The Impact of potential 'confounders' on the diagnostic sensitivity of circulating free DNA in management of FIT+ patients: a pilot study.

Cell-free DNA (cfDNA) has long been established as a useful diagnostic and prognostic tool in a variety of clinical settings, ranging from infectious to cardiovascular and neoplastic diseases. However, non-neoplastic diseases can act as confounders impacting on the amount of cfDNA shed in bloodstream and on technical feasibility of tumour derived free circulating nucleic acids selecting patients with cancer. Here, we investigated the potential impact of other pathological processes in the clinical stratification of 637 FIT+ patients. A single and multiple logistic regression yielded similar results. Crude sensitivity was 75.9% versus adjusted sensitivity of 74.1%, relative risk 0.9761 (0.8516 to 1.1188), risk difference 0.0181 (-0.0835 to 0.1199) and OR 0.9079 (0.5264 to 1.5658). Potential confounding effect from other source of cfDNA plays a pivotal role in the clinical stratification of FIT+ patients.

Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions.

BACKGROUND: Due to the adoption of electronic health records (EHRs) and legislation on meaningful use in recent decades, health systems are increasingly interdependent on EHR capabilities, offerings, and innovations to better capture patient data. A novel capability offered by health systems encompasses the integration between EHRs and wearable health technology. Although wearables have the potential to transform patient care, issues such as concerns with patient privacy, system interoperability, and patient data overload pose a challenge to the adoption of wearables by providers. OBJECTIVE: This study aimed to review the landscape of wearable health technology and data integration to provider EHRs, specifically Epic, because of its prevalence among health systems. The objectives of the study were to (1) identify the current innovations and new directions in the field across start-ups, health systems, and insurance companies and (2) understand the associated challenges to inform future wearable health technology projects at other health organizations. METHODS: We used a scoping process to survey existing efforts through Epic's Web-based hub and discussion forum, UserWeb, and on the general Web, PubMed, and Google Scholar. We contacted Epic, because of their position as the largest commercial EHR system, for information on published client work in the integration of patient-collected data. Results from our searches had to meet criteria such as publication date and matching relevant search terms. RESULTS: Numerous health institutions have started to integrate device data into patient portals. We identified the following 10 start-up organizations that have developed, or are in the process of developing, technology to enhance wearable health technology and enable EHR integration for health systems: Overlap, Royal Philips, Vivify Health, Validic, Doximity Dialer, Xealth, Redox, Conversa, Human API, and Glooko. We reported sample start-up partnerships with a total of 16 health systems in addressing challenges of the meaningful use of device data and streamlining provider workflows. We also found 4 insurance companies that encourage the growth and uptake of wearables through health tracking and incentive programs: Oscar Health, United Healthcare, Humana, and John Hancock. CONCLUSIONS: The future design and development of digital technology in this space will rely on continued analysis of best practices, pain points, and potential solutions to mitigate existing challenges. Although this study does not provide a full comprehensive catalog of all wearable health technology initiatives, it is representative of trends and implications for the integration of patient data into the EHR. Our work serves as an initial foundation to provide resources on implementation and workflows around wearable health technology for organizations across the health care industry.