Speaking the same language: treatment outcome definitions for multidrug-resistant tuberculosis.

SETTING: Globally it is estimated that 273000 new cases of multidrug-resistant tuberculosis (MDR-TB, resistance to isoniazid and rifampicin) occurred in 2000. To address MDR-TB management in the context of the DOTS strategy, the World Health Organization and partners have been promoting an expanded treatment strategy called DOTS-Plus. However, standard definitions for MDR-TB patient registration and treatment outcomes do not exist. OBJECTIVE: To propose a standardized set of case registration groups and treatment outcome definitions for MDR-TB and procedures for conducting cohort analyses under the DOTS-Plus strategy. DESIGN: Using published definitions for drug-susceptible TB as a guide, a 2-year-long series of meetings, conferences, and correspondence was undertaken to review published literature and country-specific program experience, and to develop international agreement. RESULTS: Definitions were designed for MDR-TB patient categorization, smear and culture conversion, and treatment outcomes (cure, treatment completion, death, default, failure, transfer out). Standards for conducting outcome analyses were developed to ensure comparability between programs. CONCLUSION: Optimal management strategies for MDR-TB have not been evaluated in controlled clinical trials. Standardized definitions and cohort analyses will facilitate assessment and comparison of program performance. These data will contribute to the evidence base to inform decision makers on approaches to MDR-TB control.

Electronic laboratory system reduces errors in National Tuberculosis Program: a cluster randomized controlled trial.

OBJECTIVE: To evaluate the impact of the e-Chasqui laboratory information system in reducing reporting errors compared to the current paper system. DESIGN: Cluster randomized controlled trial in 76 health centers (HCs) between 2004 and 2008. METHODS: Baseline data were collected every 4 months for 12 months. HCs were then randomly assigned to intervention (e-Chasqui) or control (paper). Further data were collected for the same months the following year. Comparisons were made between intervention and control HCs, and before and after the intervention. RESULTS: Intervention HCs had respectively 82% and 87% fewer errors in reporting results for drug susceptibility tests (2.1% vs. 11.9%, P = 0.001, OR 0.17, 95%CI 0.09-0.31) and cultures (2.0% vs. 15.1%, P < 0.001, OR 0.13, 95%CI 0.07-0.24), than control HCs. Preventing missing results through online viewing accounted for at least 72% of all errors. e-Chasqui users sent on average three electronic error reports per week to the laboratories. CONCLUSIONS: e-Chasqui reduced the number of missing laboratory results at point-of-care health centers. Clinical users confirmed viewing electronic results not available on paper. Reporting errors to the laboratory using e-Chasqui promoted continuous quality improvement. The e-Chasqui laboratory information system is an important part of laboratory infrastructure improvements to support multidrug-resistant tuberculosis care in Peru.

Human factors for capacity building: lessons learned from the OpenMRS implementers network.

OBJECTIVES: The overall objective of this project was to investigate ways to strengthen the OpenMRS community by (i) developing capacity and implementing a network focusing specifically on the needs of OpenMRS implementers, (ii) strengthening community-driven aspects of OpenMRS and providing a dedicated forum for implementation-specific issues, and; (iii) providing regional support for OpenMRS implementations as well as mentorship and training. METHODS: The methods used included (i) face-to-face networking using meetings and workshops; (ii) online collaboration tools, peer support and mentorship programmes; (iii) capacity and community development programmes, and; (iv) community outreach programmes. RESULTS: The community-driven approach, combined with a few simple interventions, has been a key factor in the growth and success of the OpenMRS Implementers Network. It has contributed to implementations in at least twenty-three different countries using basic online tools; and provided mentorship and peer support through an annual meeting, workshops and an internship program. The OpenMRS Implementers Network has formed collaborations with several other open source networks and is evolving regional OpenMRS Centres of Excellence to provide localized support for OpenMRS development and implementation. These initiatives are increasing the range of functionality and sustainability of open source software in the health domain, resulting in improved adoption and enterprise-readiness. CONCLUSIONS: Social organization and capacity development activities are important in growing a successful community-driven open source software model.