# Healthcare clinic group: 36 hours a week of hidden time Source: https://getstartedwithai.net/case-studies/healthcare-clinic-time-tax Site: Get Started With AI Tagline: Build AI automations that actually run your business. Audience: solo professionals, freelancers, consultants and AI implementers in training Contact: hello@getstartedwithai.co.uk This Markdown companion is generated from the prerendered page for AI crawlers. # Healthcare clinic group: 36 hours a week of hidden time A private clinic group with six clinicians across three sites had each clinician spending six hours a week on pre-visit documentation: pulling patient history, structuring clinical notes, flagging contra-indications. Nobody had counted those hours; it was just how the job worked. When we calculated the Time Tax across all six clinicians, the number was 36 hours a week. At clinical billing rates, that was over £3,000 a week of high-cost time spent on templated administrative work. The clinicians did not know the number. Neither did the practice manager. ## The starting point - Clinicians: 6 across 3 sites. - Pre-visit documentation: 6 hours per clinician per week, 36 hours total. - Visible cost: £0 because the work happened during clinical hours. - Real cost: about £3,000 a week at clinical billing rates. - Pre-existing tools: a clinical records system, a paper-based pre-visit checklist. ## What the audit revealed The Time Tax was invisible because each clinician carried it individually. The conversation changed when we put a single number on the board: 36 hours a week, £3,000 a week, £156,000 a year. The practice manager had been planning to hire a part-time admin role for £30,000 to help with documentation. The Time Tax calculation revealed the problem was 5x bigger than the planned solution. ## The first build - Step W: counted the hours. Documented the variation between clinicians. - Step I: chose pre-visit summary generation as the first build. Same shape across all six clinicians. - Step R: built a Custom GPT trained on the clinic notes structure, plus a small intake form integration. - Step E: named a senior clinician as the owner. Weekly review of sample outputs for the first month. ## The result - Pre-visit documentation: under 2 hours per clinician per week (down from 6). - Time recovered: 24 hours a week across the practice. - Annual saving in clinical-hour terms: about £100,000. - Build cost: £8,500 plus £200 a month tooling. - Patient-facing time per week: increased by an average of 4 hours per clinician. ## The compliance side No patient data left the clinics approved tenant. The Custom GPT ran inside their existing Microsoft 365 Copilot setup. Every output was reviewed and edited by the clinician before being filed. The handover document included the data-handling rules, the escalation path and the monthly review cadence. ## See this kind of build run live The free webinar walks through the WIRE Method end to end on a real audience workflow. 60 minutes, no upsell. Bring one repeatable task; leave with a mapped automation. ### Live build session The next live build session covers the same shape as the case studies on this page. [Join the next session](/webinar) ## Questions people ask before they start ### Did patient data leave the clinic? No. The build ran inside the clinics existing Microsoft 365 tenant. All processing happened with training turned off and tenant-grade controls. ### Did the clinicians push back? Initially yes. The trust moment was a side-by-side comparison of an AI-drafted pre-visit summary versus a hand-written one on the same patient. The AI version caught two contra-indications the clinician had missed. ### How is this different from a clinical AI tool? It is not a clinical decision tool. It produces structured pre-visit summaries from existing records. The clinical decisions are still human. ### Could a single-site clinic do this? Yes. The smaller the practice the easier the deployment. The Time Tax calculation is even more powerful for a solo practitioner.