Engagement model for enhancing tuberculosis service quality among network partners in prisons, correctional institutions, and four referral hospitals in Nakhon Si Thammarat Province, Thailand
DOI:
https://doi.org/10.14456/taj.2026.4Keywords:
participation, quality of tuberculosis service delivery, Nakhon Si ThammaratAbstract
This action research aimed to examine the participatory process for improving the quality of tuberculosis (TB) service delivery in four prisons and correctional institutions in Nakhon Si Thammarat Province, using the PDCA (plan-do-check-act) framework. The target group consisted of 30 TB service providers from prisons, correctional institutions, and referral hospitals. The study was conducted from February to July 2025. Data were collected through document review, workflow assessment, questionnaires, and focus group discussions. Quantitative data were analyzed using percentages, and qualitative data were analyzed using content analysis. The findings revealed several inefficiencies in the TB service delivery process. TB screening by chest X-ray required a waiting time of 60-90 days and the turnaround time for X-ray results was 15 days. Delays were also observed in referral reporting, along with inadequate referral for household contact screening and post-release follow-up. To reduce these inefficiencies, the team implemented the following improvements: (1) provision of a mobile X-ray unit; (2) utilization of an artificial intelligence (AI) program for chest X-ray interpretation; and (3) strengthening referral processes to ensure comprehensive household contact screening and post-release follow-up. As a result, a quality strategy for prison TB service delivery under the concept of “early detection and rapid cure” was established, consisting of three steps: (1) screening and diagnosis with results available within 14 days (4,887 individuals screened); (2) treatment initiation within 1 day (14 patients, 100%); and (3) post-release referral within 7 days (70 individuals,100%). It is recommended that mobile X-ray units be supported in prisons, and that AI programs be utilized for preliminary chest X-ray interpretation.
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