מתווה קורס מפורט
Module 1: Fundamentals of AI for Healthcare Administrators
AI is already shaping how care is delivered and how hospitals run, so you need to make confident decisions on tools, vendors, workflows, and risk. You use AI to reduce delays, cut manual workload, raise service quality, and protect privacy, while guiding teams through change and keeping performance and compliance on track. In this module, you explore AI, ML, DL, and RPA with healthcare examples, then separate myths from real-world reality. You review how AI improves accuracy, speed, and compliance, and map your responsibilities across adoption—from use-case selection to monitoring results. You also see where AI fits into hospital operations like scheduling, triage, and document management, with practical use cases and nocode tools that support analysis and automation.
Module 2: Data Literacy for Healthcare Admins
You operate in a healthcare environment where performance, compliance, and patient outcomes depend on the decisions you make from data. You need data literacy to spot operational risks early, reduce errors in records, support AI initiatives with reliable inputs, and collaborate effectively with IT and analytics teams—without relying on technical skills to add strategic value. This module shows you how hospital data works in practice: structured vs unstructured formats, where data lives across EHRs, HIS, and financial systems, and why data quality directly affects AI results. You practice identifying duplication and entry issues, learn dashboard and KPI thinking, and use no-code, natural-language tools (such as Vizly, ChatGPT data analysis, and FormulAI) through use cases and case studies to turn raw hospital metrics into real-time decisions.
Module 3: AI in Operations Optimization
AI can help you move faster with fewer resources by predicting demand, reducing bottlenecks, and keeping operations stable during surges. You rely on it to improve throughput, lower overtime, prevent stockouts, cut equipment downtime, and protect patient experience by shifting from reactive firefighting to proactive coordination across beds, staff, and supplies.
This module shows you how AI supports operations optimization across patient flow, resource allocation, and logistics. You explore AI-driven bed management and patient movement, no-show and surge prediction, and staffing adjustments based on forecasts through dashboard-style workflows. You also cover inventory, procurement, and supply chain forecasting, plus predictive maintenance for medical devices and a smart pharmacy inventory case study using RFID with AI analytics to enable real-time visibility and automated reordering.
Module 4: NLP and Generative AI in Admin Work
You deal with nonstop messages, policies, and coordination work, so AI-driven language tools help you move faster without losing consistency. You use them to cut time spent on routine communication, reduce errors in memos and summaries, and keep information clear across departments, so your effort stays focused on priorities that need human judgment.
This module covers how NLP powers admin tools that read and generate language, and how chatbots handle HR FAQs, onboarding, and scheduling through intent detection and response workflows. You also work with Generative AI for drafting emails, memos, and policy documents, summarizing long meetings with effective prompts, and using no-code platforms and tools like ChatGPT, Google MedLM, and Microsoft Copilot—while learning to manage risks such as hallucinations, bias, and privacy through safe governance practices.
Module 5: AI in Billing, Coding & Claims
You manage the revenue cycle under constant pressure, where small documentation gaps can trigger denials, slow reimbursements, and create compliance exposure. You need AI here to reduce manual workload, prevent revenue leakage, shorten claim turnaround, and keep audits from becoming costly disruptions while maintaining accuracy across high-volume billing operations. This module shows you how AI improves medical coding and documentation using NLP and ML to extract details from clinical notes and recommend CPT/ICD codes, support documentation improvement, and automate audits. You also explore AI for denial prevention through predictive analytics, real-time risk scoring dashboards, and explainable AI methods like SHAP, plus pattern recognition for fraud detection with NLP/ML and dashboard red-flagging, reinforced with a case study and a no-code denial prediction practical workflow.
Module 6: Ethics, Bias & Regulation in Admin AI
AI now shapes triage support, claims decisions, scheduling, and resource allocation, so you must prevent unfair outcomes and compliance failures. You protect patients and staff by spotting hidden bias early, demanding transparency from tools, and keeping human oversight in place, because even “neutral” automation can trigger unequal treatment, legal exposure, and reputational damage for your organization. In this module, you learn where bias enters administrative AI, review real-world failures in triage, claims, and scheduling, and use checklists to audit outcomes across race, gender, and socioeconomic groups. You also cover legal and compliance duties tied to HIPAA, GDPR, and CMS, build audit-ready documentation trails, and create a practical AI policy with roles, overrides, monitoring, and incident escalation so you can deploy AI responsibly.
Module 7: Evaluating and Procuring AI Tools
AI tools can look impressive in demos yet fail in real hospital workflows, create compliance exposure, or drain budgets through hidden costs. You need a clear way to judge performance claims, validate fit with your EHR and operations, and protect patient safety, privacy, and ROI before you commit to a vendor and scale deployment In this module, you follow a step-by-step approach to evaluating and procuring AI tools, including quality metrics like accuracy, precision, and recall, plus financial analysis with ROI and cost-benefit thinking. You learn to spot vendor red flags, build an RFP, engage key stakeholders, run pilots with milestones, and plan implementation with governance for security, compliance, monitoring, and longterm support. You also explore practical examples, case studies, and a no-code exercise that shows you how models can be built, tested, and assessed quickly.
Module 8: Telehealth, Virtual Care, and Cybersecurity
in the Age of AI AI-enabled telehealth and virtual care expand your reach beyond hospital walls, improving access, collaboration, and cost efficiency while reducing dependence on in-person visits. You also face higher cyber risk because connected devices, cloud systems, and AI models create new attack surfaces, where a breach can disrupt operations, expose PHI, and even threaten patient safety and trust. In this module, you learn how AI is used across virtual care (scheduling, chatbots, diagnostic support) and then map the cybersecurity threats that come with it, including ransomware, phishing, data breaches, IoMT vulnerabilities, and AI-specific risks like data poisoning, adversarial attacks, prompt injection, and model inversion. You explore administrator responsibilities in governance and vendor risk, bestpractice controls (MFA, RBAC, patching, Zero Trust, monitoring), collaboration with IT/compliance, and how to build an AI-incident response plan, supported by real incidents, dashboards, and a no-code threat detection exercise.
Module 9: Becoming an AI Champion in Admin Settings
You face constant pressure to modernize operations without disrupting teams, budgets, or compliance, and AI adoption can stall if nobody leads it from the inside. You need to step into a visible leadership role that builds trust, aligns stakeholders, proves value through small wins, and turns AI from “an IT project” into a practical improvement staff will use.
In this module, you learn what it means to become an AI Champion and act as the bridge between AI capabilities and real hospital needs. You plan and lead small-scale AI pilots with the right scope, data, timeline, and KPIs; select pilot-ready departments; and coordinate IT, compliance, finance, and frontline staff using clear role mapping and communication templates. You also build organizational readiness through staff training, change management, governance structures, and no-code pilot execution, supported by scenarios, role-plays, and real case examples.