ABSTRACT
Veteran suicide is one of the most complex and pressing health issues in the United States. According to the 2020 National Veteran Suicide Prevention Annual Report, since 2018 an average of 17.2 Veterans died by suicide each day. Veteran suicide risk screening is currently limited to suicide hotlines, patient reporting, patient visits, and family or friend reporting. As a result of these limitations, innovative approaches in suicide screening are increasingly garnering attention. An essential feature of these innovative methods includes better incorporation of risk factors that might indicate higher risk for tracking suicidal ideation based on personal behavior. Digital technologies create a means through which measuring these risk factors more reliably, with higher fidelity, and more frequently throughout daily life is possible, with the capacity to identify potentially telling behavior patterns. In this review, digital predictive biomarkers are discussed as they pertain to suicide risk, such as sleep vital signs, sleep disturbance, sleep quality, and speech pattern recognition. Various digital predictive biomarkers are reviewed and evaluated as well as their potential utility in predicting and diagnosing Veteran suicidal ideation in real time. In the future, these digital biomarkers could be combined to generate further suicide screening for diagnosis and severity assessments, allowing healthcare providers and healthcare teams to intervene more optimally.
ABSTRACT
Artificial intelligence offers the promise of transforming biomedical research and helping clinicians put the "care" back in healthcare. Digital medicine is on its way to becoming just plain medicine. But who will digitize how we define health and disease? And who will deploy this knowledge to improve the lives of patients that medicine - and digital medicine - exists to serve? Here we define the emerging field of digital medicine and identify the disciplines and skills needed for success. We examine the current and projected skills gaps. We also consider the impact of the culture clash that occurs at the intersection of healthcare and technology, and the lack of diversity in the workforce of both of these fields. We conclude by describing the requirements for the skills pivot needed to ensure that the digital transformation of healthcare is successful: (1) big tent thinking to recognize the critical importance of new technical skills alongside more traditional clinical disciplines, (2) the integration of clinical and technical skill sets within educational curricula, companies, and professional institutions, and (3) a commitment to diversity that goes beyond lip service.
ABSTRACT
Requests for outpatient specialty consultations occur frequently but often are of poor quality because of incompleteness. The authors searched bibliographic databases, trial registries, and references during October 2014 for studies evaluating interventions to improve the quality of outpatient specialty referral requests compared to usual practice. Two reviewers independently extracted data and assessed quality. Findings were qualitatively summarized for completeness of information relayed in a referral request within naturally emerging intervention categories. Of 3495 articles screened, 11 were eligible. All 3 studies evaluating software-based interventions found statistically significant improvements. Among 4 studies evaluating template/pro forma interventions, completeness was uniformly improved but with variable or unreported statistical significance. Of 4 studies evaluating educational interventions, 2 favored the intervention and 2 found no difference. One study evaluating referral management was negative. Current evidence for improving referral request quality is strongest for software-based interventions and templates, although methodological quality varied and findings may be setting specific.
