Using a Multicountry Learning Network to Harvest and Rapidly Spread Implementation Knowledge across Programs Aimed to Reduce Mother-to-Child Transmission of HIV and Improve Nutrition: Perspectives and Lessons Learned for Similar Large-Scale Initiatives.

As countries pursue UNAIDS's 90-90-90 target for ending the AIDS epidemic, success is dependent on learning how to deliver effective care. We describe a learning network and mechanisms used to foster communication and sharing of ideas and results across 6 countries in the Partnership for HIV-Free Survival. The network used 2 forms of peer exchange, in-person and virtual, and a variety of knowledge management mechanisms to harvest and spread key learning. Key learning included valuable insights on how to design and convene a multicountry learning network, including top enablers of success and practical insights on the network's value. The network was instrumental in accelerating learning about improving care. Our experience shows the value of creating a quality improvement-driven, multicountry learning network to accelerate the pace of improving care systems. Government ownership and adaptation of collaborative learning efforts to the country context must be considered when designing future networks.

Using quality improvement to accelerate highly active antiretroviral treatment coverage in South Africa.

INTRODUCTION: The authors report on a health systems strengthening intervention using quality improvement (QI) methods at the subdistrict level to accelerate highly active antiretroviral treatment (HAART) initiation in South Africa. METHODS: Using a phased scale-up design between August 2006 and November 2009, 14 primary healthcare clinics, one community health centre, one district hospital and one tertiary hospital in a subdistrict were recruited into a 'learning network' using QI methods to facilitate cross-facility learning/mentorship/support. Clinic teams consisting of nurses, counsellors, clerks and/or doctors set collective and individual performance targets, analysed their care systems using 'real-time' data feedback, and designed/implemented a set of simple changes to improve HIV testing and HAART initiation rates across the region. DATA ANALYSIS: Primary clinic data were used to measure HAART initiation rates (primary outcome) and HIV testing (secondary outcome). We analysed data variation/trends using an interrupted time series design. Logistic regression analysis was applied to examine trends in HAART initiation during the intervention phases. RESULTS: Clinics in the learning network increased HIV testing by 301.8% from 891/month (SD=94.2) to 3580/month (SD=327.7) (p<0.0001). Monthly HAART initiations increased by 185.5% from 179/month (SD=17.22) to 511/month (SD=44.93) (p<0.0001). During the pilot (phase I), the monthly rate of HAART initiations increased by 3.6 patients. In the prototype collaborative (phase II), there was no acceleration in the rate of increase (3.3/month, p=0.92). Significant acceleration was observed in the rate of increase during the QI scale up (phase III) (10.1/month, p<0.001). The proportion of estimated need for HAART met in the region increased from 35.8% to 72.4% at a time of rapid population growth. CONCLUSION: A QI approach, using learning networks to teach simple data-driven methods for addressing system failures, with increased training and resource inputs, can assist districts to quickly reach universal coverage targets.