OBJECTIVE:Alert fatigue limits the effectiveness of medication safety alerts, a type of computerized clinical decision support (CDS). Researchers have suggested alternative interactive designs, as well as tailoring alerts to clinical roles. As examples, alerts may be tiered to convey risk, and certain alerts may be sent to pharmacists. We aimed to evaluate which variants elicit less alert fatigue. MATERIALS AND METHODS:We searched for articles published between 2007 and 2017 using the PubMed, Embase, CINAHL, and Cochrane databases. We included articles documenting peer-reviewed empirical research that described the interactive design of a CDS system, to which clinical role it was presented, and how often prescribers accepted the resultant advice. Next, we compared the acceptance rates of conventional CDS-presenting prescribers with interruptive modal dialogs (ie, "pop-ups")-with alternative designs, such as role-tailored alerts. RESULTS:Of 1011 articles returned by the search, we included 39. We found different methods for measuring acceptance rates; these produced incomparable results. The most common type of CDS-in which modals interrupted prescribers-was accepted the least often. Tiering by risk, providing shortcuts for common corrections, requiring a reason to override, and tailoring CDS to match the roles of pharmacists and prescribers were the most common alternatives. Only 1 alternative appeared to increase prescriber acceptance: role tailoring. Possible reasons include the importance of etiquette in delivering advice, the cognitive benefits of delegation, and the difficulties of computing "relevance." CONCLUSIONS:Alert fatigue may be mitigated by redesigning the interactive behavior of CDS and tailoring CDS to clinical roles. Further research is needed to develop alternative designs, and to standardize measurement methods to enable meta-analyses.

Objective

Physician champions are "boots on the ground" physician leaders who facilitate the implementation of, and transition to, new health information technology (HIT) systems within an organization. They are commonly cited as key personnel in HIT implementations, yet little research has focused on their practices and perspectives.

Materials and methods

We addressed this research gap through a qualitative study of physician champions that aimed to capture their challenges and strategies during a large-scale HIT implementation. Email interviews were conducted with 45 physician champions from diverse clinical areas 5 months after a new electronic health record (EHR) system went live in a large academic medical center. We adopted a grounded theory approach to analyze the data.

Results

Our physician champion participants reported multiple challenges, including insufficient training, limited at-the-elbow support, unreliable communication with leadership and the EHR vendor, as well as flawed system design. To overcome these challenges, physician champions developed their own personalized training programs in a simulated context or in the live environment, sought and obtained more at-the-elbow support both internally and externally, and adapted their departmental sociotechnical context to make the system work better.

Discussion and conclusions

This study identified the challenges physician champions faced and the strategies they developed to overcome these challenges. Our findings suggest factors that are crucial to the successful involvement of physician champions in HIT implementations, including the availability of instrumental (eg, reward for efforts), emotional (eg, mechanisms for expressing frustrations), and peer support; ongoing engagement with the champions; and appropriate training and customization planning.

Computerized clinical decision-support systems are members of larger sociotechnical systems, composed of human and automated actors, who send, receive, and manipulate artifacts. Sociotechnical consideration is rare in the literature. This makes it difficult to comparatively evaluate the success of CDS implementations, and it may also indicate that sociotechnical context receives inadequate consideration in practice. To facilitate sociotechnical consideration, we developed the Thinking Together model, a flexible diagrammatical means of representing CDS systems as sociotechnical systems. To develop this model, we examined the literature with the lens of Distributed Cognition (DCog) theory. We then present two case studies of vastly different CDSSs, one almost fully automated and the other with minimal automation, to illustrate the flexibility of the Thinking Together model. We show that this model, informed by DCog and the CDS literature, are capable of supporting both research, by enabling comparative evaluation, and practice, by facilitating explicit sociotechnical planning and communication.

Objective

Facial masks are an essential personal protective measure to fight the COVID-19 (coronavirus disease) pandemic. However, the mask adoption rate in the United States is still less than optimal. This study aims to understand the beliefs held by individuals who oppose the use of facial masks, and the evidence that they use to support these beliefs, to inform the development of targeted public health communication strategies.

Materials and methods

We analyzed a total of 771 268 U.S.-based tweets between January to October 2020. We developed machine learning classifiers to identify and categorize relevant tweets, followed by a qualitative content analysis of a subset of the tweets to understand the rationale of those opposed mask wearing.

Results

We identified 267 152 tweets that contained personal opinions about wearing facial masks to prevent the spread of COVID-19. While the majority of the tweets supported mask wearing, the proportion of anti-mask tweets stayed constant at about a 10% level throughout the study period. Common reasons for opposition included physical discomfort and negative effects, lack of effectiveness, and being unnecessary or inappropriate for certain people or under certain circumstances. The opposing tweets were significantly less likely to cite external sources of information such as public health agencies' websites to support the arguments.

Conclusions

Combining machine learning and qualitative content analysis is an effective strategy for identifying public attitudes toward mask wearing and the reasons for opposition. The results may inform better communication strategies to improve the public perception of wearing masks and, in particular, to specifically address common anti-mask beliefs.

There are many benefits of online patient access to their medical records through technologies such as patient portals. However, patients often have difficulties understanding the clinical data presented in portals. In response, increasingly, patients go online to make sense of this data. One commonly used online resource is health forums. In this pilot study, we focus on one type of clinical data, laboratory results, and one popular forum, MedHelp. We examined patient question posts that contain laboratory results to gain insights into the nature of these questions and of the answers. Our analyses revealed a typology of confusion (i.e., topics of their questions) and potential gaps in traditional healthcare supports (i.e., patients' requests and situational factors), as well as the supports patients may gain through the forum (i.e., what the community provides). These results offer preliminary evidence of opportunities to redesign patient portals, and will inform our future work.

As healthcare organizations continue to grow and evolve, migrations from one commercial electronic health record (EHR) system to another are likely to become more common. However, little is known about front-line clinicians' and staff's perceptions of such changes. Our study addresses this gap through an organization-wide survey of employees immediately prior to the transition to a new commercial EHR. We found that almost all front-line clinicians and staff were aware of the upcoming migration, and that most felt positive or neutral about the change, with only about 11% indicating that they were uncomfortable with the migration. Reasons for discomfort included the beliefs that the new EHR will be more time consuming to use and that moving to a new EHR is too costly, as well as concerns about the migration process. Attitudes differed by demographic characteristics and satisfaction with the current EHR. We discuss the implications of these results.

Objective

To evaluate end-user acceptance and the effect of a commercial handheld decision support device in pediatric intensive care settings. The technology, pac2, was designed to assist nurses in calculating medication dose volumes and infusion rates at the bedside.

Materials and methods

The devices, manufactured by InformMed Inc., were deployed in the pediatric and neonatal intensive care units in 2 health systems. This mixed methods study assessed end-user acceptance, as well as pac2's effect on the cognitive load associated with bedside dose calculations and the rate of administration errors. Towards this end, data were collected in both pre- and postimplementation phases, including through ethnographic observations, semistructured interviews, and surveys.

Results

Although participants desired a handheld decision support tool such as pac2, their use of pac2 was limited. The nature of the critical care environment, nurses' risk perceptions, and the usability of the technology emerged as major barriers to use. Data did not reveal significant differences in cognitive load or administration errors after pac2 was deployed.

Discussion and conclusion

Despite its potential for reducing adverse medication events, the commercial standalone device evaluated in the study was not used by the nursing participants and thus had very limited effect. Our results have implications for the development and deployment of similar mobile decision support technologies. For example, they suggest that integrating the technology into hospitals' existing IT infrastructure and employing targeted implementation strategies may facilitate nurse acceptance. Ultimately, the usability of the design will be essential to reaping any potential benefits.