CareWatch – Elder Care Quality Monitor

4.00

Derivation Chain

Step 1 Parent's long-term care grade application & reassessment navigation

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Step 2 Selecting in-home or facility services after grade approval

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Step 3 Quality monitoring & anomaly detection during active service

Problem

After a parent receives a long-term care grade, there is no way to monitor the actual service quality of visiting caregivers or day/night care centers. Caregivers change frequently, visits are shorter than promised, or unauthorized charges are billed—but adult children living in other cities cannot assess actual care quality just by checking National Health Insurance Service (NHIS) benefit statements. By the time problems are noticed, the parent's health has often already deteriorated, leading to care grade reassessment.

Solution

1) Auto-tracking dashboard via NHIS long-term care benefit statement scraping to monitor visit times and service items 2) Compliance alerts comparing actual delivery against children's expected service settings (e.g., 3 visits/week, 90 min each) 3) Anomaly detection (sudden drop in visit frequency, spike in out-of-pocket costs) triggers KakaoTalk alerts to family members

Target: Working adults aged 45–60 living in a different region whose parents (aged 70–80) are receiving in-home long-term care services

Revenue Model: Monthly Subscription at $5.90/mo (per parent), $2.90/mo per additional family member, referral commission for care facility switching consultation

Ecosystem Role: Consumer

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

5.0/5

M Market

4.0/5

R Realizability

4.0/5

V Validation

4.0/5

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 (70%)

Tech Complexity

29.3/40

Data Availability

20.8/25

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 (62/100)

Competition

10.0/20

Market Demand

20.0/20

Timing

14.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

7.5/15

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

NHIS benefit statement scraping module [medium] Anomaly pattern detection logic [medium] KakaoTalk alert integration [low]

Dashboard