Using video-based observation research methods in primary care health encounters to evaluate complex interactions

Objective The purpose of this paper is to describe the use of video-based observation research methods in primary care environment and highlight important methodological considerations and provide practical guidance for primary care and human factors researchers conducting video studies to understand patient–clinician interaction in primary care settings.Methods We reviewed studies in the literature which used video methods in health care research, and we also used our own experience based on the video studies we conducted in primary care settings.Results This paper highlighted the benefits of using video techniques, such as multi-channel recording and video coding, and compared “unmanned” video recording with the traditional observation method in primary care research. We proposed a list that can be followed step by step to conduct an effective video study in a primary care setting for a given problem. This paper also described obstacles, researchers should anticipate when using video recording methods in future studies.Conclusion With the new technological improvements, video-based observation research is becoming a promising method in primary care and HFE research. Video recording has been under-utilised as a data collection tool because of confidentiality and privacy issues. However, it has many benefits as opposed to traditional observations, and recent studies using video recording methods have introduced new research areas and approaches

Providers' assessment of a novel interactive health information technology in a pediatric intensive care unit

Objective: To explore perceptions of critical care providers about a novel collaborative inpatient health information technology (HIT) in a pediatric intensive care unit (PICU) setting. Methods: This cross-sectional, concurrent mixed methods study was conducted in the PICU of a large midwestern children's hospital. The technology, the Large Customizable Interactive Monitor (LCIM), is a flat panel touch screen monitor that displays validated patient information from the electronic health record. It does not require a password to login and is available in each patient's room for viewing and interactive use by physicians, nurses, and families. Quantitative data were collected via self-administered, standardized surveys, and qualitative data via in-person, semistructured interviews between January and April 2015. Data were analyzed using descriptive statistics and inductive thematic analysis. Results: The qualitative analysis showed positive impacts of the LCIM on providers' workflow, team interactions, and interactions with families. Providers reported concerns regarding perceived patient information overload and associated anxiety and burden for families. Sixty percent of providers thought that LCIM was useful for their jobs at different levels, and almost 70% of providers reported that LCIM improved information sharing and communication with families. The average overall satisfaction score was 3.4 on a 0 to 6 scale, between "a moderate amount" and "pretty much." Discussion and Conclusion: This study provides new insight into collaborative HIT in the inpatient pediatric setting and demonstrates that using such technology has the potential to improve providers' experiences with families and just-in-time access to EHR information in a format more easily shared with families

Provider Use of a Novel EHR display in the Pediatric Intensive Care Unit. Large Customizable Interactive Monitor (LCIM)

OBJECTIVES: The purpose of this study was to explore providers' perspectives on the use of a novel technology, "Large Customizable Interactive Monitor" (LCIM), a novel application of the electronic health record system implemented in a Pediatric Intensive Care Unit. METHODS: We employed a qualitative approach to collect and analyze data from pediatric intensive care physicians, pediatric nurse practitioners, and acute care specialists. Using semi-structured interviews, we collected data from January to April, 2015. The research team analyzed the transcripts using an iterative coding method to identify common themes. RESULTS: Study results highlight contextual data on providers' use routines of the LCIM. Findings from thirty six interviews were classified into three groups: 1) providers' familiarity with the LCIM; 2) providers' use routines (i.e. when and how they use it); and 3) reasons why they use or do not use it. CONCLUSION: It is important to conduct baseline studies of the use of novel technologies. The importance of training and orientation affects the adoption and use patterns of this new technology. This study is notable for being the first to investigate a LCIM system, a next generation system implemented in the pediatric critical care setting. Our study revealed this next generation HIT might have great potential for family-centered rounds, team education during rounds, and family education/engagement in their child's health in the patient room. This study also highlights the effect of training and orientation on the adoption patterns of new technology

Perceived Patient Workload and Its Impact on Outcomes During New Cancer Patient Visits: Analysis of a Convenience Sample

BackgroundStudies exploring the workload in health care focus on the doctors’ perspectives. The ecology of the health care environment is critical and different for doctors and patients. ObjectiveIn this study, we explore the patient workload among newly diagnosed patients with cancer during their first visit and its impact on the patient’s perceptions of the quality of care (their trust in their doctors, their satisfaction with the care visits, their perception of technology use). MethodsWe collected data from the Hackensack Meridian Health, John Theurer Cancer Center between February 2021 and May 2022. The technology use considered during the visit is related to doctors’ use of electronic health records. A total of 135 participants were included in the study. Most participants were 50-64 years old (n=91, 67.41%). A majority (n=81, 60%) of them were White, and only (n=16, 11.85%) went to graduate schools. ResultsThe findings captured the significant effect of overall workload on trust in doctors and perception of health IT use within the visits. On the other hand, the overall workload did not impact patients’ satisfaction during the visit. A total of 80% (n=108) of patients experienced an overall high level of workload. Despite almost 55% (n=75) of them experiencing a high mental load, 71.1% (n=96) reported low levels of effort, 89% (n=120) experienced low time pressure, 85.2% (n=115) experienced low frustration levels, and 69.6% (n=94) experienced low physical activity. The more overall workload patients felt, the less they trusted their doctors (odds ratio [OR] 0.059, 95% CI 0.001-2.34; P=.007). Low trust was also associated with the demanding mental tasks in the visits (OR 0.055, 95% CI 0.002-2.64; P<.001), the physical load (OR 0.194, 95% CI 0.004-4.23; P<.001), the time load (OR 0.183, 95% CI 0.02-2.35; P=.046) the effort needed to cope with the environment (OR 0.163, 95% CI 0.05-1.69; P<.001), and the frustration levels (OR 0.323, 95% CI 0.04-2.55; P=.03). The patients’ perceptions of electronic health record use during the visit were negatively impacted by the overall workload experienced by the patients (OR 0.315, 95% CI 0.08-6.35; P=.01) and the high frustration level experienced (OR 0.111, 95% CI 0.015-3.75; P<.001). ConclusionsThe study’s findings established pathways for future research and have implications for cancer patients’ workload. Better technology design and use can minimize perceived workload, which might contribute to the trust relationship between doctors and patients in this critical environment. Future human factors work needs to explore the workload and driving factors in longitudinal studies and assess whether these workloads might contribute to unintended patient outcomes and medical errors

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

BackgroundDespite advancements in artificial intelligence (AI) to develop prediction and classification models, little research has been devoted to real-world translations with a user-centered design approach. AI development studies in the health care context have often ignored two critical factors of ecological validity and human cognition, creating challenges at the interface with clinicians and the clinical environment. ObjectiveThe aim of this literature review was to investigate the contributions made by major human factors communities in health care AI applications. This review also discusses emerging research gaps, and provides future research directions to facilitate a safer and user-centered integration of AI into the clinical workflow. MethodsWe performed an extensive mapping review to capture all relevant articles published within the last 10 years in the major human factors journals and conference proceedings listed in the “Human Factors and Ergonomics” category of the Scopus Master List. In each published volume, we searched for studies reporting qualitative or quantitative findings in the context of AI in health care. Studies are discussed based on the key principles such as evaluating workload, usability, trust in technology, perception, and user-centered design. ResultsForty-eight articles were included in the final review. Most of the studies emphasized user perception, the usability of AI-based devices or technologies, cognitive workload, and user’s trust in AI. The review revealed a nascent but growing body of literature focusing on augmenting health care AI; however, little effort has been made to ensure ecological validity with user-centered design approaches. Moreover, few studies (n=5 against clinical/baseline standards, n=5 against clinicians) compared their AI models against a standard measure. ConclusionsHuman factors researchers should actively be part of efforts in AI design and implementation, as well as dynamic assessments of AI systems’ effects on interaction, workflow, and patient outcomes. An AI system is part of a greater sociotechnical system. Investigators with human factors and ergonomics expertise are essential when defining the dynamic interaction of AI within each element, process, and result of the work system

Designing Patient-facing Health Information Technologies for the Outpatient Settings: A Literature Review

Introduction: The implementation of health information technologies (HITs) has changed the dynamics of doctor–patient communication in outpatient settings. Designing patient-facing HITs provides patients with easy access to healthcare information during the visit and has the potential to enhance the patient-centred care.   Objectives: The objectives of this study are to systematically review how the designs of patient-facing HITs have been suggested and evaluated, and how they may potentially affect the doctor–patient communication and patient-centred care.   Method: We conducted an online database search to identify articles published before December 2014 relevant to the objectives of this study. A total of nine papers have been identified and reviewed in this study.   Results: Designing patient-facing HITs is at an early stage. The current literature has been exploring the impact of HITs on doctor–patient communication dynamics. Based on the findings of these studies, there is an emergent need to design more patient-centred HITs. There are also some papers that focus on the usability evaluation of some preliminary prototypes of the patient-facing HITs. The design styles of patient-facing HITs included sharing the health information with the patients on: (1) a separate patient display, (2) a projector, (3) a portable tablet, (4) a touch-based screen and (5) a shared computer display that can be viewed by both doctors and patients. Each of them had the strengths and limitations to facilitate the patient-centred care, and it is worthwhile to make a comparison of them in order to identify future research directions.   Conclusion: The designs of patient-facing HITs in outpatient settings are promising in facilitating the doctor-patient communication and patient engagement. However, their effectiveness and usefulness need to be further evaluated and improved from a systems perspective

Digital twins for better healthcare management: rapid literature review

We performed a rapid review of studies involving digital twins’ technology to improve healthcare services management. Rapid reviews typically do not include an exhaustive set of studies, do not involve formal analyses of study quality, and report findings from prior studies via narrative synthesis

Role of Trust in AI-Driven Healthcare Systems: Discussion from the Perspective of Patient Safety

© 2021 by Human Factors and Ergonomics Society.In the field of healthcare, enhancing patient safety depends on several factors (e.g., regulation, technology, care quality, physical environment, human factors) that are interconnected. Artificial Intelligence (AI), along with an increasing realm of use, functions as a component of the overall healthcare system from a multi-agent systems viewpoint. Far from a stand-alone agent, AI cannot be held liable for the flawed decisions in healthcare. Also, AI does not have the capacity to be trusted according to the most prevalent definitions of trust because it does not possess emotive states or cannot be held responsible for their actions. A positive experience of AI reliance comes to be indicative of ‘trustworthiness’ rather than ‘trust’, implying further consequences related to patient safety. From a multi-agent systems viewpoint, ‘trust’ requires all the environmental, psychological and technical conditions being responsive to patient safety. It is fertilized for the overall system in which ‘responsibility’, ‘accountability’, ‘privacy’, ‘transparency; and ‘fairness’ need to be secured for all the parties involved in AI-driven healthcare, given the ethical and legal concerns and their threat to the trust.Peer reviewe