• Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

          Advanced Data ETL, Reporting and Gen AI

          No-code data engineering
          Automated data transformation
          Enterprise-grade LLM
          MODULES

          An automated data orchestration and pipeline management platform.

          An AI-powered, enterprise-ready Gen AI platform for internal teams.

          Healthcare Data Management

          Parsing engine and interactive mapper.

          Precision parsing, mapping, transformation & health data analytics.

        • Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

          Advanced Data ETL, Reporting and Gen AI

          No-code data engineering
          Automated data transformation
          Enterprise-grade LLM

          Custom, integrated predictive layer.

          Automated data movement for faster time-to-insights.

          Consolidated data for improved accessibility.

          Structured data for reporting, analytics and model training.

        • Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

          Advanced Data ETL, Reporting and Gen AI

          No-code data engineering
          Automated data transformation
          Enterprise-grade LLM

          Visual insights to help you optimize your data for analytics.

          Insider knowledge into proven methodologies and best data practices.

          Explore how businesses leveraged our data solutions to their advantage.

          Keep up with the latest trends to scale faster and outwit competition.

        • Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

          Advanced Data ETL, Reporting and Gen AI

          No-code data engineering
          Automated data transformation
          Enterprise-grade LLM

          We are a bold team supporting bold leaders like you ready to adopt and migrate to new technologies.

          Discover the essence of our tech beliefs and explore the possibilities they offer your business.

          Unlock your business potential by leveraging Gen AI and capitalizing on rich datasets.

          Lead your business to new heights and scale effortlessly with expert guidance along the entire customer journey.

  • Join the team

How Does Geographic Information System Ensure Access To Quality Care?

Summary

Geographic Information Systems (GIS) are powerful healthcare analyzing and visualizing tools to provide valuable insights into patient demographics and ensure that people worldwide have access to high-quality care. 

GIS system combines technology, software, and data and aids users in studying a specific geographical area, its demographics, land usage, and other characteristics. Healthcare professionals can use GIS to review access patterns in patient populations, i.e., the availability of critical care and health outcomes.

Infiniti Research Limited reports that the global GIS market is expected to grow by $13.43 bn at a CAGR of 16.42% from 2022-2027. The research has considered market size and forecast, the latest trends, drivers, components, and challenges to implementing GIS systems. Thus, GIS in healthcare is a booming prospect. 

GIS system implementations in healthcare

  • GIS mapping

GIS maps healthcare facilities, such as hospitals, clinics, etc., as the primary approach to determining access to healthcare. This helps users quickly ascertain the nearest facilities and services available at each site. This information is vital to ensure the easy and appropriate availability of healthcare for people based on their geographical location.

  • Examine the patient demographics

Patient demographics, such as age, gender, income, basic education level, etc., are examined using GIS to better understand the requirements of care. For example, for a healthcare service provider who works in an area housing a community of older patients, the GIS determines the need for geriatric care assistance and resources.

  • Track healthcare and disease outcomes for geolocation

GIS works efficiently in studying data on illness transmission and patient health outcomes to determine locations with requirements for better resources and the risks that might lead to a disease outbreak. This information helps medical practitioners undertake preventive measures to reduce transmission and provide better care to the sick.

Sample architecture components of healthcare GIS system

  1. Data Collection and Management

This GIS component collects, stores, and manages scores of healthcare data about patient demographics, patterns of diseases, healthcare facilities, etc. This component is scalable, flexible, and easily integrated with other facilities. 

  1. Mapping and Visualization

The mapping and visualization component creates interactive visual displays of the healthcare landscape to understand the geographical distribution of facilities, patient populations, and disease patterns.

  1. Analytics

This component uses advanced data analysis tools such as statistical models and machine learning algorithms to analyze and gather insights into the data collected by the data collection and management component.

  1. Decision Support

The decision support component assists healthcare providers in making informed decisions regarding patient care, resources needed, or the services to be offered by any particular facility. It aids providers with tools such as recommendations and alerts based on the insights provided by the analytics component.

  1. User Interfaces

This component is designed to provide easy and quick access to data, maps, and insights generated by the GIS system. User interfaces are intuitive, interactive, and easy to use.

Challenges in implementing GIS systems

Despite the many advantages of the GIS system, it faces several difficulties when it comes to the healthcare industry:

  • Data Integration

The GIS system might face difficulties while obtaining and evaluating data, especially if data is kept in several systems or formats, thus, producing inaccurate results.

  • Data Quality

The healthcare industry frequently handles sensitive data governed by stringent standards. Thus, ensuring the accuracy of information is a constant problem, as inaccurate data will produce wrong conclusions and lead to wrong decisions.

  • Aversion to Use

The GIS system demands a decent level of technical knowledge. Hence, healthcare providers may find it complicated to use, be opposed to using the GIS system, and need persuasion.

Related blogs and articles