Quality of care for patients evaluated for tuberculosis in the context of Xpert MTB/RIF scale-up

Shete

Nantale

et al. 2020

BMC Health Serv Res

Self Cite

Background: Many high burden countries are scaling-up GeneXpert® MTB/RIF (Xpert) testing for tuberculosis (TB) using a hub-and-spoke model. However, the effect of scale up on reducing TB has been limited. We sought to characterize variation in implementation of referral-based Xpert TB testing across Uganda, and to identify health system factors that may enhance or prevent high-quality implementation of Xpert testing services. Methods: We conducted a cross-sectional study triangulating quantitative and qualitative data sources at 23 community health centers linked to one of 15 Xpert testing sites between November 2016 and May 2017 to assess health systems infrastructure for hub-and-spoke Xpert testing. Data sources included a standardized site assessment survey, routine TB notification data, and field notes from site visits. Results: Challenges with Xpert implementation occurred at every step of the diagnostic evaluation process, leading to low overall uptake of testing. Of 2192 patients eligible for TB testing, only 574 (26%) who initiated testing were referred for Xpert testing. Of those, 54 (9.4%) were Xpert confirmed positive just under half initiated treatment within 14 days (n = 25, 46%). Gaps in required infrastructure at 23 community health centers to support the huband-spoke system included lack of refrigeration (n = 14, 61%) for sputum testing and lack of telephone/mobile communication (n = 21, 91%). Motorcycle riders responsible for transporting sputum to Xpert sites operated variable with trips once, twice, or three times a week at 10 (43%), nine (39%) and four (17%) health centers, respectively. Staff recorded Xpert results in the TB laboratory register at only one health center and called patients with positive results at only two health centers. Of the 15 Xpert testing sites, five (33%) had at least one non-functioning module. The median number of tests per day was 3.57 (IQR 2.06-4.54), and 10 (67%) sites had error/invalid rates > 5%. Conclusions: Although Xpert devices are now widely distributed throughout Uganda, health system factors across the continuum from test referral to results reporting and treatment initiation preclude effective implementation of Xpert testing for patients presenting to peripheral health centers. Support for scale up of innovative technologies should include support for communication, coordination and health systems integration.

Section: Discussionmentioning

confidence: 95%

Challenges with scale-up of GeneXpert MTB/RIF® in Uganda: a health systems perspective

Shete

Nantale

et al. 2020

BMC Health Serv Res

Self Cite

“…The number of health centers participating spanned 15 districts of Uganda, allowing us to feel secure in making generalizations about rural and peri-urban TB care across the country. Our ability to identify challenges at each level in the Xpert referral implementation process aligns these insights with the patient cascade of TB diagnostic care in Uganda [13], which demonstrates significance of pretreatment loss to follow-up within this context. Our approach in understanding operational challenges to Xpert hub-and-spoke implementation may inform the development of targeted strategies to address these challenges while improving patient outcomes.…”

Section: Field Notesmentioning

confidence: 86%

Challenges with Scale-up of GeneXpert MTB/RIF® in Uganda: a Health Systems Perspective

Shete

Nantale

et al. 2019

Preprint

Self Cite

Background Many high burden countries are scaling-up GeneXpert® MTB/RIF (Xpert) testing for tuberculosis (TB) using a hub-and-spoke model. However, the effect of scale up on reducing TB has been limited. We sought to characterize variation in implementation of referral-based Xpert TB testing across Uganda, and to identify health system factors that may enhance or prevent high-quality implementation of Xpert testing services. Methods We conducted a cross-sectional study triangulating quantitative and qualitative data sources at 23 community health centers linked to one of 15 Xpert testing sites between November 2016 and May 2017 to assess health systems infrastructure for hub-and-spoke Xpert testing. Data sources included a standardized site assessment survey, routine TB notification data, and field notes from site visits. Results Challenges with Xpert implementation occurred at every step of the diagnostic evaluation process, leading to low overall uptake of testing. Of 2,241 patients eligible for TB testing, only 580 (26%) were referred for Xpert testing. Of those, 57 (9.6%) were Xpert confirmed positive just over half initiated treatment within 14 days (n=33, 58%). Gaps in required infrastructure at 23 community health centers to support the hub-and-spoke system included lack of refrigeration (n=14, X%) for sputum testing and lack of telephone/mobile communication (n=21, 91%). Motorcycle riders responsible for transporting sputum to Xpert sites operated variable with trips once a week, 2x/week or 3x/week at 10 (43%), 9 (39%) and 4 (17%) health centers, respectively. Staff recorded Xpert results in the TB laboratory register at only one health center and called patients with positive results at only 2 health centers. Of the 15 Xpert testing sites, 5 (33%) had at least one non-functioning module. The median number of tests per day was 3.57 (IQR 2.06-4.54), and 10 (67%) sites had error/invalid rates >5%. Conclusions Although Xpert devices are now widely distributed throughout Uganda, health system factors across the continuum from test referral to results reporting and treatment initiation preclude effective implementation of Xpert testing for patients presenting to peripheral health centers. Support for scale up of innovative technologies should include support for communication, coordination and health systems integration.

“…We found that willingness to return to the clinic increases proportionally with incentive amount, such that 25% of participants would return for an incentive of 500 USh, and 100% would return for 25,000 USh. If, as our WTA experiment found, the provision of a modest cash incentive of 5,000 USh could motivate up to 70% of patients who otherwise would not return to clinic to complete their diagnostic evaluation, completion of recommended testing in this context could be increased from a baseline of 56% (26) to over 80%. This change would substantially reduce patient attrition in the TB cascade of care.…”

Section: Discussionmentioning

confidence: 96%

“…We included community health centers if they used standard (multi-day) sputum smear microscopy and/or GeneXpert MTB/RIF (Cepheid, Sunnyvale USA) testing as the primary method of TB diagnosis. We excluded health centers that demonstrated low volume of TB testing and diagnosis: 1) performing sputum based TB diagnostic evaluation on < 150 patients per year, or 2) diagnosing < 15 smear positive TB cases per year (26).…”

Section: Study Setting and Populationmentioning

confidence: 99%

Patient perspectives and willingness to accept incentives for tuberculosis diagnostic evaluation in Uganda.

Kadota

Nabwire

et al. 2020

Preprint

Self Cite

Background Novel strategies are urgently needed to reduce gaps in the tuberculosis (TB) cascade of care. While patient centered interventions like cash transfers are increasingly recognized as a crucial approach for improving TB outcomes, data to support acceptable incentive intervention design that maximizes their utility are limited. We assessed attitudes and perceptions as well as willingness-to-accept (WTA) varying incentive structures for completing TB diagnostic evaluation among patients in Uganda. Methods We surveyed 177 adult patients undergoing TB evaluation at 10 community health centers in Uganda between September 2018 and March 2019. We collected household sociodemographic information and assessed attitudes and perceptions of incentives. We conducted a willingness-to-accept experiment assessing willingness to complete TB diagnostic evaluation in exchange for incentives ranging in value from 500 Ugandan Shillings (USh) to 25,000USh (~$0.15-6.75USD). We compared associations between willingness-to-accept and patient characteristics using ordered logistic regression. Results Participants’ willingness to return to the health center to complete TB diagnostic evaluation increased proportionally with incentive amount. The median participant had a WTA amount between 2,000 and 5,000 USh. Cash (52%) and transportation vouchers (34%) were the most popular incentive types. Half of respondents preferred unconditional incentives, but for a multi-day evaluation 84% preferred conditioning the incentive upon clinic return. In multivariate models we found the pairwise difference between the third income quartile and the reference (lowest) income quartile (aOR=2.38, 95%CI: 1.20-4.69; p=0.01), younger age, and difficulty returning to the health center to be significantly associated with willingness to accept higher incentive thresholds. Conclusions In Uganda, incentives such as cash transfers or transportation vouchers are an acceptable intervention for facilitating adherence to TB diagnostic evaluation. Household income is associated with preferred incentive structure and amount, especially for those at the cusp of the poverty threshold, who are more likely to prefer unconditional and higher valued incentives. Targeted and context-specific socioeconomic supports for at-risk patients are needed to optimize outcomes.