*admin3_name*: Administrative level 3 name - in SA that is the local municipality *admin2_abb*: Abbreviation of the DM name *admin2_name*: Administrative division level 2 name - in SA that is the district municipality *admin1_abb*: Abbreviation of the province/state name *admin1_name***: Province name but can be state or other administrative division level 1 for other countries We'll create a master table that contains columns as follows: We want to understand the process and see where () can aid by developing building blocks to facilitate similar processes and complimentary data analysis workflows. We acknowledge that this cannot be called the Master Facility List as we will only work with openly available data sets and do not have access to all information available to the Department of Health (beyond what is published in the Data Dictionary). The ultimate aim of this project is to work through the process of collating the best possible facility list for South Africa by combining various openly available resources. # Creating a master table which will be populated from the various datasets it can support case management of patients.Ī quick Google search lead to openly available MFLs for at least the following African countries: it can facilitate planning and management and it provides metadata needed by other information systems it facilitates information exchange across different health data systems it can create efficiencies by having to maintain a single list rather than maintaining several lists and continuously facing the challenge of integration The () provides further guidance on the development or strengthening of a Master Facility List.Ĭountries can benefit tremendously from having a high quality, up-to-date MFL in the following ways: types of services offered, number of beds).Īccording to the WHO, a MFL should be updated regularly (at least every two years), should be verified, and must be accessible to stakeholders. information about the service capacity (e.g. facility type, ownership, operational status) and name, unique identifier, location, contact information) data to accurately identify a facility (e.g. The article by () describes their experience in collating a MFL for Kenya and subsequently assisting other countries to develop in-house MFLs and finally the continental health facility list.Ī MFL typically contains information about health facilities including: According to the () developed in 2018 by the WHO/USAID, the MFL is a complete, up-to-date, authoritative listing of the health facilities in a particular country. These challenges are experienced in every country when health facility lists from various stakeholders are combined to create, what is called, a Master Facility List (MFL). During our conversations about developing a list of hospitals with various attributes such as address, website, contact details, services available, and corona-readiness, we realised this wasn't going to be a trivial exercise. For more information about the challenges associated with building a comprehensive list of health facilities for South Africa see (). Was a great practical use-case for the kind of tools we had in mind to build within _afrimapr_. The group recruited volunteers to assist with the the collation of information about hospital resources in South Africa and I thought In South Africa the () group created an open () to assist with local efforts.
`afrihealthsites` is under active development and we aim to get it out to potential users very early in the development cycle to allow for continuous input that can shape its functionality. The () currently allows one to compare two existing continental open data sets - one developed by the Kenya Medical Research Institute (KEMRI) in collaboration with the WHO, the second a global crowd sourced open health facilities mapping project - (). # Requires dplyr 1.0.0 to use relocate()Įarly in March 2020 the () started looking into mapping, comparing, and combining open health facility data sets to enable better access for decision makers in Africa during and after the COVID-19 pandemic. Knitr :: opts_chunk $set( echo = FALSE, message = FALSE) \*\* *Please observe individual dataset licensing if you would like to use the original datasets*
Title: "Merging Open Health Facility Data Sets: Part 1 "