The algorithm journey map: A tangible approach to implementing AI solutions in healthcare

When integrating AI tools in healthcare settings, complex interactions between technologies and primary users are not always fully understood or visible. This deficient and ambiguous understanding hampers attempts by healthcare organizations to adopt AI/ML, and it also creates new challenges for researchers to identify opportunities for simplifying adoption and developing best practices for the use of AI-based solutions. Our study fills this gap by documenting the process of designing, building, and maintaining an AI solution called SepsisWatch at Duke University Health System. We conducted 20 interviews with the team of engineers and scientists that led the multi-year effort to build the tool, integrate it into practice, and maintain the solution. This Algorithm Journey Map enumerates all social and technical activities throughout the AI solution\u27s procurement, development, integration, and full lifecycle management. In addition to mapping the who? and what? of the adoption of the AI tool, we also show several \u27lessons learned\u27 throughout the algorithm journey maps including modeling assumptions, stakeholder inclusion, and organizational structure. In doing so, we identify generalizable insights about how to recognize and navigate barriers to AI/ML adoption in healthcare settings. We expect that this effort will further the development of best practices for operationalizing and sustaining ethical principles-in algorithmic systems

Body-composition changes in the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE)-2 study: A 2-y randomized controlled trial of calorie restriction in nonobese humans

Background: Calorie restriction (CR) retards aging and increases longevity in many animal models. However, it is unclear whether CR can be implemented in humans without adverse effects on body composition.Objective: We evaluated the effect of a 2-y CR regimen on body composition including the influence of sex and body mass index (BMI; in kg/m2) among participants enrolled in CALERIE-2 (Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy), a multicenter, randomized controlled trial.Design: Participants were 218 nonobese (BMI: 21.9-28.0) adults aged 21-51 y who were randomly assigned to 25% CR (CR, n = 143) or ad libitum control (AL, n = 75) in a 2:1 ratio. Measures at baseline and 12 and 24 mo included body weight, waist circumference, fat mass (FM), fat-free mass (FFM), and appendicular mass by dual-energy X-ray absorptiometry; activity-related energy expenditure (AREE) by doubly labeled water; and dietary protein intake by self-report. Values are expressed as means ± SDs.Results: The CR group achieved 11.9% ± 0.7% CR over 2-y and had significant decreases in weight (-7.6 ± 0.3 compared with 0.4 ± 0.5 kg), waist circumference (-6.2 ± 0.4 compared with 0.9 ± 0.5 cm), FM (-5.4 ± 0.3 compared with 0.5 ± 0.4 kg), and FFM (-2.0 ± 0.2 compared with -0.0 ± 0.2 kg) at 24 mo relative to the AL group (all between-group P < 0.001). Moreover, FFM as a percentage of body weight at 24 mo was higher, and percentage of FM was lower in the CR group than in the AL. AREE, but not protein intake, predicted preservation of FFM during CR (P < 0.01). Men in the CR group lost significantly more trunk fat (P = 0.03) and FFM expressed as a percentage of weight loss (P < 0.001) than women in the CR group.Conclusions: Two years of CR had broadly favorable effects on both whole-body and regional adiposity that could facilitate health span in humans. The decrements in FFM were commensurate with the reduced body mass; although men in the CR group lost more FFM than the women did, the percentage of FFM in the men in the CR group was higher than at baseline. CALERIE was registered at clinicaltrials.gov as NCT00427193