The Precision Playbook: How to Write Problem & Outcome Statements That Drive Real Health-Tech Innovation

“A problem well-defined is a problem half-solved — but in health tech, a poorly-defined problem can cost lives, time, and millions in sunk investment.”

In healthcare, the stakes aren't just market share or user growth — they’re safety, equity, and clinical outcomes. Yet most failed products, stalled pilots, and misaligned roadmaps trace back to the same root issue:

Teams jumped to solutions without ever defining the problem or the desired outcome with precision.

This article breaks down exactly how to write problem and outcome statements in a format that creates clarity, alignment, and measurable success. We’ll use examples across health-tech roles — providers, pharma, dentists, device companies, payers, and digital health startups.

“Where do we start?”

Section 1 — The Problem Statement: Capturing Today’s Reality

A problem statement explains the current state as it exists today, why it matters, and who it affects. It’s not emotional, not ambiguous, not solution-dependent.

Formula for a Strong Problem Statement

[Current state] + [Why it’s a problem] + [Who it impacts / why it matters].

Strong:

“30% of heart-failure patients at our hospital are readmitted within 30 days, driving higher CMS penalties, lower patient satisfaction, and preventable care costs.”

Weak:

“We have a readmission problem.”

Anatomy of a Valid Problem Statement

Question

Is it factual — not opinion?

Should Be:

Yes

Example:

“Insulin-dosing errors occur in 1 of 14 ICU patients.”

Question:

Does it describe the current state only?

Should Be:

Yes

No future or solution language.

Question:

Does it state the impact or consequence?

Should Be:

Yes

Example:

“Leading to $4M in write-offs annually.”

Question:

Does it name who is affected?

Should Be:

Yes

Example:

“Affects pediatric oncology patients.”

Key Insight: It’s important to document your work. Here’s how a section of a document may look for outcome statements (markdown format).

##ProjectOverview

###ProjectName

**Name:**[ProjectName]

###ProjectType

**Type:**[web_app|mobile_app|cli_tool|library|api|microservice|desktop_app|embedded_system]

###CoreValueProposition

**ProblemStatement:**[Whatproblemdoesthissolve?]

**SolutionSummary:**[Howdoesthisprojectsolvetheproblem?]

**TargetUsers:**[Whowillusethis?]

**SuccessMetrics:**[Howwillyoumeasuresuccess?]

Section 2 — Outcome Statements: Writing the Future in One Sentence

Desired outcomes should always be written as a clear change — using THE FOLLOWING TERMS:

Increase / Reduce / Eliminate.

Your outcome is not “implementing a feature.” It is not “leveraging AI.” It is not “enhancing workflows.”

Precision Outcome Format

[Increase / Reduce / Eliminate] + [variable / barrier / risk]

Correct

  • “Increase the accuracy of drug XYZ dosage calculations.”

  • “Reduce 30-day readmission rates for heart-failure patients.”

  • “Eliminate delays in treatment caused by patient anxiety about injection.”

Incorrect

  • “Improve drug accuracy.” (Too vague)

  • “Use AI to reduce readmissions.” (Solution baked in)

  • “Fix patient anxiety issue.” (Not measurable)

Outcome Writing Rules

Rule:

Start with Increase, Reduce, Eliminate

Why it Matters:

Creates directional clarity

Example:

“Reduce adverse-event reporting backlog.”


Rule:

Focus on one variable per statement

Why it Matters:

Avoids scope creep

Example:

NOT: “Reduce risk and improve access and lower cost”


Rule:

Make it solution-agnostic

Why it Matters:

Keeps options open

Example:

Not “via chatbot,” “through AI,” “using automation.”


Rule

Implied measurability

Why it Matters:

Even without a metric, it can be measured

Example:

“Increase medication-refill adherence.”


Section 3 — Examples Across Health-Tech Stakeholders

PRO TIP: PROBLEM STATEMENTS NEED TO BE WRITTEN FROM THE PERSPECTIVE OF THE STAKEHOLDER THAT IS EXPERIENCING THE PROBLEM. SIMILAR TO A USE CASE WRITE THE PROBLEM STATEMENT FROM THIS PERSPECTIVE.


Stakeholder: Hospital Provider

Problem: “18% of CHF patients are readmitted within 30 days, creating CMS penalties and bed capacity constraints.”

Example Outcome: “Reduce CHF readmissions from 18%.”


Stakeholder: Pharma Executive

Example Problem: “34% of oncology patients discontinue oral therapies due to unmanaged side effects, reducing clinical and commercial success.”

Example Outcome: “Increase treatment-cycle completion rates.”


Stakeholder: Dentist / DSO

Example Outcome: “22% of hygiene patients don’t schedule follow-ups, leading to preventable restorative work later.”

Example Outcome: “Increase preventive-care follow-up appointments.”


Stakeholder: Behavioral Health Clinic

Example Problem: “Intake paperwork takes 45 minutes per patient, reducing daily capacity by 6 visits.”

Example Outcome: “Reduce intake time per patient.”


Stakeholder: Medical Device Company

Example Problem: “Catheter blockages are detected late, causing avoidable infections and ICU escalation.”

Example Outcome: “Increase real-time alerts for early blockage detection.”


Stakeholder: Digital Therapeutics Founder

Example Problem: “Only 38% of diabetes patients open the app weekly, limiting clinical impact and payer renewals.”

Example Outcome: “Increase weekly active engagement for diabetes users.”


Stakeholder: Payer / Health Plan

Example Problem: “Members are churning due to confusion about covered benefits.”

Example Outcome: “Eliminate churn caused by benefit-navigation friction.”


Conclusion — Precision Is a Leadership Skill

A well-written problem and outcome statement:

Aligns clinicians, executives, engineers, product, and ops
Prevents building features nobody needs
Turns “innovation” from chaos into intention
Makes ROI measurable before a single line of code is written
Saves millions in misaligned development and failed pilots

Before you build a workflow, train a model, code a feature, or purchase a platform, ask:

Have we clearly defined the problem?
Have we precisely stated the desired outcome?

If not — stop. Refine the words. The discipline of clarity is the strategy.

Because in health tech, the most dangerous risk isn't AI alignment, regulation, or EHR integration — it’s believing you’re solving the right problem when you never defined it.

Brainstorm the problem you want to solve, create a PRD outlining what you want to build, choose the right tools, add context like mockups or knowledge bases, use version control, debug. It all starts with a definition of your outcome statements.

If you would like assistance reach out through the contact form below, we’d be happy to help out.

Previous
Previous

AI Prompts That Actually Save Hours of Time for Front-Line Healthcare Workers…

Next
Next

AI in Healthcare: Automate the Obvious Before You Innovate the Extraordinary