Microheart

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PROBLEM & MOTIVATION

Problem Description: By 2030, the elderly and retired population in Singapore is expected to be approximately 90,000 -- almost twice the current figure. Despite the government’s efforts to continuously beef up the availability and accessibility of healthcare for the elderly and retired, there needs to be a means for the government to predict the optimal number of healthcare facilities that best meets the need of our target audience.

Motivation: This project is motivated by the varying ratios of (number of elderly and retired) to number of healthcare facilities in each planning area. This brings a need to detect which planning areas require better access to healthcare facilities.


OBJECTIVES

In this project, we aim to create visualisations that helps users perform and analyse the following:

Descriptive

We would like to provide users with up-to-date demographic information, specifically pertaining to the aged population and the distribution across the different areas of Singapore (as per URA 2014). In addition, we would like to include other information, such as the presence of medical facilities and its distribution mapped out on the same planning area chart.

Prescriptive

Based on the suggested design above, we aim to be able to provide users with insights on which certain planning zones or subzones require development and emphasis on medical facilities based on the volume of ageing population staying there.

Predictive

We would like to provide users with a visibility on the trend of ageing population. Based on the dependency ratio formulated from the proportion of ageing population out of the working and economically active population, we aim to be able to predict the timeline on which the ageing situation for the country reaches a critical threshold (where ageing population forms a significant proportion out of the population).


SELECTED DATASET

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Dataset/Source Data Attributes Rationale Of Usage

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BACKGROUND SURVEY OF RELATED WORKS

Our project draws inspiration from the following past works and studies:

Related Works What We Can Learn

Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64.

PastWork1.png

Source: Source URL 1

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Reference Dataset Title 2

Source: Source URL 2

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Reference Dataset Title 3

Source: Source URL 3

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PROPOSED STORYBOARD

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Proposed Layout How Analyst Can Conduct Analysis

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ADDRESSING KEY TECHNICAL CHALLENGES

The following are some of the key technical challenges that we may face throughout the course of the project:

Key Technical Challenges How We Propose To Resolve
Using D3.js to create interactive visualizations

Explore more on D3.js and understand how it works through available resources such as GitHub etc

Data preprocessing

Research on the data required, understand which data set is most important and clean up the data

Designing insightful Dashboard

Explore the possible ways of visualizing data by researching on the existing charts, graphs etc


PROJECT TIMELINE

The following shows our project timeline for the completion of this project:

Va timeline.jpg


TOOLS/TECHNOLOGIES

The following are some of the tools/technologies that we will be utilizing during the project:

  • Excel
  • Tableau
  • D3.js
  • JMP Pro



REFERENCES

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COMMENTS

Feel free to provide us with comments, suggestions and feedback to help us improve our project! (: