Polypharmacy judgment at scale

The platform analyses conditions, drug regimens, demographics and lab results to identify patients at risk of drug-related problems, then generates clinical recommendations. Whether those recommendations are accurate, adaptable and actionable is not a question an engineering team can answer internally — it requires the clinicians who would receive them.

The client's constraints were access to the right specialty mix, reviewers experienced enough to apply genuine clinical judgment rather than pattern-match, and an operation that could run the workflow without consuming their own team's time.

Matching five specialties to the clinical question

Primary care, cardiology, endocrinology, psychiatry, clinical pharmacy

Polypharmacy is not owned by one specialty. A recommendation that reads as sound to a cardiologist may look different to the psychiatrist managing the same patient's second prescription, and different again to the pharmacist reconciling both.

Medcase matched reviewers across all five, by sub-specialty and active caseload rather than by credential alone, and across a spread of ages and backgrounds.

Piloting the review workflow before production

 A small-scale pilot tested interface usability, refined the review protocol and confirmed that each case could be reliably evaluated in roughly 15 to 20 minutes. That timing figure set the economics of the full programme and gave the client a concrete preview of the output before committing to scale.

Three independent reviews per case

Every patient case was reviewed by three clinicians. One opinion on a medication recommendation is an opinion; three from different specialties is a signal, and the disagreements are often more informative than the agreements.

Medcase handled recruitment, onboarding, case distribution and time tracking, coordinating across time zones with structured incentives and responsive support, and delivered structured data reports throughout rather than at the end.

Follow-up interviews for qualitative insigh

Ten follow-up interviews were conducted with participating clinicians. These surfaced the reasoning behind the written reviews — the part that structured forms do not capture, and the part that changed how the client chose to present its recommendations.

Results: 300+ reviews within the projected timeframe

• More than 300 case reviews completed inside the projected timeframe.
  
  
• 15+ clinicians across five specialties and a diverse range of backgrounds.
  
  
• Three independent clinical perspectives on every case.
  
  
• 10 follow-up interviews providing qualitative insight behind the reviews.
  
  
• Validation of the comprehensiveness, accuracy and usability of the AI-generated recommendations — and new presentation methods for them.
  
  
• A second phase of the programme approved on the strength of the results.