Digitizing clinical trials.

Clinical trials are a fundamental tool used to evaluate the efficacy and safety of new drugs and medical devices and other health system interventions. The traditional clinical trials system acts as a quality funnel for the development and implementation of new drugs, devices and health system interventions. The concept of a "digital clinical trial" involves leveraging digital technology to improve participant access, engagement, trial-related measurements, and/or interventions, enable concealed randomized intervention allocation, and has the potential to transform clinical trials and to lower their cost. In April 2019, the US National Institutes of Health (NIH) and the National Science Foundation (NSF) held a workshop bringing together experts in clinical trials, digital technology, and digital analytics to discuss strategies to implement the use of digital technologies in clinical trials while considering potential challenges. This position paper builds on this workshop to describe the current state of the art for digital clinical trials including (1) defining and outlining the composition and elements of digital trials; (2) describing recruitment and retention using digital technology; (3) outlining data collection elements including mobile health, wearable technologies, application programming interfaces (APIs), digital transmission of data, and consideration of regulatory oversight and guidance for data security, privacy, and remotely provided informed consent; (4) elucidating digital analytics and data science approaches leveraging artificial intelligence and machine learning algorithms; and (5) setting future priorities and strategies that should be addressed to successfully harness digital methods and the myriad benefits of such technologies for clinical research.

Occupational tuberculosis among deputy sheriffs in Connecticut: a risk model of transmission.

OBJECTIVES: The purpose of this study was to identify risk factors for tuberculin skin test conversions among non-infected deputy sheriffs in Connecticut and during an out-break in an urban lock-up. METHODS: 377 tuberculin skin-test negative sheriffs statewide in 1994-1995 and 37 sheriffs in the lock-up in 1995 were screened and questionnaires administered. Cellblock volumetric air flow was measured. The Wells-Riley model of airborne transmission [C = S(1-e-Iqpt/Q)] was applied to the epidemiologic and ventilation data. RESULTS: Statewide, of 377 sheriffs screened, 22 (5.8%) had positive skin tests. Risk factors included older age (p < .0075) and longer tenure (p < .036). In the lock-up, of 37 sheriffs screened, 4 (10.8%) had positive skin tests. Measured mean outside air flow per occupant (8.0 cfm; S.D. = 2.2) was below design (15 cfm) and recommended (20 cfm) standards. Mathematical modeling estimated that TB transmission would be reduced by 62.5 percent with ventilation at design specifications. CONCLUSIONS: Inadequate ventilation may increase the risk for occupational transmission of tuberculosis. Since lock-ups do not have the time to conduct inmate TB screenings, supplemental engineering controls may be required.