methods are discussed with regard to their utility within this setting, ease of use, and difficulties in deploying within the healthcare operational environment. For rigorous analysis of shared mental models, it is recommended that a combination of qualitative and quantitative analyses be employed. Conclusion There are multitude of shared mental model measurement methods that can be used in the healthcare domain; although there is no perfect solution for every situation. Researchers can utilize this article to determine the best approach for their needs.

Team Performance Framework During Handoffs

Handoffs, the transitioning care and responsibility of patients between two or more providers, are essential in almost all medical settings whether it be during shiftchange, during breaks, or transfer from one unit to another (Riesenberg, Leitzsch, & Little, 2009). More specifically, handoffs are a communication event that can include patient treatment, services, care, background, and all pertinent information (Patterson, 2010). Unfortunately, handoffs are vulnerable to communication breakdowns, which can lead to missed diagnoses (Lorinz et al., 2011), treatment delays (Horwitz, Moin, Krumholz, Wang, & Bradley, 2008), malpractice claims (Singh, Thomas, Petersen, & Studdert, 2007), patient harm (Arora, Johnson, Lovinger, Humphrey, & Meltzer, 2005; Kitch et al., 2008; Saleem, Paulus, Vassiliou, & Parsons, 2015), and mortality (American Thoracic Society, 2016). Due to criticality of these transitions as well as their inherent vulnerabilities, it is important that key information is transferred clearly, correctly, and comprehensibly between team members. Consequently, it is important to gain a better understanding regarding the factors that impact handoffs. Because handoffs are essentially a team task, we posit that literature and even practice could benefit by better understanding handoffs through a teamwork lens. Unfortunately, little research has focused on theorizing about the components that impact and surround handoffs. Due to the multitude of factors that can influence the team task of handoffs, we believe it is important to systematically organize these various factors of handoffs to foster researchers and providers in achieving safer outcomes. Therefore, this paper embeds the process of handoffs in a prevalent psychological model with the factors that influence them, namely the inputmediator/moderator-output-input (IMOI) model presented by Ilgen et al (2005). The IMOI model postulates that inputs are properties within individuals, teams, organizations, and tasks influential to a particular process or performance episode. In essence, they set the conditions for which interactions take place (McGrath, 1984). Meanwhile, mediators and moderators are the components that occur throughout the process or performance episode, and the outputs are the outcomes or consequences of the processes or performances. Finally, the second input includes the characteristics that result from previous processes and impact future performances. Within the context of handoffs, the inputs are the individual characteristics of providers and patients, the mediators/moderators are the factors or interactions that occur during a handoff, the outputs are the results of the handoff, and the final input is the team adaptation that occurs. Refer to Figure 1 for a nonexhaustive list of influential handoff factors. Depicting handoffs within this organizational framework can provide insights to lead to better teamwork by unpacking the complexities surrounding handoffs. Ultimately,