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Abstract
In South Korea, public–private mix (PPM) was launched in 2011. This retrospective cohort study sought to determine the rate of loss to follow-up (LTFU) among drug-susceptible tuberculosis (DS-TB) patients in all nationwide PPM institutions, and the risk factors for LTFU. National notification data for DS-TB patients diagnosed between August 2011 and July 2014 in PPM institutions were analysed. Determination of LTFU included detection of instances where patients were transferred out, but when they did not attend at other TB centres in the following two months. Univariable and multivariable competing risk models were used to determine risk factors for LTFU. 73,046 patients with 78,485 records were enrolled. Nominally, 3426 (4.4%) of records were LTFU. However, after linking the multiple records in each patient, the percentage of LTFU was 12.3% (9004/73,046). Risk factors for LTFU were: being foreign-born (3.13 (95% CI 2.77–3.53)), prior LTFU (2.31 (2.06–2.59)) and greater distance between the patient’s home and the TB centre (4.27 (4.03–4.53)). ‘Transfer-out’ was a risk factor in patients managed by treatment centres close to home (1.65 (1.49–1.83)), but protective for those attending centres further (0.77 (0.66–0.89)) or far-away (0.52 (0.46–0.59)) from home. By considering the complete picture of a patient’s interactions with healthcare, we identified a much higher level of LTFU than previously documented. This has implications for how outcomes of treatment are reported and argues for a joined-up national approach for the management and surveillance of TB patients, in nations with similar healthcare systems.
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1 The Catholic University of Korea, Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Incheon St. Mary’s Hospital, College of Medicine, Seoul, Republic of Korea (GRID:grid.411947.e) (ISNI:0000 0004 0470 4224)
2 Yonsei University, Institute of Health Services Research, Seoul, Republic of Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454); Yonsei University, Department of Biostatistics, Graduate School of Public Health, Seoul, Republic of Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454)
3 The Catholic University of Korea, Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, Seoul, Republic of Korea (GRID:grid.411947.e) (ISNI:0000 0004 0470 4224)
4 Yonsei University College of Medicine, Division of Biostatistics, Department of Biomedical Systems Informatics, Seoul, Republic of Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454)
5 Dankook University College of Medicine, Division of Pulmonary Medicine, Department of Internal Medicine, Cheonan, Republic of Korea (GRID:grid.411982.7) (ISNI:0000 0001 0705 4288)
6 Inje University College of Medicine, Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Goyang, Republic of Korea (GRID:grid.411612.1) (ISNI:0000 0004 0470 5112)
7 UCL-TB, University College London, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); University College London, Division of Medicine, UCL Respiratory, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); Royal Free London NHS Foundation Trust, London, UK (GRID:grid.437485.9) (ISNI:0000 0001 0439 3380)
8 University College London, Institute for Global Health, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201)
9 The University of Edinburgh, Usher Institute, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)