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YR2- NURSING INFORMATICS FINALS REVIEW > UNIT 5- ADVANCED APPLICATIONS FOR THE 4TH NURSING IT REVOLUTION > Flashcards

UNIT 5- ADVANCED APPLICATIONS FOR THE 4TH NURSING IT REVOLUTION Flashcards

1
Q

In this stage of the industrial revolution: steam engine, hydropower, mechanization

A

1st stage/ MECHANIZATION

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2
Q

In this stage of the industrial revolution: MASS PRODUCTION, ASSEMBLY LINE, ELECTRICITY

A

2ND/ELECTRICITY

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3
Q

In this stage of the industrial revolution: automation, information and communication tech (ICT)

A

3rd/COMPUTING

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4
Q

In this stage of the industrial revolution: IoT, digital coordination, cyber-physical systems, robotics

A

4th/DIGITALIZATION

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5
Q

Drivers for New Care Delivery Models

A
  1. Health system is fundamentally broken
  2. Costs are unaffordable and unsustainable
  3. System itself is needs a serious repair
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6
Q

transforms expensive
or highly sophisticated products or
services—previously accessible to a high-end or
more-skilled segment of consumers—to those that
are more affordable and accessible to a broader
population.

A

Disruptive Innovation

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7
Q

including cloud-based open
collaboration and development platforms, AI and advanced
analytics, genomics and precision health, virtual care modalities, and population health tools are fostering
experimentation, innovation, and pilots moving to scale.

A

Disruptive technologies

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8
Q

“Big Four” Disruptive Technology Companies

A

-APPLE
-AMAZON
-GOOGLE
-MICROSOFT

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9
Q

products under Apple

A
  • iphone (2007)
  • ipad (2010)
  • healthkit/ api (2014)
  • reasearchkit/api (15-18)
  • care kit/ api(16-17)
  • health records api (2018)
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10
Q

Promotes IOS products and apps to improve to
improve care and efficiency for clinicians, nurses, and
patients for care in the hospital, chronic care in the
community and at home, while also promoting these
tools to life sciences and pharmaceutical industries.

A

APPLE

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11
Q

“Focused on changing the way people experience
health care so that is simpler, better, and lower cost”

A

AMAZON

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12
Q

WHAT IS THE RECENT NAME FOR AMAZON HEALTH

A

HAVEN IN MARCH 2019

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13
Q

AMAZON PRODUCTS/TECH

A

-PILLPACK
- ALEXA SKILLS KIT PROGRAM

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14
Q

a virtual pharmacy company
(September 2018)
- direct-to-the consumer marketing campaign to
Amazon Prime customers.

A

PillPack

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15
Q

supports the development of software that
6communicates HIPAA-protected health
information.

A

Alexa Skills Kit program

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16
Q

Has been engaged in healthcare well over a decade.

A

Google and Alphabet

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17
Q

PRODUCTS OF GOOGLE

A

Google Flu Trends (2009), DeepMind, Google Fit, Alphabet
Verily Life Sciences (formerly Google Life Sciences)
SMART CONTACT LENSES

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18
Q

multinational conglomerate established is
Google’s parent company.

A

Alphabet

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19
Q

harnesses health data through the use of AI, for clues
that might predict and prevent diseases through
partnerships with healthcare companies and
universities.

A

Verily Life Sciences

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20
Q

GOOGLES SMART CONTACT LENSES CAN MEASURE___

A
  • Glucose levels in tears
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21
Q

most well-known for starting in the personal
health record Health Vault in 2007,.

A

MICROSOFT

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22
Q

PRODUCTS OF MICROSOFT

A

-personal
health record Health Vault in
-Azure cloud (2010)
-Caradigm (2012)
-AI Health Chatbot Technology
-MDLIVE

23
Q

research-based project that will enable
partners to build AI-powered conversational
healthcare tools.

A

AI Health Chatbot Technology

24
Q

help patients self-triage inquiries before they
interact with a doctor via video.

25
is used to describe a computer program or system that can learn and make decisions based on its own accumulated experience.
Artificial Intelligence (AI)
26
This is the primary capability that distinguishes AI from an expert, decision support, or rules-based systems, which are based on expert human reasoning.
Artificial Intelligence (AI)
27
essentially referring to the application of AI methodologies to a variety of significant challenges in healthcare.
AI in healthcare
28
10 FOUNDATIONAL CONCEPTS IN AI
- Natural Language Processing - Medical Language Processing - Classifiers -Artificial Neural Networks - Machine Learning - Deep Learning - Cognitive Computing - Augmented Intelligence - Image analysis - Speech Analysis
29
process of extracting salient clinical concepts such as symptoms, diagnoses, and treatments from the narrative text such as clinical notes.
Natural Language Processing (NLP)
30
describes the application of NLP to address issues specific to medical data.
Medical Language Processing
31
___processes that map input data into categories or classes, also referred as ___
Classifiers, predictions
32
computer systems loosely modeled on biological nervous systems that are a type of classifier.
Artificial Neural Networks
33
an automated system able to process large volumes of data and extract meaningful information to address practical problems from it (data miming) as well as to use this information to address practical problems (decision support).
Machine Learning (ML)
34
process of employing multi-layered deep neural networks (DNNs), allowing integration of multiple data types.
Deep Learning
35
term applied to computing that can involve multiple. AI methodologies applied in such a way as to replicate the human cognitive performance.
Cognitive Computing
36
technology that is intended to assist humans in utilizing or extending their capabilities, i.e., assistive technologies.
Augmented Intelligence
37
process of extracting meaningful information specifically from images as opposed to numeric, categorical, or text data.
Image Analysis
38
focused on extracting meaningful diagnostic and prognostic insights from patterns discernible in recorded speech.
Speech Analysis
39
3 Major Classes of Activities (driving the need for AI solutions)
- Information synthesis (pt data, data complexity, literature) - Augmenting human performance (oldest form) - Surveillance (area of public surveillance, form of oversight)
40
can contribute to increasing efficiency, raising standards of care, delivering on the promise of precision medicine, and supporting research.
AI
41
data specifically generated on or by patients, as individuals and as populations, has dramatically increased.
Patient Data
42
increasing complexity of the individual data elements that are now being stored electronically has expanded exponentially.
Data Complexity
43
amount of medical literature published each year continues to rise.
Literature
44
Oldest and most straightforward application of AI in healthcare.
Augmenting Human Performance
45
AI Healthcare Applications
Clinical Decision Support (CDS) systems Causal Inference Precision/Personalized Medicine Image and Speech Analysis Internet of Things (IoT) Syndromic Surveillance Pharmaceutical Applications COVID-19 Response
46
assure clinicians had information available about available treatment and diagnostic options, and even to make specific suggestions, supported by the basis for the suggestions given.
Clinical Decision Support (CDS) systems
47
process of establishing a causal relationship between an exposure and an outcome via mathematical and statistical means in the absence of a direct experiment capable of demonstrating causality. (Epidemiology)
Causal Inference
48
goal is to use an individual’s genetic makeup to determine the correct choice and dose of treatment.
Precision/Personalized Medicine
49
important in reducing variability in the interpretation of image data and has recently been shown to be on a par with expert analysis in such area as retinal imaging and mammography. Speech analysis has also become a valuable diagnostic tool for conditions beyond traditional realms of speech pathology.
Image and Speech Analysis
50
widespread adoption of smart devices, combined with advances in sensor technologies, has yielded new opportunities to apply AI not just in traditional medical settings, but wherever a patient may be.
Internet of Things (IoT)
51
application of a variety of computational technologies to the task of correctly identifying patterns of concern to public health agencies.
Syndromic Surveillance
52
used in the process of drug discovery to predict the potential toxicity of target drugs as well in drug repurposing to capitalize on approved drugs.
Pharmaceutical Applications
53
acceleration of drug and vaccine discovery, smart chatbots, mobile phone apps to prevent misinformation.
COVID-19 Response

YR2- NURSING INFORMATICS FINALS REVIEW (7 decks)

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