Implementation of artificial intelligence Chatbot in peritoneal dialysis nursing care: Experience from a Taiwan medical center.

PURPOSE: Coronavirus disease pandemic makes high requirements in delivering remote and efficient communication, and patient education. Because of the increases of digital and social media applications in Taiwan, we aim to apply Artificial Intelligence of LINE Chatbot to improve the self-care ability of patients undergoing peritoneal dialysis. MATERIALS AND METHODS: We conducted the project since 1 May 2021 to 30 April 2022. We designed an automatically replied Chatbot system, and divided into six scopes of interaction interfaces, including peritoneal dialysis technique operation video, clinical reminder, home caring, hospital registration service, dietary guideline, and Automatic Peritoneal dialysis guidance. We surveyed patients' satisfaction with the LINE Chatbot 3 months later by the Likert 1-5 score-based questionnaire and the higher score indicated higher satisfaction. RESULTS: There were 440 patients who joined the PD AI Chatbot study and use the Chatbot, but the satisfaction questionnaire recovery rate was only 297 patients. We found that 91.7% of participants agreed 'Overall satisfaction with patient intelligent Chatbot application'. More than 4 points accounted for 86.6%. We traced every click in each section of the Chatbot and explored the potential scenario patients face. The Chatbot statistically significant reduced infection rate of exit site and tunnel infection before using (p = .049 and .024). Furthermore, peritonitis rate decreased from 0.93 to 0.8/100 patient month after using Artificial Intelligence technique. Peritoneal dialysis Artificial Intelligence Chatbot had similar effect with face-to-face education. CONCLUSION: The innovative Chatbot allowed delivering remote and digital information's to improve patients' self-care ability. Peritoneal dialysis patients were highly recognized and satisfied with the tools. It deserves to further explore the long-term impact of Artificial Intelligence Chatbot in peritoneal dialysis care.

Integrating the Surprise Question, Palliative Care Screening Tool, and Clinical Risk Models to Identify Peritoneal Dialysis Patients With High One-Year Mortality.

CONTEXT: Universal screening to identify vulnerable patients who may receive limited benefits from life-sustaining treatments can facilitate palliative care in dialysis populations. OBJECTIVES: We aimed to develop prediction models for one-year mortality in peritoneal dialysis (PD) patients. METHODS: This prospective cohort study included 401 adult Taiwanese prevalent PD patients (average age 56.2 ± 14 years). In addition to obtaining clinical characteristics and laboratory data, the primary care nurses evaluated the surprise question (SQ) and palliative care screening tool (PCST) for each patient in March 2015. Multivariate logistic regression models were conducted to predict the primary outcome of one-year all-cause mortality. RESULTS: There were 34 (8.5%) patients who died during the first year of follow-up. Patients allocated to the not surprised group according to the SQ and those who received a score of ≥4 on the PCST had increased odds of death (odds ratio 24.68 [95% CI 10.66-57.13] and 12.18 [95% CI 5.66-26.21], respectively). We also developed a clinical risk model for one-year mortality that included sex, dialysis vintage, coronary artery disease, malignancy, normalized protein nitrogen appearance, white blood cell count, and serum albumin and sodium levels. Integrating the SQ, PCST, and clinical risk model exhibited good discrimination with an area under the receiver operating characteristic curve of 0.95. Kaplan-Meier analysis showed worse survival in high-risk patients predicted by the integrated model (log-rank P < 0.001). CONCLUSION: Screening with the use of the integrated measurement can identify high-risk PD patients. This approach may facilitate palliative care interventions for at-risk subpopulations.

The Effectiveness of Peritoneal Dialysis System Implementation on Case Management.

Peritoneal dialysis management system (PDS) is special design system to integrate all dialysis-related information for PD case managers. This study aims to investigate the impact of peritoneal dialysis system (PDS) implementation on the work efficacy of PD case managers. This study carried out in the PD unit of medical center in northern Taiwan. We utilized work sampling and chart reviews to compare the changes of work efficacy of PD case managers before and 3 months after PDS implementation. The results of this study showed direct care increased to 38.3% while indirect care decreased to 18% and unit-related care to 6.2%. The time spent on the five category activities has statistically significant difference before and after implementation of PDS. The completion rate of records has no statistically significant difference before and after the implementation of PDS. This study demonstrated that PDS implementation significantly affected the care patterns of PD for case managers.