A Guide to User-Centered Healthcare Software Design and Development

UX Research Dimensions

In this section we uncover and give a high-level overview of some of the key research tools available for uncovering user requirements, pain points, and their overall experience. To successfully pick the right research technique, you should already know the goal for the research (what problem you want to solve, or what question you need an answer for). Each research technique has its pros and cons. To successfully find your answer and deliver true usability with your app, you may find the best solution is to combine more than one research technique. This will allow you to better interpret the data and deliver meaningful answers. Often a blend of qualitative and quantitative techniques results in the most success in understanding your customer and it is also recommended if you’re seeking certification.

Tip: Certification Requirements

When considering the research methods you will use during your development process, don’t forget to think about certification requirements (ISO requirements or Meaningful Use Stage 2 or 3). Certain certifications require different types of research and reviewing those requirements and what is required for reporting to obtain certification prior to starting will help you during your design process and speed your way to achieving certification.

There are numerous other research techniques that are not mentioned in this chart that could also be used. For example: you could study user manuals and other existing documentation. They are often a good source of data about the steps involved in an existing activity and also highlight any regulations that could be governing the task. But tread with caution: Documentation like this should not be the only source of information as everyday practices may have been augmented to make procedures work in a practical setting. You’ll need to observe what really happens and compare and contrast that with the user manual.

Taking a user-centered approach means that you should be interested in the everyday practices rather than an idealized account. With that in mind, it also can be helpful to track down any analytics available on existing systems and processes and investigate customer support calls for any existing software.

When considering your application and your users, it’s important to think about the questions you have about its design and use and review the available research techniques. Regardless of the technique you choose, that process will bring you one step closer to better understanding who your user really is and what they really need to accomplish within your app.

Taking a user- centered approach means that you should be interested in the everyday practices rather than an idealized account.

This chart also can help you determine the right research technique. It illustrates how the dimensions affect the types of questions that can be asked, and that may help you narrow down where you need to start. For example, qualitative methods are much better suited for answering questions about why (or how to) fix a problem, whereas quantitative methods do a much better job answering how many and how much type of questions.

Research Dimensions

Qualitative vs. Quantitative

Qualitative studies usually gather data directly whereas quantitative studies the data is gathered indirectly.


Answers the Question:


What kind of data is gathered?

Data is gathered by directly observing the user or interacting with the user. As
a result it is not easily parsed
or analyzed mathematically and can be highly subjective. On
the other hand researchers can easily ask follow- up questions, probe further on certain behaviors, and make adjustments to the study protocol on-the-fly.

Sample Data Gathering Tools / Methods

Focus Groups, Interviews


Answers the Question:

How Many? How Much?

What kind of data is gathered?

Data is collected in a consistent and formative way. It can often be analyzed mathematically.

Sample Data Gathering Tools / Methods


Attitudinal vs. Behavioral

This distinction can be summed up by contrasting “what people say” with “what people do”. There are methods that include a mix of attitudinal and behavioral data. They are generally best for understanding user behavior. For example: contextual inquiry


Answers the Question:

What People Say

What kind of data is gathered?

This is often called “self-reported data”. It helps
the researcher understand and measure people’s stated beliefs. Depending on the method, it could be mathematically analyzed.

Sample Data Gathering Tools / Methods

Questionnaires, Focus Groups, Interviews, Contextual Inquiry


Answers the Question:

What People Do

What kind of data is gathered?

The research reports on the actions users
take. This allows the researcher
to minimize the impact on the user of the method as much as possible (focus groups,
for example can be impacted
by group bias or group think), and begin to understand exactly what people do.

Sample Data Gathering Tools / Methods

Observation Contextual Inquiry


Conducting one-on-one interviews with your users is a simple and cost-effective way to gather data. Interviews can help you to better understand the user’s goals and needs by giving you a chance to obtain direct feedback from users. Semi-structured or unstructured interviews are often used to elicit usage scenarios. Whether structured or unstructured interviews should take into consideration the focus of your inquiry and what research questions you’re looking to answer (what you hope to learn). As well, you’ll need to understand time constrictions and access issues, particularly in healthcare when conducting interviews on-site can be impossible and access to quality time with doctors, very limited. All of this can impact the success of using interviews as a research tool.


Interviews are a great, personal approach to obtaining direct feedback from users and due to their iterative process (open- ended questions, ability to move beyond the initial base questions and delve into new areas approached by the user) offer the opportunity to probe in-depth on a user’s experience. This can yield rich data, critical details, and new insights.


Because interviews are so personal, you’re beholden to the skills of the interview and the content / results can be influenced by interviewer error or bias. Depending on how many users you have and the access you can get, they can be time-consuming and costly. Also, because the resulting data is fluid and can be unique to each user, connecting the dots and conducting analysis can be difficult.


An observation exercise is a technique where you observe actual users or representative users in their natural environment through the whole process of using a particular product or system. This technique is used to understand the nature of the tasks and the context in which they are performed.


Observation, because it gives you immediate access to the way users act and interact with the process, provides a deeper understanding of the users’ lifestyles, cultures, process, and workarounds. It gives a better understanding of their needs and problems, some of which they are not even aware of (workarounds can become so ingrained they can see them as a normal part of their day). Observation provides a collection of detailed, descriptive narrative data. It is a great technique for capturing environmental factors such as the context in which a product is used.


Some of the disadvantages associated with using observation as a research technique are actually the reason it’s successful: you’re conducting research in a work environment. This can be complicated in all industries, but particularly healthcare. Distractions are rampant, scheduling is a challenge, and privacy concerns can bar the observer from seeing the full process. As well, as there is interviewer bias, there is observer bias. The observer must be skilled in observation techniques, understand what they are seeing, and must remain as objective as possible so as not to influence the user and skew results.

Contextual Inquiry

Contextual inquiry is a method of research specific to usability knowledge. It combines a semi-structured interview with direct observation. It’s more involved, where users are typically first asked a set of standard questions and then they are directly observed in their environments and questioned during that observation. It’s much more direct “while you work” research. “Because users are interviewed in their own environments, the analysis data is more realistic than laboratory data.”

The Usability Body of Knowledge lists the four principles of contextual inquiry as:


Plan for the inquiry, based on a clear understanding of your purpose


Go to the customer’s workplace and watch them do their own work


Talk to customers about their work and engage them in uncovering unarticulated aspects of work


Develop a shared understanding with the customer about the aspects of work that matter

Ideally, the researcher should stay in the background and let the user lead the situation as much as possible (this minimizes skewing the results by influencing how the user interacts with the process).


Contextual inquiry offers a lot of insights for usability studies as it provides the opportunity to see what really happens and also allows the observer to clarify in context. It is a critical source of information for persona and scenario development.


One of the challenges with contextual inquiry is that the analysis relies on the capabilities of the observer. As with interviews and observation having a skilled researcher / usability expert is essential. As well, in healthcare, the ability to conduct an intensive, in the workplace study such as this can be difficult. Time, privacy restrictions, etc., can impact the ability to gather a clear picture.


Questionnaires can be used for collecting data about preferences, behaviors, facts, latent traits, and attitudes.


Questionnaires are a cheap and highly effective way to quickly and conveniently collect large amounts of data. Particularly when users are busy and struggle to block off time (common in healthcare) or are in geographically diverse locations questionnaires can be offered in a portable format, even online, allowing the user to complete and submit at their leisure. They are exceptionally good when you need relative answers (better / worse). Plus, with correct standardized responses they can be analyzed and reported on.


Questionnaires, unless kept to highly simple questions, can be difficult to write. Many a study have been discarded when questions skewed responses. They also are limited in scope (people will not fill out pages and pages of questions), and are highly one-sided. If the questions aren’t clear, people will guess at an answer. Or if rushed they’ll answer quickly not truly thinking through their response. And as they are a one-sided research collection method, there is not opportunity to get more information on an answer to a specific question.

Focus Groups

We’ve all heard of focus groups. You put a group of people together in a room and have them provide their thoughts, experiences and/or perspectives around a product or service.

A moderator is present to guide the group and its interactions and focus the group to obtain information about a specific issue. Typically the focus group is composed of users / individuals with a common interest or set of characteristics to ensure the consistency of the information gathered.


Focus groups are great for providing attitudinal data, and can often be a quick and cost-effective way to get qualitative information. They’re collaborative and can encourage new insights or quickly offer a central pain point for a group of users.


Because focus groups include a group of users / people and are not a one-on-one conversation, participants react differently. Depending on personality types within the group, focus groups are susceptible to group think, or users may imagine their interaction with a product / service. It can be harder to then detect true patterns across individuals because the exercise does not allow for independent opinions. Focus groups do not provide quantitative information.

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