Turnover of healthcare professionals’ is a rapidly growing human resource issue that affects healthcare systems. During the COVID-19 pandemic, healthcare professionals have faced stressful situations that have negatively impacted their psychological health. In this study, we explored impacts of the emotional wellbeing of healthcare professionals on their intention to quit their jobs. A cross-sectional survey design was used for this study. The respondents were selected based on simple random sampling. In total, 345 questionaries were returned and used for the analysis. Respondents were healthcare professionals (nurses, doctors, midwives, technicians, etc.) working in a pandemic hospital in Turkey. A multivariable logistic regression model was used to predict the emotions that encouraged the respondents to intend to quit their jobs. Emotions including anxiety, burnout, and depression were measured using validated scales. We found that the COVID-19 situation increased the turnover intention, especially among doctors and nurses (ORnurse/midwife = 22.28 (2.78–41.25), p = 0.01; ORdoctors = 18.13 (2.22–2.27), p = 0.01) mediating the emotional pressure it was putting them under. Anxiety related to work-pressure and burnout especially were the main emotional predictors of turnover intention. The more severe the anxiety was, the more the professional considered quitting (ORmoderate = 18.96 (6.75–137.69), p = 0.005; ORsevere = 37.94 (2.46–107.40), p = 0.016). Only severe burnout, however, engendered such an intention among them (ORsevere = 13.05 (1.10–33.48), p = 0.000).

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Background Online medical records are being used to organize processes in clinical and outpatient settings and to forge doctor-patient communication techniques that build mutual understanding and trust. Objective We aimed to understand the reasons why patients tend to avoid using online medical records and to compare the perceptions that patients have of online medical records based on demographics and cancer diagnosis. Methods We used data from the Health Information National Trends Survey Cycle 3, a nationally representative survey, and assessed outcomes using descriptive statistics and chi-square tests. The patients (N=4328) included in the analysis had experienced an outpatient visit within the previous 12 months and had answered the online behavior question regarding their use of online medical records. Results Patients who were nonusers of online medical records consisted of 58.36% of the sample (2526/4328). The highest nonuser rates were for patients who were Hispanic (460/683, 67.35%), patients who were non-Hispanic Black (434/653, 66.46%), and patients who were older than 65 years (968/1520, 63.6%). Patients older than 65 years were less likely to use online medical records (odds ratio [OR] 1.51, 95% CI 1.24-1.84, P<.001). Patients who were White were more likely to use online medical records than patients who were Black (OR 1.71, 95% CI 1.43-2.05, P<.001) or Hispanic (OR 1.65, 95% CI 1.37-1.98, P<.001). Patients who were diagnosed with cancer were more likely to use online medical records compared to patients with no cancer (OR 1.31, 95% CI 1.11-1.55, 95% CI 1.11-1.55, P=.001). Among nonusers, older patients (≥65 years old) preferred speaking directly to their health care providers (OR 1.76, 95% CI 1.35-2.31, P<.001), were more concerned about privacy issues caused by online medical records (OR 1.79, 95% CI 1.22-2.66, P<.001), and felt uncomfortable using the online medical record systems (OR 10.55, 95% CI 6.06-19.89, P<.001) compared to those aged 18-34 years. Patients who were Black or Hispanic were more concerned about privacy issues (OR 1.42, 1.09-1.84, P=.007). Conclusions Studies should consider social factors such as gender, race/ethnicity, and age when monitoring trends in eHealth use to ensure that eHealth use does not induce greater health status and health care disparities between people with different backgrounds and demographic characteristics.

Background Although most digital twin (DT) applications for health care have emerged in precision medicine, DTs can potentially support the overall health care process. DTs (twinned systems, processes, and products) can be used to optimize flows, improve performance, improve health outcomes, and improve the experiences of patients, doctors, and other stakeholders with minimal risk. Objective This paper aims to review applications of DT systems, products, and processes as well as analyze the potential of these applications for improving health care management and the challenges associated with this emerging technology. Methods We performed a rapid review of the literature and reported available studies on DTs and their applications in health care management. We searched 5 databases for studies published between January 2002 and January 2022 and included peer-reviewed studies written in English. We excluded studies reporting DT usage to support health care practice (organ transplant, precision medicine, etc). Studies were analyzed based on their contribution toward DT technology to improve user experience in health care from human factors and systems engineering perspectives, accounting for the type of impact (product, process, or performance/system level). Challenges related to the adoption of DTs were also summarized. Results The DT-related studies aimed at managing health care systems have been growing over time from 0 studies in 2002 to 17 in 2022, with 7 published in 2021 (N=17 studies). The findings reported on applications categorized by DT type (system: n=8; process: n=5; product: n=4) and their contributions or functions. We identified 4 main functions of DTs in health care management including safety management (n=3), information management (n=2), health management and well-being promotion (n=3), and operational control (n=9). DTs used in health care systems management have the potential to avoid unintended or unexpected harm to people during the provision of health care processes. They also can help identify crisis-related threats to a system and control the impacts. In addition, DTs ensure privacy, security, and real-time information access to all stakeholders. Furthermore, they are beneficial in empowering self-care abilities by enabling health management practices and providing high system efficiency levels by ensuring that health care facilities run smoothly and offer high-quality care to every patient. Conclusions The use of DTs for health care systems management is an emerging topic. This can be seen in the limited literature supporting this technology. However, DTs are increasingly being used to ensure patient safety and well-being in an organized system. Thus, further studies aiming to address the challenges of health care systems challenges and improve their performance should investigate the potential of DT technology. In addition, such technologies should embed human factors and ergonomics principles to ensure better design and more successful impact on patient and doctor experiences.

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PURPOSE Early detection of cancer risk is essential as it is associated with a higher chance of survival, more successful treatment, and improved quality of life. Genetic testing helps at-risk patients estimate the likelihood of developing cancer in a lifetime. This study aims to indentify the factors (perceived susceptibility, severity, benefits, and self-efficacy) that impact one's decision to take the genetic test. METHODS We examined the impacts of different factors of the health belief model on the engagement of patients in genetic testing using data from the National Cancer Institute's 2020 cross-sectional nationally representative data published in 2021. Complete surveys were answered by 3,865 participants (weighted population size = 253,815,197). All estimates were weighted to be nationally representative of the US population using the jackknife weighting method for parameter estimation. We used multivariable logistic regression to test our hypotheses for patients who have taken the genetic test for cancer risk detection. We adjusted the multivariate model for age, education, income, race, sex, cancer history, familial cancer history, and education. RESULTS We tested five hypotheses using the health belief model. Respondents who had genetic testing were more likely to rely on their health care providers and genetic counselors to make their decisions. Respondents who had genetic tests also reported less reliability on other sources than doctors: for the internet and social media (odds ratio = 0.33; P < .001) and for journals and magazines (odds ratio = 0.48; P = .007). CONCLUSION The findings show that patients generally rely on suggestions from their health care providers and counselors in genetic testing decisions. These findings also indicate that health care providers play a critical role in helping patients decide whether to use genetic testing to detect cancer risk in the early stages.

Diagnostic errors contribute to hospital complications that can lead to death. It is essential to create a favorable environment for implementing AI-related technologies to improve medical diagnostics. This study aims to present the different categories of A.I. diagnostic applications, as well as the organizational factors and policies, influencing the best adoption and implementation of A.I. applications. We conducted an online database search to identify peer-reviewed papers published between Jan 2009 and May 2019 that were related to A.I. applications in medical diagnostics. Papers were included as indexed in database PubMed if they contain any one of the following: (1) the research used Artificial Intelligence or Machine Learning or Deep Learning to perform medical diagnostics, and (2) the research conducted validation analysis or clinical trial. Additionally, we explored whether the study can promisingly improve social welfare or achieve cost-savings by improving clinical outcomes. 197 selected papers were explored that covered the following topics: types of diagnostic technology, medical application scenario, clinical outcome measurement, potential benefit, and how the AI-related diagnostics is improving the clinical outcome and produce economic value.

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