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Publication round-up: BID publishes new costing data, learnings, and best practices

By Celina Kareiva, Senior Communications Associate

Dec 3, 2019

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Photo: PATH/Trevor Snapp. A health worker at Mareu Health Center in Tanzania checks her mobile phone. New evidence demonstrates that digital tools are improving immunization service delivery.

The BID Initiative is committed to advancing the global evidence base around data quality and use interventions to improve immunization service delivery. Informed by our own progress in Tanzania and Zambia, we recently published a series of journal articles and publications that demonstrate the impact of electronic immunization registries (EIRs) on cost savings, vaccine stock levels, and data quality, among other areas. Below is a round-up of recent publications and some of the learnings from each.

The cost of developing, introducing, and scaling EIRs

When BID’s work began in Tanzania and Zambia, there was no existing EIR system that met the requirements of each country. By supporting the development of two different systems to meet diverse country needs, BID aimed to reduce the likelihood of other countries needing to invest in new software development. But EIRs require a significant upfront cost. To help countries navigate their own digital journey, BID conducted an analysis of the financial expenditures incurred under the initiative to develop, deploy, and maintain the systems between 2013 and 2018.

Costs included categories such as system development, hardware procurement, software upgrades, project administration, and research. Costing data indicates that the average expenditure for deploying the EIR system ranged from US$332 to US$515 per health facility in Tanzania; and US$1,516 per health facility in Zambia. The total average expenditure for rolling out the EIR system was between US$709 and US$1,320 for Tanzania and US$2,591 for Zambia. With limited evidence on the costs of EIRs, we hope these findings will help others benefit from BID’s learnings, leading to more functional and affordable platforms. To read the full article, visit BMJ Global Health.

The impact of EIRs on vaccine stock levels

Before EIR systems were introduced in Tanzania and Zambia, health workers often had difficulty identifying how much vaccine stock they had on hand, which made it challenging to plan for immunization clinics. Under the BID Initiative, the Tanzania Immunization Registry (TImR) includes stock notifications, allowing for five main functionalities that greatly improve the availability of vaccines and promise to reduce stockouts:

  • Automated deduction in stock at the facility each time vaccines were administered;
  • Low-stock and stock-out notifications;
  • Predictive vaccine requisition to estimate daily, weekly and monthly caseloads of due children;
  • Visualizations of stock levels;
  • Automated data exchange with the district-level Vaccine Information Management System (VIMS), so that supervisors and frontline workers access the same information.

But would better stock data contribute to improved vaccine availability and reductions in stockouts? BID tested this hypothesis in three regions in Tanzania, including Arusha, Kilimanjaro, and Tanga. Findings reveal that vaccine availability increased overall, including for three of the six evaluated vaccines. The more experience health workers had with the system, the less likely they were to experience stockouts. To read the full article, visit Vaccine.

The three waves of data use

A critical part of any EIR introduction is the change management strategy that can help to shape a culture of data use within countries’ health systems. Based on its implementation experience in Tanzania and Zambia, BID defined three distinct phases of data use. Each wave signals the greater ownership and ability of health workers to use data in their day-to-day responsibilities. These include:

  • Strengthening data collection: In the initial wave, health workers focused on receiving and learning how to use the new data collection tools and processes.
  • Improving data quality: During the second wave, health workers strengthened their understanding of the data collected, EIR functionality to check data validity, and the requirements to fill in specific data elements.
  • Increasing use of data: In the third and final wave, health workers began to use the data to strengthen their work and improve programmatic decision making.

These waves clearly demonstrated the growing ability of health workers to move from data collectors to data analyzers who began to focus on the data quality and value of data use in their day-to-day activities. For the full article, visit Global Health: Science and Practice.

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