case study timeline

How to write a case study — examples, templates, and tools

It’s a marketer’s job to communicate the effectiveness of a product or service to potential and current customers to convince them to buy and keep business moving. One of the best methods for doing this is to share success stories that are relatable to prospects and customers based on their pain points, experiences, and overall needs.

That’s where case studies come in. Case studies are an essential part of a content marketing plan. These in-depth stories of customer experiences are some of the most effective at demonstrating the value of a product or service. Yet many marketers don’t use them, whether because of their regimented formats or the process of customer involvement and approval.

A case study is a powerful tool for showcasing your hard work and the success your customer achieved. But writing a great case study can be difficult if you’ve never done it before or if it’s been a while. This guide will show you how to write an effective case study and provide real-world examples and templates that will keep readers engaged and support your business.

In this article, you’ll learn:

What is a case study?

How to write a case study, case study templates, case study examples, case study tools.

A case study is the detailed story of a customer’s experience with a product or service that demonstrates their success and often includes measurable outcomes. Case studies are used in a range of fields and for various reasons, from business to academic research. They’re especially impactful in marketing as brands work to convince and convert consumers with relatable, real-world stories of actual customer experiences.

The best case studies tell the story of a customer’s success, including the steps they took, the results they achieved, and the support they received from a brand along the way. To write a great case study, you need to:

• Celebrate the customer and make them — not a product or service — the star of the story.
• Craft the story with specific audiences or target segments in mind so that the story of one customer will be viewed as relatable and actionable for another customer.
• Write copy that is easy to read and engaging so that readers will gain the insights and messages intended.
• Follow a standardized format that includes all of the essentials a potential customer would find interesting and useful.
• Support all of the claims for success made in the story with data in the forms of hard numbers and customer statements.

Case studies are a type of review but more in depth, aiming to show — rather than just tell — the positive experiences that customers have with a brand. Notably, 89% of consumers read reviews before deciding to buy, and 79% view case study content as part of their purchasing process. When it comes to B2B sales, 52% of buyers rank case studies as an important part of their evaluation process.

Telling a brand story through the experience of a tried-and-true customer matters. The story is relatable to potential new customers as they imagine themselves in the shoes of the company or individual featured in the case study. Showcasing previous customers can help new ones see themselves engaging with your brand in the ways that are most meaningful to them.

Besides sharing the perspective of another customer, case studies stand out from other content marketing forms because they are based on evidence. Whether pulling from client testimonials or data-driven results, case studies tend to have more impact on new business because the story contains information that is both objective (data) and subjective (customer experience) — and the brand doesn’t sound too self-promotional.

Case studies are unique in that there’s a fairly standardized format for telling a customer’s story. But that doesn’t mean there isn’t room for creativity. It’s all about making sure that teams are clear on the goals for the case study — along with strategies for supporting content and channels — and understanding how the story fits within the framework of the company’s overall marketing goals.

Here are the basic steps to writing a good case study.

1. Identify your goal

Start by defining exactly who your case study will be designed to help. Case studies are about specific instances where a company works with a customer to achieve a goal. Identify which customers are likely to have these goals, as well as other needs the story should cover to appeal to them.

The answer is often found in one of the buyer personas that have been constructed as part of your larger marketing strategy. This can include anything from new leads generated by the marketing team to long-term customers that are being pressed for cross-sell opportunities. In all of these cases, demonstrating value through a relatable customer success story can be part of the solution to conversion.

2. Choose your client or subject

Who you highlight matters. Case studies tie brands together that might otherwise not cross paths. A writer will want to ensure that the highlighted customer aligns with their own company’s brand identity and offerings. Look for a customer with positive name recognition who has had great success with a product or service and is willing to be an advocate.

The client should also match up with the identified target audience. Whichever company or individual is selected should be a reflection of other potential customers who can see themselves in similar circumstances, having the same problems and possible solutions.

Some of the most compelling case studies feature customers who:

• Switch from one product or service to another while naming competitors that missed the mark.
• Experience measurable results that are relatable to others in a specific industry.
• Represent well-known brands and recognizable names that are likely to compel action.
• Advocate for a product or service as a champion and are well-versed in its advantages.

Whoever or whatever customer is selected, marketers must ensure they have the permission of the company involved before getting started. Some brands have strict review and approval procedures for any official marketing or promotional materials that include their name. Acquiring those approvals in advance will prevent any miscommunication or wasted effort if there is an issue with their legal or compliance teams.

3. Conduct research and compile data

Substantiating the claims made in a case study — either by the marketing team or customers themselves — adds validity to the story. To do this, include data and feedback from the client that defines what success looks like. This can be anything from demonstrating return on investment (ROI) to a specific metric the customer was striving to improve. Case studies should prove how an outcome was achieved and show tangible results that indicate to the customer that your solution is the right one.

This step could also include customer interviews. Make sure that the people being interviewed are key stakeholders in the purchase decision or deployment and use of the product or service that is being highlighted. Content writers should work off a set list of questions prepared in advance. It can be helpful to share these with the interviewees beforehand so they have time to consider and craft their responses. One of the best interview tactics to keep in mind is to ask questions where yes and no are not natural answers. This way, your subject will provide more open-ended responses that produce more meaningful content.

4. Choose the right format

There are a number of different ways to format a case study. Depending on what you hope to achieve, one style will be better than another. However, there are some common elements to include, such as:

• An engaging headline
• A subject and customer introduction
• The unique challenge or challenges the customer faced
• The solution the customer used to solve the problem
• The results achieved
• Data and statistics to back up claims of success
• A strong call to action (CTA) to engage with the vendor

It’s also important to note that while case studies are traditionally written as stories, they don’t have to be in a written format. Some companies choose to get more creative with their case studies and produce multimedia content, depending on their audience and objectives. Case study formats can include traditional print stories, interactive web or social content, data-heavy infographics, professionally shot videos, podcasts, and more.

5. Write your case study

We’ll go into more detail later about how exactly to write a case study, including templates and examples. Generally speaking, though, there are a few things to keep in mind when writing your case study.

• Be clear and concise. Readers want to get to the point of the story quickly and easily, and they’ll be looking to see themselves reflected in the story right from the start.
• Provide a big picture. Always make sure to explain who the client is, their goals, and how they achieved success in a short introduction to engage the reader.
• Construct a clear narrative. Stick to the story from the perspective of the customer and what they needed to solve instead of just listing product features or benefits.
• Leverage graphics. Incorporating infographics, charts, and sidebars can be a more engaging and eye-catching way to share key statistics and data in readable ways.
• Offer the right amount of detail. Most case studies are one or two pages with clear sections that a reader can skim to find the information most important to them.
• Include data to support claims. Show real results — both facts and figures and customer quotes — to demonstrate credibility and prove the solution works.

6. Promote your story

Marketers have a number of options for distribution of a freshly minted case study. Many brands choose to publish case studies on their website and post them on social media. This can help support SEO and organic content strategies while also boosting company credibility and trust as visitors see that other businesses have used the product or service.

Marketers are always looking for quality content they can use for lead generation. Consider offering a case study as gated content behind a form on a landing page or as an offer in an email message. One great way to do this is to summarize the content and tease the full story available for download after the user takes an action.

Sales teams can also leverage case studies, so be sure they are aware that the assets exist once they’re published. Especially when it comes to larger B2B sales, companies often ask for examples of similar customer challenges that have been solved.

Now that you’ve learned a bit about case studies and what they should include, you may be wondering how to start creating great customer story content. Here are a couple of templates you can use to structure your case study.

Template 1 — Challenge-solution-result format

• Start with an engaging title. This should be fewer than 70 characters long for SEO best practices. One of the best ways to approach the title is to include the customer’s name and a hint at the challenge they overcame in the end.
• Create an introduction. Lead with an explanation as to who the customer is, the need they had, and the opportunity they found with a specific product or solution. Writers can also suggest the success the customer experienced with the solution they chose.
• Present the challenge. This should be several paragraphs long and explain the problem the customer faced and the issues they were trying to solve. Details should tie into the company’s products and services naturally. This section needs to be the most relatable to the reader so they can picture themselves in a similar situation.
• Share the solution. Explain which product or service offered was the ideal fit for the customer and why. Feel free to delve into their experience setting up, purchasing, and onboarding the solution.
• Explain the results. Demonstrate the impact of the solution they chose by backing up their positive experience with data. Fill in with customer quotes and tangible, measurable results that show the effect of their choice.
• Ask for action. Include a CTA at the end of the case study that invites readers to reach out for more information, try a demo, or learn more — to nurture them further in the marketing pipeline. What you ask of the reader should tie directly into the goals that were established for the case study in the first place.

Template 2 — Data-driven format

• Start with an engaging title. Be sure to include a statistic or data point in the first 70 characters. Again, it’s best to include the customer’s name as part of the title.
• Create an overview. Share the customer’s background and a short version of the challenge they faced. Present the reason a particular product or service was chosen, and feel free to include quotes from the customer about their selection process.
• Present data point 1. Isolate the first metric that the customer used to define success and explain how the product or solution helped to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Present data point 2. Isolate the second metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Present data point 3. Isolate the final metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Summarize the results. Reiterate the fact that the customer was able to achieve success thanks to a specific product or service. Include quotes and statements that reflect customer satisfaction and suggest they plan to continue using the solution.
• Ask for action. Include a CTA at the end of the case study that asks readers to reach out for more information, try a demo, or learn more — to further nurture them in the marketing pipeline. Again, remember that this is where marketers can look to convert their content into action with the customer.

While templates are helpful, seeing a case study in action can also be a great way to learn. Here are some examples of how Adobe customers have experienced success.

Juniper Networks

One example is the Adobe and Juniper Networks case study , which puts the reader in the customer’s shoes. The beginning of the story quickly orients the reader so that they know exactly who the article is about and what they were trying to achieve. Solutions are outlined in a way that shows Adobe Experience Manager is the best choice and a natural fit for the customer. Along the way, quotes from the client are incorporated to help add validity to the statements. The results in the case study are conveyed with clear evidence of scale and volume using tangible data.

The story of Lenovo’s journey with Adobe is one that spans years of planning, implementation, and rollout. The Lenovo case study does a great job of consolidating all of this into a relatable journey that other enterprise organizations can see themselves taking, despite the project size. This case study also features descriptive headers and compelling visual elements that engage the reader and strengthen the content.

Tata Consulting

When it comes to using data to show customer results, this case study does an excellent job of conveying details and numbers in an easy-to-digest manner. Bullet points at the start break up the content while also helping the reader understand exactly what the case study will be about. Tata Consulting used Adobe to deliver elevated, engaging content experiences for a large telecommunications client of its own — an objective that’s relatable for a lot of companies.

Case studies are a vital tool for any marketing team as they enable you to demonstrate the value of your company’s products and services to others. They help marketers do their job and add credibility to a brand trying to promote its solutions by using the experiences and stories of real customers.

When you’re ready to get started with a case study:

• Think about a few goals you’d like to accomplish with your content.
• Make a list of successful clients that would be strong candidates for a case study.
• Reach out to the client to get their approval and conduct an interview.
• Gather the data to present an engaging and effective customer story.

Adobe can help

There are several Adobe products that can help you craft compelling case studies. Adobe Experience Platform helps you collect data and deliver great customer experiences across every channel. Once you’ve created your case studies, Experience Platform will help you deliver the right information to the right customer at the right time for maximum impact.

To learn more, watch the Adobe Experience Platform story .

Keep in mind that the best case studies are backed by data. That’s where Adobe Real-Time Customer Data Platform and Adobe Analytics come into play. With Real-Time CDP, you can gather the data you need to build a great case study and target specific customers to deliver the content to the right audience at the perfect moment.

Watch the Real-Time CDP overview video to learn more.

Finally, Adobe Analytics turns real-time data into real-time insights. It helps your business collect and synthesize data from multiple platforms to make more informed decisions and create the best case study possible.

Request a demo to learn more about Adobe Analytics.

https://business.adobe.com/blog/perspectives/b2b-ecommerce-10-case-studies-inspire-you

https://business.adobe.com/blog/basics/business-case

https://business.adobe.com/blog/basics/what-is-real-time-analytics

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Blog Case Study

How to Present a Case Study like a Pro (With Examples)

By Danesh Ramuthi , Sep 07, 2023

In today’s world, where data is king and persuasion is queen, a killer case study can change the game. Think high-powered meetings at fancy companies or even nailing that college presentation: a rock-solid case study could be the magic weapon you need.

Okay, let’s get real: case studies can be kinda snooze-worthy. But guess what? They don’t have to be!

In this article, you’ll learn all about crafting and presenting powerful case studies. From selecting the right metrics to using persuasive narrative techniques, I will cover every element that transforms a mere report into a compelling case study. 

And if you’re feeling a little lost, don’t worry! There are cool tools like Venngage’s Case Study Creator to help you whip up something awesome, even if you’re short on time. Plus, the pre-designed case study templates are like instant polish because let’s be honest, everyone loves a shortcut.

Click to jump ahead: 

What is a case study presentation?

Purpose of presenting a case study, how to structure a case study presentation, how long should a case study presentation be, 5 case study presentation templates, tips for delivering an effective case study presentation, common mistakes to avoid in a case study presentation, how to present a case study faqs.

A case study presentation involves a comprehensive examination of a specific subject, which could range from an individual, group, location, event, organization or phenomenon.

They’re like puzzles you get to solve with the audience, all while making you think outside the box.

Unlike a basic report or whitepaper, the purpose of a case study presentation is to stimulate critical thinking among the viewers. 

The primary objective of a case study is to provide an extensive and profound comprehension of the chosen topic. You don’t just throw numbers at your audience. You use examples and real-life cases to make you think and see things from different angles.

The primary purpose of presenting a case study is to offer a comprehensive, evidence-based argument that informs, persuades and engages your audience.

Here’s the juicy part: presenting that case study can be your secret weapon. Whether you’re pitching a groundbreaking idea to a room full of suits or trying to impress your professor with your A-game, a well-crafted case study can be the magic dust that sprinkles brilliance over your words.

Think of it like digging into a puzzle you can’t quite crack . A case study lets you explore every piece, turn it over and see how it fits together. This close-up look helps you understand the whole picture, not just a blurry snapshot.

It’s also your chance to showcase how you analyze things, step by step, until you reach a conclusion. It’s all about being open and honest about how you got there.

Besides, presenting a case study gives you an opportunity to connect data and real-world scenarios in a compelling narrative. It helps to make your argument more relatable and accessible, increasing its impact on your audience.

One of the contexts where case studies can be very helpful is during the job interview. In some job interviews, you as candidates may be asked to present a case study as part of the selection process.

Having a case study presentation prepared allows the candidate to demonstrate their ability to understand complex issues, formulate strategies and communicate their ideas effectively.

The way you present a case study can make all the difference in how it’s received. A well-structured presentation not only holds the attention of your audience but also ensures that your key points are communicated clearly and effectively.

In this section, let’s go through the key steps that’ll help you structure your case study presentation for maximum impact.

Let’s get into it. 

Open with an introductory overview 

Start by introducing the subject of your case study and its relevance. Explain why this case study is important and who would benefit from the insights gained. This is your opportunity to grab your audience’s attention.

Explain the problem in question

Dive into the problem or challenge that the case study focuses on. Provide enough background information for the audience to understand the issue. If possible, quantify the problem using data or metrics to show the magnitude or severity.

Detail the solutions to solve the problem

After outlining the problem, describe the steps taken to find a solution. This could include the methodology, any experiments or tests performed and the options that were considered. Make sure to elaborate on why the final solution was chosen over the others.

Key stakeholders Involved

Talk about the individuals, groups or organizations that were directly impacted by or involved in the problem and its solution. 

Stakeholders may experience a range of outcomes—some may benefit, while others could face setbacks.

For example, in a business transformation case study, employees could face job relocations or changes in work culture, while shareholders might be looking at potential gains or losses.

Discuss the key results & outcomes

Discuss the results of implementing the solution. Use data and metrics to back up your statements. Did the solution meet its objectives? What impact did it have on the stakeholders? Be honest about any setbacks or areas for improvement as well.

Include visuals to support your analysis

Visual aids can be incredibly effective in helping your audience grasp complex issues. Utilize charts, graphs, images or video clips to supplement your points. Make sure to explain each visual and how it contributes to your overall argument.

Pie charts illustrate the proportion of different components within a whole, useful for visualizing market share, budget allocation or user demographics.

This is particularly useful especially if you’re displaying survey results in your case study presentation.

Stacked charts on the other hand are perfect for visualizing composition and trends. This is great for analyzing things like customer demographics, product breakdowns or budget allocation in your case study.

Consider this example of a stacked bar chart template. It provides a straightforward summary of the top-selling cake flavors across various locations, offering a quick and comprehensive view of the data.

Not the chart you’re looking for? Browse Venngage’s gallery of chart templates to find the perfect one that’ll captivate your audience and level up your data storytelling.

Recommendations and next steps

Wrap up by providing recommendations based on the case study findings. Outline the next steps that stakeholders should take to either expand on the success of the project or address any remaining challenges.

Acknowledgments and references

Thank the people who contributed to the case study and helped in the problem-solving process. Cite any external resources, reports or data sets that contributed to your analysis.

Feedback & Q&A session

Open the floor for questions and feedback from your audience. This allows for further discussion and can provide additional insights that may not have been considered previously.

Closing remarks

Conclude the presentation by summarizing the key points and emphasizing the takeaways. Thank your audience for their time and participation and express your willingness to engage in further discussions or collaborations on the subject.

Well, the length of a case study presentation can vary depending on the complexity of the topic and the needs of your audience. However, a typical business or academic presentation often lasts between 15 to 30 minutes. 

This time frame usually allows for a thorough explanation of the case while maintaining audience engagement. However, always consider leaving a few minutes at the end for a Q&A session to address any questions or clarify points made during the presentation.

When it comes to presenting a compelling case study, having a well-structured template can be a game-changer. 

It helps you organize your thoughts, data and findings in a coherent and visually pleasing manner. 

Not all case studies are created equal and different scenarios require distinct approaches for maximum impact. 

To save you time and effort, I have curated a list of 5 versatile case study presentation templates, each designed for specific needs and audiences. 

Here are some best case study presentation examples that showcase effective strategies for engaging your audience and conveying complex information clearly.

1) Lab report case study template

Ever feel like your research gets lost in a world of endless numbers and jargon? Lab case studies are your way out!

Think of it as building a bridge between your cool experiment and everyone else. It’s more than just reporting results – it’s explaining the “why” and “how” in a way that grabs attention and makes sense.

This lap report template acts as a blueprint for your report, guiding you through each essential section (introduction, methods, results, etc.) in a logical order.

2) Product case study template

It’s time you ditch those boring slideshows and bullet points because I’ve got a better way to win over clients: product case study templates.

Instead of just listing features and benefits, you get to create a clear and concise story that shows potential clients exactly what your product can do for them. It’s like painting a picture they can easily visualize, helping them understand the value your product brings to the table.

Grab the template below, fill in the details, and watch as your product’s impact comes to life!

3) Content marketing case study template

In digital marketing, showcasing your accomplishments is as vital as achieving them. 

A well-crafted case study not only acts as a testament to your successes but can also serve as an instructional tool for others. 

With this coral content marketing case study template—a perfect blend of vibrant design and structured documentation, you can narrate your marketing triumphs effectively.

4) Case study psychology template

Understanding how people tick is one of psychology’s biggest quests and case studies are like magnifying glasses for the mind. They offer in-depth looks at real-life behaviors, emotions and thought processes, revealing fascinating insights into what makes us human.

Writing a top-notch case study, though, can be a challenge. It requires careful organization, clear presentation and meticulous attention to detail. That’s where a good case study psychology template comes in handy.

Think of it as a helpful guide, taking care of formatting and structure while you focus on the juicy content. No more wrestling with layouts or margins – just pour your research magic into crafting a compelling narrative.

5) Lead generation case study template

Lead generation can be a real head-scratcher. But here’s a little help: a lead generation case study.

Think of it like a friendly handshake and a confident resume all rolled into one. It’s your chance to showcase your expertise, share real-world successes and offer valuable insights. Potential clients get to see your track record, understand your approach and decide if you’re the right fit.

No need to start from scratch, though. This lead generation case study template guides you step-by-step through crafting a clear, compelling narrative that highlights your wins and offers actionable tips for others. Fill in the gaps with your specific data and strategies, and voilà! You’ve got a powerful tool to attract new customers.

Related: 15+ Professional Case Study Examples [Design Tips + Templates]

So, you’ve spent hours crafting the perfect case study and are now tasked with presenting it. Crafting the case study is only half the battle; delivering it effectively is equally important. 

Whether you’re facing a room of executives, academics or potential clients, how you present your findings can make a significant difference in how your work is received. 

Forget boring reports and snooze-inducing presentations! Let’s make your case study sing. Here are some key pointers to turn information into an engaging and persuasive performance:

• Know your audience : Tailor your presentation to the knowledge level and interests of your audience. Remember to use language and examples that resonate with them.
• Rehearse : Rehearsing your case study presentation is the key to a smooth delivery and for ensuring that you stay within the allotted time. Practice helps you fine-tune your pacing, hone your speaking skills with good word pronunciations and become comfortable with the material, leading to a more confident, conversational and effective presentation.
• Start strong : Open with a compelling introduction that grabs your audience’s attention. You might want to use an interesting statistic, a provocative question or a brief story that sets the stage for your case study.
• Be clear and concise : Avoid jargon and overly complex sentences. Get to the point quickly and stay focused on your objectives.
• Use visual aids : Incorporate slides with graphics, charts or videos to supplement your verbal presentation. Make sure they are easy to read and understand.
• Tell a story : Use storytelling techniques to make the case study more engaging. A well-told narrative can help you make complex data more relatable and easier to digest.

Ditching the dry reports and slide decks? Venngage’s case study templates let you wow customers with your solutions and gain insights to improve your business plan. Pre-built templates, visual magic and customer captivation – all just a click away. Go tell your story and watch them say “wow!”

Crafting and presenting a case study is a skillful task that requires careful planning and execution. While a well-prepared case study can be a powerful tool for showcasing your successes, educating your audience or encouraging discussion, there are several pitfalls you should avoid to make your presentation as effective as possible. Here are some common mistakes to watch out for:

Overloading with information

A case study is not an encyclopedia. Overloading your presentation with excessive data, text or jargon can make it cumbersome and difficult for the audience to digest the key points. Stick to what’s essential and impactful.

Lack of structure

Jumping haphazardly between points or topics can confuse your audience. A well-structured presentation, with a logical flow from introduction to conclusion, is crucial for effective communication.

Ignoring the audience

Different audiences have different needs and levels of understanding. Failing to adapt your presentation to your audience can result in a disconnect and a less impactful presentation.

Poor visual elements

While content is king, poor design or lack of visual elements can make your case study dull or hard to follow. Make sure you use high-quality images, graphs and other visual aids to support your narrative.

Not focusing on results

A case study aims to showcase a problem and its solution, but what most people care about are the results. Failing to highlight or adequately explain the outcomes can make your presentation fall flat.

How to start a case study presentation?

Starting a case study presentation effectively involves a few key steps:

• Grab attention : Open with a hook—an intriguing statistic, a provocative question or a compelling visual—to engage your audience from the get-go.
• Set the stage : Briefly introduce the subject, context and relevance of the case study to give your audience an idea of what to expect.
• Outline objectives : Clearly state what the case study aims to achieve. Are you solving a problem, proving a point or showcasing a success?
• Agenda : Give a quick outline of the key sections or topics you’ll cover to help the audience follow along.
• Set expectations : Let your audience know what you want them to take away from the presentation, whether it’s knowledge, inspiration or a call to action.

How to present a case study on PowerPoint and on Google Slides?

Presenting a case study on PowerPoint and Google Slides involves a structured approach for clarity and impact using presentation slides:

• Title slide : Start with a title slide that includes the name of the case study, your name and any relevant institutional affiliations.
• Introduction : Follow with a slide that outlines the problem or situation your case study addresses. Include a hook to engage the audience.
• Objectives : Clearly state the goals of the case study in a dedicated slide.
• Findings : Use charts, graphs and bullet points to present your findings succinctly.
• Analysis : Discuss what the findings mean, drawing on supporting data or secondary research as necessary.
• Conclusion : Summarize key takeaways and results.
• Q&A : End with a slide inviting questions from the audience.

What’s the role of analysis in a case study presentation?

The role of analysis in a case study presentation is to interpret the data and findings, providing context and meaning to them. 

It helps your audience understand the implications of the case study, connects the dots between the problem and the solution and may offer recommendations for future action.

Is it important to include real data and results in the presentation?

Yes, including real data and results in a case study presentation is crucial to show experience,  credibility and impact. Authentic data lends weight to your findings and conclusions, enabling the audience to trust your analysis and take your recommendations more seriously

How do I conclude a case study presentation effectively?

To conclude a case study presentation effectively, summarize the key findings, insights and recommendations in a clear and concise manner. 

End with a strong call-to-action or a thought-provoking question to leave a lasting impression on your audience.

What’s the best way to showcase data in a case study presentation ?

The best way to showcase data in a case study presentation is through visual aids like charts, graphs and infographics which make complex information easily digestible, engaging and creative. 

Don’t just report results, visualize them! This template for example lets you transform your social media case study into a captivating infographic that sparks conversation.

Choose the type of visual that best represents the data you’re showing; for example, use bar charts for comparisons or pie charts for parts of a whole. 

Ensure that the visuals are high-quality and clearly labeled, so the audience can quickly grasp the key points. 

Keep the design consistent and simple, avoiding clutter or overly complex visuals that could distract from the message.

Choose a template that perfectly suits your case study where you can utilize different visual aids for maximum impact. 

Need more inspiration on how to turn numbers into impact with the help of infographics? Our ready-to-use infographic templates take the guesswork out of creating visual impact for your case studies with just a few clicks.

Related: 10+ Case Study Infographic Templates That Convert

Congrats on mastering the art of compelling case study presentations! This guide has equipped you with all the essentials, from structure and nuances to avoiding common pitfalls. You’re ready to impress any audience, whether in the boardroom, the classroom or beyond.

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The “Case Study Timeline PowerPoint Template” offers a detailed and attractive format for presenting your case study. It has different questions, approaches, and history sections for easier organization and communication of important information related to the case study.

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Health timeline: an insight-based study of a timeline visualization of clinical data

Andres ledesma.

1 Tampere University, Faculty of Medicine and Health Technology, Tampere, Finland

Niranjan Bidargaddi

2 College of Medicine & Public Health, Flinders University, Medical Sciences Rd, Adelaide, Australia

Jörg Strobel

3 Discipline of Psychiatry, The Queen Elizabeth Hospital, South Australia, University of Adelaide, 28 Woodville Rd, Woodville South, Adelaide, Australia

Geoffrey Schrader

4 Country Health Local Health Network, South Australia, and Flinders University, Medical Sciences Rd, Adelaide, Australia

Hannu Nieminen

Ilkka korhonen, miikka ermes.

5 VTT Technical Research Center Ltd, Tekniikankatu 1, Tampere, Finland

Associated Data

All data generated or analyzed during this study are included in this published article and its supplementary information files.

The increasing complexity and volume of clinical data poses a challenge in the decision-making process. Data visualizations can assist in this process by speeding up the time required to analyze and understand clinical data. Even though empirical experiments show that visualizations facilitate clinical data understanding, a consistent method to assess their effectiveness is still missing.

The insight-based methodology determines the quality of insights a user acquires from the visualization. Insights receive a value from one to five points based on a domain-specific criteria. Five professional psychiatrists took part in the study using real de-identified clinical data spanning 4 years of medical history.

A total of 50 assessments were transcribed and analyzed. Comparing a total of 558 insights using Health Timeline and 576 without, the mean value using the Timeline (1.7) was higher than without (1.26; p<0.01), similarly the cumulative value with the Timeline (11.87) was higher than without (10.96: p<0.01). The average time required to formulate the first insight with the Timeline was higher (13.16 s) than without (7 s; p<0.01). Seven insights achieved the highest possible value using Health Timeline while none were obtained without it.

Conclusions

The Health Timeline effectively improved understanding of clinical data and helped participants recognize complex patterns from the data. By applying the insight-based methodology, the effectiveness of the Health Timeline was quantified, documented and demonstrated. As an outcome of this exercise, we propose the use of such methodologies to measure the effectiveness of visualizations that assist the clinical decision-making process.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0885-x) contains supplementary material, which is available to authorized users.

Researchers estimate that clinical data will grow [ 1 ], from 153 exabytes in 2013 to 2314 in 2020 [ 2 ]. Electronic health records (EHRs) constitute most of the clinical data. These records are the “purest type” of electronic clinical data obtained at the point of care [ 3 ]. EHRs collected over time represent a patient’s clinical history. Healthcare professionals rely on them for diagnosis and treatment.

As clinical data increases in volume, so does the potential value for healthcare providers to benefit from it. IT-based information systems can summarize and visualize clinical data. Health Informatics is the “interdisciplinary study of the design, development, adoption and application of IT-based innovations in healthcare services delivery” [ 4 ]. Numerous research efforts have addressed the need to understand clinical data by designing and building a variety of visualizations [ 5 , 6 ].

North suggests that the purpose of visualizations is to help readers derive insights [ 7 ]. A measure of an effective visualization is its ability to generate new insights that go beyond predefined data analysis tasks [ 8 ]. The effectiveness of clinical data visualizations is an area of active research [ 5 , 6 , 9 ]. Graphical representation techniques have been addressed in several studies [ 10 ]. One significant example was reported by Goetz who demonstrated that data presentation greatly affects the understanding of a person’s health [ 11 ]. Thus, visualization concepts applied to clinical data should enable healthcare professionals to obtain insights about the condition of the patient more comprehensively and efficiently than traditional textual or tabular presentations.

Researchers have implemented several visualization tools for clinical data [ 5 ]. A literature survey identified fourteen computerized tools for visualizing EHRs [ 6 ]. The articles describe in detail the design and implementation of these tools. However, they do not use a structured method, such as the insight-based methodology, to perform assessments.

We extracted data from the Australian “My Health Record” initiative [ 12 ] and developed a computerized solution to visualize clinical data chronologically. The solution was named Health Timeline to emphasize the significance of time in the clinical data. The software organizes and displays the clinical data in an interactive timeline using visual enhancements to facilitate readability. This article documents the assessment of Health Timeline which applies the insight-based methodology. Five psychiatrists took part in the study by reviewing the clinical data of five de-identified patients. The psychiatrists were instructed to use the “thinking aloud process”. This process consists of verbalizing the thought pattern followed while inspecting the data. Their findings were recorded using a voice recording software. These findings were later transcribed and analyzed following the insight-based methodology.

Related work

The findings of Lesselroth and Pieczkiewicz [ 5 ], as well as those of Rind and colleagues [ 6 ] are further discussed. The study reported in this article relates to other computerized solutions. The key distinction is the assessment methodology.

The focus of this study is on time-based visualizations of clinical data (EHR) and the assessment methodology used to validate them. Time-based visualizations are graphical representations of data collected over time. The research literature has a large number of data visualization techniques that vary in their strategies. However, we refined our search to include only visualization tools based on time, and the longitudinal nature of the data. The search was narrowed down further to only include those techniques that were used in the context of clinical data. We were particularly interested in the assessment methodology used to evaluate these visualizations.

Review of similar solutions in the healthcare context

LifeLines is a computerized tool that displays clinical data [ 13 ] using dots positioned along horizontal lines [ 14 ]. A study showed that participants responded 50% faster to a “post-experimental memory test” ( p <0.004) [ 15 ]. LifeLines was extended in a second version with support for aggregation of temporal events [ 16 ]. The focus was on emphasizing prevalence and temporal order of the clinical data. A study revealed that the clinicians were able to confirm hypotheses on the hospital length of stay of patients. LifeLines [ 13 ] and LifeLines2 [ 16 ] are Java software applications, thus they must be installed in a Java-capable device. These tools provide data filters to narrow down the data exploration and enable the user to focus on certain aspects of the timeline.

TimeLine is a visualization software that displays EHRs chronologically [ 17 ]. The data is grouped by categories and displayed along a visual timeline. No assessment of the software was reported in the article. Timeline [ 17 ] is the closest application to Health Timeline. It features web support, EHR interfacing and a timeline representation of data with a focus on oncology. Timeline also has a large number of features such as causal models, imaging files, data search, disease progression visualization and data category toggling. It is probable that using Timeline involves a learning curve as it offers several features that would require the user to become acquainted with.

LifeFlow is a visualization tool that summarizes data in sequences using temporal spacing of events [ 18 ]. One physician took part in a briefing interview about the visualization of patient transportation data. EventFlow is a drug prescription pattern visualization [ 19 ]. A study on the use of asthma drugs was conducted to identify patterns that complied with regulations. LifeFlow and EventFlow are also software applications that require installation. The data are not visualized in a timeline but instead the representation is chronologically ordered as a series of events and outcomes. These visualizations are optimized for understanding the causes and outcomes of patient admissions to hospital.

Assessment methods

Bertini and colleagues [ 20 ] made a strong case for the objective assessment of visualization tools. A literature review on assessment methods for information visualization reports a number of practical cases and proposes a classification of these methods. The Visual Data Analysis and Reasoning (VDAR) classification group is relevant to our study because it emphasizes the decision-making process, knowledge discovery and visual data analysis. We found that no assessments of this kind have been conducted using clinical data and medical experts.

Time-based visualizations have been found helpful in several use cases. However, without a systematic assessment method, it is difficult to demonstrate how they improve the understanding of the data. To provide a contribution towards the good practice of assessment methods for clinical data visualizations, we conducted and documented the assessment of the Health Timeline using the insight-based methodology. This methodology has been previously used in bioinformatics [ 8 , 21 – 23 ] and well-being data analysis [ 9 , 24 ].

Key contribution

The key contribution is to test out the insight-based methodology for the assessment of a clinical data visualization of EHRs. To our understanding, researchers have not documented an insight-based evaluation in this specific context.

Evaluating visual data analysis and reasoning

The VDAR classification group proposed by Lam and colleagues [ 25 ] is relevant to this study due to the nature of the clinical data. The purpose of our study is to measure the degree to which a time-based visualization can assist the data analysis and the reasoning process of a clinician when analyzing the clinical history of a patient. In the context of clinical data, we found in the research literature that studies tend to focus on the usability of the interactions with the visualization system. Other studies conduct briefing interviews and questionnaires to try to assess the participants’ understanding of the data. Nevertheless, a consistent evaluation methodology is still missing.

The purpose of our study is to measure the degree to which a time-based visualization can assist the data analysis and reasoning process of a clinician when analyzing the clinical history of a patient. In the context of clinical data, we found in the research literature that studies tend to focus on the usability of the interactions with the visualization system. Other studies conduct briefing interviews and questionnaires to try to assess the participants’ understanding of the data. Nevertheless, a consistent evaluation methodology is still missing.

Contextualizing the insight-based methodology

The insight-based methodology provides an assessment method focusing on the insights generated by a visualization [ 7 ]. In this approach, the insights formulated by the visualization audience are assessed in a Likert scale from 1 to 5. To contextualize the insight-based methodology to the clinical data domain, we consulted with two subject matter experts to assist us in establishing the assessment criteria of the insights.

From bioinformatics to clinical data

The insights gained in this study are analogous to those observed in the bioinformatics context because they demonstrate different degrees of completeness and accuracy in the understanding of the data represented by the visualization. In the bioinformatics context, predetermined information deemed as correct and complete, was used to compare the insights obtained in the study [ 8 , 21 , 22 ]. The same is true for our study, since two professional psychiatrists reviewed the evaluation criteria. Due to their experience, these psychiatrists were qualified to evaluate the degree of completeness and accuracy of the insights. These experts were also acquainted with the clinical data used in our study.

The insight-based methodology could be used in future studies to quantify the effectiveness of clinical data visualizations. This study provides details on the application of the methodology, including the process required to establish criteria to assess the insight value. The insight value is a key component to analyze and interpret the results of the evaluation. We hope to provide enough documentation about the steps followed to apply the insight-based methodology. The purpose is to provide a case study on evaluating visualizations using the insight-based methodology contextualized to the healthcare domain.

In this study we documented the application of the insight-based methodology. This process involved the recording of insights, the formulation of a consistent criteria for insight assessment and the application of those criteria to collect and analyze the results. To this extent, we define the goals of the study as follows:

• To apply the insight-based methodology to assess the Health Timeline visualization using clinical data and Healthcare professionals.
• To document the assessment process so that it may serve as a reference for future studies on clinical data visualizations.

In this section we present the experiment protocol and the hypothesis that we proposed on the outcome of the study. We also present the Health Timeline and explain its design rationale. The counterpart of the Health Timeline is a table showing the clinical history of the patient in textual format. We refer to this table as the “baseline”. This section also provides information about the clinical data used in the study, as well as the order in which the visualizations were displayed to the participants. Finally, we explain the metrics used to analyze and interpret the results of the study in accordance with the insight-based methodology.

We propose the following hypothesis: a time-based visualization will enable clinicians to obtain valuable insights regarding the clinical condition of patients. A valuable insight demonstrates a complete and accurate understanding of the data. This understanding of the data is corroborated by the evaluation criteria used to assess the insight value. The criteria were designed and reviewed by subject matter experts. Valuable insights will translate to better patient diagnosis. This in turn will result in better decision-making processes thereby improving patient outcomes.

Health timeline

The Health Timeline was designed to provide a simple and interactive way to review a patient’s medical history using a time-based visualization. For healthcare professionals, the visualization software aims to assist in the decision-making process when assessing the overall status of the patient.

The Health Timeline is a cloud-based software that acquires data from the Medicare and Pharmaceutical Benefits Scheme (PBS) claims systems as part of Australia’s “My Health Record” initiative. These claims include a multitude of information as well as pharmaceutical aspects of patient data, including consultations, laboratory tests, in-patient admissions and other relevant information. The application handles the consent, sign up and compliance processes for using the clinical data. It has received conformance certification from Australia’s National E-Health Transition Authority (NEHTA) and the Commonwealth Department of Health for use with production servers and deployment in clinical practice.

Graphical representation and interactivity

The events in the timeline are grouped in adjacent rows. Each event is depicted as a box. The boxes are grouped in rows with labels on the left edge of the timeline. The events are shown at the corresponding start date position displayed on the horizontal axis. The width of the event box is adjusted to the corresponding end date. The group labels correspond to domains that are clinically relevant, for example medical treatments, visits to the general practitioner, psychiatric consultations and laboratory tests. Users can interact with the timeline by adjusting the displayed time frame (start and end dates). This is done by zooming in and out or panning left and right. Figure  1 shows an example of the Health Timeline portraying the clinical history of a patient.

Health Timeline. Timeline visualization showing the collection of EHRs of a patient used in the study

Design rationale and requirements

The rationale behind the design of Health Timeline is to provide a web-based (usable with any device with a web browser) visualization tool for clinicians to assist in the process of understanding the overall condition of a patient. The Health Timeline extracts information from EHR systems and presents the data in an interactive interface.

The design principles followed to develop Health Timeline were based on a simple and comprehensive visualization. In the “ Related work ” section, we identified similar visualization tools. These tools supersede the Health Timeline in terms of features and complexity. However, in this study, the participants did not receive an introduction or explanation on how Health Timeline software works, this was part of the intended strategy of the study. That is, to design and develop a simple yet comprehensive visualization that would require no introduction to clinicians. In other words, we aim to provide an intuitive visualization of clinical data that clinicians can understand without requiring training.

The Health Timeline builds on similar time-based visualizations and tries to address the challenge of representing data clearly and in a meaningful way without overwhelming the user with excessive details and complex interfaces. During the first assessment, the participants became acquainted with the Health Timeline visualization. In contrast, more complex visualization software, such as LifeFlow [ 18 ] or EventFlow [ 19 ] would probably require the participants to get acquainted with the tool before conducting the experiment.

The key requirements of Health Timeline came from Australia’s “My Health Record” initiative and were gathered from interviews with clinicians and Information Technology experts with a background in data visualization. These requirements are summarized as follows:

• Web-based visualization software
• Acquisition of data from Medicare and PBS
• Cloud-hosted application software
• A clean and simple user-interface. For the purpose of the study, no tutorials or explanations were given to the participants. This was done to “stress test” the design of the graphical interface.
• Interactivity for data exploration (time adjustment via panning and zooming)

Data representation baseline

The baseline representation of the clinical data is the current interface that clinicians have to the EHRs. The tabular data show in the baseline is the starting point of the study and contains the same information as the Health Timeline. The tabular data representation allows the user to sort the events chronologically, alphabetically, by document type and category. Figure  2 shows an example the tabular format representation of the baseline.

Visualization Baseline. The baseline visualization showing a set of EHRs of a patient used in the study

Insight-based methodology

The study documented in this article follows the insight-based methodology as proposed by North [ 7 ]. An insight is defined as “the capacity to gain an accurate and deep understanding” (Oxford, 2016). As presented in the literature survey, the most prevalent approach to evaluate clinical data visualization is to conduct briefing interviews or to measure the performance of the user conducting a set of predefined tasks. By contrast, the insight-based methodology focuses on recognition and quantification of insights gained from exploratory use of the data visualization. In the context of this study, an insight is a unit of discovery based on observation [ 8 , 9 , 21 , 22 , 24 ].

Insights have a quantifiable value based on the assessment criteria. The proposed criteria take into consideration the following characteristics of an insight [ 7 , 8 , 21 – 23 ]:

• Observation : The observation or finding provided by the participant during the process of analyzing the data via a representation.
• Time : The amount of time taken to reach the insight.
• Domain Value : The value, importance, or significance of the insight.
• Hypotheses : Some insights enable users to identify a new relevant hypothesis.
• Directed versus Unexpected : Directed insights are those that answer specific questions. Unexpected insights are those that were not considered in the design of the study.
• Correctness : Insights can be correct or incorrect depending on the data represented in the visualization. Some insights are incorrect conclusions that result from misinterpreting the data visualization. For our study, the insights formulated by the participants need to be clinically valid assessments on the patient’s condition.

Time, domain value, hypothesis and correctness are characteristics included in this study. We did not compile a set predefined of insights that the participants were required to formulate. Instead, the focus of the study was on allowing the participants to explore the data and formulate observations freely. This was designed to simulate the typical use case in which a healthcare provider is presented with a patient history and has to become acquainted with the data in a short span of time before the consultation. Therefore, the directed versus unexpected characteristic was not used in our study.

Domain value criteria and insight value coding

General Criteria: The domain value of an insight is determined using a five-point Likert scale as suggested in the methodology [ 7 ] and applied in previous studies [ 8 , 9 , 21 – 23 ]. The value depends on the insight’s complexity and depth. An insight is complex if it can associate more than one element in the data by providing a relationship or association between them, for example; “if “a” increases then “b” decreases”. The depth is the degree to which the underlying reasons behind the data are explained, that is, a plausible explanation was given that could justify the state of the data. For instance, an explanation for values outside of the recommended range for certain physiological measurements could indicate the presence of a disease. In our study, we recognized that additional refinement was needed for the evaluation criteria used to assess the insight value, due to the complexity of the data.

Longitudinal Nature: Previous studies focused on the visualization of “static” data. The data used for this study was essentially chronological since it was comprised of clinical histories of psychiatric patients. The medications, appointments, inpatient and outpatient treatments were all visualized over time for the duration of the clinical history. Therefore, suitable criteria should evaluate the insights considering the temporal nature of the data.

Criteria Formulation and Review Process: To determine the insight value, we applied the complexity and depth criteria as used in previous studies. However, as the Insight-based Methodology had not been previously applied in this context and lacked a precedent, to overcome this limitation, we asked two professional psychiatrists to assess the usefulness of the insights using a five-point Likert scale.

The consulting psychiatrists analyzed a sample of 100 insights (extracted from the assessments made by the participants) and evaluated them according to what they considered informative and helpful in understanding the patient’s condition. The consulting psychiatrists were acquainted with the data and thus were able to understand the underlying condition and overall health of the patients. The insights provided to the consulting psychiatrists included the patient identifier number and the text transcribed manually from the voice recording. This allowed them to have a reference to the original data to objectively determine if an insight was accurate and meaningful in understanding the medical history and clinical condition of the patient.

Agreed Criteria and Value Coding: The result of this process was a set of rules that enabled us to systematically and consistently assign a numeric value (domain value) to the insights. For example, an insight with a value of one, describes an event in the timeline without associations to other events or without possible explanations for the causes behind the event. Examples of these insights are: “the patient has an elevated heart-rate” or “the patient is taking medication for diabetes”.

Insights that describe associations of events regarding their frequency, pattern and irregularities were evaluated with two points. These insights connect multiple occurrences of similar events and show that the clinician can track down a pattern. For example, insights like “the patient has regular appointments with a General Practitioner” or “the patient is taking a high dose of the medication with regular frequency”. These insights have a time component as the participant identifies a regularity or irregularity in their occurrence.

The insights that include theories that could explain some or all the symptoms and thus the reasoning behind a prescription, or a specialist appointment, were evaluated with three, four or five points depending on how much information they could combine to produce a valid clinical statement. These insights could be considered a hypothesis and could explain valid clinical scenarios that result in drug treatment, laboratory tests, specialists’ visits and in-patient treatments. The following insight provides an illustration: “the patient has experienced depression and anxiety, that would explain the prescription and regular use of the drug treatment and also visits to the specialists, this also ties together an emergency episode in January 2013 and another admission in June, overall the patient’s mental health improved towards the summer and it seems that changing the drug treatment improved the outlook”. Table  1 summarized the criteria for each value with examples extracted from the transcription of the assessments.

Criteria used to determine the insight value

Examples are provided from the insights we obtained during the study

Thinking aloud process

The insight-based methodology recommends two mechanisms to record the insights, the “thinking aloud process” and the use of a written diary to record the steps taken during the data analysis. We aimed at making the participation in the study as simple as possible since the participants were professional psychiatrists with busy schedules. For this reason, we opted to use the “thinking aloud process” and capture the insights, comments and other statements via phone calls and recording software. We later transcribed the recordings manually to proceed to the analysis stage of the study.

The “thinking aloud process” is one of the most common techniques in usability studies [ 26 ]. It consists of asking the participant to verbally express the thought process while using the system under testing. In this study, we asked the participants to follow a link received via email and once they were ready to begin, they called a number and started the “thinking aloud process” of verbalizing their thoughts as they explored the data. This was an effective and convenient way to conduct the study since the participants had the freedom to conduct the assessments at their convenience.

By using the “thinking aloud process” we were able to capture the actions the participants were conducting during the assessments, for example scrolling, panning and zooming to a particular time frame.

Clinical data

De-identified patient data used for the purpose of the study was obtained with consent from mental health patients with various psychiatric disorders [ 27 ]. The patients were either outpatients seen in clinics in rural South Australia (77) or patients reviewed in an urban hospital emergency department (63). Ethical approval for the study was obtained from the South Australian Health Ethics Research Ethics Committee and the Medicare Australia Ethics Committee. Each patient gave written consent to use their data for research purposes. From the pool of 144 patients, the de-identified data of five patients was selected for this evaluation based on the complexity of diagnosis and treatment.

Patient data selection

The patient selection was based on the complexity of the diagnosis. All five cases had a diagnosed mental disorder and received continuous care and monitoring throughout their treatment. Three cases had in-patient episodes. A fourth patient was compliant with the treatment and the disorder was managed throughout the recorded period. A fifth patient had substantial changes in overall mental health.

Clinical data included in the study

The selected data included Pharmaceutical Benefit claims, Medicare Benefits claims and hospitalization dates over 3 years between 2012 and 2014. The data also included visits to General Practitioners, specialists, laboratory tests, emergency hospital admissions, drug treatment, among other categories. The claims records were sourced from Medicare Australia and hospitalization events were sourced from SA Health. Australia’s Pharmaceutical Benefits Scheme (PBS) contains information about the type of medication, amount of medication supplied, and the date of supply, while the Medicare Benefits Scheme (MBS) contains information on tests and services by Medicare eligible practitioners and the associated date of the service. The PBS and MBS measures were relabeled into clinical terminologies by psychiatrists involved in the project. The data used are considered a clinical history of a patient as part of the EHR.

Experiment protocol

The participating psychiatrists received written instructions on how to conduct the assessments. The instructions contained 10 web links used to access a web portal that displayed the patient data. Five assessments were conducted with the Health Timeline and another five with the tabular format. The web links displayed one patient data set at a time in either representations.

A log-out timer was set after accessing each link. This was done to provide the psychiatrist with three minutes to analyze the available information and formulate insights. Subsequently, the psychiatrist was automatically logged out of the system and the assessment session was concluded. The psychiatrists accessed the links with their personal computers and thus they were familiar with the browser and operating system of their choice. The psychiatrist’s observations during the assessment sessions were recorded on an answering machine over a phone connection.

As in previous studies [ 8 , 9 , 21 – 23 ], the assessments were transcribed from the recorded sessions. The transcriptions were annotated with the times at which the insights were mentioned by the participant. The insights were evaluated using the previously specified criteria.

Visualization presentation and order

All five patients were presented with both visualizations to account for control. The display order was controlled to first show the Health Timeline and direct any bias towards this visualization upon starting the assessments. There was no introduction or instructions given to the participants on how the Timeline works. The idea was to build a visualization that would be intuitive from the start.

The participants conducted the same assessments independently. The participants were asked to make one assessment at a time. The order was the same for all the participants. Each assessment featured the clinical data of a single patient. The patient clinical data was presented to the participant twice, one time in tabular data and another in the Health Timeline visualization. The participants conducted a total of 10 assessments, 5 with the Health Timeline and another 5 with the tabular data. The visualizations were alternated throughout the study. The first assessment used the Health Timeline, the second tabular data, the third Health Timeline, the fourth tabular data and so on. The order of the patients (clinical data) was also controlled so that no consecutive visualization would show the same patient data.

Time constraints

The experiment was intended to be performed by clinicians. As such, time was a major constraint. Empirically we have observed that taking no more than 30 min of their time would be ideal. Keeping each assessment to no more than three minutes was considered to be short enough for them to be willing to take part in the experiment. The 30-min time frame was determined by the three-minute duration of each assessment, a total of 10 assessments which showed the clinical data of five patients with both visualizations, Health Timeline and the textual data. Additionally, we allowed clinicians to take the assessments at their convenience, so if a clinician was able to spare three minutes, then that would be enough to conduct one of the 10 assessments.

Sample size

A total of 10 psychiatrists were invited to take part in the study. Five of them accepted the invitation. Each participant conducted a total of 10 assessments, 5 with the Health Timeline and 5 in textual data. The presentation order was the same for all participants.

Participants

We recruited five professional psychiatrists to participate in the assessments. The participants had experience in the field and had previously worked with similar patients as those used in the study. The participants also expressed their written consent to participate.

Data analysis

A total of 121 min of audio were transcribed. The transcribed text for each insight was organized using a spreadsheet that included the patient identifier, the participant identifier and the time at which the insight was mentioned. The data set produced was saved as a comma separated value file for further analysis and contained the following attributes (Additional file  1 ):

• The experimentId refers to the sequential identifier number of the assessments.
• The patientId refers to an identifier created for the sole purpose of this study and is used to link together the assessments with the de-identified patient data. The identifier does not contain clinical or personal information.
• The assessmentId refers to the assessment during which the participants used either the Timeline or the baseline to conduct their observations.
• The visualization refers to either the Health Timeline (referred to as timeline) or the baseline (referred to as table).
• The time refers to the time at which the insight began to be voiced by the participant. In some cases, multiple insights share the same starting time indicating that they were given by the participant during the same sentence (thought process).
• The insight refers to the textual insight as transcribed from the audio.
• The value refers to the domain value of the insight which follows the criteria detailed in this article.

As in previous studies [ 8 , 9 , 21 – 23 ], we analyzed the data and applied the following metrics to evaluate the data representations:

• Metrics per assessment : For each assessment we calculated the average number of insights, as well as their average and cumulative value.
• Number of insights : the total count of insights across all the assessments. We also counted the number of insights separated by their value (from one to five points).
• Time to first insight : the time required by the participant to formulate the first insight regardless of its value. Additionally, we also calculated separately the insight time for each of the values.

Statistical tests

Mann–Whitney–Wilcoxon (MWW) was used to calculate the statistical significance of the metrics per assessment and the time to first insight since they are not normal distributions. MWW is the recommended method for these distributions [ 28 , 29 ].

The statistical significance of the total number of insights was calculated using standard Chi squared because the two populations could be treated as categorical data. The insight value corresponds to the categories, the values are discrete from 1 to 5 using a Likert scale. Therefore, the statistical significance can be obtained with Chi squared [ 29 ].

The participants completed all 50 assessments per the protocol. The total duration of resulting recordings was 78,783 s, mean and standard deviation was calculated for the distributions (69.47 μ ±51.63 σ ). The recordings resulted in 1,134 transcribed insights (per participant 22.68 μ ±9.70 σ ).

Metrics per assessment

The collection of insights was analyzed to calculate the average number of occurrences, the mean and cumulative value for each assessment. Figure  3 illustrates, using box plots, the difference in the metrics per assessment and Table  2 summarizes the characteristics of the distributions such as the minimum, maximum, mean, median and standard deviation.

Metrics per assessment. The box plots represent the number of insights, mean and cumulative value of the insights per assessment

Metrics per Assessment

The table shows the insights generated by participants using Health Timeline and the visualization baseline per assessment. Statistical significance is shown in the p column using Mann-Whitney U tests

The distribution of the number of insights per assessment was not statistically significant, with the Timeline having an average of 22.32 insights compared to the baseline with 23.04 ( p =0.7047). The mean value with the Timeline (1.70) was higher than the baseline (1.26; p =0.01). Similarly, the cumulative value with the Timeline (34.68) was significantly higher than the baseline (24.96; p =0.01).

Number of insights

The value of each insight was collected from the dataset. The distribution is shown in Table  3 as a total count of insights by value. The total distribution of insights was not statistically significant. The Timeline (558) had a lower count that the baseline (576; p =0.7). Table  4 shows the characteristics of the value distribution. The average and median insight value with the Timeline ( μ =1.0833; Md =1; σ =±1.10) was higher than the baseline ( μ =1.55; Md =2; σ =±1.25; p <0.01)

Insight Distribution

The table shows the distribution of the insights according to their domain value. The ratio column shows the observations of the Health Timeline divided by the baseline. The p -values are obtained using Wilcoxon Signed-Rank Test

The table compares the distributions showing the minimum, maximum, median, average and standard deviation of the two populations, in this case these are the Health Timeline and the baseline representation

The statistical tests were conducted with Chi-squared since the populations can be treated as categorical data (value 1 to 5 each comprise their own category)

Table  3 shows that the distribution was statistically significant for insights of value 1 ( p =0.03), 2 ( p <0.01), 4 ( p <0.01) and 5 ( p <0.01) but not for value 3 ( p =0.53). Insights of value 3 or more demonstrate an understanding of the data that can detect patterns. A total of 81 insights were observed using the baseline compared to 118 with the Health Timeline. Additionally, only 7 insights of value five were generated and all occurred with the Timeline.

Time to first insight

The average time at which the participants formulated their first insight was analyzed. Figure  4 shows the distribution and Table  5 shows the calculated values with their statistical significance. For insights of any given value, the Timeline was slower (13.16 s) compared to the baseline (7 s; p <0.01). Insights with a value greater than one and two were also slower with the Timeline (22.24 s and 51.21 s) compared to the baseline (20.36 s; p =0.14 and 40.01 s; p <0.01). For insights with a value greater than 3, the Timeline was faster (68.44 s) compared to the baseline (92.83 s; p <0.01). Only the Timeline was able to generate insights of value greater than 4 with an average time of 63.50 s.

Time to first insight. The box plots represent the time to first insight of any value, value 3 or higher and value 4 or higher

Time to First Insight

The table shows the mean and standard deviation of the time to first insight from any value to values 1 to 5. The ratio column shows the observations of the Health Timeline divided by the baseline. The p -values are obtained using Wilcoxon Signed-Rank Test

The insight-based methodology applied to this case study, provided an approach to quantify the degree to which a visualization tool assisted the process of understanding longitudinal clinical data. The design of the study enabled us to investigate the usefulness of a visualization in a real-world environment with medical doctors as participants of the study (domain experts and the intended audience for the visualization software).

The high number of low value insights from the baseline visualization could be partly explained by difficulty in putting together smaller units of information contained in each row of the tabular format. This, in turn made it difficult to derive deeper and more complex insights leading to a hypothesis. In contrast, the Health Timeline assisted participants in generating higher value insights at the cost of a longer time delay. Health Timeline could have encouraged the participants to take a more “deliberate” approach when making decisions about the data, which was in turn reflected in the insights derived during the assessments.

Possible generalization of the results

It can be said that in the context of longitudinal clinical data, a time-based visualization of chronological events assists its audience better than textual information. In this context, the data visualization assisted the participants in gaining a greater understanding of the data (complete and accurate). In some cases, clinicians were able to understand the clinical history of the patients, formulate a diagnosis and suggest treatments.

This study shows the need to use a structured assessment methodology in the context of healthcare to determine the extent to which a visualization can assist clinicians to understand data. Without an objective assessment, it becomes subjective to state with confidence that one visualization is “useful” or “better”. Lam and colleagues [ 25 ], as well as Bertini and researchers [ 20 ] also emphasize the importance of structured assessment methods to evaluate data visualizations. This study also serves as a documented example of a contextualized assessment of visualizations in order to provide a use-case evaluation that is based on a real-life scenario. Even though the results of this study are encouraging, a larger study is warranted to examine objective outcomes and the impact that clinical data visualization may have in patient outcomes over longer periods of time.

Limitations and considerations

To facilitate participation in our study, we applied the insight-based methodology with the “thinking aloud process”. All the audio recordings were transcribed for evaluation. The sample size and the clinical data used in this study required a large number of working hours for the transcription and evaluation of the insights. Increasing sample size or participants would improve representativeness and statistical reliability of the results but at the cost of a greater number of hours, which was outside our resources, unfortunately. Therefore, the generalizability of this study may be limited, and further studies would be desirable to confirm our findings.

Another limitation of the study was the time available to conduct the assessments. Even with the relatively brief time window of 30 min, we failed to recruit more subjects. This could probably be explained by the busy schedules of the psychiatrists.

The evaluation criteria, even though revised and peer-reviewed by domain experts, could also be subject to bias. A larger group of domain experts could provide more objective criteria. It is possible that experts that were not acquainted with the data might have provided better evaluation criteria, as these experts would have a fresh look at the clinical data without preconceived notions.

Given the results obtained in this study, we propose a further study to test if the visualization can assist a larger group of experts in providing higher quality of care to patients. Such a study would require a larger number of participants, a larger number of patients with the required ethical approval and a randomized controlled trial.

Clinical data in a real healthcare context

The clinical data used in this study did not include diagnoses and notes taken by the practitioners during previous consultations. This was deliberate to allow the participants to come up with their own conclusions and assessments.

In a real life scenario, practitioners would have access to the diagnoses, notes and observations made by other clinicians. For the purpose of the study, we did not want to include this information to test the effectiveness of the visualization. The insights formulated in the assessments were our measurement to let us know the degree to which the participants were able to understand the clinical data without any previous information. We acknowledge that this is not an entirely realistic scenario however, for the purpose of the experiment, it allowed us to understand the usefulness of the visualization.

The clinical data was comparable to the reality of the healthcare context because it was extracted directly from real patients. In terms of complexity, we selected patients with a high degree of complexity of their treatment, in-patient events and diagnosis to base the study on complex real-life scenarios.

This study detailed the assessment of a time-based EHR visualization software by applying the insight-based methodology. The results show that the Health Timeline data visualization tool supported the generation of valuable insights following the proposed criteria. Furthermore, the use of the assessment method demonstrates the feasibility of applying a consistent methodology to assess visualization techniques and tools in the clinical context. We propose that the insight-based methodology could be used in future studies as a methodological approach to assess the value of a clinical data visualizations.

Additional file

A comma-separated values data file containing the transcribed insights, with the annotations used for the study. The file is in a standard format and is machine-readable. The annotations of the file are detailed in the “ Data analysis ” section of this article. (CSV 24 kb)

Acknowledgements

This research work was supported by VTT Technical Research Centre of Finland and the EU program for Research and Innovation Horizon 2020.

Abbreviations

Authors’ contributions.

AL conducted the data analysis including the transcription of the audio into the machine-readable file. AL applied the insight-based methodology to obtain the domain value of the insights. ME, NB, JS, GS and AL designed and agreed on the criteria for the insight domain value. ME, NB and AL conducted the statistical tests. HN and IK provided counseling and feedback on the study methodology and the article writing. NB developed the Health Timeline. JS, GS and NB designed the Health Timeline. ME, NB, JS, GS and AL designed the experiment protocol. JS, GS and NB facilitated the de-identified clinical data. All authors have read and approved the manuscript.

VTT Technical Research Centre of Finland has funded the design of the study, collection, analysis and interpretation of data. The writing of the manuscript was funded by the EU program for Research and Innovation Horizon 2020 under the Grant Agreement number 689260.

Availability of data and materials

Ethics approval and consent to participate.

Ethical approval was obtained from the South Australian Mental Health Observatory (MHO). Each patient gave a written informed consent to use their data for research purposes. MHO is currently undertaking a study, the “SPARK Study - A project of Mental Health Observatory”. The de-identified patient data used in the study was obtained with the informed consent of the patients through the SPARK study [ 27 ]. Consent for publication was also obtained from the South Australian MHO under the SPARK study. Additionally, the data published in this study is comprised of clinical observations, or insights, made by psychiatrists as a result of examining de-identified patient information. These insights are also approved for publication by South Australian MHO.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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• Essay on Management

Establishing A Timeline Case Study

Type of paper: Case Study

Topic: Management , Time Management , Project , Time , Path , Chart , Delay

Published: 11/15/2019

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1. PERT (Performance Evaluation and Review Technique) chart is a visual tool, which helps to create a formal project timeline. It lists all the necessary resources, sequences activities (vectors) and indicates milestones (nodes). Therefore, the chart gives a good overview of the project, allowing tracking the overall progress and meeting deadlines.

PERT chart also helps to identify the critical path of a project, the path, which determines the shortest time needed to complete the project. Whenever a deviation from the plan occurs, managers should pay most attention to the problems along the critical path. Once those activities are delayed, the whole project won’t be able to be completed on time. All the activities outside the critical path usually have so called “slack time”, which means that it is possible to delay this activity for some time, without affecting the whole duration of the project.

2. As step B is a part of the critical path, it is important to give its timely completion the highest priority, as it can delay the whole project. For activities C and D there should be some slack time, which gives an opportunity to complete the project on time even if C and D are delayed. Therefore, repairs in B should be taken up first, followed by C and D.

3. Repairs in C and D are prioritized based on their impact on the whole project flow. Whichever step requires a delay longer than its slack time should be started first, in order to avoid costly project delays.

Carpenter, C. (2006). Real world project management. Success Solutions Press. Envision Software. (2009, April 10). PERT diagram and CPM. Retrieved from http://www.envisionsoftware.com/articles/Pert_Chart.html

Luecke, R. (2004). Managing projects large and small. Boston, MA: Harvard Business School Publishing Corporation.

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