India Health Facilities Import

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Goal

RMSI is currently working to support expanded Information Management capacity within India. The goal is to provide accessible data of accurate health care information from the Open Government Data directories for Hospitals, Health facilities, Blood banks, Health Centers and Health Clinics information which can be useful for all the people and also the Humanitarian team in India

The primary goal is to add/improve the known Hospital records to OSM from the available directories with the help of the individual users. The secondary goal is to do small imports for the unknown health facilities records with coordinates following the Import Guidelines with specific user IDs.


To accomplish the defined goal we are going to follow two different approaches:  

Approach 1- Maproulette:

The first step is to add/improve the known health facility records to OSM from the available directories with the help of the individual local users.

Approach 2- Import for small amount of records:

In the next step for the unknown health facilities records which are having coordinates will be added to OSM by performing small imports based on the district/block.

If you have any queries, please write to osm@rmsi.com.

Schedule

Planning: First half of the April 2019.

Import: Starts after First half of July ’2019.

QA: Post-import.

Announce Import :

https://lists.openstreetmap.org/pipermail/talk-in/2019-July/003282.html

https://lists.openstreetmap.org/pipermail/imports/2019-July/006034.html

Import Data

Data source site: https://data.gov.in/

Data license:  https://data.gov.in/government-open-data-license-india

Type of License: Public Domain with attribution.

ODbL Compliance verified: yes [1]

Background

Open Government Data (OGD) has published three directories with huge list of medical facility records which includes Hospitals, Clinics, Blood Banks, Health centers in India.

According to the OGD these data were published on 10th August, 2017 contributed by the Ministry of Health and Family Welfare, Department of Health and Family Welfare,The National Institute of Health and Family Welfare (NIHFW).

The public healthcare system in India is organised into primary, secondary, and tertiary levels.

  • At the primary level are Sub Centres and Primary Health Centres (PHCs).
  • At the secondary level there are Community Health Centres (CHCs) and smaller Sub-District hospitals.
  • Finally, the top level of public care provided by the government is the tertiary level, which consists of Medical Colleges and District/General Hospitals.


Data Files

  • National Hospital Directory - Click here
  • National Identification Number (NIN) Health Facilities - Click here
  • Blood-bank Directory - Click here - Click here

Import Type

This is an OSM India community-based, one-time import. There are currently no plans for taking in or processing subsequent updates that open.data.gov might provide.This would be a nice capability, but it is outside the scope of this immediate effort.

Method of import: All the imports will be done using JOSM with the import specific OSM accounts.

Data Preparation


Data Reduction & Simplification

The original Government data-sets are in .csv format and it contains several attributes in each directories.

The data will be validated by cleaning the inconsistent attributes and retaining the attributes which are useful combinations for the Health care related facilities.

The list of attributes which have been retained from the Open Government Data for the import are listed below:

  • Name
  • Address
  • Street
  • Locality
  • Pincode
  • Landline_number
  • State_Name
  • District_Name
  • Taluka_Name
  • Block_Name
  • Hospital_Primary_Email_Id
  • Mobile_Number
  • Emergency_Services
  • Hospital_Fax Facility
  • Name Hospital_Category
  • Telephone Website
  • Facilities
  • Specialties

The excluded attributes for import: Hospital_Reg_No, Nodel_personan_Information, Established_year, state_ID, Miscellaneous_Facilities, Apheresis, License etc...

Input Data Cleaning:

The input data has few quality issues which will be addressed and further cleaned on the basis of values before the import .

Before cleaning he raw data:

The input data sets have been further cleaned on the basis of

  • Removal of invalid values - N/A, 0, /N etc…,
  • Removal of duplicate records,
  • Modification of the source data into OSM compatible values - separating the multiple values with ";", changing the opening hours Syntax etc.

OGD India Raw Dataset.jpg

After cleaning : The final data after removing all the issues from the raw data

Tagging Plans

Here are the original fields and how they will be converted to the resulting OSM file, for government dataset.

Health Facility Related tags:

Following is the list of tagging schema which we are using to map the healthcare feature in India- India:Tags/healthcare

Government Facility Type OSM Key
Hospital amenity=hospital
Polyclinics amenity=clinic
Community Health Centres

Primary Health Centres

Sub Centres

healthcare=centre

description="Category of Indian Government health facility"

ANM/PPU healthcare=midwife
Dispensaries healthcare=centre & health_facility:type=dispensary
Facilities health_facility:type
Specialties healthcare:speciality

Other General attributes:

The values for addressing and contact details are tagged based on the global OSM Keys from the Key:addr, Key:contact etc..

Government Attributes OSM Key
Address addr:full
street addr:street
locality addr:place
pincode addr:postcode
landline_number, Telephone contact:phone
State_Name addr:state
District_Name addr:district
Taluka_Name addr:subdistrict
Block_Name addr:block
Hospital_Primary_Email_Id contact:email
Mobile_Number contact:mobile
Emergency_Services emergency_telephone_code
Hospital_Fax contact:fax
Facility Name name
Hospital_Category operator:type
Website contact:website


Tags

Element Tags:

  • Source=OpenGovernmentData

Change-set Tags:

Data Transformation

  • Initially Data source files are in .csv format.  
  • Split the data sets into sections (city / block wise).
  • Load the data to JOSM.
  • Run and fix the JOSM validation errors.
  • Save the each section in .geojson/.json format

Data Merge Workflow

Team Approach

The import will be done manually by JOSM experienced user with dedicated usernames.

References

Each user will consider the following information when importing the data by:

Maproulette:

  • Local knowledge
  • Ground Truth Verification
  • Contacting the facilities
  • Satellite Imagery
  • Existing OSM data
  • Building outline
  • Health Facility data from MR challenge

Import:

  • Satellite Imagery
  • Existing OSM data
  • Building outline
  • Health Facility data Json file

Workflow:

The work for this effort will be divided up into sections - block/city wise.

Health Facilities Import workflow.jpg


Maproulette:

Please find the workflow for the Maproulette in this link https://github.com/RMSI-OSM/India-Health-Facilities/issues/2

Small Imports:

The cleaned up data sets will be divided into sections and assigned to the each users based on city or block wise.

  • The location of the health facilities nodes is generally never more than 150-200 meters of the actual location. In case if the user is not sure about the location then he/she should leave the feature in the original position provided by OGD and add a fixme stating "Please verify the accurate position of the hospital/health care center as I have mapped the facility based on the address provided in Open Government data".
  • Data that is already in OSM will not be overwritten unless it’s clear that the OSM data is outdated/incomplete


Every individual user will follow the below instructions:

  1. Install the ToDo list and the OpenData plugins in JOSM
  2. Load the cleaned csv file into JOSM.
  3. convert/save the csv file as .geojson/.json
  4. Select all the elements and add to ToDo list.
  5. Go to the first element, download OMS data and check all the attributes of the same - the address, position of the feature and check for another similar feature in the area.
    1. If the feature is already existing in OSM then add the missing attributes.
    2. If there isn't a feature and the address of the element is correct then copy the same into the OSM layer .
  6. Repeat with all the elements on ToDo list, verify with JOSM validator and upload the changes with the import change set tags.

Dedicated Import Account

R1_sowmya,

R2_tejan,

R3_anusha,

R4_shubham,

R5_sainath,

R6_harish,

R7_vinay,

R8_sravathi,

R9_charan,

R10_sindhu,

R11_bharath,

R12_sreeram,

Import Status

S.No Facilities Type Batch Region Status Date Remarks
1 Hospital TG Hospitals batch 1A Hyderabad- Telangana Completed - Added 663 TG Hospitals
2 Hospitals TG Hospitals batch 1B Telangana Completed - Added 317 TG Hospitals
3 Health Centers Telangana Completed - Added 661 TG Health centers
4 Hospitals TG Hospitals batch 1C Telangana Completed - Added 266 TG Hospitals
5 subcenters Telangana Completed - Added 1850 TG subcenters
6 Blood Banks Telangana Completed 21 July Added 126 TG Blood banks
7 Hospitals TG Hospitals batch 1D Telangana Completed - Added 102 TG Hospitals
8 Subcenters RR Sub centers Batch 1A Ranga Reddy - Telangana Completed 23 July
9 Subcenters RR Sub centers Batch 1B Ranga Reddy - Telangana Completed 29 July
10 Subcenters RR Sub centers Batch 1C Ranga Reddy - Telangana Completed 29 July
11 Subcenters RR Sub centers Batch 1D Ranga Reddy - Telangana Completed 23 July
12 Blood Banks Andhra Pradesh Completed 28 Aug Added 117 AP blood banks
13 Hospitals Andhra Pradesh Completed Added 374 (In Progress)
14 Hospitals TG Hospitals batch 1E Telangana Completed
15 PAN India Blood Banks India Completed 21 Oct Added 2259 Blood Banks
16 Hospitals Assam Assam Completed 25 Oct Added 116 Hospitals
17 Hospitals JK Jammu and Kashmir Completed 24 Oct Added 59 Hospitals
18 Hospitals Mizoram Mizoram Completed 24 Oct Added 71 Hospitals
19 Hospitals Goa Goa Completed 23 Oct Added 51 Hospitals
20 Hospitals Meghalaya Meghalaya Completed 23 Oct Added 27 Hospitals
21 Hospitals Chandigarh Chandigarh Completed 22 Oct Added 45 Hospitals
22 Hospitals Puducherry Puducherry Completed 22 Oct Added 26 Hospitals
23 Hospitals Tripura Tripura Completed 22 Oct Added 27 Hospitals
24 Hospitals Manipur Manipur Completed 22 Oct Added 13 Hospitals
25 Hospitals Dadra and Nagar Haveli Dadra and Nagar Haveli Completed 22 Oct Added 13 Hospitals
26 Hospitals Nagaland Nagaland Completed 22 Oct Added 11 Hospitals
27 Hospitals Arunachal Pradesh Arunachal Pradesh Completed 22 Oct Added 9 Hospitals
28 Hospitals Andaman and Nicobar Islands Andaman and Nicobar Islands Completed 22 Oct Added 4 Hospitals
29 Hospitals Daman and Diu Daman and Diu Completed 22 Oct Added 4 Hospitals
30 Hospitals Sikkim Sikkim Completed 22 Oct Added 2 Hospitals
31 Hospitals Lakshadweep Lakshadweep Completed 22 Oct Added 1 Hospitals
32 Hospitals TN Tamil Nadu Completed 1 Nov Added 1689 Hospitals
33 Hospitals Karnataka Karnataka Completed 6 Nov Added 1386 Hospitals
35 Hospitals Uttarakhand Uttarakhand Completed 8 Nov Added 228 Hospitals
34 Hospitals Kerala Kerala Completed 11 Nov Added 569 Hospitals
36 Hospitals Bihar Bihar Completed 12 Nov Added 499 Hospitals
37 Hospitals Chhattisgarh Chhattisgarh Completed 12 Nov Added 272 Hospitals
38 Hospitals Gujarat Gujarat Completed 21 Nov Added 2196 Hospitals
39 Hospitals Himachal Pradesh Himachal Pradesh Completed 28 Nov Added 246 Hospitals
40 Hospitals Haryana Haryana Completed 26 Nov Added 1080 Hospitals
41 Hospitals Jharkhand Jharkhand Completed 27 Nov Added 221 Hospitals
42 Hospitals Madhya Pradesh Madhya Pradesh Completed 28 Nov Added 562 Hospitals
43 Hospitals Uttar Pradesh Uttar Pradesh Completed 7 Dec Added 1882 Hospitals
44 Hospitals Rajasthan Rajasthan Completed 9 Dec Added 794 Hospitals
45 Hospitals Maharashtra Maharashtra In Progress 27 Dec Added 3398 Hospitals
46 Hospitals Odisha Odisha In Progress 27 Dec Added 485 Hospitals
47 Hospitals West Bengal West Bengal In Progress 23 Dec Added 832 Hospitals
48 Hospitals Punjab Punjab In Progress 4 Jan Added 697 Hospitals

Local Community support

To support and improve health facilities import at your local region use the following regional wise Maproulette links.

S.No State Maproulette Link OGD Directory MR Challange Status
1 Chandigarh https://maproulette.org/browse/challenges/9967 Hospitals In Progress
2 Puducherry Hospitals In Progress
3 Tripura Hospitals In Progress
4 Tamil Nadu https://maproulette.org/browse/challenges/9995 Hospitals In Progress
5 Karnataka https://maproulette.org/browse/challenges/10111 Hospitals In Progress
6 Kerala https://maproulette.org/browse/challenges/10122 Hospitals In Progress
7 Maharastra https://maproulette.org/browse/challenges/11541 Hospitals In Progress
8 Odhisa https://maproulette.org/browse/challenges/11544 Hospitals In Progress


Revise Plan

In case of any issue, JOSM reverter tool will be used to revise the import.

QA

We will do QA after the completion of every import will be continued for the each sections.

  1. Download the imported Health Facilities data using the overpass query, based on district/city.
  2. Load the cleaned .csv file into JOSM.
  3. Run the conflation tool for both the layers - OSM layer and the OGD data-set.


See also