October-November 2016: A collection of global experts led the discussion on how to use data from monitoring and evaluation to guide supply chain strategies, policies, decisions and technical assistance. The following three topics were moderated by different groups of experts:
1. People and process solutions for improved data-driven decision making. Moderated by Steven Harsono, Senior Advisor, Healthcare Initiative and Michael Krautmann, Senior Research Associate at the William Davidson Institute at the University of Michigan.
2. Using Harmonized metrics and definitions to improve country supply chains. Moderated by Hitesh Hurkchand, Public Health Advisor at the RMNCH Trust Fund, and Lisa Hedman, Group Lead for Supply and Access to Medicines at the World Health Organization.
3. How can we ensure supply chain assessments are relevant and useful for countries? Moderated by Patrick Lydon, Technical Advisor, Supply Chain Optimization & Economics at the World Health Organization and Kevin Pilz, Senior Supply Chain Advisor at USAID.
Recap of the three topics:
People and process solutions for improved data-driven decision making
Members focused on discussing the human aspect of data technology and decision-making, and the importance of designing a technology project around human needs and motivations. As a result of the discussion, the main points were the following:
1. Process is more important than technology: Good data use does not necessarily require advanced technology, only a committed organization with clear decisions and processes in place. As one member pointed out, we can achieve high service levels, good reporting rates, and extensive data visibility with a system that is entirely manual or SMS-based. Once that strong foundation is in place, then “electrification” of that data system can create even more impact as an investment opportunity.
2. Simplicity & visualization are key to long-term success: This was a recurring theme in several posts, that for data to get used at any level, it must be as simple and visually-oriented as possible. Color coded tables, graphs, and diagrams make data easier to read and act upon. Reports and dashboards can be simplified greatly by highlighting only the information relevant to a certain user, e.g. emphasizing reporting rates and data accuracy for facility and district staff, while utilizing nation-wide “heat maps” to quickly alert central-level supply chain managers to stocked-out facilities.
3. Multidisciplinary teams lead to better decisions: As one member pointed out, success can come not just from developing the right tool or metric, but also from putting the right people together to make decisions. Including teams from a variety of professions (pharmacist, nurse, logistician, health information officer), different geographic regions, and different levels in the supply chain (e.g. sub-county, county, and regional) can ensure more system-wide discussions, leading to better root cause and solution identification. It also facilitates sharing of challenges and best practices between different parts of the same organization, making optimal use of available data.
4. Different investments needed for data collection vs. data use: Problems with data use aren’t limited to low- and middle-income countries. As a member mentioned, even in places like the U.S. computers, barcode scanners, and other technologies are widespread, healthcare organizations still face challenges actually using their data to make better decisions. As global health begins to incorporate these types of technologies, it will become increasingly important that we are rigorous and thorough about developing standardized metrics, publishing and referencing data dictionaries, and developing sufficient intermediaries who understanding the interactions between HMIS, DHIS, LMIS and other emerging data systems.
5. Shared commitment requires shared benefit: This was an underlying theme in several posts – that successful data initiatives manage to find a way for everyone to contribute, but also for everyone to clearly see value from their contribution. A data system is not a one-way pipeline of information from facility staff to national planner; the results of that information must filter back to the facility staff in the form of better service levels, faster problem solving, rewards for a job well-done, and more advanced warning of potential supply issues.