How Marvix AI Helped MOHC Transform Oncology Documentation in Just Three Months

How Marvix AI Helped MOHC Transform Oncology Documentation in Just Three Months
Marvix AI Editorial Team

Reviewed by

July 23, 2026

Every oncology visit builds on a complex clinical history. Beyond just recording today’s symptoms, providers are connecting diagnoses, staging, chemotherapy regimens, biomarker testing, imaging, treatment responses, side effects, referrals, and follow-up plans.

That complexity makes oncology one of the most documentation-intensive specialties in medicine, often extending documentation well beyond scheduled clinic hours.

Marvix AI was selected by Medical Oncology & Hematology Consultants (MOHC), part of The US Oncology Network (USON), to help reduce the documentation burden on oncology providers without compromising the quality and completeness of clinical documentation. To understand the impact of Marvix AI in day-to-day clinical practice, we tracked key operational and provider outcomes over a three-month period.

The Challenge: More Time On Paperwork, Less Time On Patients

Before implementing Marvix AI, providers at MOHC faced three challenges:

  • 14.6 minutes spent documenting every patient
  • 82 minutes of documentation after clinic each day
  • 90% of providers reporting documentation as a contributor to burnout

Together, these baseline data showed that documentation was consuming valuable clinical time and extending providers' workdays, creating an opportunity to improve efficiency without compromising documentation quality.

What Changed After Three Months

Over the three-month period, providers generated 3,853 clinical notes using Marvix AI from more than 1,100 hours of recorded patient consultations.

  1. 30% Reduction in Documentation Time
Time spent on documentation per patient: Before Marvix AI vs with Marvix AI

Marvix reduced the average time providers spent documenting each patient from 14.6 minutes to 10.25 minutes, saving 4.35 minutes per encounter. Across the three-month period, this translated into approximately 245 hours of documentation time saved. Based on an estimated provider value of $200 per clinical hour, this represented approximately $48,592 in estimated productivity gains and an estimated 7.8× return on investment after accounting for the cost of Marvix.

Percentage of providers finishing a note in under 10 mins: Before Marvix AI vs with Marvix AI

The improvement was reflected in provider behavior as well. Following implementation, 60% of providers completed documentation in under 10 minutes, compared with 20% at baseline.

  1. 23% Reduction in After-Hours Documentation
Average time spent documenting after clinic hours: Before Marvix AI vs After Marvix AI

Average time spent documenting after clinic declined from 82 minutes to 63 minutes per day, returning 19 minutes to providers each day.

By the end of the 3-month period, 70% of providers were completing their documentation in less than an hour after the clinic.

  1. Provider Feedback Reinforced the Results

    The operational improvements were reflected in provider feedback as well. Providers consistently described feeling less occupied by documentation during patient visits.
“Marvix AI has significantly improved not only my workflow but work-life balance. I spend more time engaged with patients rather than on the computer. Burnout has significantly decreased. I no longer have the burden of worrying about staying up-to-date on notes and working outside of office hours on weekends. I have my personal life back again.”
— Nicole Schneider, APP

Provider sentiment aligned closely with the measured outcomes. 90% of the providers reported a reduction in documentation-related burnout, with 50% describing that reduction as significant. 70% said they were able to spend more time maintaining eye contact and engaging with patients during consultations

“Without a doubt, that time with the patient made both Jake and the patient feel better. Marvix has undoubtedly improved many aspects of care, not to mention quality of life and work-life balance.”
— Amy Brett, APP
  1. Improved Documentation Quality

Along with reducing documentation time, providers reported better documentation quality. 90% of the providers said the quality and completeness of their documentation improved, with overall satisfaction reaching 4.3 out of 5.

“It has decreased the amount of time I spend completing visit notes and has captured elements of the visit I might have otherwise forgotten or omitted from documentation.”
— Jodie Delesio, APP

Conclusion

Over three months, Marvix AI delivered measurable improvements in documentation efficiency, after-hours workload, documentation quality, and provider experience at Medical Oncology & Hematology Consultants (MOHC), part of The US Oncology Network (USON).

Unlike generic ambient documentation tools, Marvix AI is designed to support the complexity of specialty care documentation. These outcomes demonstrate Marvix’s ability to reduce administrative burden while maintaining the quality and completeness of clinical documentation.

Key Outcomes

Metric Before With Marvix Change
Documentation time per patient 14.6 min 10.25 min −30%
After-hours work per day 82 min 63 min −19 min
Providers finishing under 10 min 20% 60%
Providers under 1 hr after clinic 70%
Reported reduced burnout 9 of 10
Said note quality improved 90%
Documentation satisfaction 4.3 / 5

Curious what Marvix could do for your practice? Book a demo with us to know more.

About The Study

The outcomes in this article are based on a three-month study conducted at Medical Oncology & Hematology Consultants (MOHC), part of The US Oncology Network (USON).

Reported outcomes combine objective platform usage data such as clinical notes generated, documentation time saved, and recorded consultation hours, with provider survey responses collected during the pilot. Financial estimates were calculated using an assumed provider value of $200 per clinical hour and are intended to illustrate the potential operational value of reclaimed provider time. Actual financial outcomes will vary depending on provider compensation models, patient volumes, practice workflows, and technology adoption.

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