April 29, 2021

Status Quo of Spatial Datasets of Health Facilities in India

Highlights of recent additions in the public domain

 

Important healthcare data like locations of health facilities should be geotagged and publicly accessible. This encourages reuse of data for innovation, i.e. research, developing new services and tools, or improving evidence-based policies. If such geographic information is available, it can be used to help decision makers and humanitarian agencies measure access to facilities, improve overall service delivery of the health sector and/or plan emergency response. However, until recently, the sole open source location-based dataset for health facilities in India was OpenStreetMap, a volunteer-run mapping platform. As positive externalities of ongoing government programmes to improve road infrastructure, and the government’s response to COVID-19, two new datasets containing locations of Indian health facilities have now been added to the public sphere. 

 

These include:

 

  1. Rural public health facilities surveyed under Pradhan Mantri Gram Sadak Yojana (PMGSY) Phase - III

  2. Private facilities empanelled under Pradhan Mantri Jan Arogya Yojana (PM-JAY) (functioning as COVID-19 Vaccination Centres or CVCs)

 

First, the Ministry of Rural Development (MoRD) published geo-tagged data for more than 700,000 public amenities in rural areas under the Government Open Data License. The government collected these datasets under the central government initiative for upgrading road infrastructure, Pradhan Mantri Gramin Sadak Yojana (PMGSY). Part of the data collection involved a  survey of the type and number of facilities accessed along rural roads to help decide which roads needed to be upgraded as a priority. The data on facilities was captured under four broad categories: Medical, Agro, Education and Transport/Admin. The ‘Medical’ category comprises Primary Health Centres, Community Health Centres, Bedded Hospitals, and Veterinary Hospitals.

 

The interactive map below shows this category, except the Veterinary Hospitals.

 

 

Second, private facilities empanelled under Pradhan Mantri Jan Arogya Yojana (PMJAY). PMJAY aims to provide quality healthcare to  100 million vulnerable families, i.e. about 40% of the population.  The Indian government published a list of all private facilities empanelled under the centrally sponsored scheme of PMJAY and the Central Government Health Scheme (CGHS) that would function as COVID-19 Vaccination Centres (CVCs). The geo-tagged dataset was published through a press release. We mapped the private facilities for which location data was available in the following interactive. (Note: Location data of CGHS hospitals functioning as CVCs is not available). The dashboard below shows a list of these facilities at the city level. 

 

 

How can India improve further? 

 

We recommend collecting and publishing data at the city-level and more rigorous capture of  the location of private facilities. In India, people use private facilities around three times more than public ones. Health departments at city and state levels should develop ways of collecting information about private sector facilities more systematically.

 

There have been instances where city or state governments published lists of public health facilities without spatial information. For example, the Greater Chennai Corporation put up a list of Urban Primary Health Centres and Urban Community Health Centres on the SmartCities data portal along with their addresses, and the Department of Health in Kerala shared a list of facilities covering all levels of healthcare (SCs, PHCs, CHCs, General Hospitals, and so on) along with information on sanctioned beds and contact information. While this is a useful public resource, lack of location information limits their value and possibility of reuse for building any application-based services, such as an app to find the nearest public health facility during an immunisation drive; or for the local authorities to set up an application during an event of disaster, such as floods, showing live availability of beds and essential drugs in the nearest facilities; or even to understand access to healthcare in general. 

 

To improve the overall quality of spatial datasets for health facilities in the country, the central, state, and city governments can collaborate with volunteers, and community-driven mapping efforts to start publishing and updating geo-tagged datasets of all levels of public health facilities. One such collaboration can be with the OSM community in India that has carried out multiple mapping projects in the past with the help of its local volunteers. 

 

Benefits of Open Spatial Datasets of Health Facilities

 

As mentioned earlier in this piece, one of the most crucial benefits of open data on locations of health facilities is during disasters. For example, in 2012, Open Cities project launched in the city of Kathmandu, trained university students, volunteers, and government officials to digitally map their communities using the open-source OSM. The survey covered about 3,000 educational and 350 medical facilities. These mapping efforts were highly useful in planning a response to future earthquakes. In fact, much later in 2015, when two high magnitude earthquakes struck the area, the data added to the OSM by the volunteers in response to the earthquakes, was used by Nepal military, the Red Cross, and many other humanitarian organizations to provide relief and other assistance.

 

Another potential benefit of comprehensively mapping out health facilities can be to identify optimal number of and locations of new health facilities to maximise the coverage of the health network in the region. This can be achieved using spatial analysis tools such as location allocation models, which allow allocating the existing demand to all the facilities and helping pick the ideal locations for new facilities. Such an approach is most useful when the reach of the existing healthcare facilities has to be enhanced with the limited financial and other resources available to the state authorities.

 

Sources:

1. PMGSY Rural Dataset, 2020 (http://omms.nic.in/Home/PMGSYRuralDataset/)

2. Ministry of Family and Health Welfare, Press Release by PIB Delhi, 27th Feb 2021 (https://pib.gov.in/PressReleasePage.aspx?PRID=1701407)

3. Pratap Vardhan, Rural Facilities PMGSY (2020), GitHub Repository (https://github.com/pratapvardhan/rural-facilities-pmgsy)

4. India International Boundary, Survey of India (https://surveyofindia.gov.in/pages/downloads)

 

Acknowledgements: I am grateful to Isalyne GennaroVikram Sinha, Harsh Pachisia, and Sridhar Ganapathy for their editorial inputs.

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