Amy Franklin

A multimodal analysis of floor control in meetings

The participant in a human-to-human communication who controls the floor bears the burden of moving the communication process along. Change in control of the floor can happen through a number of mechanisms, including interruptions, delegation of the floor, and so on. This paper investigates floor control in multiparty meetings that are both audio and video taped; hence, we are able to analyze patterns not only of speech (e.g., discourse markers) but also of visual cues (e.g, eye gaze exchanges) that are commonly involved in floor control changes. Identifying who has control of the floor provides an important focus for information retrieval and summarization of meetings. Additionally, without understanding who has control of the floor, it is impossible to identify important events such as challenges for the floor. In this paper, we analyze multimodal cues related to floor control in two different meetings involving five participants each.

Making sense: Sensor-based investigation of clinician activities in complex critical care environments

In many respects, the critical care workplace resembles a paradigmatic complex system: on account of the dynamic and interactive nature of collaborative clinical work, these settings are characterized by non-linear, inter-dependent and emergent activities. Developing a comprehensive understanding of the work activities in critical care settings enables the development of streamlined work practices, better clinician workflow and most importantly, helps in the avoidance of and recovery from potential errors. Sensor-based technology provides a flexible and viable way to complement human observations by providing a mechanism to capture the nuances of certain activities with greater precision and timing. In this paper, we use sensor-based technology to capture the movement and interactions of clinicians in the Trauma Center of an Emergency Department (ED). Remarkable consistency was found between sensor data and human observations in terms of clinician locations and interactions. With this validation and greater precision with sensors, ED environment was characterized in terms of (a) the degree of randomness or entropy in the environment, (b) the movement patterns of clinicians, (c) interactions with other clinicians and finally, (d) patterns of collaborative organization with team aggregation and dispersion. Based on our results, we propose three opportunities for the use of sensor technologies in critical care settings: as a mechanism for real-time monitoring and analysis for ED activities, education and training of clinicians, and perhaps most importantly, investigating the root-causes, origins and progression of errors in the ED. Lessons learned and the challenges encountered in designing and implementing the sensor technology sensor data are discussed.

Negation, questions, and structure building in a homesign system

Deaf children whose hearing losses are so severe that they cannot acquire spoken language, and whose hearing parents have not exposed them to sign language, use gestures called homesigns to communicate. Homesigns have been shown to contain many of the properties of natural languages. Here we ask whether homesign has structure building devices for negation and questions. We identify two meanings (negation, question) that correspond semantically to propositional functions, that is, to functions that apply to a sentence (whose semantic value is a proposition, ϕ) and yield another proposition that is more complex (¬ϕ for negation; ?ϕ for question). Combining ϕ with ¬ or ? thus involves sentence modification. We propose that these negative and question functions are structure building operators, and we support this claim with data from an American homesigner. We show that: (a) each meaning is marked by a particular form in the childs gesture system (side-to-side headshake for negation, manual flip for question); (b) the two markers occupy systematic, and different, positions at the periphery of the gesture sentences (headshake at the beginning, flip at the end); and (c) the flip is extended from questions to other uses associated with the wh-form (exclamatives, referential expressions of location) and thus functions like a category in natural languages. If what we see in homesign is a language creation process (Goldin-Meadow, 2003), and if negation and question formation involve sentential modification, then our analysis implies that homesign has at least this minimal sentential syntax. Our findings thus contribute to ongoing debates about properties that are fundamental to language and language learning.

Opportunistic decision making and complexity in emergency care

In critical care environments such as the emergency department (ED), many activities and decisions are not planned. In this study, we developed a new methodology for systematically studying what are these unplanned activities and decisions. This methodology expands the traditional naturalistic decision making (NDM) frameworks by explicitly identifying the role of environmental factors in decision making. We focused on decisions made by ED physicians as they transitioned between tasks. Through ethnographic data collection, we developed a taxonomy of decision types. The empirical data provide important insight to the complexity of the ED environment by highlighting adaptive behavior in this intricate milieu. Our results show that half of decisions in the ED we studied are not planned, rather decisions are opportunistic decision (34%) or influenced by interruptions or distractions (21%). What impacts these unplanned decisions have on the quality, safety, and efficiency in the ED environment are important research topics for future investigation.

Factors affecting accuracy of data abstracted from medical records

Objective Medical record abstraction (MRA) is often cited as a significant source of error in research data, yet MRA methodology has rarely been the subject of investigation. Lack of a common framework has hindered application of the extant literature in practice, and, until now, there were no evidence-based guidelines for ensuring data quality in MRA. We aimed to identify the factors affecting the accuracy of data abstracted from medical records and to generate a framework for data quality assurance and control in MRA. Methods Candidate factors were identified from published reports of MRA. Content validity of the top candidate factors was assessed via a four-round two-group Delphi process with expert abstractors with experience in clinical research, registries, and quality improvement. The resulting coded factors were categorized into a control theory-based framework of MRA. Coverage of the framework was evaluated using the recent published literature. Results Analysis of the identified articles yielded 292 unique factors that affect the accuracy of abstracted data. Delphi processes overall refuted three of the top factors identified from the literature based on importance and five based on reliability (six total factors refuted). Four new factors were identified by the Delphi. The generated framework demonstrated comprehensive coverage. Significant underreporting of MRA methodology in recent studies was discovered. Conclusion The framework generated from this research provides a guide for planning data quality assurance and control for studies using MRA. The large number and variability of factors indicate that while prospective quality assurance likely increases the accuracy of abstracted data, monitoring the accuracy during the abstraction process is also required. Recent studies reporting research results based on MRA rarely reported data quality assurance or control measures, and even less frequently reported data quality metrics with research results. Given the demonstrated variability, these methods and measures should be reported with research results.

Digilego: A Standardized Analytics-Driven Consumer-Oriented Connected Health Framework

Connected health solutions provide novel pathways to provide integrated and affordable care. Emerging research suggests these connected tools can result improved health outcomes and sustainable self-health management. However, current health technology frameworks limit flexibility, engagement, and reusability of underlying connected health components. The objective of this paper is to develop a data-driven consumer engagement framework, which we call Digilego, to facilitate development of connected health solutions that are targeted, modular, extensible, and engaging. The major components include social media analysis, patient engagement features, and behavioral intervention technologies. We propose implementation of these Digilego components using FHIR specification such that the resulting technology is compliant to industry standards. We apply and evaluate the proposed framework to characterize four individual building blocks (DigiMe, DigiSocial, DigiConnect, DigiEHR) for a connected health solution that is responsive to cancer survivor needs. Results indicate that the framework (a) allows identification of survivor needs (e.g. social integration, treatment side effects) through semi-automated social media analysis, (b) facilitates infusion of engagement elements (e.g. smart health trackers, integrated electronic health records), and (c) integrates behavior change constructs into the design architecture of survivorship applications (e.g. goal setting, emotional coping). End user evaluation with 16 cancer survivors indicated general user acceptance and enthusiasm to adopt the solution for self-care management. Implications for design of patient-engaging chronic disease management solutions are discussed.

Engagement and Design Barriers of mHealth Applications for Older Adults

With the growth of gerontechnology, there is an increasing awareness of the importance of accessibility and usability in product designs7. Here we consider the degree to which those factors along with patient engagement are currently being provided by mobile health applications aimed towards an older population. Specifically, we used a hybrid usability checklist, that is inclusive of age related guidelines and mobile platform atributes along with HIMSS Patient Engagement Framework to evaluate accessibility, usability, and engagement levels facilitated by the mobile apps targeting older adults. Expert review found a limited range of features to support accessibility and significant violations of general usability heuristics. Analyses of Patient Engagement levels suggest that the majority of the apps provide information and way finding, education, and community support. However, utilization of health monitoring tools, record-keeping features, and shared decision making with providers has been minimal. Implications for care coordination and technology design for enabling independent living are discussed.

A Methodology for Adapting Psychoeducational Content to Mobile Platforms.

UNLABELLED Studies show that current modes of psychoeducation (PE) cannot be availed of by a substantial population of those in need. Mobile health technologies have great potential to serve such populations. However converting PE to mobile platforms is challenging. We present a methodology for this purpose based on existing learning styles theory, and developed PE apps successfully, using it. CONCLUSION Useful PE apps can be developed easily using the proposed method.

The Unintended Consequences of the Technology in Clinical Settings

In this chapter, we highlight unexpected outcomes created by technology use in clinical settings. We define unintended consequences as both positive serendipitous results as well as negative, unintended, and potentially harmful consequences of technology in use. A review of different classification systems for studying the unanticipated impacts of health information technology (HIT) is followed by specific examples from the use of electronic health records (EHR). EHR systems are one example of how even well-designed technology can yield unexpected results. Although HIT such as EHRs has the potential to improve care by reducing the burden placed on its users, it can also increase memory demands, alter communication channels, and provoke sub-optimal decision-making. This can lead to errors, inefficiencies in workflows, overdependence on technology and, importantly, risk to patients. By understanding the impact of technology on performance we can potentially manage the negative unintended consequences engendered by HIT systems allowing such systems to function as expected. Additionally, by understanding unanticipated beneficial outcomes, we can promote the development of future tools that further induce positive results.

Cognitive Considerations for Health Information Technology

This chapter discusses the cognitive and usability factors for complex team environments by exploring the challenges brought about by human cognitive limitations and the unintended consequences of technology. In the final sections, both the challenges and opportunities in a distributed cognition framework are presented.