References in the content below refer to the PBMEF Guide.
Definitions
Number of people with drug- sensitive (DS) TB (new and relapse), all forms, with each defined DS-TB treatment outcome, among the cohort of people who were initiated DS-TB treatment during a reporting period. Cohort reporting: Treatment outcomes are defined by the time of initiation on treatment; e.g., “2018 cohort successfully treated” reflect those who were initiated on treatment in 2018, even though treatment may have extended into 2019. For this reason, reports of treatment outcome data lag by one year.
(World Health Organization [WHO] revised treatment definitions for both DS and drug-resistant (DR) TB (Ch.10):https://tbksp.org/en/node/617
Numerator
Denominator
Ref # |
TX_DS_OUT_SUCC
(Previously SS-1B) |
Tier Level |
National Level Indicators
|
Category |
Cure
|
Type |
Outcome
|
Unit of Measure |
Number of people
|
Data Type |
Integer
|
Disaggregations |
Age (<15, 15+)
Sex
HIV Status
|
Reporting Level |
National Level indicators should be reported at the national level; data may also be reported subnationally or at the project level if national data is not available.
|
Reporting Frequency |
This indicator should be reported on an annual basis at a minimum. More frequent monitoring on a quarterly or monthly basis is recommended.
|
The data sources are the TB register or electronic management information systems available at the health facility and district level. Quarterly cohort analysis reports may also be used if these analyses are being conducted. The following WHO indicators can be used to report this indicator:
Died: newrel_succ
Systematic analysis of treatment outcomes for people initiated on DS-TB treatment is an important activity to track the quality of TB services and measures the National TB Program’s (NTP) ability to ensure successful completion of TB treatment. Monitoring various treatment outcomes reported under this indicator is useful in understanding reasons for suboptimal treatment success, which is a key outcome in the USAID TB strategy.
As a WHO standard indicator, the percent of people with DS-TB who died during treatment allows countries to monitor their progress in reducing the number of deaths due to TB among those who are diagnosed and initiating treatment. High death rates in a treatment cohort may be indicative of long delays in diagnosis and treatment regimens, problems with selected treatment regimens, or lack of support for those on TB treatment.
Cohort analysis of treatment outcomes is a major management tool for monitoring the effectiveness of the NTP. The treatment success rate (a core indicator) is a useful way to monitor success of treatment. The treatment success rate is a subset of data from this indicator. The data reported for each treatment outcome in this indicator should be compared to the cohort size which is reported with the core indicator for TSR; to determine the percent of people with each outcome, divide the number of people with the outcome by the number of people in the treatment cohort (newrel_coh).
The percent LTFU can also be a useful metric for analysis. Ideally, there should be no LTFU during treatment, and a high rate of LTFU (5% or above) may warrant further investigation. The percent of people who died during TB treatment can also be analyzed as a trend showing whether the rate of death is increasing or decreasing over time. Monitoring this indicator is important as countries strive to reach zero deaths due to TB but it can also prompt NTPs to implement additional or better-targeted treatment support services with the aim of improving DS-TB treatment outcomes. This indicator should also be considered in the context of HIV prevalence or other co-infections, since a high percent of HIV-associated TB (or other comorbidities) will result in a greater number of deaths. Death rates above 5% may warrant a formal analysis of deaths that occur while on treatment, to ensure those on DS-TB treatment do not have DR-TB.
Example charts/graphs:
- TB outcome pie chart trend over time comparisons
- TB treatment cascade
Indicator Visualizations
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