Our persona interviews surfaced an important commonality: the users’ jobs were incredibly detailed and “in-the-weeds.”  The interfaces of the old system were cluttered with numerous fields and excessive information, overwhelming users. Each time challenged their need to see all of those fields, they reiterated that the inclusion of all fields was necessary. We would need to find a way to reduce cognitive load without removing content.

Our research surfaced challenges around managing daily work:

• Delegating work was not always cut-and-dry. Some of the teams interacting with the system were fairly large, and most often, multiple eyes were required on the same order, specimen, or patient. Resolution of issues required for phone calls, emails, notes, and cross-system usage. Users always needed multiple tabs open, to reference other systems.

• Many of the issues needing resolution were complex in nature and often required multiple users with their own knowledge and background information.

• Much of the time spent by users was focused on painstakingly tracking down orders or patients, like a bad treasure hunt. For example, users would be forced to use the slow and clunky filtering capabilities on the old system to open multiple tabs to see if they offered the right set of characteristics for the user to accomplish their tasks.

• The highlight use-case for the order management system was that users needed to manage their daily work by looking for active orders that had similarly related problems. This approach helped them cognitively address the same “chunk” of problems within a period of time.

Navigation offered by the old system was intuitive, as though an afterthought.

Our UX team was able to learn a lot and seek guidance from Carbon’s thoughtful navigation guidelines. We later brought this thinking into a few simple, yet promising navigational improvements.

1. Re-focusing patient architecture, lists, linking

Adaptive aims to be a patient advocacy organization. There is immense business value in orienting the user experience around any opportunity to clarify patient information.

We discovered the following pain points for users viewing patient data:

• Patient Details pages lacked real-time information about Orders and Specimens.
  We discovered that this information lived at the heart of inquiries by our customers (Clinicians offering clinical care for the patients.) Ie. users had to search for a list of orders relevant to a patient open all those orders in separate tabs, and then cognitively distill an overview of the most recent issues, orders, and statuses.
   

• Patients often showed up as duplicates in the system.
  Due to easily made human errors of birthdate or name-change discrepancies, one patient might end up in a fragmented display of duplicate records. These were high-priority issues that our analysts had to address.
   

• Information architecture was oriented around Orders, not Patients.
  If a physician called in curious about the status of clinical care for one of their patients, there was no quick view in the old system to provide that information.
   

• Clinical trials offering de-identified information had no way of linking to Patient information that was already in the system. This implication on the patient's end was painful: they would have to take multiple blood or bone marrow samples to provide the same information, over and over again. Knowing that the information was in the system but simply lacking the wiring to connect – this highlighted a high-priority concern.

Historically, the molecular biology laboratory at Adaptive, which handles specimens and samples for clinical diagnostics (Dx) and clinical trials research, has used varied terminology and labels across its systems. The data transfer between these systems is nuanced and complex. To streamline this, a significant reorganization effort was undertaken to simplify system labeling and clarify the parent-child relationships among specimens, samples, shipments, and orders. A key outcome of this effort is the introduction of "Flags," a feature designed as a catch-all indicator for any significant events affecting an order throughout its lifecycle. While "Flags" is detailed in a previous chapter, it also plays a crucial role across data tables, alerting users to any flagged orders, specimens, samples, or shipments that require attention due to alerts or discrepancies before they can proceed in the processing pipeline.

We discovered the following needs for an improved treatment of Specimens and Shipments:

• The users of the New LIMs Ecosystem at Adaptive require a unified approach to manage specimen samples and shipments across multiple software systems. 
   

• Within the order management software, it would be critical for Clinical Services to receive timely updates once specimens complete the intake process and are ready for the resolution of any flags that may arise during the shipment receiving or intake phases.
   

• Users would require a centralized interface for updates and data, rather than being forced to navigate multiple siloed sources like Salesforce and Tableau. This fragmentation complicated workflows and hampers efficiency, highlighting the need for a more consolidated, integrated approach to data management and notification within the ecosystem.

The new Order Management System (OMS), used by various customer-facing teams was lacking the contextual tools necessary for understanding:

• order statuses, 

• issues and 

• assignments.

Additionally, leadership faced challenges in gaining deep insights into critical metrics like:

• Revenues, 

• sales, and 

• incoming orders.

Please read on to discover our recommendations for the findings we’ve described in this last section.