Public Hospital AI Impact Tracker SaaS

2.70

Derivation Chain

Step 1 Expansion of AI adoption in public Medical institutions

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Step 2 Demand for proving ROI on public hospital AI investments

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Step 3 Automated pre/post-AI KPI tracking and reporting tool

Problem

Public hospitals (approximately 40 institutions including Seoul Medical Center) that adopt AI Solutions must quantitatively report adoption outcomes to higher authorities (local governments, Ministry of Health and Welfare). However, manually compiling KPIs such as pre/post-AI consultation time, misdiagnosis rate, and complaint processing time takes 40-60 hours per month, and inconsistent data formats across departments make consolidated Report generation difficult.

Solution

(1) Auto-extract pre/post-AI adoption KPIs (consultation time, length of stay, complaint response time, etc.) from hospital EMR/OCS systems, (2) visualize Before/After comparisons on a dashboard, (3) auto-generate PDF Reports formatted for regulatory reporting requirements. Core: standardized KPI framework + automated data integration.

Target: Public hospital IT departments and Medical quality management teams, 200-1,000 staff

Revenue Model: SaaS Monthly Subscription at 990,000 KRW (~$740)/hospital (up to 10 KPIs), additional KPIs at 50,000 KRW (~$37) each/month. 15% discount for Annual Subscription.

Ecosystem Role: Supplier

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

4.0/5

U Urgency

3.0/5

M Market

2.0/5

R Realizability

2.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (59%)

Tech Complexity

24.0/40

Data Availability

15.0/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (55/100)

Competition

8.0/20

Market Demand

9.4/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

3.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [medium] Data Pipeline [medium]

Dashboard