5 Metrics to Track Before and After Veterinary Software Adoption
A practical framework for veterinary practices to measure software ROI. Learn five must track metrics, simple formulas, baseline tips, and how to compare before and after adoption.
Buying new software should reduce stress, not add it. The easiest way to know if a tool is working is to measure a clean before and after. This guide gives you five clinic friendly metrics, simple formulas, and a quick baseline plan so you can prove time saved, revenue gained, and headaches removed.
Why this matters
New software only earns its keep if it saves time or drives revenue. Without a baseline, it is hard to tell. Track these five metrics for 30 days before adoption, then again for 30 to 60 days after go live. Keep the setup light, use existing reports where possible, and focus on trend lines rather than perfection.
Quick baseline setup
- Pick a clean 30 day window before go live
- Decide where each number comes from (PIMS, phone systems, online booking, payment tools, inventory, pharmacy)
- Export weekly and drop into a simple sheet
- Repeat for 30 to 60 days after go live
- Compare deltas and note for seasonality
Metric 1: Visit cycle time and throughput
What it is: Minutes from check in to check out, plus completed visits per doctor hour.
What it matters: Faster, smoother visits reduce bottlenecks and stress at the front desk.
How to capture: Use PIMS timestamps for check in and invoice close, or a short time study sample for a few days.
Formula:
Cycle time (minutes) = checkout_time - checkin_time
Throughput = completed_visits + staffed_doctor_hours
Target direction: Cycle time down, throughput stable or up
Example improvement: Online forms, digital consent, or kiosk check in reduce front desk back and forth, cycle time drops 6 to 12 minutes.
Watch outs: Do not chase speed at the expense of client experience. Track callbacks or compliance rate alongside this number.
Metric 2: Estimate Acceptance Rate
What it is: The percent of presented estimates that are accepted within a defined window
Why it matters: Clear estimates with easy approval and payment options increase medical compliance.
How to capture: PIMS estimate report, plus e-signatute and payment tool logs.
Formula:
estimate_acceptance_rate = accepted_estimates + presented_esitimates
Target direction: Up. Many clinics see 5 to 15 point gains with cleaner templates and one click approvals.
Example improvement: Digital estimate with item bundles, financing options, and mobile approval increases acceptance from 54 percent to 66 percent.
Watch outs: Do not compare apples to oranges. Exlcude purely informational estimates if you never expected a decision.
Metric 3: Refill capture and time to fill
What it is: Percent of refill requests you capture in house, plus average hours from request to ready for pickup.
Why it matters: Faster refills keep clients loyal and protect pharmacy revenue.
How to capture: Refill request counts from your messaging tool or portal, plus PIMS dispense logs.
Formulas:
Capture rate = refills_filled_in_house ÷ total_refill_requests
Time to fill (hours) = ready_time − request_time
Target direction: Capture rate up, time to fill down. Clinics using two way texting often see both move the right way.
Watch outs: Track controlled drug exceptions separately. They follow different rules and timelines.
Metric 4: Missed charges rate and average charge per visit
What it is: The share of visits with work performed that never hit the invoice, plus the average dollars per completed visit.
Why it matters: Missed charges quietly erode margins. Better workflow and checklists usually fix this fast.
How to capture: Compare medical records or treatment sheets to invoice line items. Many PIMS have missed charge reports.
Formulas:
Missed charge rate = visits_with_discrepancy ÷ total_visits
Avg charge per visit = total_revenue ÷ completed_visits
Target direction: Missed charge rate down, average charge per visit up or stable.
Example improvement: Treatment plan linking and discharge checklists drop missed charges from 7 percent to under 3 percent.
Watch outs: Seasonality can move average charge per visit. Compare to the same month last year when possible.
Metric 5: Client Contact Success and Conversion
What it is: Two parts, message deliverability and response, plus conversion to a booking or payment.
Why it matters: If messages do not reach clients, nothing else works. If they reach clients but do not convert, you are leaving value on the table.
How to capture: Reminder and campaign logs from your messaging or CRM tool, online booking or payment confirmations, phone system reports for backup.
Formulas:
Delivered rate = delivered ÷ sent
Response rate = responses ÷ delivered
Conversion rate = completed_action ÷ delivered (completed action can be a booked appointment, paid invoice, or signed estimate)
Target direction: All up. Start by improving deliverability, then test subject lines and timing.
Watch outs: Remove wrong numbers and bounced emails from the denominator once they are confirmed bad.
Pulling it together, a simple scorecard
Track each metric weekly. Color code changes from the pre adoption baseline.
| Metric | Baseline | Week 2 | Week 4 | Week 6 | Direction |
| Visit Cycle Time (min) | 54 | 49 | 46 | 45 | ↓ good |
| Throughput (visits per doctor hour) | 1.9 | 2.0 | 2.1 | 2.0 | ↑ good |
| Estimate acceptance rate | 58% | 61% | 64% | 66% | ↑ good |
| Refill capture rate | 62% | 68% | 72% | 74% | ↑ good |
| Time to fill (hours) | 28 | 20 | 16 | 14 | ↓ good |
| Missed charge rate | 6.5% | 5.1% | 3.9% | 3.2% | ↓ good |
| Avg Charge per visit | 191 | 196 | 199 | 198 | ↑ or stable |
| Delivered, Response, Conversion | 92%, 19%, 8% | 95%, 22%, 10% | 96%, 24%, 11% | 96%, 25%, 12% | ↑ good |
Tip, keep the math transparent. Add short notes for policy or staffing changes so you can separate software effects from everything else.
Implementation Checklist
- Choose one owner per metric
- Decide the exact report or export
- Schedule a 20 minute weekly review
- Make one small change per week
- Re check after 30 and 60 days, then keep only the three metrics that moved the most for long term tracking
Closing Thought
You do not need a perfect data warehouse to measure ROI. You need a clean baseline, a short list of metrics, and a weekly habit. Once the team sees time saved or fewer mistakes, adoption improves on its own.
Time spent reading, 7 minutes. Decision time you just saved, hours, maybe days.
Adam Wysocki
Contributor