Dataset: Haiti Health Facilities Locations

About this Dataset

Haiti Health Facilities Locations

An Evaluation of Operating Health Facilities in 2019

By Humanitarian Data Exchange [source]

About this dataset

This dataset provides an authoritative list of operating health facilities in Haiti. It includes comprehensive information that can be used to analyze the geographical distribution of medical resources throughout the country. The data includes attributes such as facility name, nature and type; categories of services offered; and their exact geographic coordinates (latitude/longitude). This dataset is compiled by a registry, ensuring it is up-to-date and reliable, making it a valuable resource for organizations seeking to understand healthcare infrastructure in the nation.
The data can be employed to study inequalities within countries between rural and urban areas or urban hubs versus peripheral regions. Given that access to quality health care should be equitable regardless of geographic areas, researchers could use this dataset to trace unevenness across Haiti's geography—or within certain districts or cities—so that corresponding resources may then be allocated accordingly within the region. In addition, major restructuring initiatives can use this kind of detailed information for effective decision making capabilities with respect to delivery networks – allowing for critical epidemiological analysis on population coverage, accessibility issues faced by citizens from remote locations etc. This dataset is released under Creative Commons Attribution license with no rights reserved which allows users to share or adapt the material in any medium or format they wish as long as they attribute its original creator adequately

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How to use the dataset

Getting Started:

Exploring Data:

Analyzing Data:
Now that you know what information is provided in each column within a view; analyzing data becomes easier than ever! For example if a researcher wanted insight into specific healthcare facilities in one area they could filter by “Adm 1 Code” which is administrative area level one code - selecting only those located geographical regions would be quickly displayed in first view allowing quick insights into what kind facilities (private / public; pharmacy/hospital) are actually being utilized by people living within those boundaries without having manually sort through every row then totalling up counts across all rows - saving invaluable time when working with large datasets such as those found on Kaggle today! With this data we can determine how accessible healthcare is per region within selected parameters like sectorial access (public/private) or hospital capacity related studies etcetera – helping us understand patient shift trends across various areas that could prove invaluable during times like COVID-19 pandemic where numerous areas might lack resources due higher influxes coming from other surrounding regions facing similar restrictions due same natural hazards etcetera… Allowing us draw insights depending upon our research goals quickly without having sort manage thousands plus rows line item basis saves time & money over long haul allowing quicker actions if needed be put place intervene locally on regional level depending upon findings

Research Ideas

Finding hospitals in relation to natural disasters or humanitarian crises using a heatmap representation of the data to visualize health facility locations.

Mapping rural healthcare facilities to provide residents with access to health services and for the government to monitor usage trends over time.

Plotting data points on an interactive map of Haiti with lines connecting population centers and medical facilities, providing useful data-driven insight into public transportation networks and health infrastructure covering geographic areas across the country

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: haiti-healthsites-hdx-1.csv

Column name	Description
Adm1code	Administrative Level 1 Code (Integer)
adm1_fr	Administrative Level 1 Name in French (String)
adm1_ht	Administrative Level 1 Name in Haitian Creole (String)
adm2code	Administrative Level 2 Code (Integer)
adm2_en	Administrative Level 2 Name in English (String)
adm2_fr	Administrative Level 2 Name in French (String)
adm3code	Administrative Level 3 Code (Integer)
adm3_en	Administrative Level 3 Name in English (String)
adm3_fr	Administrative Level 3 Name in French (String)
Institution name	Name of the Health Facility (String)
Catégorie	Category of the Health Facility (String)
Institution_Type	Type of Institution (String)
Institution_Code	Institution Code (Integer)
LatDD	Latitude in Decimal Degrees (Float)
LongDD	Longitude in Decimal Degrees (Float)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Humanitarian Data Exchange.

Tables

Haiti Healthsites Hdx 1

@kaggle.thedevastator_haiti_health_facilities_locations.haiti_healthsites_hdx_1

77.77 KB
3814 rows
16 columns


CREATE TABLE haiti_healthsites_hdx_1 (
  "index" BIGINT,
  "adm1code" VARCHAR,
  "adm1_fr" VARCHAR,
  "adm1_ht" VARCHAR,
  "adm2code" VARCHAR,
  "adm2_en" VARCHAR,
  "adm2_fr" VARCHAR,
  "adm3code" VARCHAR,
  "adm3_en" VARCHAR,
  "adm3_fr" VARCHAR,
  "institution_name" VARCHAR,
  "cat_gorie" VARCHAR,
  "institution_type" VARCHAR,
  "institution_code" VARCHAR,
  "latdd" VARCHAR,
  "longdd" VARCHAR
);