JMIR Human Factors
(Re-)designing health care and making health care interventions and technologies usable, safe, and effective
JMIR Human Factors (JHF, ISSN 2292-9495; Editor-in-Chief: Prof. Andre Kushniruk) is a multidisciplinary journal with contributions from design experts, medical researchers, engineers, and social scientists.
JMIR Human Factors focuses on understanding how the behaviour and thinking of humans can influence and shape the design of health care interventions and technologies, and how the design can be evaluated and improved to make health care interventions and technologies usable, safe, and effective. This includes usability studies and heuristic evaluations, studies concerning ergonomics and error prevention, design studies for medical devices and healthcare systems/workflows, enhancing teamwork through Human Factors based teamwork training, measuring non-technical skills in staff like leadership, communication, situational awareness and teamwork, and healthcare policies and procedures to reduce errors and increase safety.
JHF aspires to lead health care towards a culture of "usability by design", as well as to a culture of testing, error-prevention and safety, by promoting and publishing reports rigorously evaluating the usability and human factors aspects in health care, as well as encouraging the development and debate on new methods in this emerging field. Possible contributions include usability studies and heuristic evaluations, studies concerning ergonomics and error prevention, design studies for medical devices and healthcare systems/workflows, enhancing teamwork through human factors-based teamwork training, measuring non-technical skills in staff like leadership, communication, situational awareness and teamwork, and healthcare policies and procedures to reduce errors and increase safety. Reviews, viewpoint papers and tutorials are as welcome as original research.
Although mobile health (mHealth) apps are increasingly being used to support patients with multiple chronic conditions (multimorbidity), most mHealth apps experience low interaction and eventual abandonment. To tackle this engagement issue, when developing an mHealth program, it is important to understand the social-behavioral factors that affect patients’ use behavior.
COVID-19 has led to over 500 million cases and 6.2 million deaths around the world. Low- and middle-income countries (LMICs) like Armenia face unique infrastructure, financial, and capacity challenges that in many cases result in worse outcomes. Health care facilities across Armenia experienced a shortage of resources, including hospital beds and oxygen, which was further exacerbated by the war with neighboring Azerbaijan. Without a framework for home-based care, health care facilities were severely strained by COVID-19 patients who had prolonged oxygen requirements but were otherwise clinically stable.
Misinformation related to the COVID-19 pandemic has accelerated global public concern and panic. The glut of information, or “infodemic,” has caused concern for authorities due to its negative impacts on COVID-19 prevention and control, spurring calls for a greater scholarly focus on health literacy during the pandemic. Nevertheless, few studies have sought to qualitatively examine how individuals interpreted and assimilated health information at the initial wave of COVID-19 restrictions.
Diabetes self-management is crucial for patients with type 1 diabetes, and digital services can support their self-management and facilitate flexible follow-up. The potential of using digital patient-reported outcome (PRO) measures in routine outpatient care is not fully used owing to a lack of adapted PRO measures.
Implementing mass vaccination clinics for COVID-19 immunization has been a successful public health activity worldwide. However, this tightly coupled system has many logistical challenges, leading to increased workplace stress, as evidenced throughout the pandemic. The complexities of mass vaccination clinics that combine multidisciplinary teams working within nonclinical environments are yet to be understood through a human systems perspective.
QR codes have played an integral role during the pandemic in many sectors, but their use has been limited in the health care sector, especially by patients. Although some authors have stated that developing specific content for women on how to cope with health problems could be an effective way to prevent problems, especially during pandemics, there is little research regarding the use of QR codes to promote health during a pandemic, and even fewer studies are focused on women. Moreover, although the importance of assessing these interventions from the users’ perspective has been stated, research carried out from this point of view is still scarce.
According to the US Food and Drug Administration Center for Biologics Evaluation and Research, health care systems have been experiencing blood transfusion overuse. To minimize the overuse of blood product transfusions, a proprietary artificial intelligence (AI)–based blood utilization calculator (BUC) was developed and integrated into a US hospital’s electronic health record. Despite the promising performance of the BUC, this technology remains underused in the clinical setting.
Smartphone ownership and mobile app use are steadily increasing in individuals of diverse racial and ethnic backgrounds living in the United States. Growing adoption of technology creates a perfect opportunity for digital health interventions to increase access to health care. To successfully implement digital health interventions and engage users, intervention development should be guided by user input, which is best achieved by the process of co-design. Digital health interventions co-designed with the active engagement of users have the potential to increase the uptake of guideline recommendations, which can reduce morbidity and mortality and advance health equity.
Sepsis is a major burden for health care systems in the United States, with over 750,000 cases annually and a total cost of approximately US $20 billion. The hallmark of sepsis treatment is early and appropriate initiation of antibiotic therapy. Although sepsis clinical decision support (CDS) systems can provide clinicians with early predictions of suspected sepsis or imminent clinical decline, such systems have not reliably demonstrated improvements in clinical outcomes or care processes. Growing evidence suggests that the challenges of integrating sepsis CDS systems into clinical workflows, gaining the trust of clinicians, and making sepsis CDS systems clinically relevant at the bedside are all obstacles to successful deployment. However, there are significant knowledge gaps regarding the achievement of these implementation and deployment goals.