Effect of Medication Reconciliation at Hospital Admission on 30-Day Returns to Hospital: A Randomized Clinical Trial.

Importance: According to international recommendations, hospitals should use medication reconciliation to prevent medication errors and improve patient safety. Objective: To assess the impact of medication reconciliation at hospital admission on patient-centered health care outcomes. Design, Setting, and Participants: This parallel group, open-label randomized controlled trial used centralized randomization to the intervention group (ie, individuals with medication reconciliation) or control group (ie, individuals with only standard, physician-acquired medication history). Outcome assessors and data analysts were blinded to group allocation. Participants included 1702 patients aged 85 years or older, with more than 10 medications at hospital admission, or meeting both conditions at 2 regional secondary teaching hospitals in southern Switzerland. Study duration was 14.5 months, from November 1, 2018, to January 15, 2020. Data were analyzed from December 2018 through March 2020. Interventions: Medication reconciliation was performed at hospital admission in 3 steps: (1) the pharmacy assistant obtained the list of the patient's current medications (ie, the best possible medication history [BPMH]); (2) the clinical pharmacist led reconciliation of the BPMH with the list of home medications recorded at hospital admission by the attending physician (according to the hospital standard procedure); and (3) medication discrepancies were communicated to the attending physician, and, when necessary, medications prescribed at admission were adapted. Main Outcomes and Measures: The primary outcome was a composite postdischarge health care use variable quantified as the proportion of patients with unplanned all-cause hospital visits (including visits to the emergency department and hospital readmissions) within 30 days after discharge from the hospital when medication reconciliation took place. A time-to-event analysis was performed. Results: Among 1702 patients (median [interquartile range] age, 86.0 [79.0-89.0] years; 720 [42.3%] men), 866 patients (50.9%) were allocated to the intervention group and 836 patients (49.1%) to the control group. The primary outcome occurred among 340 participants (39.3%) in the intervention group and 330 participants (39.5%) in the control group (P = .93). In time-to-event analyses at study closeout, unplanned all-cause hospital visits to the emergency department (log-rank P = .08) and unplanned all-cause hospital readmissions (log-rank P = .10) occurred similarly in the intervention and control groups. Conclusions and Relevance: These findings suggest that medication reconciliation at hospital admission has no impact on postdischarge health care outcomes among patients aged 85 years or older, with more than 10 medications at hospital admission, or meeting both conditions. Trial Registration: ClinicalTrials.gov Identifier: NCT03654963.

Can a Humanoid Face be Expressive? A Psychophysiological Investigation.

Non-verbal signals expressed through body language play a crucial role in multi-modal human communication during social relations. Indeed, in all cultures, facial expressions are the most universal and direct signs to express innate emotional cues. A human face conveys important information in social interactions and helps us to better understand our social partners and establish empathic links. Latest researches show that humanoid and social robots are becoming increasingly similar to humans, both esthetically and expressively. However, their visual expressiveness is a crucial issue that must be improved to make these robots more realistic and intuitively perceivable by humans as not different from them. This study concerns the capability of a humanoid robot to exhibit emotions through facial expressions. More specifically, emotional signs performed by a humanoid robot have been compared with corresponding human facial expressions in terms of recognition rate and response time. The set of stimuli included standardized human expressions taken from an Ekman-based database and the same facial expressions performed by the robot. Furthermore, participants' psychophysiological responses have been explored to investigate whether there could be differences induced by interpreting robot or human emotional stimuli. Preliminary results show a trend to better recognize expressions performed by the robot than 2D photos or 3D models. Moreover, no significant differences in the subjects' psychophysiological state have been found during the discrimination of facial expressions performed by the robot in comparison with the same task performed with 2D photos and 3D models.

Development and evaluation of a social robot platform for therapy in autism.

People with ASD (Autism Spectrum Disorders) have difficulty in managing interpersonal relationships and common life social situations. A modular platform for Human Robot Interaction and Human Machine Interaction studies has been developed to manage and analyze therapeutic sessions in which subjects are driven by a psychologist through simulated social scenarios. This innovative therapeutic approach uses a humanoid robot called FACE capable of expressing and conveying emotions and empathy. Using FACE as a social interlocutor the psychologist can emulate real life scenarios where the emotional state of the interlocutor is adaptively adjusted through a semi closed loop control algorithm which uses the ASD subject's inferred "affective" state as input. Preliminary results demonstrate that the platform is well accepted by ASDs and can be consequently used as novel therapy for social skills training.