The WASH Health Facility Data Exchange (WHdx) is a new free and open data sharing and decision-support platform to compile and transform information into insights for impact. The global-local support tool will guide decision-making about funding, progress and gaps around WASH services in healthcare facilities. The purpose of WHdx is to:
Leverage analytics and tools for policy decisions and investments
The lack of widespread, easily accessible and credible health facility-level data impedes progress towards universal coverage of WASH services in healthcare facilities. Currently, on the national/international scale only broad data from externally-conducted facility assessments (WHO/UNICEF/JMP) exist. Few national health monitoring systems collect useful information on WASH at healthcare facilities and there is often limited capacity to turn this raw data into meaningful insights. Any localized data is gathered by combination of NGOs and governments and is rarely compiled into a user-friendly, updated dataset for easy access and sharing.
Without granular, updated and publicly available data on the quality of WASH in HCFs, it is almost impossible to understand and respond to needs.
The primary target users of WHdx are government officials who lead decision-making for WASH services in healthcare facilities. This audience may include national and subnational offices of health and water who are responsible for allocating resources and monitoring services within healthcare facilities. NGOs, donors, private sector entities, and advocates may also benefit from the data insights.
The platform will allow for stakeholders to identify significant gaps in WASH services in healthcare facilities, track which WASH issues are consistently problematic, and determine where resources may be most impactful. Overlaying the WHdx data with external databases such as population data, areas of greatest impact can be identified. These insights can inform national roadmaps & standards, integrate WASH into health sector planning, support sector coordination, and allocate resources.
The platform will include data from healthcare facilities of all sizes, from health posts up to hospitals, and will allow users to disaggregate data by hospital vs. non-hospital.
Investment evaluation: potential sites to determine which would have most impact
Global Water Challenge, in partnership with Millennium Water Alliance, is leading the development of the WHdx platform, with funding from the Conrad N. Hilton Foundation. It is guided by a Working Group composed of technical experts from Catholic Relief Services, the US Centers for Disease Control and Prevention (CDC), Emory University’s Center for Global Safe WASH, Helvetas, and the Safe Water and AIDS Project (SWAP).
The Water Point Data Exchange (WPdx) is the world’s largest, free and open on-line platform for rural water services data sharing, access, and analysis. WPdx was developed to address lack of understanding of water point functionality in the rural water sector. By using the WPdx Data Standard, any entity can share rural water point data through the ingestion engine, which produces a harmonized, publicly available dataset. WPdx decision-support tools enable users to explore rural water access levels/gaps for geographies and/or compare coverage across districts, regions or countries.
WHdx is a new platform developed building off the success and functionalities of WPdx. While WPdx was focused only on water point data, WHdx is broader including water, sanitation, hygiene, environmental health and healthcare waste management, but with a focus only on healthcare facilities.
The Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP) has developed indicators for WASH in HCF and collects data on a routine basis to provide global and national statistics. These data are instrumental in understanding the global situation; however, they are limited in the data that they collect and are unable to provide a more granular analysis of subnational data. Meanwhile the WASH FIT tool, which provides a much more robust assessment tool, is not designed to feed into a data repository for analysis.
WHdx is not intended as a data collection tool but instead a data harmonization platform which compiles data from different sources into an analysis-ready dataset. The compiled dataset is intended to provide a more comprehensive view on the status of WASH in HCF than most individual entities would have on their own. WHdx is data source agnostic and will accept data from a variety of formats including online databases, excel and csv files. WPdx is intended to be complementary to but not replace or duplicate data collection and analysis platforms such as AKVO, ODK and mWater. Furthermore, the ability of WPdx to compile diverse data sets based on a common standard and provide decision support tools makes it complimentary to many individually developed government systems. WHdx will offer a suite of decision-support tools which utilize cutting edge analytics to help identify gaps, prioritize resources and optimize investments.
Data can be shared by a range of stakeholders including governments, NGOs, academic researchers, and others. WHdx will be built using a similar module as used for WPdx which allows for user to upload data from a variety of formats including .xls, .xlsx, .csv, Google Sheets, as well as direct connections to online databases including Akvo Flow, mWater and Open Data Kit (ODK).
Sharing data with WHdx will not impact or change data ownership. As per the “Data Provider Agreement”, the data is simply licensed to the WASH in Health Facilities Data Exchange under the Creative Commons Attribution 4.0 license, available at https://creativecommons.org/licenses/by/4.0/. The original owner remains the owner even after the data is shared.
The standard for the WHdx platform is currently under development, with support from the Working Group.
The development team and its Working Group partners are defining the Data Exchange Standard, creating the data sharing/access platform, identifying focus countries for piloting, training on how to share data, and developing initial Decision Support Tools.