A new causal inference method called the Stability-Controlled Quasi-Experiment (SCQE) was recently proposed for identifying the effect of a treatment on units in a population that are treated. It allows for non-randomized or otherwise unknown means of selection into treatment, relying only on an assumption about the stability of the non-treatment outcomes of the population. We apply SCQE to the case of a national public health intervention in Tanzania to prevent active tuberculosis in HIV-positive patients by prescribing Isoniazid (IPT). Our preliminary results suggest much of the treatment is given to patients at low risk for developing active tuberculosis. In the process, we offer best practices and discuss challenges faced during its implementation. We share steps currently underway to generate confidence in these results, extend the method further, and derive valid standard errors.