Readmission Risk Assessment Technologies and the Anchoring and Adjustment Heuristic.

Approximately 23% of patients discharged from primary healthcare facilities are readmitted within 30 days at an annual cost of roughly $42 billion. To remedy this problem, healthcare providers are attempting to deploy readmission risk estimation tools, but how they might be used in the traditional, human-expert-centered decision process is not well understood. One such tool estimates readmission risk based on 50 patient-specific factors. This paper reports on a study performed in collaboration with Order of St. Francis Healthcare to determine how healthcare workers' own risk estimates are influenced by the tool, specifically testing the hypothesis that they will first anchor towards tool results while making adjustments based on their expertise, and then make further adjustments when additional human expert opinions are presented. Task analysis was performed, fictional patient scenarios were developed, and a survey of 56 subjects in two stratified groups of case managers was conducted. Data from the control and experiment groups were analyzed using ANOVA/GLM and t-tests. Results indicate that the healthcare workers' risk estimates were influenced by the anchor provided by the tool, then adjusted based on their expertise. The workers further adjusted their estimates in response to new expert human inputs. Thus, a reliance on both the predictive model and human expertise was observed.

Steady-state and dynamic desorption of organic vapor from activated carbon with electrothermal swing adsorption.

A new method to achieve steady-state and dynamic-tracking desorption of organic compounds from activated carbon was developed and tested with a bench-scale system. Activated carbon fiber cloth (ACFC) was used to adsorb methyl ethyl ketone (MEK) from air streams. Direct electrothermal heating was then used to desorb the vapor to generate select vapor concentrations at 500 ppmv and 5000 ppmv in air. Dynamic-tracking desorption was also achieved with carefully controlled yet variable vapor concentrations between 250 ppmv and 5000 ppmv, while also allowing the flow rate of the carrier gas to change by 100%. These results were also compared to conditions when recovering MEK as a liquid, and using microwaves as the source of energy to regenerate the adsorbent to provide MEK as a vapor or a liquid.

Constrained optimization for green engineering decision-making.

Green engineering requires the designer to consider a very extensive set of environmental impacts. To minimize these impacts, the designer must significantly expand his or her "toolset" of product design concepts, alternative materials, manufacturing systems, and analytic methods for addressing life cycle impacts. This can overwhelm a designer, who then resorts to overly simplistic rules or checklists out of necessity. The central issue is how to identify all "pollution prevention pays" opportunities and then how to deal with the unavoidable tradeoffs that arise after all these opportunities have been exhausted. This paper presents a framework for employing mathematical decision modeling toward this end. A domain-independent constrained optimization formulation is presented. A multiattribute utility function reflects the willingness to pay for environmental improvement and is the basis of the objective function. The feasibility constraints reflect the unavoidable tradeoffs. Several case studies are presented, including power systems, floor tile manufacturing, and computer systems.