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Using computerized clinical decision support for latent tuberculosis infection screening

https://doi.org/10.1016/j.amepre.2004.12.012Get rights and content

Background

The Centers for Disease Control and Prevention (CDC) has published guidelines recommending screening high-risk groups for latent tuberculosis infection (LTBI). The goal of this study was to determine the impact of computerized clinical decision support and guided web-based documentation on screening rates for LTBI.

Design

Nonrandomized, prospective, intervention study.

Setting and participants

Participants were 8463 patients seen at two primary care, outpatient, public community health center clinics in late 2002 and early 2003.

Intervention

The CDC’s LTBI guidelines were encoded into a computerized clinical decision support system that provided an alert recommending further assessment of LTBI risk if certain guideline criteria were met (birth in a high-risk TB country and aged <40). A guided web-based documentation tool was provided to facilitate appropriate adherence to the LTBI screening guideline and to promote accurate documentation and evaluation. Baseline data were collected for 15 weeks and study-phase data were collected for 12 weeks.

Main outcome measures

Appropriate LTBI screening according to CDC guidelines based on chart review.

Results

Among 4135 patients registering during the post-intervention phase, 73% had at least one CDC-defined risk factor, and 610 met the alert criteria (birth in a high-risk TB country and aged <40 years) for potential screening for LTBI. Adherence with the LTBI screening guideline improved significantly from 8.9% at baseline to 25.2% during the study phase (183% increase, p < 0.001).

Conclusions

This study demonstrated that computerized, clinical decision support using alerts and guided web-based documentation increased screening of high-risk patients for LTBI. This type of technology could lead to an improvement in LTBI screening in the United States and also holds promise for improved care for other preventive and chronic conditions.

Section snippets

Background

Tuberculosis (TB) remains a major disease in the United States and in the world. Given the estimated 2 million deaths annually, tuberculosis is the second leading infectious cause of death worldwide behind human immunodeficiency virus (HIV).1 Among U.S.-born people, there was a 62% decrease in the number of reported TB cases from 1992 to 2002. In contrast, there was a 5% increase in the reported TB cases among foreign-born people during the same time period.2 With over 50% of new cases

Methods

A computerized clinical decision support system at two outpatient primary care clinics in Denver CO was used to assess screening for latent tuberculosis infection following the CDC guideline: “Targeted Tuberculin Testing and Treatment of Latent Tuberculosis.”4 In collaboration with the Public Health Practice Program Office of the CDC and Siemens Medical Solutions USA, Inc., the CDC LTBI screening guidelines were encoded into a computerized clinical decision support system using a rules engine

Results

There were 4328 and 4135 unique adult registrations during the baseline and study phases, respectively. The average age of this group was 49 years, 64% were female, 71% were Hispanic, and 50% were uninsured. Seventy-four percent of the baseline patients (3213 of 4328), and 73% of the study period patients (3034 of 4135) had at least one LTBI risk factor that qualified for screening by CDC guidelines. Country of birth was the most common risk factor, accounting for 39% of the patients

Discussion

This study demonstrated successful application of computerized clinical decision support to adapt a national clinical guideline to local needs in a safety-net institution outpatient setting. This study is the first to demonstrate that computerized clinical decision support systems can improve screening for latent tuberculosis infection. It was surprising to observe that >70% of the patients seen in the safety-net setting had at least one CDC-defined LTBI risk factor. In addition, the high

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There are more references available in the full text version of this article.

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