Brady Patzer

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.

Utilizing telemedicine in the trauma intensive care unit: does it impact teamwork?

BACKGROUND The aim of this study was to examine the impact of a telemedical robot on trauma intensive care unit (TICU) clinician teamwork (i.e., team attitudes, behaviors, and cognitions) during patient rounds. MATERIALS AND METHODS Thirty-two healthcare providers who conduct rounds volunteered to take surveys assessing teamwork attitudes and cognitions at three time periods: (1) the onset of the study, (2) the end of the 30-day control period, and (3) the end of the 30-day experimental period, which immediately followed the control period. Rounds were recorded throughout the 30-day control period and 30-day experimental period to observe provider behaviors. For the initial 30 days, there was no access to telemedicine. For the final 30 days, the rounding healthcare providers had access to the RP-7 robot (Intouch Health Inc., Santa Barbara, CA), a telemedical tool that can facilitate patient rounds conducted away from bedside. RESULTS Using a one-tailed, one-way repeated-measures analysis of variance (ANOVA) to compare trust at Times 1, 2, and 3, there was no significant effect on trust: F(2, 14)=1.20, p=0.16. When a one-tailed, one-way repeated-measures ANOVA to compare transactive memory systems (TMS) at Times 1, 2, and 3 was conducted, there was no significant effect on TMS: F(2, 15)=1.33, p=0.15. We conducted a one-tailed, one-way repeated-measures ANOVA to compare team psychological safety at Times 1, 2, and 3, and there was no significant effect on team psychological safety: F(2,15)=1.53, p=0.12. There was a significant difference in communication between rounds with and without telemedicine [t(25)=-1.76, p<0.05], such that there was more task-based communication during telerounds. Telemedicine increased task-based communication and did not negatively impact team trust, psychological safety, or TMS during rounds. CONCLUSIONS Telemedicine may offer advantages for some teamwork competencies without sacrificing the efficacy of others and may be adopted by intact rounding teams without hindering teamwork.

Review of Combat Identification Training: Technologies, Metrics, and Individual Differences

Combat identification (CID) has been studied throughout the 20th and into the 21st century, with a renewed interest in the topic in the past few decades. CID research has demonstrated that an emerging set of technologies could potentially mitigate some of the negative battlefield outcomes of failures in CID, including high rates of fratricide due to friendly fire. This paper discusses major CID research and provides an update on previous CID research by the authors. We review training technologies, effective measurement tools in this research, and important individual differences to consider for others researching training outcomes in relation to learning to differentiate between highly similar combat vehicles.

Considerations for Multiteam Systems in Emergency Medical Services.

Objective Despite good intentions, mishaps in teamwork continue to affect patients lives and plague the medical community at large and Emergency Medical Services (EMS) in particular. Effective and efficient management of patient care necessitates that sets of multiple teams (i.e., multiteam systems [MTSs] - EMS ground crews, EMS air crews, dispatch, and receiving hospital teams) seamlessly work together. Although advances have been made to improve teams, little research has been dedicated to enhancing MTSs especially in the critical yet often under studied domain of EMS. The purpose of this paper is to assist the pre-hospital community in strengthening patient care by presenting considerations unique to multiteam systems. Methods We synthesized the literature pertinent to multi-team systems and emergency medical services. Results From this synthesis, we derived five unique considerations: goals, boundary spanning, adaptation, leadership, and social identity. Conclusions MTSs are prevalent in prehospital care, as they define how multiple component healthcare teams work together to intervene in emergency situations. We provided some initial directions regarding considerations for success in EMS MTSs based on existing research, but we also recognize the need for further study on these issues.

Novelty and Retention for Two Augmented Reality Learning Systems

Studies were conducted to measure novelty and learning retention while utilizing augmented reality (AR) in two learning systems. The first taught participants the basics of guitar and either a melody or scale using an AR guitar with an LED-embedded fret board. The guitar provided digital representations of learning patterns that users would otherwise need to visualize during the learning process. Results of three studies indicate that participants using the AR learning tool were able to perform more of the melody or scale after two-weeks. The second taught participants the basic functioning and anatomy of the heart, using either an AR model or a fiberglass model. Learning and technology acceptance were measured. Results indicated that the AR learning tool was as effective for participant learning when compared to the conventional fiberglass model learning tool. Furthermore, the AR learning tool was rated more enjoyable, curiosity inducing, and easier-to-use than the fiberglass model.

Building a Simulated Medical Augmented Reality Training System

Medical decision-making largely depends on the caregiver’s fundamental knowledge of anatomy. To this end, the authors discuss a cost-effective augmented reality system for simulated medical research and education. First, we define augmented reality. Second, we will review the history of augmented reality in medical training. Third, we will discuss some of the human factors principles associated with augmented reality training systems. Fourth, we will describe our insight and methods for building a Simulated Medical Augmented Reality Training (SMART) system, which can be used as an alternative training tool for medical and anatomy students. Finally, we will outline five steps that can be taken to build a SMART system.

Minimizing the impact of interruptions in a pediatric retail pharmacy

Researchers identified two needs of the in-hospital pediatric retail pharmacy. First was the reduction of the risk and frequency of errors. Second was the need to improve the efficiency of primary pharmacy tasks. Interruptions were identified as the primary issue. The team performed an extensive literature review and conducted interviews and observations to assess the pharmacy work system, work flow, and the impact of interruptions. A human factors analysis was done to accurately represent the pharmacy work system from data collection, and derive recommendations to improve efficiency and accuracy. Some of the recommendations were rapidly implemented into the pharmacy work system, including increased staffing during periods of high work demand, changes to counter spacing, and design changes to bags intended to contain refrigerated components. The research team conducted follow-up observations and collected survey data from pharmacy staff to determine the impact of the implemented interventions and identify key improvements.