How AI Is Helping Healthcare Companies in Tampa Cut Costs and Improve Efficiency

Tampa's hospitals are leaning hard into AI because the results are concrete: Tampa General's multi‑year work with Palantir - expanded in 2024 into a systemwide Care Coordination Operating System - helped cut patient placement time by 83% and reduced PACU holds by 28%, while ambient‑listening tools and Nuance's DAX Copilot (deployed to more than 500 physicians) have slashed documentation time roughly in half, freeing clinicians for bedside care; similarly, AI and computer‑vision tools in ORs (deployed in 28 of 52 rooms) are saving over 3,000 minutes a week and could enable some 600 additional procedures in year one.

Those measurable efficiency and capacity gains explain Tampa's rapid adoption, even as local leaders emphasize governance to manage bias, privacy, and clinician trust.

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“We're seeing real, measurable improvements in fewer infections, better patient outcomes, and more lives saved. With the help of AI, providers spend more time with patients and less time buried in paperwork.” - Laura DeBerardinis, Senior Nurse Manager, Tampa General

Tampa General's deployment of Apella reads like a practical blueprint for AI-driven savings: the platform layers AI, computer vision and real‑time communications to give perioperative teams a 360‑degree, live view of operating rooms so staff can predict case and turnover durations, get staffing recommendations, and spot process bottlenecks before they cascade through the day - which shortens time in the OR, lowers clinical risk, accelerates recovery, and frees up rooms and people to treat more patients.

Those workflow gains translate into tangible cost avoidance (less idle OR time, fewer delays, smarter staffing) and stronger access to high‑quality surgical care across Tampa's health system; learn more from Tampa General's announcement about the Apella deployment or Apella's perioperative capabilities summary for surgical teams.

“Through innovation and technology such as Apella, we're giving our teams the tools and information to enhance quality, strengthen safety and improve patient outcomes.” - John Couris, President and CEO of Tampa General Hospital

AI is reshaping how Tampa's ORs run day-to-day: Tampa General's rollout of the Apella perioperative platform uses cameras, computer vision and AI to automate time tracking, predict case and turnover durations, and even suggest staffing so teams can schedule with surgeon‑specific accuracy rather than relying on error‑prone manual timestamps; the system is active in 28 of 52 rooms and has helped reclaim more than 3,000 minutes per week - enough capacity to add roughly 600 procedures in year one.

By feeding live, 360° insights to schedulers and perioperative leaders, the tools let staff make small, real‑time adjustments that prevent delays, shorten OR time, and free clinicians for clinical work instead of calls and paperwork.

Read Tampa General's announcement about Apella or the independent coverage of the deployment to see how predictive analytics and ambient sensors are turning OR logistics from guesswork into data‑driven operations.

“The new technology is entirely automated and captures everything, ‘wheels in to wheels out to wheels in again,'” - Kathleen Ulrich, senior vice president of perioperative services at Tampa General Hospital (HealthTech).

“OpenTable” for operating rooms

: AI that surfaces live room status, predicts case end times and suggests the next best use of a bay so schedulers can seat the next patient with confidence instead of chasing late starts - an approach already taking root across Florida health systems from Tampa General's perioperative work to broader statewide research and deployments.

UF Health's AI programs and its “ICU of the Future” research show how high‑quality data and predictive models can support real‑time decision making, while statewide reporting on Florida hospitals highlights practical wins - from automated patient transport to streamlined workflows - that together make dynamic, demand‑driven scheduling possible across a hospital campus (UF Health AI research and ICU of the Future program, AI innovations in Florida hospitals case study).

When scheduling shifts from static calendars to live, model‑backed recommendations, the payoff is tangible: fewer empty rooms, shorter turnover waits, and more predictable days for surgeons and patients alike - like seeing the next available table and knowing the kitchen will be ready when you arrive.

Reducing clinician burden with ambient documentation is moving from promise to practice across Tampa: Tampa General's June 2024 rollout of DAX Copilot - now used by more than 500 physicians - ambiently captures multi‑party conversations, identifies speakers, extracts key observations and converts the patient story into specialty‑specific clinical summaries in seconds, a change reported to cut documentation time roughly in half and to reduce burnout for nearly three‑quarters of users; the tool is integrated into the Epic EHR so notes, orders and after‑visit summaries flow into existing workflows while meeting HIPAA and security standards, meaning clinicians spend less time “tethered to keyboards” and more time bedside, and patients notice the difference (about 85% say their physician is more personable).

For a closer look at the hospital deployment and the Nuance–Epic integration that enables it, see the Tampa General DAX Copilot announcement and Epic DAX Express overview.

“Simply put, documentation is necessary, but it's a growing burden on all involved. At Tampa General Hospital, we're not willing to settle for the status quo. We're focused on pursuing innovative solutions to transform the way we deliver care. With the help of AI, we're easing the burden of documentation on providers and in turn giving them the ability and the additional time to focus on our top priority - our patients.” - John Couris, president and CEO of Tampa General Hospital

In Florida operating rooms, AI-enabled imaging and anatomy mapping are turning intuition into an exact, 3D plan: HCA Florida Trinity's new robotic platform pairs AI and virtual reality to render a patient's unique anatomy with computing power “10,000 times” greater than prior systems, letting surgeons plan segmental lung resections that preserve healthy tissue instead of removing an entire lobe (HCA Florida Trinity AI robotic-assisted surgery announcement); in central Florida, AdventHealth is testing CytoVeris' MarginASSURE multispectral imaging to assess prostate margins intraoperatively and deliver near‑real‑time tissue characterization to guide nerve‑sparing decisions (AdventHealth CytoVeris MarginASSURE multispectral imaging study).

University of Florida engineers are feeding stereoscopic video and kinematic data into machine‑learning models to boost robotic precision, map instruments and anatomy, and accelerate surgical skill assessment - advances that aim to shorten OR time, reduce radiation and dye use, and measurably improve recovery.

The net effect in Florida: more targeted resections, fewer repeat operations, and a clearer path to safer, faster surgeries that preserve patients' function and speed their return home (University of Florida AI surgical robotics research).

“The segmentation profile benefits the patient by allowing the surgeon to perform a resection by removing less lung tissue than a lobectomy. Using AI/VR helps a surgeon visualize the exact location of the tumor in the lung, thus allowing us to remove less lung tissue with the cancer.”

- Mathew Ninan, MD, Thoracic Surgeon

Automating patient logistics has become a practical lever for efficiency in Tampa hospitals: Tampa General's partnership with Enroute layers AI on top of the hospital's EMR so dispatchers and transporters gain real‑time visibility of staff location and equipment (wheelchair, stretcher) and the system can automatically assign the closest, properly equipped transporter; the SaaS platform can create multiple assignments at once, coordinate trips to reduce redundant moves, speed discharge notifications and boost bed utilization, and in pilot departments transport times fell as much as 35% on average.

Built through TGH Innoventures' Co‑Lab and integrated into a dedicated device carried by transport staff, the tool turns a once-manual dispatcher workflow into a data‑driven, campus‑wide flow manager - Enroute's approach is described as making intra‑hospital transport “as easy and as seamless as using your phone to hail and track your ride,” and Tampa General's press materials and industry coverage outline how tighter logistics free rooms, speed OR handoffs, and improve patient experience across the system (see the Tampa General press release on Enroute or TechTarget's coverage of the pilot for details).

“With Enroute, we can see the transporters' availability, location, and if they have a wheelchair or stretcher with them in real time. The system can then automatically assign the closest transporter with the right equipment to transport that patient. It's critical to our world-class care that the patient transport department be as efficient as possible in moving patients to the services they need to recover.” - Donna Tope, senior director of support services at Tampa General Hospital

Tampa's AI investments have produced concrete, countable wins: a one‑time study of Tampa General's command center and predictive tools documented roughly $40M in operational savings, the elimination of 20,000 excess patient days and the equivalent of about 30 beds of added capacity (HealthLeaders Media: Tampa General $40M operational savings); perioperative AI like Apella reclaimed more than 3,000 minutes per week - enough to schedule roughly 600 extra procedures in year one - and is live in 28 of 52 ORs to tighten turnover and boost throughput (Apella perioperative AI case study at Tampa General).

Systemwide coordination and Palantir‑backed analytics drove an 83% cut in patient placement time and a 28% drop in PACU holds, while ambient listening tools (DAX Copilot and Microsoft integrations) halve documentation time for many clinicians and promise to return hours per shift to bedside care (Tampa General ambient listening rollout for nurses).

Those stacked gains - faster placement, fewer transport delays, shorter stays and reclaimed OR minutes - translate directly into lower cost-per-case, fewer diverted ERs and measurable capacity to treat more patients without building new beds.

Metric	Impact (Tampa)
Operational savings	$40M (CareComm)
Excess patient days eliminated	20,000
Added capacity	~30 beds (equivalent)
OR minutes reclaimed	3,000+ per week (~600 procedures/yr)
Patient placement time	↓83%
PACU holds	↓28%
Documentation time	↓50% for many users
Transport times (pilot)	↓up to 35%

“We're seeing real, measurable improvements in fewer infections, better patient outcomes, and more lives saved. With the help of AI, providers spend more time with patients and less time buried in paperwork.” - Laura DeBerardinis, Senior Nurse Manager, Tampa General

Tampa providers moving from pilot to scale should treat AI like a clinical service - start with a formal security review and small pilots, then layer governance, clinician training and continuous monitoring onto any rollout; Tampa General's OR program, for example, required an IT security sign‑off, facilities‑led wiring for four cameras per room, and a major change‑management push so staff understood “why” as well as “how” (Tampa General AI operating room security review and clinician education).

At the same time, invest in data protections and vendor due diligence: Presidio notes 57% of healthcare executives name data exposure a top concern and recommends encryption, anomaly monitoring and strict controls around third‑party tools to prevent shadow AI and leaks (Presidio data security recommendations for healthcare AI).

Finally, build regulatory and ethical guardrails up front - document HIPAA compliance, map FDA pathways for SaMD, run bias and explainability audits, and create cross‑functional AI governance so models are validated, auditable and human‑overseen before they touch patient care (Regulatory and ethical considerations for AI adoption in healthcare).

These steps reduce the chance of rushed implementations, preserve patient trust, and keep measurable gains - like shorter stays and reclaimed OR minutes - from evaporating under legal or operational risk.

“The new technology is entirely automated and captures everything, ‘wheels in to wheels out to wheels in again,'” - Kathleen Ulrich, senior vice president of perioperative services at Tampa General Hospital

Vendors and tools driving Florida's OR AI wave are led locally by Apella, whose perioperative platform combines always‑on ambient sensors, computer vision and predictive AI to give teams a 360‑degree, real‑time view of rooms, forecast case and turnover durations, and even suggest staffing - capabilities detailed in Apella's case study and implementation guides (Apella perioperative platform overview and case study).

Tampa General's announcement shows how that stack cut manual checks and interruptions - about 1.4 fewer door openings per case - which the vendor estimated translated into roughly 40,000 minutes of clinician productivity saved in the first 10 months; successful rollouts also lean on field engineering, facilities and IT coordination to install sensors, integrate with the EHR, and train models for each hospital's rhythms (Tampa General Hospital AI-powered operating room safety and efficiency announcement), making Apella the most visible vendor moving OR AI from pilot to scale in Florida.

“Through innovation and technology such as Apella, we're giving our teams the tools and information to enhance quality, strengthen safety and improve patient outcomes. We're also increasing access for more patients to benefit from the exceptional, academic-based care we offer at TGH.” - John Couris, President and CEO of Tampa General Hospital

Tampa healthcare leaders measure AI ROI the way surgeons plan an operation: start with clear goals, map the risks, and track the vitals - financial and clinical - over time.

That means running a thorough total cost‑of‑ownership analysis (software, hardware, integration, training and hidden change‑management costs), establishing baseline KPIs (operational efficiency, clinical outcomes, financial indicators and patient satisfaction), and phasing pilots into scale with embedded ROI timelines so projects are treated like capital investments rather than one‑off experiments; these best practices mirror the playbook in industry guidance on measuring AI's cost and return (Measuring AI Cost and Return on Investment for Healthcare AI Implementation) and the rise of AI‑specific KPIs for revenue cycle and scheduling described by Black Book's RCM framework.

Practical moves that boost confidence include stressing data readiness (ten KPIs for data quality and accessibility), tying governance and finance into a cross‑functional prioritization committee, and using healthcare‑specific value models (QALYs, PROMs) alongside dollars saved - because the clearest wins in Tampa have come when teams can point to minutes reclaimed, fewer denials, and beds freed rather than vague promises.

Treating AI like an operational investment - measure, iterate, scale - turns pilot wins into systemwide capacity, not just good headlines.

Measure	Why it matters
Total Cost of Ownership	Captures software, infra, training and hidden rollout costs
KPIs (operational, clinical, financial, patient)	Links AI performance to capacity, outcomes and revenue
Phased pilots + embedded ROI timelines	Enables accountable scaling and rapid stop/go decisions

“This report marks a pivotal moment in healthcare finance. AI-driven automation is reshaping revenue cycle operations, and this is the first independent research effort to quantify its real-world impact.” - Doug Brown, Founder, Black Book Research

Expect practical change, not sci‑fi: Tampa's AI wave is already turning into faster bed placement, shorter sepsis stays and reclaimed OR time that boosts capacity without new construction - results driven by Tampa General's Palantir‑backed Care Coordination Operating System (an 83% cut in placement time and a 30% drop in sepsis length of stay) and Apella's perioperative platform that gives teams a live, 360° view of rooms to cut turnover and delays; read the FloridaPolitics recap of the Palantir work or Apella's case study to see the operational playbook in action.

Clinicians and patients should expect steadier schedules, fewer administrative bottlenecks and more bedside time as ambient documentation (now used by 500+ physicians) halves note time, but leaders also warn that careful governance, clinician training and vendor due diligence remain essential as systems scale.

For Florida professionals wanting practical AI skills to help run, evaluate or govern these tools, Nucamp's 15‑Week AI Essentials for Work bootcamp registration teaches workplace AI, promptcraft, and applied workflows - useful preparation for the real, measurable transformations underway in Tampa's hospitals.

Bootcamp	Length	Early bird cost	Registration
AI Essentials for Work	15 Weeks	$3,582	Register for AI Essentials for Work (15‑Week Bootcamp)

“We're seeing real, measurable improvements in fewer infections, better patient outcomes, and more lives saved. With the help of AI, providers spend more time with patients and less time buried in paperwork.” - Laura DeBerardinis, Senior Nurse Manager, Tampa General