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10 Kinds of Stories to Tell with Healthcare Data

Data has the potential to tell stories. Data storytelling builds a narrative around a set of data, insights, and visualizations. In healthcare, we are increasingly seeing the value of using data to communicate the wins and challenges through effective data storytelling.


Data provides us with the means to glean key insights into business operations, practices, and experiences, but the numbers need a narrative to become a story. Storytelling bridges the gap between cold, hard data and what is most important to our audience through visual and narrative design.


Smiling doctor is patient room with two visitors at the bedside

Storytelling with data is an important means of sharing information so that we can compel action and communicate impact. The numbers we collect in our healthcare institutions capture and represent the experience of our stakeholders. Those experiences can tell stories when the data is paired with visual design and narrative.


This article provides a framework of 10 kinds of stories to tell with data in healthcare. Knowing what kind of story you want to tell will focus your purpose.


WHAT IS A STORY

A good story grabs our attention and takes the audience on a journey. Stories have order, they have a clear beginning, middle, and end. Stories tell your audience about cause and effect or about a connected series of events. Data stories do this in a meaningful way that emerges from the data but is shaped for engagement of the audience.

“Storytelling reveals meaning without committing the error of defining it” – Hannah Arendt

Stories result in a changed state. Narrative is an important way to communicate data in a way that is understandable and able to be acted upon. The narrative design of the data story arc follows a path similar to the classic story arc.


Illustrated diagram of data story arc
The data story arc

WHAT IS A DATA STORY

An effective data story resides at the intersection of data, visualization, and narrative. The data drives the content, the visualization clarifies the key takeaways, and the narrative provides the contextual framework. A data story provides the viewer with a breadth of insight embedded in a design articulated for the intended audience.


A data story communicates impact or compels action. To start your data story where it matters, you need to first know your purpose and understand your audience.


A data story can be a collection of visualizations, such as an annual report or presentation, or it may be presented as a single slide, email or infographic.


10 KINDS OF STORIES TO TELL WITH HEALTHCARE DATA

Tom Davenport introduced a taxonomy for data stories that is adapted here. The types are not mutually exclusive of one another nor are they exhaustive, but the narrative types provide a framework. Use this framework as a great resource for helping to identify the purpose of your story and guiding it through the design of the narrative data story arc.


HCAHPS HOSPITAL EXPERIENCE DATA

The visuals used for illustration have been created from publicly reported HCAHPS data.

For those who may not be familiar - the Hospital Consumer Assessment of Healthcare Providers and Systems survey allows for valid comparisons across hospitals locally, regionally, and nationally. The HCAHPS survey asks recently discharged patients about aspects of their hospital experience that they are uniquely suited to address.


The core of the survey asks "how often" a patient experienced a critical aspect of hospital care, for example, "How often was the area around your room quiet at night?". Response selections are "Always", "Usually", "Sometimes", and "Never" (the latter two are combined in the reporting). Only responses in the top box, those marked "Always", ultimately count.

The continuous rolling data is published quarterly (January, April, July, October).


Now that we are past PX101, let's talk about the data. The data set below explores the Quiet-at-Night top box responses from 10 regional hospitals located within the Northern California counties of Butte, Tehama, Siskiyou, Shasta, Yolo, and Yuba Counties.

I examined data for the last eight reporting periods published between July 2021 and April 2023. The data reported was collected between January 1, 2019 and March 31, 2022. It is the most recent data available as of publication.


Take a look at the data set of the percent of patients that said they "Always" had a quiet area around their room at night in ten regional hospitals.


A table of the data set used in this blog post.
Percent of patients who reported that the area around their room was "Always" quiet at night.
Multiple series line graph with legend
Multiple series line graph with legend

This healthcare data set will be used to illustrate the following kinds of stories to tell with healthcare data.


The initial spaghetti line graph out of Excel is not very helpful. However, a few insights do emerge from the data just by using graphic visualization.


We can use this data set to illustrate the types of data stories.


I will assume various stakeholder roles and context scenarios. To simplify things I will focus on using the same multiple-series line graph in the various iterations.



STORY #1 | PAST REPORTING

This type of data story is about what happened last week, month, or quarter. It is about trying to understand what happened in the past.


STORY #2 | PRESENT REPORTING

A present reporting data story is about what is happening right now. Survey and experience data that explains the voice of the customer ‘today’. Most survey data is present reporting.


Imagine that you have been asked by Hospital B to provide them with an update concerning their current scores compared to other hospitals in their region.


An example of a data storytelling visualization using the Preset Reporting framework

This data story provides the narrative structure of context, the challenge, and discovery, and the resolution and call to action while also staying focused primarily on current state.


STORY #3 | FUTURE REPORTING

Stories about the future engage in predictive forecasting. Using data from the past to predict the future involves assumptions and probability. This type of reporting aids in immediate decision making.


STORY #4 | THE WHAT STORY

The 'what’ story tells about what happened. The story simply explains the record of events that occurred to get to the outcome. Much like reporter, the story needs to stay true to the data so that you can explain good or bad causal events.


STORY #5 | THE WHY STORY

Underlying causes of the ‘what’ are explored in the 'why' story. These stories go into the underlying factors that led to the outcome.


Imagine that you have been asked by Hospital D to explain to stakeholders why the data for the reporting periods of January and April 2022 remained static.


An example of a data storytelling visualization using the Why Story framework

The data story provides all the story arc elements while focusing on answering the "why" question. Hospital D is doing really well in this area, so the data story makes note of that accomplishment while keeping the focus on understanding the targeted area in the chart.


STORY #6 | THE HOW STORY

Stories that explore changes that will improve the situation also engage in predictive forecasting. This is a great to use when you want to communicate comparative advantages, for example when developing policies, procedures, and best practice.


STORY #7 | INVESTIGATION STORY

Some data stories are set into motion to investigate a short-term incident or episode. The depth may be focused to quickly spotlight and find a solution for a specific non-complex issue that needs to be addressed. The investigation story has a clear and explicit question for which you have sought an answer.


STORY #8 | EUREKA! STORY

For complex issues, the investigative focus of a data story can be a long, data-driven search for a solution. The ‘Eureka!’ story is like striking gold after a long, difficult stretch of mining the data for a valuable, hard-to-find discovery. In this case, the data must be clear and compelling enough to provide that discovery moment.


STORY #9 | CORRELATION STORY

When two things occur at the same time, they are said to be correlated. The relation between the variables is that they rise and fall at the same time. This type of data story explains the relationship.


Imagine that you have been asked by Hospital D to share insights on how an increase in focused efforts around Quiet-at-Night initiatives have impacted that score.


An example of a data storytelling visualization using the Correlation  framework

This data story contains the elements of narrative while making the connection between initiatives on the unit and improved scores. I don't have data to establish a firm causal relationship, but clearly effort and improvement are correlated. Kudos to Hospital D, aka Mercy Medical Center Mt Shasta (it is publicly reported data after all), for making a quiet environment a priority for their patients, the data shows they have clearly been putting effort into it!


There are many initiatives that hospitals can engage in to improve Quiet at Night scores. This HCAHPS improvement brief from Planetree provides some ways to approach initiatives in this important part of the patient experience.


STORY #10 | CAUSATION STORY

Causation stories start out with a question of "what caused 'X'" and through storytelling provides the answer that led to the outcome. You have to be able to show that one variable is causing the other. Causation stories involve predictive analytics.


DESCRIPTIVE VS INFERENTIAL ANALYTICS

There are two main types of analytics to include in data stories. Descriptive statistics provide a means to describe data in a manageable form. It is primarily explanatory in nature. Inferential analytics, on the other hand, assist in drawing conclusions from our insights. Inferential analytics are primarily predictive. Aside from data scientists, most business leaders in an organization are going to use descriptive statistics.


Most of the kinds of stories to tell with healthcare data lend themselves to descriptive data, some are better for inferential analytics, and a couple can do both. The following table summarizes this point.

DATA STORY TYPE

DESCRIPTIVE ANALYTICS

INFERENTIAL ANALYTICS

PAST REPORTING

X

PRESENT REPORTING

X

FUTURE REPORTING

X

THE WHAT STORY

X

THE WHY STORY

X

THE HOW STORY

X

INCIDENT INVESTIGATION STORY

X

X

EUREKA! STORY

X

X

CORRELATION STORY

X

CAUSATION STORY

X


There are different types of business stories to share. This article explored a framework with 10 kinds of stories to tell with healthcare data. Using publicly reported patient experience data, the "Quiet at Night" scores for 10 regional California hospitals were analyzed and visualized for illustrative purposes. Whether your story is about the current state, future state, last quarter, or a Eureka! discovery, use of a narrative framework can help guide the development of your story.

 
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Roseanna Galindo, ECBA, CAVS

Roseanna Galindo is Principal at Periscope Business Process Analysis and a champion for data literacy, the human experience in healthcare, and volunteer leaders everywhere. Learn more about Roseanna and her blog, The Periscope Insighter, by reading the opening post, Venn The Time Is Right



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