Factors influencing integration of TB services in general hospitals in two regions of China: a qualitative study

<p>Abstract</p> <p>Background</p> <p>In the majority of China, the Centre for Disease Control (CDC) at the county level provides both clinical and public health care for TB cases, with hospitals and other health facilities referring suspected TB cases to the CDC. In recent years, an integrated model has emerged, where the CDC remains the basic management unit for TB control, while a general hospital is designated to provide clinical care for TB patients. This study aims to explore the factors that influence the integration of TB services in general hospitals and generate knowledge to aid the scale-up of integration of TB services in China.</p> <p>Methods</p> <p>This study adopted a qualitative approach using interviews from sites in East and West China. Analysis was conducted using a thematic framework approach.</p> <p>Results</p> <p>The more prosperous site in East China was more coordinated and thus had a better method of resource allocation and more patient-orientated service, compared with the poorer site in the West. The development of public health organizations appeared to influence how effectively integration occurred. An understanding from staff that hospitals had better capacity to treat TB patients than CDCs was a strong rationale for integration. However, the economic and political interests might act as a barrier to effective integration. Both sites shared the same challenges of attracting and retaining a skilled workforce for the TB services. The role of the health bureau was more directive in the Western site, while a more participatory and collaborative approach was adopted in the Eastern site.</p> <p>Conclusion</p> <p>The process of integration identifies similarities and differences between sites in more affluent East China and poorer West China. Integration of TB services in the hospitals needs to address the challenges of stakeholder motivations and resource allocation. Effective inter-organizational collaboration could help to improve the efficiency and quality of TB service. Key words: TB control, service delivery, integration, hospitals, China.</p

Antibiotic prescribing for upper respiratory infections among children in rural China: a cross-sectional study of outpatient prescriptions

Background: Overuse of antibiotics contributes to the development of antimicrobial resistance. Objective: This study aims to assess the condition of antibiotic use at health facilities at county, township and village levels in rural Guangxi, China. Methods: We conducted a cross-sectional study of outpatient antibiotic prescriptions in 2014 for children aged 2–14 years with upper respiratory infections (URI). Twenty health facilities were randomly selected, including four county hospitals, eight township hospitals and eight village clinics. Prescriptions were extracted from the electronic records in the county hospitals and paper copies in the township hospitals and village clinics. Results: The antibiotic prescription rate was higher in township hospitals (593/877, 68%) compared to county hospitals (2736/8166, 34%) and village clinics (96/297, 32%) (p < 0.001). Among prescriptions containing antibiotics, county hospitals were found to have the highest use rate of broad-spectrum antibiotics (82 vs 57% [township], vs 54% [village], p < 0.001), injectable antibiotics (65 vs 43% [township], vs 33% [village], p < 0.001) and multiple antibiotics (47 vs 15% [township], vs 0% [village], p < 0.001). Logistic regression showed that the likelihood of prescribing an antibiotic was significantly associated with patients being 6–14 years old compared with being 2–5 years old (adjusted odds ratio [aOR] = 1.3, 95% CI 1.2–1.5), and receiving care at township hospitals compared with county hospitals (aOR = 5.0, 95% CI 4.1–6.0). Prescriptions with insurance copayment appeared to lower the risk of prescribing antibiotics compared with those without (aOR = 0.8, 95% CI 0.7–0.9). Conclusions: Inappropriate use of antibiotics was high for outpatient childhood URI in the four counties of Guangxi, China, with the highest rate found in township hospitals. A significant high proportion of prescriptions containing antibiotics were broad-spectrum, by intravenous infusion or with multiple antibiotics, especially at county hospitals. Urgent attention is needed to address this challenge

Evaluating the impact of decentralising tuberculosis microscopy services to rural township hospitals in gansu province, china

<p>Abstract</p> <p>Background</p> <p>In 2004, the Ministry of Health issued the policy of decentralising microscopy services (MCs) to one third of all township hospitals in China. The study was conducted in Gansu Province, a poor western one in China. Ganzhou was one county in Gansu Province. Ganzhou County was identified as a unique case of further decentralisation of tuberculosis (TB) treatment services in township hospitals. The study evaluated the impact of the MC policy on providers and patients in Gansu Province. The second objective was to assess the unique case of Ganzhou County compared with other counties in the province.</p> <p>Methods</p> <p>Both quantitative and qualitative methods were used. All 523 MCs in the province completed an institutional survey regarding their performance. Four counties were selected for in-depth investigation, where 169 TB suspects were randomly selected from the MC and county TB dispensary registers for questionnaire surveys. Informant interviews were conducted with 38 health staff at the township and county levels in the four counties.</p> <p>Results</p> <p>Gansu established MCs in 39% of its township hospitals. From January 2006 to June 2007, 8% of MCs identified more than 10 TB sputum smear positive patients while 54% did not find any. MCs identified 1546 TB sputum smear positive patients, accounting for 9% of the total in the province. The throughputs of MCs in Ganzhou County were eight times of those in other counties. Interviews identified several barriers to implement the MC policy, such as inadequate health financing, low laboratory capacity, lack of human resources, poor treatment and management capacities, and lack of supervisions from county TB dispensaries.</p> <p>Conclusion</p> <p>Microscopy centre throughputs were generally low in Gansu Province, and the contribution of MCs to TB case detection was insignificant taking account the number of MCs established. As a unique case of full decentralisation of TB service, Ganzhou County presented better results. However, standards and quality of TB care needed to be improved. The MC policy needs to be reviewed in light of evidence from this study.</p

Patient health expenditure for TB care in three models.

<p>1 USD = 6.8 RMB, M =  Median.</p><p>* 29 patients of SL and 9 patients of SDC who were never treated in the TB dispensary, so they were excluded from the calculation of DOTS treatment expenditure. They were treated in the specialist hospital with a median treatment period of 209 days and the median health expenditure of RMB 11,985.</p>†<p>Significant difference was found among six sites (F = 19.859, P<0.001). ZD was significantly higher than GP (P<0.001), SC (P<0.001) and GN (P = 0.001). SL was significantly higher than GP (P<0.001), SC (P<0.001) and GN (P<0.001). SDC was significantly higher than GP (P<0.001), SC (P<0.001) and GN (P<0.001).</p>‡<p>Significant difference was found among ix sites (F = 18.408, P<0.001). ZD was significantly higher than GP (P = 0.002), SC (P<0.001) and GN (P<0.001). SL was significantly higher than GP (P<0.001), SC (P<0.001) and GN (P<0.001). SDC was significantly higher than GP (P = 0.026), SC (P = 0.011) and GN (P = 0.015).</p>§<p>Significant difference was found among six sites (F = 3.7328, P = 0.011). ZD (P<0.001) and GN(P<0.001) were significantly higher than GP. SDC was significantly higher than GP (P = 0.001) and SC (P = 0.028).</p>£<p>ZD was significantly higher than SC (χ² = 9.647, P = 0.002). SL was significantly higher than ZD (χ² = 9.450, P = 0.002), GP (χ² = 21.223, P<0.001), SC (χ² = 32.918, P<0.001) and GN (χ² = 21.335, P<0.001). SDC was significantly higher than GP (χ² = 12.391, P<0.001), SC (χ² = 22.408, P<0.001) and GN (χ² = 12.432, P<0.001).</p

Hospitalization of TB patients in the three models.

<p>1 USD = 6.8 RMB, M =  Median.</p>†<p>ZD was significantly higher than GP (χ² = 29.910, P<0.001), SC (χ² = 24.836, P<0.001) and GN (χ² = 29.122, P<0.001). SL was significantly higher than ZD (χ² = 9.114, P = 0.003), GP (χ² = 57.389, P<0.001), SC (χ² = 52.556, P<0.001) and GN (χ² = 58.115, P<0.001). SDC was significantly higher than GP (χ² = 39.420, P<0.001), SC (χ² = 34.980, P<0.001) and GN (χ² = 39.862, P<0.001).</p>‡<p>Significant difference was found among six sites (F = 4.034, P = 0.004). SL was significantly longer than GN (P = 0.028).</p>§<p>ZD was significantly higher than GP (χ² = 31.392, P<0.001), SC (χ² = 32.025, P<0.001) and GN (χ² = 36.975, P<0.001). SL was significantly higher than ZD (χ² = 7.255, P = 0.007), GP (χ² = 57.495, P<0.001), SDC (χ² = 11.761, P = 0.001), SC (χ² = 58.385, P<0.001) and GN (χ² = 64.510, P<0.001). SDC was significantly higher than GP (χ² = 22.979, P<0.001), SC (χ² = 23.487, P<0.001) and GN (χ² = 27.879, P<0.001).</p

Health care seeking behavior of TB patients in the three models.

<p>M =  Median.</p>†<p>SL was significantly higher than ZD (χ² = 6.844, P = 0.009), GP (χ² = 74.037, P<0.001), SDC (χ² = 11.819, P = 0.001), SC (χ² = 19.388, P<0.001) and GN (χ² = 55.892, P<0.001). ZD was significantly higher than GP (χ² = 49.242, P<0.001) and GN (χ² = 32.534, P<0.001). SDC was significantly higher than GP (χ² = 37.521, P<0.001) and GN (χ² = 22.093, P<0.001). SC was significantly higher than GP (χ² = 28.015, P<0.001) and GN (χ² = 14.064, P<0.001).</p>‡<p>ZD was significantly higher than GP (χ² = 25.997, P<0.001), SC (χ² = 24.458, P<0.001) and GN (χ² = 22.319, P<0.001). SL was significantly higher than GP (χ² = 42.627, P<0.001), SC (χ² = 40.911, P<0.001) and GN (χ² = 38.580, P<0.001). SDC was significantly higher than GP (χ² = 23.631, P<0.001), SC (χ² = 22.144, P<0.001) and GN (χ² = 20.065, P<0.001).</p>§<p>Significant difference was found among six sites (F = 22.386, P<0.001). SL was significantly higher than ZD (p = 0.002) and GP (P<0.001). SDC was significantly higher than ZD (P<0.001) and GP (P<0.001). ZD was significantly higher than SC (P<0.001) and GN (P<0.001).</p

Delays of TB patients in three models.

<p>*29 patients of SL and 9 patients of SDC who were never treated in the TB dispensary, so they were excluded from the calculation of treatment delay and total delay.  =  Mean, M =  Median.</p>†<p>Significant difference was found among six sites (Z = 2.659, P = 0.025). SDC was significantly higher than SC (P = 0.040).</p>‡<p>Significant difference was found among six sites (Z = 3.651, P = 0.005). ZD was significantly higher than SC (P = 0.001) and GN (P = 0.001).</p