Top 10 AI Prompts and Use Cases and in the Healthcare Industry in Columbia

Columbia's health ecosystem is rapidly turning AI prompts from curiosity into clinic-ready tools - driven by Prisma Health's 10‑year strategic partnership with Siemens Healthineers to build an Intelligence Insights Center that uses de‑identified patient data to speed more precise diagnoses and reduce administrative burden (Prisma Health and Siemens Healthineers partnership announcement), University of South Carolina work on virtual‑assistant telehealth to monitor mental‑health between visits (University of South Carolina AI telehealth project), and local deployments of RPM/chatbots shown to improve chronic‑care access and cut contact‑center volume (over 172,000 chatbot engagements).

For clinicians and administrators in South Carolina, precise prompt design is the bridge between raw models and safer, faster workflows - a skill taught in practical programs like Nucamp's Nucamp AI Essentials for Work bootcamp, which focuses on usable prompts, tool selection, and real‑world validation so teams can measure impact at the bedside and in the billing office.

Program	Length	Cost (early bird)	Register
AI Essentials for Work	15 Weeks	$3,582	Register for the AI Essentials for Work bootcamp

“We are excited to announce this innovative, long-term relationship to enhance quality and create even more value for our patients, and support our excellent team members and physicians in providing the best patient care and service possible.”

Selection used three pragmatic filters tailored for Columbia and South Carolina providers: measurable ROI, workforce impact, and regulatory feasibility. Measurable ROI emphasized prompts tied to clear metrics - like reduced length of stay and staff redeployment - so teams can validate value at the bedside and in billing (Measuring ROI through reduced length of stay and staff redeployment in Columbia healthcare); workforce impact prioritized use cases that enable at‑risk roles to pivot into higher‑value tasks, for example moving utilization‑review nurses toward complex case management (How utilization-review nurses can pivot to complex case management in Columbia); and regulatory feasibility filtered for prompts compatible with local rules and auditability (AI policy and compliance for South Carolina healthcare providers (2025)).

The result: ten use cases that are immediately testable, auditable, and likely to free clinical time for complex care - metrics Columbia organizations can track from day one.

Embedding clinical decision‑support (CDS) prompts into electronic health records is a practical lever for safer, faster diagnosis and treatment workflows in Columbia: local EHR consolidation efforts - such as Prisma Health's Epic rollout documented in HCTec's legacy‑EHR case study - create the single medication workflow where prompts can fire at the point of prescribing (HCTec case study on Prisma Health Epic transition and legacy‑EHR support); the international literature likewise shows growing interest in pharmacogenomic CDS implementations that aggregate genotype‑aware alerts into EHRs, which clinicians can view without leaving the chart, making precision prescribing actionable in real time (Pharmacogenomic Clinical Decision‑Support scoping review (DOI:10.1002/cpt.2711)).

Columbia's own research community - highlighted at the 5th National Big Data Health Science Conference held in Columbia, SC - supplies local data and collaboration pathways to pilot and evaluate prompt designs before system‑wide deployment (Proceedings of the 5th National Big Data Health Science Conference (Columbia, SC)); the immediate payoff: clinicians get concise, auditable genotype or guideline alerts inside Epic's meds screen so decisions can be made at the bedside and measured against clear implementation KPIs.

Resource	Key details
Pharmacogenomic Clinical Decision Support: A Scoping Review	Authors: D. Max Smith et al. - First published: 15 July 2022 - Pharmacogenomic CDS scoping review (DOI:10.1002/cpt.2711)

Radiology second‑reads for chest X‑ray and lung CT become practical in Columbia when AI is embedded into the reporting pipeline and PACS/RIS workflow: recent work describes a novel reporting workflow that enables automated pre‑population of structured radiology reports with AI results (Automated integration of AI into structured radiology reports - Insights into Imaging (Mar 2024)), vendors document end‑to‑end PACS/RIS integration that prioritizes critical findings and minimizes IT lift (PACS AI guide for radiology workflow integration - Aidoc), and product studies highlight chest X‑ray/CT workflows that route AI‑flagged cases for rapid second reads (Rayscape study on chest X‑ray and lung CT AI reporting workflows - Rayscape research).

The practical payoff for South Carolina systems: AI‑prepopulated, structured reports speed triage and create auditable findings that align with local compliance needs, so radiology teams can measure turnaround and redeploy staff toward complex interpretations.

Resource	Key detail
Automated integration of AI into structured radiology reports - Insights into Imaging (Mar 2024)	Insights into Imaging - Open access; published 19 March 2024; describes automated pre‑population of structured reports
PACS AI guide for radiology workflow integration - Aidoc	Aidoc - practical guidance on integrating AI into PACS/RIS to prioritize findings and enable enterprise deployment
Rayscape study on chest X‑ray and lung CT AI reporting workflows - Rayscape research	Rayscape research page - describes CXR and lung CT AI workflows and demo/contact for integration

Well‑crafted AI prompts that prefill SOAP‑note sections and suggest candidate ICD‑10/CPT codes can turn tedious documentation into a measurable operational lever: by routing high‑confidence suggestions to coders and surfacing low‑confidence items for clinician review, teams can redeploy coders and utilization reviewers to higher‑value tasks - an ROI strategy shown in local analyses that measure gains through reduced length‑of‑stay and staff redeployment (AI prompts reducing length of stay and enabling staff redeployment in Columbia healthcare - ROI study).

Thoughtful prompt design also creates reviewable trails that let utilization‑review nurses pivot into complex case management instead of manual coding work (How AI enables utilization‑review nurses to move into complex case management in Columbia), while adherence to South Carolina AI policy and compliance guidance ensures documentation and automated code suggestions remain auditable and clinic‑safe (South Carolina AI policy and compliance guidance for clinical documentation and coding (2025)); the so‑what is simple: validated prompts can convert hours of charting into measurable clinic capacity.

Pharmacogenomics alerts turn genetic variation from an academic detail into a practical safety tool for Columbia clinicians by surfacing drug‑gene risks and dose guidance at the point of care: more than 90% of people carry at least one potentially actionable variant and the FDA lists 450+ drugs with pharmacogenomic considerations, so embedding evidence‑based PGx alerts into EHR and pharmacy workflows can prevent adverse drug reactions and tailor therapy in real time (Wolters Kluwer pharmacogenomics guidance for clinicians).

Local pilots should follow user‑centered CDS design - like TPMT alert work that emphasizes clinician workflow fit - to avoid alert fatigue and make genotype results actionable at prescribing time (BMC Medical Informatics user-centered pharmacogenomics CDS study).

The payoff is concrete: genotype‑guided adjustments changed medications for 22% of patients in a cited study, and a coordinated, multidisciplinary rollout (prescribers, pharmacists, lab/IT) plus EMR integration is the fastest path to measurable reductions in harmful ADRs and better pharmacotherapy across South Carolina practices.

Step	Action
Awareness	Educate clinicians when and why to use PGx
Alerting	Embed evidence‑based PGx alerts into EHR/pharmacy systems
Alignment	Coordinate prescribers, pharmacists, labs, IT, and counselors

“scientific advances continue to offer new options for medications that have the potential to improve and save lives. … Pharmacogenomics represents one such approach toward precision prescribing.”

Remote monitoring and telemedicine in South Carolina work best when chatbots and RPM devices are treated as a single, auditable care pathway: ensure device streams feed directly into the EHR with documented mapping and clinical‑alert rules so nurses and primary‑care teams see trend flags inside the chart (RPM EHR integration best practices for electronic medical records); pair that integration with vendor contracts that enforce HIPAA safeguards, encryption, routine audits, clear patient consent, and business‑associate agreements to shorten onboarding and preserve trust (remote monitoring vendor regulatory and HIPAA considerations).

Chatbots add measurable continuity for chronic conditions - automating symptom check‑ins, med reminders, and triage that reduce unnecessary calls and enable clinicians to focus on high‑risk patients - so pilots should track EHR‑linked alerts, adherence, and escalation accuracy from day one (AI‑enhanced remote monitoring evidence for rural chronic‑care).

Key consideration	Practical action
EHR integration	Map RPM streams to discrete fields and surface trend alerts in the chart
Data security & privacy	Require encryption, audits, consent records, and BAAs
Device & FDA compliance	Confirm device classification and intended use before deployment
Chatbot follow‑up	Measure engagement, escalation accuracy, and reduction in contact‑center volume

Population‑level prompts that forecast vaccine coverage and flag 30‑day readmission risk turn local research into operational action: studies and collaborations showcased at the 5th National Big Data Health Science Conference in Columbia, SC provide the regional context needed to train and validate models (Proceedings of the 5th National Big Data Health Science Conference - Columbia, SC (BMC Proceedings)).

When predictive prompts generate prioritized outreach lists and chart flags, health systems can track concrete KPIs - such as reduced length‑of‑stay and strategic staff redeployment - to prove program value and reallocate nurses toward high‑impact care management rather than manual case finding (Measuring ROI from reduced hospital length of stay and staff redeployment in Columbia healthcare).

Embed these pilots in South Carolina‑specific AI policy and compliance playbooks to keep forecasts auditable and clinic‑safe, so teams can confidently use predictive prompts to close immunization gaps and lower avoidable readmissions (South Carolina AI policy and compliance guidance for healthcare providers (2025)).

Resource	Key details
Meeting Abstracts - 5th National Big Data Health Science Conference	Published 16 May 2024; BMC Proceedings Volume 18, Article 9; Open access; Conference held Feb 2–3, 2024 in Columbia, SC

Connecting eligible Columbia patients to clinical trials becomes much more practical when trial‑matching is powered and coordinated: the American Cancer Society's ACS ACTS offers a personalized clinical trial matching service that partners with Massive Bio for AI‑driven matching, connects patients with ACS cancer information specialists, and arranges practical supports like lodging and transportation - services available to residents who live in or will travel to South Carolina - while intake can start via the online form, the ACS CARES app, or the 24/7 helpline at 1‑800‑227‑2345 (ACS ACTS personalized clinical trial matching service); Columbia research teams should pair such matching tools with local AI governance and compliance playbooks so trial referrals remain auditable and clinic‑safe (South Carolina AI policy and compliance guidance (2025)), enabling coordinators to focus on consent, follow‑up, and retention rather than manual trial discovery.

Resource	Key detail
AI partner	Massive Bio - AI‑driven clinical trial matching (ACS ACTS)
Availability	United States - service available to South Carolina residents
Practical support	Lodging, transportation, and ACS cancer information specialist connections
Contact	Sign‑up form, ACS CARES app, 24/7 helpline: 1‑800‑227‑2345

Design patient‑facing triage prompts to speak Colombian Spanish and fit South Carolina care paths by combining evidence from chatbot reviews, multilingual trials, and local telehealth services: the rapid review of chatbot roles, users, benefits, and limitations outlines where bots safely automate symptom screening and education (JMIR review: Chatbots in health care - roles, benefits, and limitations), while a 2025 JMIR retrospective analysis evaluates a multilingual AI care agent specifically for engaging Spanish‑speaking patients in colorectal cancer screening and fecal immunochemical test (FIT) workflows - useful when designing escalation rules and outreach (JMIR 2025: Multilingual AI care agent for colorectal cancer screening and FIT workflows).

Pair those insights with operational tools already active in South Carolina (for example, Prisma Health's Respiratory Virus chat that starts via SMS - text FLU to 47225 - and integrates symptom triage and reminders) so clinics can deploy auditable Spanish triage flows that reduce friction, increase screening outreach, and route only high‑risk patients to clinicians (Prisma Health Virtual Care: Respiratory virus SMS triage and virtual care services).

The so‑what: culturally tuned prompts plus clear escalation rules turn passive messages into measurable actions - faster triage, documented EHR escalations, and traceable outreach metrics that clinics can track from day one.

Resource	Practical use
JMIR chatbot review (PMC11303905)	Define safe chatbot roles, limitations, and audit trails
JMIR 2025 multilingual AI study	Model for Spanish‑language outreach and FIT screening pathways
Prisma Health Virtual Care	Operational SMS triage example (text FLU to 47225) to emulate local escalation

Administrative automation turns AI prompts into a practical revenue‑cycle tool for South Carolina clinics by automating ICD‑10 insertion, pre‑submission claim scrubbing, and HIPAA‑guarded workflows so billing teams spend less time fixing denials and more time closing accounts: implement appointment‑ or patient‑level ICD‑10 automation to reduce repetitive coding work (Automating ICD‑10 and process coding - AppointmentGuru tutorial), layer in South Carolina‑specific HIPAA and Medicaid checklists to enforce BAAs, encryption, and clean‑claim rules (HIPAA-compliant medical billing services in South Carolina - Zmed Solutions), and pair EHR‑native coding expertise for complex Epic workflows where certified coders can review AI suggestions before submission (Epic EHR ICD‑10 medical coding services - Billing Paradise).

The payoff is measurable: Zmed documents a Columbia clinic that cut A/R days from 60 to 35 and increased collections by 20% after secure RCM and automated scrubbing - so start with auditable prompts, preflight checks, and quarterly compliance reviews to convert chart time into cash flow.

Automation	Practical action	Impact / example
ICD‑10 automation	Auto‑apply codes by client or appointment type	Reduces repetitive coding; faster invoicing
HIPAA‑compliant RCM	Encrypted portals, BAAs, clean‑claim workflows	Columbia clinic: A/R days 60→35; collections +20%
Epic coding support	Certified coder review for EHR‑suggested codes	Improves first‑pass acceptance and auditability

Case-based, AI‑assisted training modules give Columbia clinicians a practical bridge from simulation to safe practice by embedding the proven elements of standardized patient safety curricula - systems‑approach to medical error, a just‑and‑fair culture, and structured reporting - into prompt‑driven scenarios that can be completed, reviewed, and audited on demand; when these modules are aligned to operational KPIs used locally - such as tracking impacts on length‑of‑stay and staff redeployment - they become a measurable workforce strategy rather than a theoretical exercise, helping teams validate skill acquisition before live deployment (standardized patient safety curriculum and program innovations - Simulation in Healthcare) and tie education directly to cost and capacity metrics (measuring ROI through reduced length of stay and staff redeployment).

Resource	Key detail
Simulation in Healthcare (Program Innovations)	13th Annual International Meeting abstracts; standardized patient safety curriculum elements: systems‑approach, just‑and‑fair culture, reporting - Simulation in Healthcare, Dec 2012 (DOI: 10.1097/SIH.0b013e31827e7589)

Getting started in Columbia means validating small, auditable prompts against clear KPIs and South Carolina policy before scaling: launch short pilots that log outcomes you can measure - reduced length of stay and staff redeployment are practical ROI metrics shown in local analyses (Measuring ROI through reduced length of stay and staff redeployment in Columbia healthcare); design prompt review trails so utilization‑review nurses can safely pivot into complex case management rather than manual coding (How utilization‑review nurses can transition to complex case management in Columbia); and lock every pilot to South Carolina's AI policy and compliance playbook to keep decisions auditable and clinic‑safe (South Carolina AI policy and compliance guidance for healthcare providers (2025)).

Pair these steps with practical training - Nucamp's 15‑week AI Essentials for Work program teaches prompt writing, tool selection, and validation workflows - so teams translate pilot wins into measurable capacity and safer care.

Program	Length	Cost (early bird)	Register
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work registration page