PrecisePK
Real-time Monitoring and Data-driven Analytics for Acute Kidney Injury Management
The Basics
Company
PrecisePK
Team
7 people
Time
4 months
My Role
Product Designer
The Problem
Acute Kidney Injury (AKI) is an abrupt decrease in kidney function, resulting in the renal failure to filter waste products from blood. AKI is commonly observed among patients suffering from serious infections disease that need antibiotic drugs, like Vancomycin. AKI can be fatal and leave permanent damage to the kidney. It develops rapidly, usually in less than a few days. It is crucial for hospitals to detect AKI responsively to patients' biomarker in real time and then perform retrospective analyses on their clinical practice to evaluate and improve their patient care. Therefore, our team was inspired to design a tool that would provide our users with real-time monitoring for AKI assessment and a dashboard with data-driven insights for retrospective quality evaluation.
Usere & Audience
The target users of PrecisePK are pharmacists working in hospitals who treat patients with infection diseases. Pharmacists usually work in a team with rotating shifts, and need to attend a number of patients. In their daily workflow, it’s a great challenge to detect AKI responsively to patient's changing lab results, prioritize patients most in need accordingly and perform institutional quality evaluation regularly. The traditional way done by manual documentation just doesn’t work swimmingly.
Team & Role
Working as the only Product Designer, I led a team with 7 core team members, collaborating closely with software engineers, in-house pharmacists and Sales & Operational team.
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I coordinated and led all facets of design including: design research, ideation, information architecture, use flows, UI/UX prototyping and testing. I also defined KPIs for this feature and broke them down to specific metrics and users actions to track in our program. I was provided internal training to other team members and worked closely with Sales team in marketing campaigns.
Process
In order to identify what and how this product needed accomplish, I started out with secondary research, learning from pharmacological guidelines and dosing protocols from multiple institutions to gain thorough understanding of the clinical context -- the possible causes, symptoms of AKI, and various widely adopted classification criteria. Then I conducted in-person user interview with our in-house pharmacists and sent out google survey to our valued customers to further uncover users needs regarding AKI management in hospitals.
After sifting through all of the resources, I was able to identify the key user needs: pharmacists wanted a real-time AKI assessment, and get the notification seamlessly in their workflow. They also desire retrospective analysis for insightful statistics that inform them the efficacy and quality of their overall dosing practices.
With the mission to help pharmacists perform better AKI management and ultimately improve patient outcome, I set up 3 Design Principles that became the overarching goals guided us throughout the project process.
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Insightful Information – provide comprehensive information relevant to AKI assessments and analytics to support clinical practice.
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Seamless and Digestible – provide meaningful statistics that are easily digestible and guide users to take further actions seamlessly.
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Customizability – give user options to choose the criteria & other relevant data that best fit to their workflows.
I ideated key specs that had to be included in this project, and prioritized these key specs in terms of how efficient they were in meeting users’ needs and how technically feasible to develop.
Based on the key specs, I constructed the information architecture applying the Model-Controller-View framework so that our developers would know which aspects of the application they should focus on and how they would be reflected onto user interfaces. Although there could have been more customizability that we could add to this feature, like allowing users to manually add an AKI event to the patient case based on their own judgement, but we decided to focus on the core jobs-to-be-done, which was to provide real-time, automatic AKI assessment to support clinical workflow. Besides, adding another layer of complexity would also significantly put off the deliver time of this project.
The Challenge
As I started to explore the interface and interaction design for the analytical dashboard, I encountered the biggest challenge in the process: After assessed the patients’ AKI status with patient biomarkers, how might we translate these unsorted data into meaningful statistics and visualize them into insightful and easily digestible infographics.
From research, 2 technical use cases were identified -- users were interested in running analysis based on 1) the incidences of AKI events and 2) AKI patients that are diagnosed. Our initial idea was compiling data into only 2 types of chart -- one line chart showing data changing over time, and a pie chart showing the ratios of different segments. But as one single patient could experience multiple AKI events at one or different stages during a period of time, we were struggling in defining the most meaningful way to group these data from backend and visualize them in these 2 types of charts to the user interfaces.
I brought everyone together to brainstorm an optimal solution. At the beginning we had lots of different thoughts throwing out —“we can only count patients by their latest AKI event”, or “let’s only count the severest events”, and later "we should also show the non-AKI patients..."
But none of the ideas satisfied us because either they didn’t provide much value to users or they actually contradicted to other features.
Early prototypes for infographics UI/UX Design
The Solution
While listening to them closely, I started to realize where the problem was: everyone was thinking of solutions mainly from a technical perspective — what kind of data we could pull up and what logic was most 'programmable'. The team was more like solving problems for ourselves instead of for our users.
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That was when I stepped out again. Acting as the voice of customers, I started writing down user needs/stories into simple clear statements, and then translating these statements into programmable logics.
For example, one statement could be like:
“In a given month, as a pharmacists, I want to know the number of patients at AKI stage 1, 2, and 3, and the total number of AKI patients within that month.”
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And to translate into statistic logic:
“if the patient has multiple AKI events at Stage 1, 2 and/or 3, then we count this patient 1 time in each stage (n_stage1 + 1, n_stage2 + 1..), but only count them once in the total number of patient (N+1).”
Keeping user needs as the core, I drove the decision that we should separate the two technical complex use cases and develop the most appropriate infographics for each, since the 'one-style-fit-all' pie chart would not address users' needs effectively.​
User Interface Design
Color coded tags indicating AKI status at different stage. Prominently showing these tags on Home page and allow advanced search to help pharmacists prioritize and coordinate care accordingly.
Automatically assess patient’s AKI status based on their lab results (SCr values) and individual patients characteristics, adhering to the widely adopted AKI classification criteria.
This assessment happens in real time and is seamlessly integrated to user's current workflow.
A customizable Filter that makes it easy to quickly generate analytics on data of interests.
Interactive and data-driven infographics that help users visualize patient data over time and over the overall population.
A table lists all selected patients based on the filters users have defined. Quick action buttons allow users to quickly further inspect specific cases.
The infographics compile patient data into meaningful visualizations and are truly interactive. The stacked line chart shows users an overview of how AKI Events at different stages change over time at their institutions, and the pie chart shows them each stage as a percentage of the Total AKI Events detected in the program.User can hover on the graph to read more detailed statistics in tooltips.
To account for the fact that single patient may have experienced multiple AKI events during their treatment, I designed a bar chart that compares the counts of AKI Patients at different stages and their ratios to the Total AKI Patients and to the Total Patient Population as recorded in the database.
Within the Patient Case List, "Quick View" button opens an overlay that gives user a snapshot of the patient's SCr history trend and how their AKI status changes over time. Users can also hover on the graph and then read the corresponding lab data and the time of AKI event. If user wants to inspect this patient case more, they can also Load Case directly from the table.
The Impact
Taking this user-centered approach, everything we designed and developed made great sense. Different elements on the dashboard could be complementary to each other and provide helpful insights to our users. We launched this feature in Mid October 2021, and the new release has led a great increase in traction to our platform, our daily site visiting increased 48%.
Next Steps
I believe defining the key metrics for success of a product is crucial for its growth. As the owner and the designer of this features, I defined its KPIs and the specific user actions we need to track to measure its success.
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More importantly, this project blazed a new market vertical -- Data Analytics, for PrecisePK, which had only focused on therapeutic drug monitoring before this. After proving the market opportunity in this field, now I am leading a new project to develop more powerful and comprehensive Therapeutic Analytics, which will then shed more lights for our users in evaluating and improving their dosing strategies.
