Top 10 AI Prompts and Use Cases and in the Healthcare Industry in Oklahoma City

Oklahoma City is becoming a practical lab for healthcare AI because local startups, hospitals, and research centers are piloting tools that can predict patient changes, personalize genomic risk, and generate synthetic data to protect privacy - concrete gains for both urban clinics and rural Oklahomans.

An Oklahoma biotech, General Genomics, is partnering with the OKC Innovation District to build AI that helps predict health changes for patients (General Genomics and OKC Innovation District AI partnership), while university analysis of generative models outlines uses from imaging to drug discovery and highlights risks around data quality, bias, consent, and privacy that local pilots must address (OKCU study: Generative AI impact on healthcare).

The bottom line: Oklahoma City can speed diagnosis and target prevention - if providers run measured pilots that track ROI, protect patient data, and follow emerging state policy.

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"How can we help; how can we make it easier for doctors."

Selection of the Top 10 use cases used pragmatic, evidence-based criteria grounded in Mercy's real-world pilots across Oklahoma: priority went to prompts that demonstrably free clinician time (AI-assisted lab explanations, scheduling and HR bots already on Mercy's roadmap), scale across sites, and expose clear ROI metrics such as reduced length of stay from Azure analytics - while insisting on strict data governance and staged testing with patients and clinicians.

Criteria included clinical impact (time saved on admin tasks and faster imaging triage), technical feasibility on the Mercy–Microsoft Azure stack, regulatory and privacy safeguards, and measurable patient benefit validated through Mercy's large test panel and rollout plans.

Cases that rose to the top - patient-facing explanations, appointment automation, internal policy chatbots, ambient scribing, imaging alerts - map directly to Mercy's published use cases and early deployments, so Oklahoma City providers can pilot with local evidence and a path to scale (Mercy and Microsoft AI collaboration press release, regional coverage of Mercy Hospital Oklahoma AI plans) and follow best-practice imaging safeguards used in recent Mercy rollouts (Mercy AI-powered imaging adoption report).

A concrete test: use cases were required to show a measurable clinician-time or patient-experience improvement in Mercy's pilots before being elevated to the Top 10 list, making adoption in OKC less speculative and more operational.

Mercy metric (FY2024)	Value
Hospitals	33
Co-workers	52,267
Physicians	2,604

"We're a heavily regulated industry and nurses are incredibly burdened right now."

Patient-facing generative AI can turn cryptic lab reports into clear, actionable explanations for Oklahoma patients by pulling results from MyChart, flagging abnormal values, and linking next steps to local Mercy workflows - helpful for rural Oklahomans who often call clinics for interpretation.

Mercy already shares most lab results via MyChart/MyMercy and notes routine lab results are

usually available the next morning

so an AI that annotates a CBC (for example, WBC 4,500–10,000 cells/mcL) with plain-language meaning, suggested questions for a provider, and whether a result was sent to Quest Diagnostics for outreach testing could cut call-center volume and reduce patient anxiety.

Combine Mercy's patient delivery routes (Mercy Laboratory Services FAQs for patients) with MyChart access (MyChart Mercy patient portal information) and best-practice interpretation guidance (MedlinePlus guide to understanding your lab results) to build explainers that cite reference ranges, note prep/follow-up, and prompt urgent outreach when needed - one concrete win: fewer same-day nurse callbacks for routine next-morning labs.

Delivery	Typical turnaround
MyChart/MyMercy	Routine tests: usually available the next morning
Outreach tests	May be performed by Quest Diagnostics; timing varies

AI-assisted appointment scheduling and call handling is already on Mercy's roadmap for Oklahoma patients: Mercy plans to apply Microsoft Azure OpenAI generative AI to take patient calls, book appointments, and surface recommended follow-up actions so more needs are resolved in a single interaction - reducing repeat calls and easing clinic front-desk load (Mercy–Microsoft generative AI collaboration).

That same consumer-first access model underpins Mercy's urgent care strategy with GoHealth, where co-branded centers across the Midwest offer seven-day hours, online pre-registration and check-in, and EHR/MyMercy integration - practical features that make AI-driven scheduling immediately useful for busy Oklahomans and rural patients who rely on extended hours and clear digital check-in (Mercy–GoHealth urgent care partnership).

The combined play - AI to handle calls plus integrated urgent-care workflows - translates to fewer hold times, fewer callbacks, and faster access to same-week care for Oklahoma communities.

“Our partnership with GoHealth Urgent Care will help fulfill our mission to transform health in our communities.”

An internal HR and policy chatbot modeled on Mercy's Joy can give Oklahoma clinicians and staff instant, consistent answers to benefits, leave, and policy questions - especially during high-demand windows like open enrollment - by indexing intranet documents and routing only complex cases to human specialists; Mercy reports Joy reduces call volume to benefits teams and runs on Microsoft Azure OpenAI Service, so one concrete win for Oklahoma sites is fewer routine HR calls and faster escalation for tricky cases that require human review (Mercy Joy benefits chatbot launch on Microsoft Azure OpenAI Service).

For OKC health systems with thousands of staff, pairing a policy-aware bot with clear privacy and compliance contacts helps maintain governance while cutting HR response time - see Mercy's corporate compliance and HR contact framework for operational guardrails (Mercy corporate responsibility and HR contacts for compliance and governance).

Metric	Value
Co‑workers across Mercy footprint	More than 50,000 (includes Oklahoma)
Platform	Microsoft Azure OpenAI Service
Primary use	Benefits & HR policy Q&A, 24/7 escalation routing

"With Joy, it's as simple as having a conversation with someone who has all the answers and can respond to your questions and offer an explanation 24/7."

Ambient scribing with tools like Heidi brings immediate, practical benefits for Oklahoma clinicians by turning live conversations into EHR‑ready notes so providers spend less time on screens and more time with patients - Heidi's materials report clinicians reclaiming up to three hours daily and cutting documentation time by as much as 40%, with adaptive templates that learn specialty preferences and plug into common EHR workflows (Heidi Health ambient scribe guide for clinicians).

For OKC practices juggling high clinic volumes and rural outreach, that time can translate to extra same‑day appointments or shorter after‑hours charting; Heidi also offers a basic free tier and SDK/EHR integrations to simplify pilots and reduce vendor friction (Healthcare IT Today article on Heidi Health free AI medical scribe).

Early independent coverage highlights both gains and governance questions - use staged rollouts, clinician edit loops, and local privacy reviews to preserve accuracy and trust while measuring FTE and patient‑experience wins (BMJ analysis of ambient scribing governance and safety).

Metric	Value (Heidi)
Time reclaimed per clinician	Up to 3 hours/day
Documentation reduction	Up to 40%
Specialties supported	300+
Patient sessions	2+ million weekly

“I can listen more intently and pick up non‑verbal cues, which are important in the GP setting.”

Predictive and real-time clinical decision support is already delivering measurable wins that Oklahoma City providers can emulate: Mercy's Azure-based analytics and machine‑learning pipeline has been used to identify patients at risk for conditions like hypertension and congestive heart failure and - by surfacing “next best actions” on dashboards - helped remove thousands of hospital‑stay days across its system, shortening length of stay for many patients (Mercy and Microsoft Azure digital strategy for predictive clinical analytics).

Complementary point‑of‑care alerts for documentation and coding show a clear operational payoff: Stanson Health's clinical decision support implementation at Bon Secours Mercy Health activated 30 actionable HCC alerts and documented over 35,000 HCC categories in six months, improving risk capture and enabling more accurate care planning and revenue alignment - concrete levers Oklahoma systems can pilot to tighten risk adjustment and trigger real‑time clinical actions (Stanson Health CDS HCC alerts case study and results).

The combined lesson for OKC: pair cloud‑scale data unification with a small, well‑tuned alert set to reduce clinician burden while improving predictive triage and resource allocation.

Metric	Value
HCC categories documented (Bon Secours Mercy Health)	35,000+ (6 months)
HCC alerts activated	30
Mercy patient data footprint	Nearly 5 petabytes
Outcome (Mercy)	Removed thousands of hospital‑stay days

“We've reduced our average length of stay… removed thousands of days of hospital stay over the last year by giving our care teams smart dashboards and better visibility into the factors that affect when we can send patients home.” - Brian Albrecht

Genomics-based risk prediction can give Oklahoma City clinicians, payers, and public‑health teams a practical way to plan prevention: General Genomics' SYN46™ offers privacy‑compliant, downloadable synthetic datasets and virtual patient models that simulate individual health trajectories so teams can forecast disease trends and test interventions without exposing PHI (SYN46™ synthetic data and virtual patient models for healthcare planning).

By combining SYN46™ scenarios with the company's AI platforms (Curo46™) and R&D stack, local hospitals or county health departments can run realistic outbreak, screening, or risk‑stratification pilots - measuring impact on rural cohorts and payer risk pools before clinical rollout - and use the same synthetic sets for insurer risk analysis, claims modeling, and preparedness planning (General Genomics innovation and R&D for AI-driven health solutions).

The net result for OKC: safer, faster design of targeted prevention with datasets that protect privacy and make pilot ROI measurable.

Product	Capability	Local application (Oklahoma)
SYN46™	Downloadable synthetic datasets; virtual patient simulations	Run prevention and outbreak scenarios for urban and rural populations without PHI
Curo46™	AI-driven predictive health risk management	Integrate risk scores into care pathways and payer models

Computer vision for imaging triage - already used by Northwestern Medicine through the Dell AI Factory with NVIDIA - can speed detection and alerting of critical findings so Oklahoma hospitals and rural clinics get faster, actionable flags without moving PHI offsite; Dell's validated stack pairs AI software, GPU/CPU-optimized infrastructure, and orchestration to run models that analyze DICOM streams and send real-time caregiver alerts (Dell AI Factory computer vision customer story for healthcare imaging triage).

A recent Dell PoC shows a ResNet50 pneumonia classifier deployed on PowerEdge servers with AMD EPYC CPUs achieving up to 1,390 images/sec after optimizations and keeping inference on‑premises - demonstrating that regional systems can process large imaging volumes quickly while preserving privacy and integrating with existing DICOM/Orthanc and OHIF viewers (CPU‑based pneumonia PoC on Dell PowerEdge servers and on‑prem DICOM integration); concrete payoff for Oklahoma: faster triage alerts to clinicians, reduced radiologist bottlenecks, and a clear technical path to pilot imaging automation within local IT governance.

Metric	Value
Model	ResNet50 (pneumonia classifier)
Inference throughput (default)	337 images/sec
Inference throughput (optimized)	1,390 images/sec
Validation accuracy	85%
Deployment	Dell PowerEdge servers with AMD EPYC CPUs; on‑prem DICOM pipeline

Digital twins and fast simulation give Oklahoma City health systems a risk‑free way to rehearse decisions on a per‑patient basis - Duke's work shows vascular twins can reconstruct a patient's vasculature and simulate stent size and placement before surgery, helping teams choose options that may minimize complications (Duke digital twins for surgical planning); GE HealthCare's Digital Twin approach extends that capability to hospital operations, letting command centers model capacity, unit redesign, and pediatric surge timing so leaders can test tradeoffs without costly pilots (GE HealthCare digital twin capacity and surge simulation).

Clinical results are emerging: a multicenter digital‑twin diabetes program reported a 1.8% A1c reduction and 89% of participants below 7% at one year, proving twins can move from theory to measurable patient benefit - Oklahoma City hospitals can pilot surgical, outpatient, or capacity twins on local infrastructure, keep PHI on‑premises, and measure ROI in months (Mayo Clinic Platform clinical digital twin examples).

Application	Example Source	Concrete result
Surgical planning (vascular)	Duke	Simulate stent size/placement to compare options
Capacity & surge planning	GE HealthCare	Model command‑center scenarios and pediatric surge timing
Personalized treatment simulation	Mayo Clinic review / diabetes study	1.8% A1c drop; 89% <7% at one year

“The DT system continuously collects and analyzes data from various sensors and inputs, allowing it to offer personalized dietary and lifestyle recommendations that are precisely calibrated to minimize PPGRs [postprandial glucose response] and improve overall glycemic control.”

Agentic AI turns scattered automations into coordinated, multi-step “agents” that carry a patient from intake to discharge - verifying insurance, proposing optimized appointment times in seconds, auto-filling intake data, and handing context-rich summaries to clinicians - so Oklahoma City clinics can cut repetitive front‑desk work and free staff for higher‑value care; practical pilots should start small (automating intake or documentation) and scale modular agents into an orchestrated workflow rather than rip-and-replace the EHR (agentic AI workflow in healthcare case study).

Real-world guidance urges human‑in‑the‑loop checkpoints, strong governance, and staged rollouts to manage clinical risk and ethical concerns while capturing measurable ROI (adaptive, ethical AI in healthcare study), and strategy papers show agents can safely reduce administrative burden when paired with clear guardrails and targeted use cases (McKinsey analysis of AI agents in healthcare); one concrete starting win for OKC systems is a scheduling agent that verifies eligibility, finds an optimal slot, and updates calendars automatically - delivering faster access for patients and fewer callbacks for staff.

Generative, ChatGPT‑style tools and Smart Insights platforms let Oklahoma providers turn one-off marketing copy and generic reminders into hyperlocal, multi‑channel outreach - SMS, email, web content, and automated phone scripts - that speaks to OKC neighborhoods, tribal communities, and rural patients while keeping EHR data inside secure workflows; proven tactics include AI chatbots and automated answering to triage questions and surface scheduling options (Generative AI patient‑outreach strategies for improved engagement), personalized reminders and two‑way rescheduling that can materially cut no‑shows and recover revenue (Case study: AI reduces patient no‑shows), and local vendor partnerships to integrate messaging into existing ops (Calvient: Oklahoma AI healthcare support company).

One concrete win: AI‑driven reminders and two‑way outreach have produced a 32% drop in no‑shows, a $100K monthly revenue lift in a pilot, and large admin time savings - making outreach automation a near‑term ROI play for OKC clinics that need higher clinic utilization and fewer callbacks.

Metric	Pilot result
No‑show reduction	32%
Monthly revenue recovery	$100,000
Admin workload reduction	40%

"Maven equips the team with tools to identify, capture, share and report data to impacted individuals, the local healthcare community, and the CDC."

Getting started safely in Oklahoma City means pairing a tight, measurable pilot with clear governance: pick one high‑value use case already proven in local pilots - patient lab explainers or AI-assisted scheduling - and set success metrics (reduced nurse callbacks, faster same‑week access, or lower no‑show rates), require human‑in‑the‑loop review, and document transparency and data sources to meet emerging state rules such as the Oklahoma Artificial Intelligence Bill of Rights and utilization‑review disclosures (Oklahoma House AI bills and disclosure rules - Government Modernization & Technology Committee).

Operate pilots on trusted stacks used by regional systems (for example, Mercy's Azure collaboration) and run them inside existing EHR/privacy controls so PHI stays protected while teams measure ROI (Mercy and Microsoft Azure collaboration for clinical AI pilots).

Parallel this with practical staff training - short, work-focused courses that teach prompt design, governance checklists, and pilot measurement - to turn technical pilots into repeatable programs (AI Essentials for Work bootcamp - practical AI skills for the workplace); one concrete payback to aim for is reclaiming clinician time so clinics can add same‑day slots without new hires.

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“In the age of AI, transparency is paramount. The Oklahoma Artificial Intelligence Bill of Rights empowers Oklahomans and ensures citizens have the right to understand AI interactions and protect their privacy and data.” - Rep. Jeff Boatman