Artificial intelligence in overcoming rifampicin resistant-screening challenges in Indonesia: a qualitative study on the user experience of CUHAS-ROBUST

• Päätekijät: Bumi Herman (Tekijä), Wandee Sirichokchatchawan (Tekijä), Chanin Nantasenamat (Tekijä), Sathirakorn Pongpanich (Tekijä)
• Aineistotyyppi: Kirja
• Julkaistu: College of Public Health Sciences, Chulalongkorn University, 2022-09-01T00:00:00Z.
• Aiheet: article
• Linkit: Connect to this object online.
• Notes: 0857-4421; 2586-940X; 10.1108/JHR-11-2020-0535
• Keywords: artificial intelligence; rifampicin-resistant tuberculosis; screening; user experience; indonesia; Other systems of medicine; RZ201-999; Public aspects of medicine; RA1-1270
• Source: Journal of Health Research, Vol 36, Iss 6, Pp 1018-1027 (2022)

Purpose - The Chulalongkorn-Hasanuddin Rifampicin-Resistant Tuberculosis Screening Tool (CUHAS-ROBUST) is an artificial intelligence-based (AI-based) application for rifampicin-resistant tuberculosis (RR-TB) screening. This study aims to elaborate on the drug-resistant TB (DR-TB) problem and the impact of CUHAS-ROBUST implementation on RR-TB screening. Design/methodology/approach - A qualitative approach with content analysis was performed from September 2020 to October 2020. Medical staff from the primary care center were invited online for application trials and in-depth video call interviews. Transcripts were derived as a data source. An inductive thematic data saturation technique was conducted. Descriptive data of participants, user experience and the impact on the health service were summarized Findings - A total of 33 participants were selected from eight major islands in Indonesia. The findings show that DR-TB is a new threat, and its diagnosis faces obstacles particularly prolonged waiting time and inevitable delayed treatment. Despite overcoming the RR-TB screening problems with fast prediction, the dubious screening performance, and the reliability of data collection for input parameters were the main concerns of CUHAS-ROBUST. Nevertheless, this application increases the confidence in decision-making, promotes medical procedure compliance, active surveillance and enhancing a low-cost screening approach. Originality/value - The CUHAS-ROBUST achieved its purpose as a tool for clinical decision-making in RR-TB screening. Moreover, this study demonstrates AI roles in enhancing health-care quality and boost public health efforts against tuberculosis.