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Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
Standards of Care II01:19

Standards of Care II

Nurses bear specific legal responsibilities under several federal statutes, including:
Ethical Dilemmas II01:30

Ethical Dilemmas II

Resolving an ethical dilemma in healthcare involves a systematic approach that considers every aspect of the issue, respecting both the patient's needs and values and the healthcare professional's ethical obligations. Here are potential steps to resolve an ethical dilemma:
Current Trends in Nursing II01:30

Current Trends in Nursing II

Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...

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Related Experiment Videos

Blueprint for Safety: Implementing a Clinically Governed AI Digital Assistant for Patient Guidance.

Claire O'Connell Boogaard1,2, Jaclyn Marshall3, Ankoor Shah4,5

  • 1Patient Safety Officer, Included Health, San Francisco, CA, USA.

NEJM Catalyst Innovations in Care Delivery
|July 8, 2026
PubMed
Summary
This summary is machine-generated.

Included Health developed a safe, risk-stratified artificial intelligence (AI) digital assistant for patient guidance. This AI tool improved clinical safety and efficiency by routing high-risk cases to human clinicians, reducing wait times and unnecessary visits.

Related Experiment Videos

Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Clinical Decision Support

Background:

  • Patients face challenges in fragmented healthcare systems, leading to reliance on unvetted AI tools.
  • Publicly available large language models (LLMs) lack patient safety, risk stratification, and escalation protocols.
  • There is a need for AI solutions designed for healthcare that prioritize safety and clinical governance.

Purpose of the Study:

  • To describe the design, pilot, and clinical governance of a risk-stratified AI digital assistant.
  • To evaluate the safety, efficiency, and patient experience of an AI assistant built on GPT-4.
  • To provide a blueprint for deploying patient-facing generative AI in healthcare responsibly.

Main Methods:

  • Developed a multitier risk classification engine for patient inquiries (emergency, high-risk, standard-risk).
  • Implemented safety guardrails to block AI advice and escalate concerning symptoms.
  • Conducted a continuous human-in-the-loop audit of 100% of clinical interactions during the pilot.
  • Performed a randomized rollout to half the patient population.

Main Results:

  • Achieved high clinical safety: 96% accurate guidance, 0% critical safety events, and no AI-generated diagnoses.
  • Reduced standard-risk queries to human support by 65%.
  • Shortened average human response times from 9.6 to 3.6 minutes.
  • Improved resolution of health inquiries, reducing the need for additional visits.

Conclusions:

  • A risk-stratified AI digital assistant can provide safe and effective generalized health guidance.
  • Proactive risk analysis, adversarial testing, and governance are crucial for safe generative AI deployment in healthcare.
  • Healthcare organizations can leverage generative AI to meet patient expectations for timely, trustworthy guidance while prioritizing safety.