98%
921
2 minutes
20
Background: The role of technology in the perioperative care of patients continues to grow. A surgeon-specific perioperative chatbot may improve the care of patients by answering questions or concerns. The purpose of this retrospective review was to assess if enrollment in a perioperative chatbot was associated with differences in clinical outcomes or patient satisfaction following periacetabular osteotomy.
Methods: We identified 62 patients who enrolled in a short message service (SMS) chatbot from December 1, 2020 to August 1, 2023. A consecutive historical cohort of 64 patients from August 1, 2018 to November 30, 2020 was identified for comparative purposes. Descriptive statistics were used to compare demographic differences between patients enrolled vs not enrolled in the chatbot. Independent t-tests, Fischer's exact tests, and chi-squared tests were also used for comparative purposes.
Results: Patients who were enrolled in a perioperative SMS-based chatbot requested significantly fewer narcotic refills ( = .0001). There were also significantly fewer clinic calls placed for patients enrolled in the chatbot compared to those not enrolled (1.1 calls vs 3.3 calls, < .0001). There were no significant differences in emergency department visits or readmissions within 90 days of surgery, reoperations, or infections. Patients enrolled in a perioperative chatbot had significantly higher satisfaction compared to those not enrolled (4.7 vs 4.3, = .039).
Conclusions: Enrollment in an SMS-based perioperative chatbot for patients undergoing periacetabular osteotomy was associated with fewer narcotic refills, fewer telephone calls to clinic, and increased patient satisfaction compared to a historical cohort not enrolled perioperative chatbot.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241380 | PMC |
http://dx.doi.org/10.1016/j.artd.2025.101752 | DOI Listing |
AJOG Glob Rep
August 2025
Department of Obstetrics, Gynecology & Women's Health, University of Hawaii, Honolulu, HI (Kho).
Background: Within public online forums, patients often seek reassurance and guidance from the community regarding postoperative symptoms and expectations, and when to seek medical assistance. Others are using artificial intelligence in the form of online search engines or chatbots such as ChatGPT or Perplexity. Artificial intelligence chatbot assistants have been growing in popularity; however, clinicians may be hesitant to use them because of concerns about accuracy.
View Article and Find Full Text PDFBMJ Open
September 2025
Department of Anesthesiology, The Third People's Hospital of Chengdu, Chengdu, Sichuan, People's Republic of China
Objective: This study aimed to explore orthopaedic patients' and families' experiences with artificial intelligence (AI)-driven chatbots for perioperative health information, focusing on usability, effectiveness and perceptions.
Design: A descriptive qualitative design was employed.
Setting: This study was conducted at a regional care centre for orthopaedics.
Sci Rep
August 2025
Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Deep vein thrombosis (DVT) is a serious complication following gastrointestinal surgery. While D-dimer is a widely used biomarker for thrombosis, its postoperative specificity is limited due to inflammatory interference. This study introduces a novel cumulative metric-7-day D-dimer exposure (7dDDE)-to quantify perioperative coagulation burden.
View Article and Find Full Text PDFAnesthesiol Clin
September 2025
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, USA.
Artificial Intelligence (AI) is widely used in various fields, including the health system and related sciences, as one of the significant advances in technology. Many efforts are being made to improve the prevention, diagnosis, prediction, treatment, and rehabilitation of diseases through the use of AI. The application of AI in the medical sciences is from machine models to search medical data and discover insights to help improve health outcomes and patient experiences.
View Article and Find Full Text PDFNPJ Digit Med
July 2025
Department of Anesthesiology, Singapore General Hospital, Singapore, Singapore.
Preoperative assessment is a critical but time-consuming component of perioperative care, often hindered by poor guideline adherence and high documentation burdens. This study evaluates the impact of PEACH (PErioperative AI CHatbot), an LLM-based clinical decision support system, on documentation efficiency, quality, user acceptance, and cost-effectiveness in preoperative consultations. PEACH did not significantly reduce overall documentation time in this randomized crossover trial involving resident physicians at Singapore General Hospital.
View Article and Find Full Text PDF