Adoption drives results. Following huge investments in EMR systems, we are all looking for the big pay-off. The results, controlling costs and improving outcomes, are why we made this collective investment. To drive results, we need to design a tool that truly works for our users–one they will adopt and bring into the fold of day-to-day decision making. Perhaps the instinctive use of natural language can connect users with their data.
Adoption is tricky, however. Analytics includes some fundamental differences from the IT projects healthcare organizations have engaged in to date. Analytics applications go well beyond supporting day-to-day transactions. New factors such as perception, attention and memory weigh much more strongly. Users arguably need to develop new ways of thinking, to formulate and explore hypotheses.
The technical challenges are no small obstacle, either. Teams can easily get lost in data wrangling, data quality and governance, not to mention simply trying to keep up with requests for data.
Cultural obstacles also need to be overcome. Analytics is comparatively new in healthcare. Data literacy and awareness need to be grown. Effectiveness of analytics applications to truly move the dial need to be proven. How to best leverage analytics for everyone across the organization may still ambiguous. Analytics programs must boost user confidence and raise the profile of analytics in their organization in a very deliberate way.
To design for adoption, we’ve learned a number of things over the years. Applications must be designed with a tight alignment to the daily, weekly and monthly goals of each user group. Too many applications simply present the user with ‘data trivia’ (and suffer low adoption rates as a result). The user interface and data visualizations need to be simple, elegant and visually-pleasing. If the user questions the professionalism of UI design, they will surely question the quality of the underlying data.
With the proliferation of artificial intelligence (AI) and natural language processing (NLP) tools (many available for free!), one of the most exciting developments to drive user adoption is the conversational interface. Healthcare providers, directors and managers are, above all, busy people. Language is how we communicate. Imagine (quite literally) asking your analytics application and getting an answer. We’re hopeful an ‘all talk and no buttons’ approach may represent a tipping point.
To get started, take a look at some of the multiple toolkits out there. These toolkits do a great job of laying out design principles for a conversational interface and leading you thru the steps of building and training your first bot.
Check out this Qlik Sense Bot (YouTube) from Michael Tarallo at Qlik which uses Qlik Sense and Narrative Science to create a conversational user interface wherein the user can request information via text or voice and have results returned instantly.
Not only does this offer a new approach to usability, it is yet another great example of leveraging Qlik as a platform. We’d love to hear what you are working on.
Come and meet Derek at the Axis Group’s booth (#701) at Qonnections 2017, to talk about driving success in your healthcare organization.
Derek got his start in healthcare informatics via graduate studies in linguistics and natural language processing. He has spent the last 13 years finding ways to help clinicians and other folks in healthcare provider organizations use electronic medical records and analytics to make healthcare better, faster and cheaper. When he’s not geeking out on healthcare analytics, Derek does yoga and surfs.