Across twelve months of practice data, MahViz surfaced a ₹22.4L / month revenue gap, a referral network with 45 dormant GPs, and a catchment in which the practice captures barely 2.2% of the patients it could realistically reach.
Every figure in this report is synthetic, created solely to demonstrate the shape of a MahViz engagement — how we structure intelligence, render it legible, and translate it into decisions. Consider it a deliberately restrained preview: the depth of our actual analysis, modelling, and forward-looking projections extends well beyond what is shown here, and is built in full around each practice we partner with.
Before any growth strategy, you need a clear-eyed view of what your practice data actually says — not what you remember. We analysed 12 months of billing, procedure logs, and patient records for Dr. Arvind Rao's practice.
Dr. Rao believed he had strong referral relationships. The data told a different story — 68% of GPs within a 12 km radius had never sent a single patient. Here's what the full referral ecosystem looked like.
Patient origin data mapped to Telangana & AP districts reveals which corridors are performing, which are cold zones, and where a single cardiac camp could unlock a new referral cluster.
MahViz models the latent volume of potential cardiac patients across Dr. Rao's top five catchment districts, then sets it against how many actually reach his practice. It answers the question most specialists never get a defensible number for: how large is the real opportunity — and where is it concentrated?
| District | Adult Population est. |
Est. Cardiac prevalence (modelled) |
Est. Annual Potential Patients |
Cases Reaching Dr. Rao |
Market Share | Revenue Gap |
|---|---|---|---|---|---|---|
| Hyderabad | 39.4L | 8.2% | ~3,230 | 142 | 4.4% | ₹6.2L/mo |
| Medchal-Malkajgiri | 26.8L | 7.6% | ~2,040 | 58 | 2.8% | ₹3.8L/mo |
| Rangareddy | 52.3L | 7.1% | ~3,715 | 44 | 1.2% | ₹5.1L/mo |
| Nalgonda | 34.8L | 8.7% | ~3,028 | 31 | 1.0% | ₹4.2L/mo |
| Sangareddy | 28.2L | 6.9% | ~1,946 | 28 | 1.4% | ₹3.1L/mo |
| TOTAL (5 Districts) | 181.5L | 7.7% avg | ~13,959 | 303 | 2.2% | ₹22.4L/mo |
* All figures are synthetic and illustrative, generated by MahViz's demand model for demonstration only. Potential-patient estimates apply a modelled cardiac-intervention rate to district adult populations; revenue gap assumes ₹85,000 average realisation per intervention.
Every quarter, MahViz delivers an 18–20 slide consulting deck with prioritised actions. Here are the four top recommendations from Dr. Rao's Q1 advisory, derived directly from the five intelligence services above.
This is what MahViz does for a solo specialist in 30 days — turn 12 months of practice data into decisions Dr. Rao couldn't have made without it.
Every practice has a revenue gap. Most don't know how big it is, where it is, or how to close it. MahViz makes this visible in 30 days.
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