I’m Jay McCormack, a systems developer. This research project aims to understand whether appointment no-shows are a significant problem for solo healthcare practitioners, and whether automated SMS reminder systems could provide value.

Before building any solution, I’m validating the problem through direct outreach to healthcare providers. This page explains the methodology, data sources, and ethical considerations behind this research.

Key Features

  • Transparent methodology: All data sources and contact methods disclosed
  • Opt-out first: Easy unsubscribe from any communication
  • Privacy focused: No data sharing or marketing list additions
  • AI-assisted: Automated response handling with human oversight
  • Ethical outreach: Using only publicly available contact information

Research Methodology

This project follows a structured approach to validate market demand:

1. Provider Discovery

Using the Google Maps Places API, I identify solo healthcare practitioners based on:

  • Public listing data: Name patterns indicating individual practitioners
  • Mobile availability: Providers who list mobile numbers publicly
  • Provider types: Physiotherapists, massage therapists, psychologists, chiropractors
  • Solo scoring: Algorithm to identify likely sole practitioners vs. clinics

2. Initial Contact

Providers receive an SMS with:

  • Clear identification of who I am and why I’m reaching out
  • Link to this research page for full transparency
  • Single validation question about appointment no-shows
  • Immediate opt-out option (reply STOP)
  • No sales pitch or service offering

3. Response Handling

All responses are processed through:

  • Automatic opt-out: Instant removal and confirmation
  • AI question answering: Honest responses to common questions
  • Data extraction: Recording no-show percentages and pain points
  • Human review: I personally review all conversations
  • Privacy protection: No sharing of individual responses

4. Analysis & Reporting

Aggregate findings will answer:

  • What percentage of providers experience significant no-shows?
  • How much revenue impact does this create?
  • Would automated reminders be valued?
  • Is this worth building a solution for?

Data Sources & Privacy

How I Found You

Your contact information was obtained through:

  • Google Maps Places API: Public business listings
  • Mobile numbers: Only contacting publicly listed mobile numbers
  • Location data: Publicly available business addresses
  • No scraping of private data: All information is publicly visible

What I’m NOT Doing

  • Adding you to marketing lists
  • Sharing your data with third parties
  • Selling lead lists to others
  • Making unsolicited sales calls
  • Accessing private healthcare information

Your Privacy Rights

  • Opt-out anytime: Reply STOP to any message
  • Data deletion: Contact me to remove all your data
  • No tracking: This page uses no analytics or cookies
  • SPAM Act compliant: Following Australian anti-spam legislation

Why This Research Matters

The Problem Statement

Healthcare providers face unique challenges:

  • Smaller patient pools than metropolitan areas
  • Higher no-show rates (industry average: 15-30%)
  • Less access to sophisticated practice management tools
  • Time spent on manual appointment reminders
  • Revenue loss from unfilled appointment slots

The Research Question

If automated, intelligent SMS reminder systems could reduce no-shows by 30-40%, would healthcare providers find this valuable enough to pay for?

This research validates whether:

  1. No-shows are painful enough to justify a solution
  2. SMS is the right channel for reminders
  3. Solo practitioners have budget for automation
  4. Regional markets are underserved by existing tools

What Happens Next

If No-Shows Are A Real Problem

If this research validates significant pain:

  1. Build an MVP: Simple SMS reminder system
  2. Beta testing: Offer free trial to interested providers
  3. Measure results: Track no-show reduction rates
  4. Consider launch: Only if it genuinely helps

If No-Shows Aren’t A Priority

If this research shows it’s not a real problem:

  1. Share findings: Publish aggregate results
  2. Thank participants: Acknowledge your time
  3. Pivot research: Explore other pain points
  4. No hard feelings: Sometimes the problem isn’t what you think

About Me

I’m Jay McCormack, a business analyst and systems architect with 30+ years in IT. I specialize in understanding business problems, designing solutions, and integrating systems to automate workflows.

Background:

  • Business analysis and requirements gathering
  • Systems architecture and integration design
  • Process improvement and workflow automation
  • Stakeholder communication and solution delivery

Contact:

Frequently Asked Questions

Why are you doing this?

I’m exploring side business opportunities and believe in validating problems before building solutions. Rather than assume healthcare providers need this, I’m asking directly.

Are you selling something?

Not yet. This is pure research. IF the data shows a real problem AND I build something that works, I might offer it as a paid service. But there’s zero obligation.

How did you get my number?

Your mobile number is publicly listed on Google Maps. I’m using the Google Places API to identify solo practitioners who list their mobile numbers.

Yes. Under Australia’s SPAM Act 2003, I can contact businesses whose contact details are publicly published, as long as I identify myself and provide an opt-out mechanism.

Can I opt out?

Absolutely. Reply STOP to any message, or email me at j@jaym.cc. I’ll remove you immediately with no questions asked.

Will you share my responses?

No. Individual responses are confidential. I may publish aggregate statistics (e.g., “60% of providers report 20%+ no-shows”) but never identify individuals.

What if I want to participate more?

If you’re interested in beta testing a solution, just let me know in your response. I’ll keep you updated on progress.

Research Timeline

  • January 2026: Initial outreach
  • February 2026: Data analysis and validation
  • March 2026: Decision point (build MVP or pivot)
  • April 2026: Beta testing (if validated)
  • May 2026: Publish findings

Contact & Opt-Out

Questions About This Research

Email: j@jaym.cc Response time: Usually within 24 hours

Opt-Out Methods

  1. Reply STOP to any SMS

Data Deletion Request

Contact j@jaym.cc with subject “Delete My Data” I’ll confirm deletion within 48 hours