Latent Tuberculosis Infection Testing Practices in a Large US Integrated Healthcare System.

BACKGROUND: Tuberculosis (TB) is a public health threat, with >80% of active TB in the United States occurring due to reactivation of latent TB infection (LTBI). We may be underscreening those with high risk for LTBI and overtesting those at lower risk. A better understanding of gaps in current LTBI testing practices in relation to LTBI test positivity is needed. METHODS: This study, conducted between 1 January 2008 and 31 December 2019 at Kaiser Permanente Southern California, included individuals aged ≥18 years without a history of active TB. We examined factors associated with LTBI testing and LTBI positivity. RESULTS: Among 3 816 884 adults (52% female, 37% White, 37% Hispanic, mean age 43.5 years [standard deviation, 16.1]), 706 367 (19%) were tested for LTBI, among whom 60 393 (9%) had ≥1 positive result. Among 1 211 971 individuals who met ≥1 screening criteria for LTBI, 210 025 (17%) were tested for LTBI. Factors associated with higher adjusted odds of testing positive included male sex (1.32; 95% confidence interval, 1.30-1.35), Asian/Pacific Islander (2.78, 2.68-2.88), current smoking (1.24, 1.20-1.28), diabetes (1.13, 1.09-1.16), hepatitis B (1.45, 1.34-1.57), hepatitis C (1.54, 1.44-1.66), and birth in a country with an elevated TB rate (3.40, 3.31-3.49). Despite being risk factors for testing positive for LTBI, none of these factors were associated with higher odds of LTBI testing. CONCLUSIONS: Current LTBI testing practices may be missing individuals at high risk of LTBI. Additional work is needed to refine and implement screening guidelines that appropriately target testing for those at highest risk for LTBI.

Patient-Reported Barriers to Treatment Initiation and Completion for Latent Tuberculosis Infection Among Patients Within a Large Integrated Health Care System in Southern California.

OBJECTIVE: More than 80% of active tuberculosis in the United States is due to reactivation of latent tuberculosis infection (LTBI), which can be prevented via screening and treatment. Treatment initiation and completion rates are low for patients with LTBI in the United States, and the barriers to successful treatment are poorly understood. DESIGN: We conducted semistructured qualitative interviews with 38 patients who were prescribed LTBI treatment (9 months isoniazid, 6 months rifampin, or 3 months rifamycin-isoniazid short-course combinations). We used purposeful sampling employing a maximum variation approach to obtain diverse perspectives of patients who did not initiate treatment, who did not complete treatment, and who completed treatment (n = 14, n = 16, and n = 8, respectively). Patients were asked about LTBI knowledge, experience regarding treatment, interactions with providers, and barriers they faced. Using a team coding model (2 coders/analysts), we developed deductively derived (a priori) codes based on our central research questions and inductively derived codes that emerged directly from the data. Analysis of our coding categories and relationships generated a hierarchy of key themes and subthemes. SETTING: Kaiser Permanente Southern California. PARTICIPANTS: Individuals 18 years or older who received a diagnosis of LTBI and prescribed treatment. MAIN OUTCOME MEASURES: LTBI knowledge, attitudes toward LTBI, attitudes toward LTBI treatment, attitudes toward providers, and explanation of barriers. RESULTS: Most patients reported having limited knowledge of LTBI. In addition to the duration of treatment, barriers to initiation and completion included perceived lack of support, uncomfortable side effects, and pervasive minimization of the positive impact of treatment on their health. Many patients felt there was little incentive to overcome barriers. CONCLUSIONS: Overall, patient experience with LTBI treatment initiation and completion could be improved with patient-centered treatment and more frequent follow-ups.

Prior Screening for Latent Tuberculosis Among Patients Diagnosed With Tuberculosis Disease: Missed Opportunities?

Background: California has the largest number of tuberculosis (TB) disease cases in the United States. This study in a large California health system assessed missed opportunities for latent tuberculosis (LTBI) screening among patients with TB disease. Methods: Kaiser Permanente Southern California patients who were ≥18 years old with membership for ≥24 months during the study period from 1 January 2008 to 31 December 2019 were included. Prior LTBI test (tuberculin skin test or interferon-γ release assay) or diagnosis code prior to TB disease diagnosis was assessed among patients with observed TB disease (confirmed by polymerase chain reaction and/or culture). In the absence of current treatment practices, more patients screened for LTBI may have developed TB disease. We estimated hypothetical TB disease cases prevented by multiplying LTBI progression rates by the number of LTBI-positive patients prescribed treatment. Results: A total of 1289 patients with observed TB disease were identified; 148 patients were LTBI positive and 84 were LTBI negative. Patients not prescreened for LTBI made up 82.0% of observed TB disease cases (1057/1289). Adding the hypothetical maximum estimate for prevented cases decreased the percentage of patients who were not prescreened for LTBI to 61.7% [1057/(1289 + 424)]. Conclusions: One-fifth of patients were screened for LTBI prior to their active TB diagnosis. Assuming the upper bound of cases prevented through current screening, almost 62% of TB disease patients were never screened for LTBI. Future work to elucidate gaps in LTBI screening practices and to identify opportunities to improve screening guidelines is needed.

Development and validation of a prediction algorithm to identify birth in countries with high tuberculosis incidence in two large California health systems.

OBJECTIVE: Though targeted testing for latent tuberculosis infection ("LTBI") for persons born in countries with high tuberculosis incidence ("HTBIC") is recommended in health care settings, this information is not routinely recorded in the electronic health record ("EHR"). We develop and validate a prediction model for birth in a HTBIC using EHR data. MATERIALS AND METHODS: In a cohort of patients within Kaiser Permanente Southern California ("KPSC") and Kaiser Permanent Northern California ("KPNC") between January 1, 2008 and December 31, 2019, KPSC was used as the development dataset and KPNC was used for external validation using logistic regression. Model performance was evaluated using area under the receiver operator curve ("AUCROC") and area under the precision and recall curve ("AUPRC"). We explored various cut-points to improve screening for LTBI. RESULTS: KPSC had 73% and KPNC had 54% of patients missing country-of-birth information in the EHR, leaving 2,036,400 and 2,880,570 patients with EHR-documented country-of-birth at KPSC and KPNC, respectively. The final model had an AUCROC of 0.85 and 0.87 on internal and external validation datasets, respectively. It had an AUPRC of 0.69 and 0.64 (compared to a baseline HTBIC-birth prevalence of 0.24 at KPSC and 0.19 at KPNC) on internal and external validation datasets, respectively. The cut-points explored resulted in a number needed to screen from 7.1-8.5 persons/positive LTBI diagnosis, compared to 4.2 and 16.8 persons/positive LTBI diagnosis from EHR-documented birth in a HTBIC and current screening criteria, respectively. DISCUSSION: Using logistic regression with EHR data, we developed a simple yet useful model to predict birth in a HTBIC which decreased the number needed to screen compared to current LTBI screening criteria. CONCLUSION: Our model improves the ability to screen for LTBI in health care settings based on birth in a HTBIC.