Fuselab Creative has become the “go-to” UX/UI design and development agency for private, state, and federal agencies across the U.S. Recently added to this list is the State of California’s Community Healthcare Department, Business Intelligence Division.
Over 784,600 people in California received long-term healthcare services and supports. California’s older adult population is expected to grow to over 10 million people by 2030, and understanding the growing needs of this population will be critical.
For our first task, DHCS asked Fuselab Creative to create transparent, comprehensive, and reliable custom Data Visualizations in an attempt to better understand and enhance the capacity of the current system and identify and address healthcare disparities and inequities across the state.
– Define the client business goals
– Identify the target audience (personas)
– Define the persona goals
– Identify the stakeholders
– Prioritize the functional requirements
– Define the business requirements
– Translate the requirements into design sprints
– In-person interviews
– Remote interviews
– Group interviews
– Online surveys
Explorations & Data Visualization Experiments
– Define the goal of the experiment
– Create the visualization
– Build clickable prototype
Test & Refine
– Evaluate the criteria for success
– Execute the test
– Refine and repeat until an effortless user experience is achieved
Data visualization is the process of transforming raw data into visuals that help us understand and make sense of it. Hopefully creating actionable insights.
By using data visualization, we can identify patterns and trends, make useful comparisons, and communicate easy to understand insights.
Beneficiaries by Ethnicity and Language
This bubble plot represents our ability to accommodate well know data visualizations with project’s needs, creating something easily scannable for healthcare stakeholders to better understand the ethnic and language diversity in their state and how these numbers have changed over a five year period.
Beneficiaries by Demographics
This heat-map of California is the most appropriate visualization to see how the numbers of beneficiaries are spread out across the state. A Choropleth Map like this helps users to instantly see how the number of beneficiaries change based on California’s counties by decoding the color that is attributed to the beneficiaries range, and then changing the timeframe to see how the numbers/colors change.
Beneficiaries by Age Group
We know that every case is unique, and a lot of data categories might be tricky to be shown and this case is an perfect example. A lot of colors are hard to decode all at once so we took advantage of the Sankey Diagram approach to make it easier to decode the numbers by using specific colors attached to specific number ranges, while also increasing and decreasing the band width to help further explain the differences.
A dashboard is a tapestry of illustrations, meant to collect insight (total, proportion or trend) quickly. Potentially, it can tell a story of what is happening but rarely why. Adding strategic descriptions through hovers or otherwise can go a long way in telling the story with data.
Our dashboards created for DHCS are helping every corner of the healthcare community in California better understand this unique and vulnerable population by creating easy-to-use functionality and self-explanatory data visualizations. Our focus from the beginning was to create human-centered UX/UI designs that need no training to use.
We are still deep in the process of developing impactful data visualizations, but we hope to move into three dimensional illustrations soon. Triangulation like this can be a game changer in understanding how certain trends can impact each other, which helps us deliver better predictive analytics.
By using data visualization, we can identify patterns and trends, make comparisons, and communicate insights in a way that is easy to understand.
Not everyone knows what they are looking for when the begin to work with a data visualization tool. This is partly why we implemented sophisticated search throughout the platform, to help users more easily navigate these cumbersome datasets and reach their goals more efficiently.
Our deliverables list for this project is still growing today as we make new discoveries and find new way to show data relationships.
DHCS had, like so many government agencies, been doing things the same way for quite long time. When we began our wireframes we focused on showing how modularity could immediately make a huge difference.
The dataset we were given spans from 2017 through 2021. We selected a Sankey style chart for its flexibility and interactivity options with dealing with multiple years of data and multiple age groups all at the same time.
The Sankey Chart
Unlike a lot of data visualization templates, the Sankey allows for the user to customize their view depending on their goals, which works perfect for this data grouping of LTSS beneficiaries. We calculated and offered an average data point as well to give users point of reference.
Illustrates 2 dimensions: Race/Ethnicity and Primary Language Spoken.
The dashboard screen is essentially divided in half and a user can navigate through categories by clicking the “Left” or “Right” buttons along the edge of both dimensions to highlight the total numbers for each data grouping.
Gives insight into Dual Eligibility Status and Delivery System
The Plan Parent Trend bar and line charts make great use of standard visualization styles to effortlessly convey the highs and lows of beneficiaries in this unique segmentation.
Gives insight into Dual Eligibility Status and Delivery System
In the form of the previously seen Line Charts that function the same, and Plan Parent Trend in the form of a Ridgeline Plot that can be scrolled up and down and by hovering on any bar, more insights are displayed.
More people use the Internet on their phones than on their computers. In fact, according to Statista, in 2021, 54.2% of all Internet traffic came from mobile devices. This means that if we want our data visualizations to be seen by as many people as possible, we need to make sure they are mobile friendly.