Intelligent Rx
An analytics platform for a pharmacy drug-safety alerting service
Project Synopsis
An analytics platform to help the pharmacy team at a health insurance company better understand the performance of a drug-safety alerting service
The Problem
The pharmacy team at a Fortune 50 health insurance company was using an alerting service to protect members from prescriptions that could be harmful.
When a member visited a pharmacy to pick up a prescription, the service would alert the pharmacist to any conflicts.
If rules were overzealous, they could be producing negative customer experiences (like turning a patient away that could safely benefit from the medication). They needed a way to measure the impact of rules on their 14,000,000 members.
Goals
- An internal, web-based tool allowing the team to better understand the outcomes of the drug-safety rules
- To better understand impact of alerts on members
- Reduce outdated sharing methods of static documents and spreadsheets
- A single “source of truth” to share results with other teams and external auditing groups
Process & Contributions
- Conducted product discovery discussions with pharmacy team and Product Owner
- Defined functionality goals, roles and personas to guide user stories
- Created user story/workflow maps highlighting rule authoring, intended outcomes and areas needing illumination through reporting
- Created wireframes of initial features and workflow
- Created interactive prototypes in HTML/CSS - Code was integrated directly into Angular templates
- Conducted usability-testing sessions
Outcomes
- A simple, responsive web-based analytics platform to help the pharmacy team understand impact of rules and improve member experience at the pharmacy
- Eliminated long delays in results collection from pharmacy benefits management service - drastically reducing time spent on information collection for auditing groups and other teams
- Reduced network and shared drive clutter and need for historical document archiving
- Tool is trusted by outside auditors as a source of truth regarding how drug-safety rules are performing and protecting the member population
- Project was delivered within budget and on-time. Part of this was due to rapid exploration and iteration processes (focusing on MVP)
- The pharmacy team is delighted with the tool and is eagerly discussing features of phase two with Product Owner
What I Learned
- Using layout code as our prototyping process reduced design asset to code translation time and energy. It also moved a portion of development time to the design process. In retrospect, we could have used more prototyping tools like Sketch for initial testing and coded product templates later in the project.
- Collaboration with dev team doing sample queries based on user story maps allowed us to design components and information displays more accurately. There were no surprises during implementation phases.
- Simpler language around drug concepts were rejected by the pharmacy services team. During initial user testing phases, I realized they used very data-specific language as a business unit. Product language evolved to reflect their technical business culture.
- I learned a lot about insurance practices around prescription fulfillment and probably more than I wanted to know about First Databank (FDB) Drug data :)
- It was rewarding to work on a project that ensured the safety of 14,000,000 people!