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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...
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,...
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...
Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare settings,...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
Data Collection I01:30

Data Collection I

Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of data...

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Related Experiment Videos

Real-World Data Needs Real-World Doctors: When Automation Advances Faster Than Clinical Workflow.

Amy Price1,2,3, Christine Von Raesfeld4

  • 1Department of Community and Family Medicine (CFMED), Dartmouth-Hitchcock Clinics, Lebanon, NH, United States.

Journal of Participatory Medicine
|May 29, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enables rapid health risk detection but requires robust human infrastructure for timely care. Without adequate clinical support and patient pathways, AI

Area of Science:

  • Healthcare Technology
  • Clinical Informatics
  • Artificial Intelligence in Medicine

Background:

  • Healthcare is rapidly advancing with AI-driven detection capabilities.
Keywords:
alert fatiguecare coordinationclinical decision support systemsclinical workflow integrationcoproduction of health caredigital health infrastructurehealth equity in AIimplementation scienceparticipatory medicinepatient-centered carepatient-led researchphysician burnoutalgorithmic governanceartificial intelligence in medicineclinical AIdiagnostic accuracyreal-world dataremote patient monitoringworkforce capacity

Related Experiment Videos

  • AI promises proactive interventions by identifying clinical risks quickly.
  • Current AI implementation often fails to match detection speed with care capacity.