Abstract:

Objective To investigate the discharge readiness of patients with drug-resistant tuberculosis and analyze the influencing factors. Methods A total of 117 patients with drug-resistant pulmonary tuberculosis hospitalized in Shanghai Pulmonary Hospital Affiliated to Tongji University from May 2020 to March 2021 were collected using convenience sampling method. General data questionnaire, discharge preparation scale and discharge guidance quality scale were used to conduct a questionnaire survey on the subjects. A total of 117 questionnaires were distributed, and 117 valid questionnaires were received with effective recovery rate of 100.0%. The scores of discharge readiness and discharge guidance quality of the subjects were analyzed. Linear regression was used to analyze the factors influencing the level of discharge readiness of patients with drug-resistant tuberculosis. Results The overall score of the study subjects’ discharge readiness was 91.03±16.06, and the item average score was 7.59±1.34, which was at the medium level; the overall score of discharge guidance quality was 142.09±18.76, and the items average score was 7.91±1.52, which was above average level. Multiple linear regression analysis showed that aged over 60 years old (standard regression coefficient=-0.209, t=-2.345, P=0.021), primary school education and below (standard regression coefficient=0.216, t=2.199, P=0.030), family per capita monthly income less than RMB 2000 yuan (standard regression coefficient=0.210, t=2.411, P=0.018), and poor quality of discharge guidance (standard regression coefficient=0.229, t=2.857, P=0.005) would cause bad discharge prepare. Conclusion For patients with drug-resistant tuberculosis, discharge guidance should be strengthened for patients with older age, low education level and poor economic conditions, and the quality of discharge guidance should be improved, and targeted intervention measures should be given according to the situation of patients.

Key words: Tuberculosis,pulmonary, Drug resistance, Aftercare, Patient care, Regression analysis