Use these digital health product development best practices listed by our experts in healthcare IT to develop simple, yet impactful user-centred products that will meet your customer’s needs and seamlessly integrate into their lives.
Whether you are figuring out your data science strategy, resolving interoperability issues, or ensuring patient and clinician engagement, the need for digital health software applications to be engaging AND solve an actual problem is at the core of its success. Healthcare is a complex domain with complex problems that require simple solutions – wait…what? Well, okay, maybe simple is not the right word. Having specialized in Healthcare technology, I have seen the same issues (over and over again) arise in projects which hinder product development success. To combat the development issues I repeatedly hear from product managers, I have highlighted the following 10 digital health software development best practices.
Solve A Meaningful Problem
This might seem obvious, but the MedTech sector is not immune to the “technology for technology’s sake” mode of thinking. Just because you can do it, and it’s really cool, doesn’t mean you should do it. This is best practice number one for a reason. If you aren’t solving a meaningful problem, then it doesn’t matter that you’ve taken items 2 through 10 below into account. You won’t be successful because users won’t use it. If you are confident you are solving a meaningful problem, great. Now you need to do it in a way that is far better than what people are currently contending with (like removing the “pain” from a task or providing the ability to do something they couldn’t do before). To do that, keep reading…
Think About The Big Picture
Everyone is focused on the product or service but are you paying enough attention to the ecosystem in which your product or service will exist?
Your product or service is likely going to do one or more of the following:
- Replace a current process/market/people;
- Interoperate with a current process/market/people;
- Fill a gap or;
- Completely disrupt the current space.
In all cases, having an understanding of the implications of these changes on the current ecosystem, as well as identifying key barriers or new opportunities, will help you make some necessary business decisions. One way to grasp a better understanding of your product’s ecosystem is through ecosystem maps.
Identify, Set, And Measure Success Metrics
Make sure everyone has a common understanding of what success looks like. Break it down, put some stakes in the ground and measure and track to ensure you are meeting the goals you’ve set. For example, if your product is going to decrease the time it takes to currently complete a task, improve medication adherence, reduce safety risks or improve outcomes, you need to set a measurable target (that is better than the current standard) and show that you are tracking towards achieving that throughout product development.
As much as you think you know your users, you probably don’t know enough. We’ve seen the best of intentions go awry because assumptions were made about target users and their requirements that were wrong. Research requires a deliberate, methodological approach to gain insights into user behavior and their needs and workflows, as it reveals both users’ articulated and unarticulated needs.
This can be done through contextual interviews and observations and other methods. This doesn’t mean that user research can’t be quick and agile. There are many approaches a qualified researcher can take to get information quickly to ensure you are building a product with the needed requirements. Oh and I probably don’t need to say this, but I will…unless you are designing an application for yourself, you are not the user!
Use The Research To Inform Product Design
You have spent the time collecting user requirements data, now USE it! So many times we’ve seen clients ignore or argue against the data they collected because it did not support their initial strategy. If you hear someone say “well I think…”, stop and ask yourself and others “is it supported by the data”? At this point, the researcher, designer, product manager, business analyst, and technical architect should be working together to translate the research data into requirements that will inform product vision, design, and development. Specifically, from a user experience perspective, this is where the designer takes the data about user needs, tasks and workflows to develop the information architecture, navigation, and high-level design concepts.
Validate, Validate, Validate, And Validate Again If Need Be
Always test your product in various states as you design and develop. Even the best designers in the world (and we do have the best designers) will get some things wrong. It is much easier and cheaper to fix and correct at an early stage. Again this doesn’t have to take a lot of time. Test early and often – don’t wait until you have a nearly finished product to discover there are major usability issues.
Look for opportunities to engage your user across multiple modalities and channels to support different contexts and abilities of use. We are at the stage where “mobile first” or “voice first” is obsolete. You need to think about which modalities make sense and support them in such a way that a user can move seamlessly back and forth between different systems and people.
Omni-channel design and development don’t just include mobile, voice applications or other forms of technology. A channel can be another person such as caregiver, social worker or physician.
Use Subject Matter Experts
Listen to them with regard to their areas of expertise to inform your product or service design. You presumably brought in designers, researchers, product managers, developers, and clinicians so they could all contribute expertise in their particular domain. And while yes, you want open collaboration across multiple disciplines, remember…designers are not doctors and doctors are not designers.
Model Your Product And/Or System
This could be by creating a prototype, simulating how it works with a statistical model, or building a technical proof of concept. Models are way less expensive to build, test, analyze and change than a full product. There are many ways of modeling or simulating a product or its interaction with the ecosystem.
Be Prepared To Change
There is no point in doing research, building models and tracking metrics unless you use them to make meaningful changes. Something about your product idea is bound to not work – no matter how much you might love it. When you use the steps above, use them to evolve your product based on data-backed evidence, not on beliefs.
The above-mentioned best practices are not groundbreaking and those of you reading now are probably thinking “I’ve heard all this before”. However, if I had a dollar for every time one or more of these best practices was overlooked or poorly executed, I’d be a very rich woman! These are core best practices – get them right and you’ll find your product/service in a much better position to achieve market adoption and success. These are table stakes. Ensure your organization is doing the above. No excuses!
Need a little guidance? Schedule a call today.
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