Email Alert | RSS

Chinese Journal of Antituberculosis ›› 2019, Vol. 41 ›› Issue (9): 974-984.doi: 10.3969/j.issn.1000-6621.2019.09.012

• Original Articles • Previous Articles     Next Articles

Analysis on economic burden of patients with tuberculosis and its influencing factors in Fengxian District of Shanghai

Chun-hua XU,Qing LIU(),Zi-chun WANG,Yong WU   

  1. Department of Tuberculosis Control, Shanghai Fengxian District Center for Disease Control and Prevention, Shanghai 201499, China
  • Received:2019-06-22 Online:2019-09-10 Published:2019-09-06
  • Contact: Qing LIU E-mail:liuqing6668@163.com

Abstract:

Objective To understand the economic burden of the patients with pulmonary tuberculosis (PTB) and its influencing factors in Fengxian District of Shanghai.Methods The study enrolled 136 initial treatment or re-treatment PTB patients, who were notified in Fengxia District CDC of Shanghai and managed by community health centers in 2018.A self-designed questionnaire was used to investigate the basic information of the patients, including sex, age, if having health insurance or not, family catastrophic health expenditure, if having complications or not, etc.; the related direct and indirect costs of the patients in the process of diagnosis and treatment were recorded. The SPSS 17.0 software was used to do the data statistical analysis and the optimal scale regression analysis.Results Two patients were excluded from the study, one died during treatment while the other was due to incomplete data on medical expenses. Finally, a total of 134 patients, who completed the whole course of anti-TB treatment and had complete information, were involved into the analysis. Among them, 88 patients had local household registration while 46 patients did not have. The average annual income per PTB patient was RMB 55181.46 yuan and the average annual income per family of the PTB patients was RMB 112937.91 yuan. The average expenses per patient was RMB 32035.99 yuan, including RMB 24363.97 yuan direct expenses and RMB 7672.02 yuan indirect expenses. The median (Q1, Q3) of total cost in the patients who had local household registration was RMB 25635.25 (8361.82,45314.05) yuan while it was RMB 18847.43 (9016.25,31894.65) yuan in those patients who did not have local household registration, there was no significant difference between the two groups of patients (Z=-0.984, P=0.325); however, the direct cost in the patients who had local household registration (RMB 19336.34 (7756.65,36700.57) yuan) was significantly higher than that who did not have local household registration (RMB 11658.03 (6716.38,20072.61) yuan) (Z=2.329, P=0.020), while the indirect cost in the patients who had local household registration (RMB 1000.00 (0.00,4075.00) yuan) was significantly lower than that who did not have local household registration (RMB 3000.00 (75.00,13500.00) yuan) (Z=-2.773, P=0.006). 23.75% (7607.26/32035.99) of the average overall expenses was reimbursed by medical insurance, 4.55% (1458.03/32035.99) was paid by government relief funds and 71.70% (22970.70/32035.99) was paid out of patient’s own pocket which occupied 20.34% (22970.70/112937.91) of average annual household income of the patients. The amounts of expenditures which were reimbursed by health insurance and paid by government relief funds in the patients who had local household registration were RMB 2703.00 (1024.00,10917.00) yuan and RMB 1210.50 (820.25,1721.75) yuan,while those were RMB 179.00 (0.00,1218.00) yuan and RMB 1480.50 (1328.75,1802.50) yuan in the patients who did not have local household registration, there were significant difference between the two groups of patients (Z values were -5.291 and -2.962; P values were 0.000 and 0.003, respectively). The results of optimal proportional regression analysis showed that the district-level health facilities in the patients who visited district-level health facilities (RMB 11535.48 (6622.96,22741.41) yuan), costs of standard daily medication (RMB 14147.86 (6878.47,27395.80) yuan), costs without hospitalization (RMB 6395.98 (4425.99,8878.89) yuan), costs with less-one-day hospitalization (RMB 6395.98 (4425.99,8878.89) yuan), costs never hospitalization (RMB 6395.98 (4425.99,8878.89) yuan), costs with treatment duration less than 8 months (RMB 11474.18 (6563.88,22880.65) yuan), costs with severity by self-assessment (RMB 8726.80 (4666.35,20642.64) yuan), costs without family catastrophic health expenditure (RMB 11474.18 (6818.67,22880.65) yuan), costs without medical insurance (RMB 7074.25 (4741.36,8660.69) yuan) were significantly lower than the direct medical expenses in the patients who visited municipal-level health facilities (RMB 15550.02 (8456.05,37171.31) yuan), costs with irregular medication (RMB 15107.080 (8901.53,34197.84) yuan), costs with hospitalization (RMB 19982.64 (9676.31,35013.72) yuan), costs with hospitalization days >30 days (RMB 56713.89 (37977.08,101972.01) yuan), costs with hospitalization for 3-5 times (RMB 53899.46 (36421.73,113670.87) yuan), costs with treatment duration >8 months (RMB 18925.76 (8616.10,36823.34) yuan), costs with mild illness by self-assessment (RMB 20070.70 (9456.83,44849.70) yuan), costs with family catastrophic health expenditure (RMB 35562.35 (20704.26,55516.06) yuan), costs with medical insurance (RMB 14907.71 (7335.28,29653.38) yuan). F values were 5.794, 5.983, 6.346, 11.102, 70.825, 8.087, 11.636, 31.912, 5.851, and P values were 0.044, 0.037, 0.034, 0.021, 0.000, 0.036, 0.011, 0.000, 0.039, respectively.Conclusion The economic burden of diagnosis and treatment of tuberculosis patients in Fengxian District is heavy. The costs of patients’ burden are mainly related to the health facilities that patients seek health care, daily standard medication, hospitalization, accumulated hospitalization days, number of hospitalizations, duration of treatment, medical insurance, self-assessment of the degree of illness, and catastrophic family health expenditure.

Key words: Tuberculosis,pulmonary, Cost of illness, Questionnaires, Fees,medical, Medical indigency, Small-area analysis, Factor analysis, statistical