Comparative yield of different active TB case finding interventions in a large urban TB project in central Uganda: a descriptive study

Introduction: Systematic screening for TB among patients presenting to care and among high risk populations is recommended to improve TB case finding. We aimed to describe the comparative yield of three TB screening approaches implemented by a large urban TB project in central Uganda. Methods: We abstracted data on the screening cascade from 65 health facilities and their surrounding communities (numbers screened, with presumptive TB, receiving a diagnostic test and diagnosed with TB) from the different clinic and community TB registers. Results: From January 2018 to December 2019, 93,378 (24%) of all patients screened at health facilities had presumptive TB; 77,381 (82.9%) received a diagnostic test and 14,305 (18.5%) were diagnosed with TB. The screening yield (the number of patients diagnosed with TB out of all patients screened) was 0.3% and was three times higher among men than women (0.6% vs 0.2% p<0.01). During targeted community screening interventions, 9874 (21.1%) of all patients screened had presumptive TB; 7034 (71.2%) of these received a diagnostic test and 1699 (24.2%) were diagnosed with TB. The screening yield was higher among men, (3.7% vs 3.3% p<0.01) and highest among children 0-14 (4.8% vs 3.2% p<0.01). Conclusion: Targeted community TB screening interventions improve access to TB diagnosis for men and children 0-14 years

Patient and health system factors associated with pretreatment loss to follow up among patients diagnosed with tuberculosis using Xpert® MTB/RIF testing in Uganda.

BackgroundIn 2018, Uganda started only 65% of persons with incident tuberculosis on treatment. Pretreatment loss to follow up is an important contributor to suboptimal treatment coverage. We aimed to describe the patient and health facility-level characteristics associated with pretreatment loss to follow up among patients diagnosed with pulmonary tuberculosis at public health facilities in Uganda.MethodsAt ten public health facilities, laboratory register data was used to identify patients aged ≥ 15 years who had a positive Xpert®MTB/RIF test. Initiation on TB treatment was ascertained using the clinical register. Factors associated with not being initiated on TB treatment within two weeks of diagnosis were examined using a multilevel logistic regression model accounting for clustering by health facility.ResultsFrom January to June 2018, 510 patients (61.2% male and 31.5% HIV co-infected) were diagnosed with tuberculosis. One hundred (19.6%) were not initiated on TB treatment within 2 weeks of diagnosis. Not having a phone number recorded in the clinic registers (aOR 7.93, 95%CI 3.93-13.05); being HIV-infected (aOR 1.83; 95% CI: 1.09-3.26) and receiving care from a high volume health facility performing more than 12 Xpert tests per day (aOR 4.37, 95%CI 1.69-11.29) and were significantly associated with pretreatment loss to follow up.ConclusionIn public health facilities in Uganda, we found a high rate of pretreatment loss to follow up especially among TBHIV co-infected patients diagnosed at high volume health facilities. Interventions to improve the efficiency of Xpert® MTB/RIF testing, including monitoring of the TB care cascade should be developed and implemented

Patient and health system level barriers to and facilitators for tuberculosis treatment initiation in Uganda: a qualitative study.

BackgroundThe WHO END TB strategy targets to place at least 90% of all patients diagnosed with Tuberculosis (TB) on appropriate treatment. In Uganda, approximately 20% of patients diagnosed with TB are not initiated on TB treatment. We sought to identify the patient and health system level barriers to and facilitators for TB treatment initiation in Uganda.MethodsWe conducted the study at ten public health facilities (three primary care, four district and three tertiary referral hospitals). We carried out in-depth interviews with patients diagnosed with TB and key informant interviews with health managers. In addition, we held focus group discussions with healthcare workers involved in TB care. Data collection and thematic analysis of transcripts was informed by the Capability, Opportunity, Motivation and Behavior (COM-B) model. We identified relevant intervention functions using the Behavior Change Wheel.ResultsWe interviewed 79 respondents (31 patients, 10 health managers and 38 healthcare workers). Common barriers at the health facility level included; lack of knowledge about the proportion of patients not initiated on TB treatment (psychological capability); difficulty accessing sputum results from the laboratory as well as difficulty tracing patients due to inadequate recording of patient addresses (physical opportunity). At the patient level, notable barriers included long turnaround time for sputum results and lack of transport funds to return to health facilities (physical opportunity); limited TB knowledge (psychological capability) and stigma (social opportunity). The most important facilitators identified were quick access to sputum test results either on the date of first visit (same-day diagnosis) or on the date of first return and availability of TB treatment (physical opportunity). We identified education, restructuring of the service environment to improve sputum results turnaround time and enablement to improve communication of test results as relevant intervention functions to alleviate these barriers to and enhance facilitators for TB treatment initiation.ConclusionWe found that barriers to treatment initiation existed at both the patient and health facility-level across all levels of the (Capability, Opportunity and Motivation) model. The intervention functions identified here should be tested for feasibility

The effect of biomass smoke exposure on quality-of-life among Ugandan patients treated for tuberculosis: A cross-sectional analysis.

More than half the global population burns biomass fuels for cooking and home heating, especially in low-middle income countries. This practice is a prominent source of indoor air pollution and has been linked to the development of a variety of cardiopulmonary diseases, including Tuberculosis (TB). The purpose of this cross-sectional study was to investigate the association between current biomass smoke exposure and self-reported quality of life scores in a cohort of previous TB patients in Uganda. We reviewed medical records from six TB clinics from 9/2019-9/2020 and conducted phone interviews to obtain information about biomass smoke exposure. A random sample of these patients were asked to complete three validated quality-of-life surveys including the St. Georges Respiratory Questionnaire (SGRQ), the EuroQol 5 Dimension 3 Level system (EQ-5D-3L) which includes the EuroQol Visual Analog Scale (EQ-VAS), and the Patient Health Questionnaire 9 (PHQ-9). The cohort was divided up into 3 levels based on years of smoke exposure-no-reported smoke exposure (0 years), light exposure (1-19 years), and heavy exposure (20+ years), and independent-samples-Kruskal-Wallis testing was performed with post-hoc pairwise comparison and the Bonferroni correction. The results of this testing indicated significant increases in survey scores for patients with current biomass exposure and a heavy smoke exposure history (20+ years) compared to no reported smoke exposure in the SGRQ activity scores (adj. p = 0.018) and EQ-5D-3L usual activity scores (adj. p = 0.002), indicating worse activity related symptoms. There was a decrease in EQ-VAS scores for heavy (adj. p = 0.007) and light (adj. p = 0.017) exposure groups compared to no reported exposure, indicating lower perceptions of overall health. These results may suggest worse outcomes or baseline health for TB patients exposed to biomass smoke at the time of treatment and recovery, however further research is needed to characterize the effect of indoor air pollution on TB treatment outcomes

Feasibility of a multifaceted intervention to improve treatment initiation among patients diagnosed with TB using Xpert MTB/RIF testing in Uganda.

BackgroundOne in five patients diagnosed with TB in Uganda are not initiated on TB treatment within two weeks of diagnosis. We evaluated a multifaceted intervention for improving TB treatment initiation among patients diagnosed with TB using Xpert® MTB/RIF testing in Uganda.MethodsThis was a pre-post interventional study at one tertiary referral hospital. The intervention was informed by the COM-B model and included; i) medical education sessions to improve healthcare worker knowledge about the magnitude and consequences of pretreatment loss to follow-up; ii) modified laboratory request forms to improve recording of patient contact information; and iii) re-designed workflow processes to improve timeliness of sputum testing and results dissemination. TB diagnostic process and outcome data were collected and compared from the period before (June to August 2019) and after (October to December 2019) intervention initiation.ResultsIn September 2019, four CME sessions were held at the hospital and were attended by 58 healthcare workers. During the study period, 1242 patients were evaluated by Xpert® MTB/RIF testing at the hospital (679 pre and 557 post intervention). Median turnaround time for sputum test results improved from 12 hours (IQR 4-46) in the pre-intervention period to 4 hours (IQR 3-6) in the post-intervention period. The proportion of patients started on treatment within two weeks of diagnosis improved from 59% (40/68) to 89% (49/55) (difference 30%, 95% CI 14%-43%, p<0.01) while the proportion of patients receiving a same-day diagnosis increased from 7.4% (5/68) to 25% (14/55) (difference 17.6%, 95% CI 3.9%-32.7%, p<0.01).ConclusionThe multifaceted intervention was feasible and resulted in a higher proportion of patients initiating TB treatment within two weeks of diagnosis

Consort diagram summarizing data collection and exclusion.

SGRQ = St. George’s Respiratory Questionnaire, EQ-5D-3L = EuroQol-5D-3L, EQ-VAS = EuroQol Visual Analog Scale, PHQ9 = Patient Health Questionnaire. *A small number of subjects were able to finish at least one survey, but not all three due to time constraints, dropped calls, etc. The SGRQ has a significantly lower number of responses than the PHQ9 and EQ-5D-3L because it requires significantly longer time to complete, and some subjects had issues with time constraints.</p