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Is Your Practice Ready for AI?

Healthcare carries obligations that other sectors do not, and a practice that adopts AI without governance in place creates risk faster than it creates efficiency. Fourteen questions covering the things that actually determine whether this goes well.

Answer for how the practice operates today. A weak score is common and entirely fixable. The value is in knowing which dimension is weak before you commit to anything.

Practice AI Readiness Scorecard

Fourteen questions. No patient information: practice processes only.

0 of 14 answered0%
1.Which practice management software do you run, and does it offer integration?
2.Is your appointment book digital and live?
3.Do you have online booking today?
4.What proportion of active patients have a valid mobile number recorded?
5.Do you have duplicate patient records?
6.Are communication preferences and consent recorded per patient?
7.Do you have a process for assessing suppliers who handle health information?
8.Is your practice privacy policy current and does it cover third-party processing?
9.Do you know where your existing software vendors store patient data?
10.Has the practice agreed what AI must never do?
11.How would an urgent or distressed caller be recognised and handled?
12.Is there a clear escalation path to a clinician outside business hours?
13.Have reception staff been involved in the discussion?
14.Is there a named person who would own this and review how it performs?
Answer all 14 questions to see your score and a tailored recommendation.

A self-assessment to structure an internal discussion. It is not a compliance audit and not legal advice. Nothing entered here is recorded or transmitted, and no patient information should be entered.

What Readiness Means in Healthcare

Technical readiness is the easy part. What separates practices that adopt AI well from those that struggle is whether the governance and clinical safety boundaries were decided before the technology arrived.

Clinical boundaries come first

The most important decision is not which vendor to use. It is which decisions the practice will never delegate to a system. Practices that settle this early adopt confidently; those that leave it vague end up with clinicians and reception disagreeing about what the tool is allowed to do.

Privacy accountability stays with you

Health information is sensitive information under the Privacy Act 1988. Engaging a supplier does not shift your obligations, so knowing where data goes and who can reach it is a precondition for adoption rather than a detail to sort out later.

Integration decides the benefit

A tool that cannot write into your practice management software creates a second system for staff to check. Confirming genuine integration with your specific software, at your specific version, is the difference between saving reception time and adding to it.

The Five Dimensions

Fourteen questions across five areas. Weakness in clinical governance matters more than weakness anywhere else.

1

Systems and integration

Whether your practice management software can be connected, and whether anyone knows what that would involve.

2

Data quality

Whether patient records, contact details and recall lists are accurate enough for an automated system to act on.

3

Privacy and governance

Whether the practice has decided how it assesses suppliers handling health information, and who signs that off.

4

Clinical safety

Whether the boundary between administrative automation and clinical decision-making has been drawn explicitly.

5

People and process

Whether reception and clinical staff have been involved, and whether someone owns the outcome.

The Four Things to Settle Before You Start

All four are free, none take long, and each one prevents a category of problem that is genuinely painful to fix afterwards.

Write down what AI must never do

A short written statement of the clinical boundary, no symptom advice, no triage decisions, no medication guidance, immediate escalation for anything clinical or distressed, takes an hour to agree and settles most future disagreements before they occur.

  • State explicitly which decisions remain with clinicians
  • Define what triggers immediate handover to a person
  • Agree how urgent and distressed callers are recognised and routed
  • Have the clinical team sign off the boundary, not just management

Check your contact data before you automate contact

Automated reminders and recalls are only as good as the phone numbers and email addresses behind them. A practice with a meaningful proportion of stale contact details will automate the sending of messages nobody receives, and will not find out for months.

  • Measure how many active patients have a valid mobile number
  • Check for duplicate patient records before automating recalls
  • Confirm consent and communication preferences are recorded
  • Establish a process for capturing updated details at each visit

Decide how you assess a supplier

Agree in advance the questions any supplier touching health information must answer, and who in the practice signs off. Without this, the decision defaults to whoever ran the demo, which is not a governance process.

  • Require written answers on data location, retention and access
  • Confirm whether content is used to train shared models
  • Check the arrangement against your practice privacy policy
  • Name who approves suppliers handling health information

Involve reception before deciding, not after

Reception staff know which calls are routine, which are sensitive, and which callers need a person. That knowledge is the single most valuable input to configuring any system, and excluding them produces both worse configuration and predictable resistance.

  • Ask reception which calls they would happily hand over
  • Ask which calls they believe must always reach a person
  • Be explicit and early about what this means for their roles
  • Give them a route to flag when the system handles something poorly

Next Steps

Healthcare AI Privacy Checklist

The privacy and governance questions to work through before any supplier touches health data.

Open the checklist

Healthcare AI Vendor Questions

Twenty-six questions for any vendor selling into an Australian practice.

See the questions

Practice AI Savings Calculator

Model what the administrative saving would actually be worth.

Run the numbers

Frequently Asked Questions

Do we need a formal AI policy before adopting anything?

A full policy document is not a precondition, but a short written statement of boundaries genuinely is. One page covering what AI may do, what it must never do, who approves suppliers, and how patient information is handled is enough for most small and medium practices, and it can be expanded later. The value is less in the document than in the conversation that produces it, because that is where clinical and administrative staff discover they had different assumptions.

What is the biggest risk for a practice adopting AI?

Scope creep across the clinical boundary. A system introduced to book appointments gradually starts answering questions about symptoms, medications or results because patients ask and the system is capable of responding. Without an explicit boundary and a tested escalation path, this happens incrementally and nobody notices until something goes wrong. The second largest risk is privacy: engaging a supplier without establishing where health information goes, which remains your accountability under the Privacy Act regardless of any contract.

Does AI in a practice need to be reported to AHPRA or a regulator?

Administrative automation such as appointment booking, reminders and call handling does not ordinarily require notification. However, practitioners remain bound by their professional obligations and codes of conduct regardless of the tools a practice uses, and software that makes or influences clinical decisions may fall within the Therapeutic Goods Administration’s regulatory framework for software as a medical device. Where a tool touches clinical decision-making rather than administration, take specific advice rather than assuming. This is general information and not legal or regulatory advice.

Our data is messy. Should we fix it first?

Fix the part the automation will actually touch, and do not let the rest delay you. If you are automating appointment reminders, valid mobile numbers and duplicate patient records are the things that matter; the tidiness of clinical notes from 2019 is irrelevant to that project. A targeted clean-up of the specific fields involved usually takes days rather than months, and it prevents the most common early failure, which is automated messages going to contact details nobody has updated in years.

How do we handle patients who do not want to speak to an AI?

Give them a fast, obvious route to a person and make sure it works. In practice the proportion of patients who object is smaller than most practices expect, and it drops further when the system is genuinely useful, patients care considerably more about being able to book quickly than about who books them. What generates complaints is not the AI itself but being unable to escape it. Test that escalation path specifically, including out of hours, and brief reception on what arrives escalated and why.

Is anything I enter in this scorecard recorded?

No. The assessment runs entirely in your browser, nothing is transmitted or stored on our side, and there is no email gate. You can screenshot the result for a practice meeting if that is useful. Do not enter any patient information. The questions ask only about practice systems and processes, and no free-text patient data is requested or accepted anywhere in the tool.

Sources and further reading

Know Where the Gap Is?

Tell us your weakest dimension and what you had in mind. We will tell you what to settle first, and if the honest answer is "not yet", we will say that.