The Physicians’ Barriers to Practice of Advance Care Planning:A Single Facility Questionnaire Survey

Background: Although practicing advanced care planning (ACP) has recently been recommended, little is known about physicians’ practice of ACP, and barriers to ACP in Japan. We aimed to clarify the proportion of physicians practicing ACP and explore barriers to ACP. Methods: We conducted a cross-sectional survey among physicians at a tertiary hospital (934 beds) in 2019, and asked them about their practice and awareness of ACP as well as beliefs regarding end-of-life discussions. A multivariate logistic regression analysis was conducted to explore barriers to their practice of ACP. Results: In total, 90 of 186 physicians responded (response rate, 48%). Forty-two (46%; 95% confidence interval=37-57%) reported that they practiced ACP. In multivariate analysis, determinants of “not” practicing ACP included the lack of awareness of ACP and physicians’ greater beliefs regarding the lack of resources as well as the lack of time and perception of burden. Conclusion: Even at the tertiary hospital, only less than a half of physicians practiced ACP, and the lack of their awareness of ACP and various beliefs served as barriers to their practice. Initiatives to raise awareness of ACP and optimize the management to ensure sufficient time and resources for physicians may be promising to promote ACP.

5-Aminosalicylic acid intolerance is associated with a risk of adverse clinical outcomes and dysbiosis in patients with ulcerative colitis

Background/Aims@#5-Aminosalicylic acid (ASA) causes intolerance reactions in some patients. This study was performed to examine the prognosis of patients with ulcerative colitis (UC) and 5-ASA intolerance, and to evaluate the potential interaction between 5-ASA intolerance and the intestinal microbiota. @*Methods@#We performed a retrospective cohort study of patients with UC who visited participating hospitals. The primary endpoint was to compare the incidence of hospitalization within 12 months between the 5-ASA intolerance group and the 5-ASA tolerance group. The secondary endpoint was to compare the risk of adverse clinical outcomes after the start of biologics between the 2 groups. We also assessed the correlation between 5-ASA intolerance and microbial change in an independently recruited cohort of patients with UC. @*Results@#Of 793 patients, 59 (7.4%) were assigned to the 5-ASA intolerance group and 734 (92.5%) were assigned to the 5-ASA tolerance group. The admission rate and incidence of corticosteroid use were significantly higher in the intolerance than tolerance group (P< 0.001). In 108 patients undergoing treatment with anti-tumor necrosis factor biologics, 5-ASA intolerance increased the incidence of additional induction therapy after starting biologics (P< 0.001). The 5-ASA intolerance group had a greater abundance of bacteria in the genera Faecalibacterium, Streptococcus, and Clostridium than the 5-ASA tolerance group (P< 0.05). @*Conclusions@#In patients with UC, 5-ASA intolerance is associated with a risk of adverse clinical outcomes and dysbiosis. Bacterial therapeutic optimization of 5-ASA administration may be important for improving the prognosis of patients with UC.

Evaluation of Waiting Time Prediction using Data Collected from Prescriptions / 社会薬学

We performed waiting time prediction using the data collected from prescription pick-up. A regression equation was used to predict waiting time. An explanatory variable was adopted as “a number of retention prescriptions at the time of acceptance”, “the variety of drug to dispense”and “the presence or absence of a particular task of time-consuming work in computing multiple medications into one package”. Using waiting time as an objective variable, three regression equations were formulated. Method ①: A single regression equation using the number of retention prescriptions with only one explanatory variable. Method ②: Multiple regression equation using factors such as number of prescriptions and variety of drugs to be dispensed as explanatory variables. Method ③: Multiple regression equation using number of prescriptions, variety of drugs and the presence or absence of particular tasks involved in the preparation of the prescription. Compared to the prediction of Method ①, the prediction of Method ② resulted in better accuracy. Compared to Method ①, Method ② resulted in better accuracy, and Method ③ resulted in even better accuracy than Method ②, as predicted.