How to prevent medication delays and errors in high-pressure hospital environments?

Enhancing medication request control panel

Enhancing medication request control panel

About the client

The client is a healthcare institution managing a high-volume inpatient care system. Their legacy software included a drug request tracking table used by medical professionals to monitor medication orders and interventions for hospitalized patients. However, the existing interface suffered from poor readability, fragmented data hierarchies, and an inability to accommodate evolving workflow needs, leading to delays and potential errors in patient care.

The original table for medication control

The original table for medication control

The original table for medication control

The challenges

Medical professionals struggled to efficiently interpret medication requests due to critical design flaws:


Unclear Information Hierarchy

  • Statuses (Pending/Resolved) and request types (Critical/Non-Critical) were nested in complex column structures, forcing users to scan horizontally and vertically to extract key details.

  • Redundant symbols (e.g., "○") and inconsistent alignment added visual noise.

Time-Critical Decision-Making

  • Professionals needed to quickly identify urgent requests but spent excessive time parsing the table.

  • Ambiguous icons (e.g., clocks for statuses) required additional cognitive effort to interpret.

Inflexible Data Presentation

  • The table could not accommodate new request types (e.g., Extra Orders) or statuses without further cluttering the interface.

  • Detailed drug statuses were displayed upfront, overwhelming users with unnecessary information.

Information architecture: They needed to add two more states to the data table

Information architecture: They needed to add two more states to the data table

The Solution

A three-layer medication dashboard surfaces urgent requests first, hides non-critical details in expandable cards, and uses intuitive icons for clarity. This design eliminates data noise, cuts reading time, and lets medical staff prioritize patient care—not decipher chaotic tables.

The process

Redesigning the Table Structure


Three-Tier Information Hierarchy:

  1. Total Requests: Highlighted the number of medications per type (Critical/Non-Critical/Extra Order).

  2. Request Type: Grouped by urgency for quick scanning.

  3. Status Details: Hidden behind expandable cards to declutter the main view.


Visual Streamlining:

  • Replaced ambiguous "○" symbols with dashes ("-") for empty states.

  • Right-aligned numerical data and added color coding for faster recognition.

Request Type: Grouped by urgency for quick scanning, and move the status at the level of the medication

Request Type: Grouped by urgency for quick scanning, and move the status at the level of the medication

Introducing Contextual Details

  • Expandable Cards: Enabled users to view individual drug statuses (e.g., Submitted, Pending, Resolved) on demand.

  • Icon Standardization: Add intuitive symbols to reinforce status clarity.

Medication cards: Enabled users to view individual drug status.

Medication cards: Enabled users to view individual drug status.

Icon Standardization: Add intuitive symbols to reinforce status clarity.

Icon Standardization: Add intuitive symbols to reinforce status clarity.

Iterative Testing

Prototypes were validated with medical teams to ensure alignment with workflow needs, resulting in a 40% reduction in training time for new users.

The impact on the experience

By applying user-centered design principles and iterative testing, the transformed system now supports:


  • Faster decision-making through real-time data validation.

  • Simplified workflows that empower both new and experienced administrators.

  • Enhanced Focus & Accuracy: Achieved by eliminating context switching through a cohesive dashboard.

Key outcomes - Improved Readability and Clarity

Key outcomes - Improved Readability and Clarity

Key outcomes - Improved Readability and Clarity

Request identification

100%

Faster

Professionals could identify urgent requests in seconds rather than minutes

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