Opportunities › Medical record error detection and compliance › Proposed app
Chartwise Audit
Flag chart gaps and conflicts across clinic records before they cause harm
- Score
- 34
- confidence 51
- Evidence
- 8
- items on the page
- Rivals
- 0
- named in sources
- First version
- 45 d
- estimate
- Type
- Desktop and mobile
- PWA: on computers and phones alike
- Market since
- 2010
- Mature market · AI estimate
ScreensConcept
Desktop and mobile: Clinics review charts and manage worklists at desks for thorough audits and EMR connections, while providers and patients need mobile access to review flags and answer questions in clinical settings. Sample screens on a computer and a phone, in the proposed brand. Their numbers are sample data.
Chart scan
Scan complete3 flags
About this appAI proposal
Chartwise Audit reads medical records, from PDF uploads or an EMR connection, and flags what looks wrong: medications that do not match between notes, an empty Allergies field, vaccinations that look out of date, and required fields left blank. Each flag points to the page and line.
It is built for clinic and hospital quality teams, including acute care and substance use disorder programs, who today scrub charts by hand for dozens of hours a month. Reviewers need no clinical expertise to triage flags. Clinical staff decide what is actually an error.
Unlike a one-off checker, it runs across a whole clinic's records, keeps a worklist with owners and due dates, and produces an audit trail for compliance review. A patient mode lets people check their own records too.
- Tagline
- Find the chart errors before they find your patients.
- Voice
- CalmPrecisePlain
- Why this name
- Chart is the record being checked; wise suggests careful judgment. Two plain words, easy to say. Audit names the job.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Chart scan from PDF
Drop in a record PDF and get a list of flags in minutes, each linked to the source page and line.
No member yet
Medication mismatch check
Compares medication lists across notes and visits and flags differences in drug, dose or status.
No member yet
Empty critical fields
Highlights blank Allergies, problem list and any other fields your team marks as required.
No member yet
Outdated item alerts
Surfaces vaccinations and entries not updated within a window you set.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#0F4C5CDeep Teal · primary#F7F5F0Paper · surface#1B2B30Ink · text#E09F3ESignal Amber · accent / warning#9E2A2BBrick · high severity#6B9080Sage · data / resolved
Typography
Aa
Chartwise Audit
PricingAI proposal
The material gives no competitor prices. It says the existing patient product is free. Clinic and hospital tiers are a starting point to test, per-audit or per-site.
Patient
Free
- Check your own records
- Plain-language questions
- Share a summary with your provider
Clinic
Contact us
- Clinic-wide scans
- Worklist with owners
- Audit trail export
- Price to be tested
Hospital
Contact us
- Many sites
- EMR API connection
- Custom required-field rules
- Priority support
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$190,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Shared outputs. Patients send a flag summary to their provider, and clinics send audit reports to compliance reviewers and partner sites. Each carries the product name and invites the recipient to run their own scan.
- Do they become customers?
- Recipients are often clinic staff who could buy, but a patient summary may be opened once and ignored. Test how many provider recipients start a clinic trial.
- First customers
- Quality or compliance managers at small substance use disorder treatment clinics with one to five sites, who scrub charts by hand each month.
- Where to reach them
- Direct outreach: Contact quality managers and clinical directors at treatment providers with an offer to scan a sample batch of de-identified charts.
- Industry associations: Present at behavioral health association webinars and post in their member forums about reducing chart-scrubbing hours.
- Hacker News and communities: Share the patient mode and ask for provider referrals from commenters and health-tech groups.
- First milestone
- Five clinics each complete a paid pilot audit, and at least three say they would renew monthly.
Why people already pay for this
- VerifiedHacker News post received 16 points and 4 comments
- AI inferenceMedical records contain errors such as missing allergies, mismatched medications, or outdated information that can cause treatment mistakes or denied insurance claims.
- AI inferenceReviewing medical records is vital because healthcare providers may forget to write down information or make mistakes during documentation.
- Public claimEmpty or missing fields like 'Allergies' in medical records can be disastrous in emergency situations.
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Document extractionPDF text and table parsing with OCRScanned and exported charts must be read into structured fields.
- This app · Language modelHosted LLM with a no-training data agreementMatches medication and note text across visits; every flag cites its source.
RisksAI inference
- RegulatoryRecords are protected health information. HIPAA duties, business associate agreements and 42 CFR Part 2 rules for substance use treatment records apply and need legal review before launch.
- AIThe model may miss real errors or flag false ones. Clinicians must make the call, and the product must say flags are prompts, not clinical advice.
- TechnicalScanned PDFs vary widely in quality, so extraction may fail on handwriting or odd layouts. EMR connections differ by vendor and take time to approve.
- CommercialThe material shows a free patient product and only a small Hacker News signal (16 points, 4 comments). Providers' willingness to pay is untested.
- PlatformEMR vendors control API access and may limit or charge for it, which could slow clinic-wide rollout.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.