Health Informatics & Medical Terminology Quiz

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Questions and Answers

What is the minimum passing score for the assessments in this course?

60/100 (correct)

70/100

50/100

75/100

Which two subjects are emphasized in Module (1-2) of the course?

Anatomy and physiology (correct)

Medical terminology and pharmacology

Patient care and medical technology

Health management and coding

What percentage of the total marks is allocated to the final examination?

40 Marks

50 Marks (correct)

30 Marks

20 Marks

What is the first step in the process of managing health informatics according to the programming outline?

Updating medical codes Signup and view all the answers

Which of the following best describes medical terminology?

A language used in health care settings Signup and view all the answers

What does the prefix 'preAx' signify in a medical term?

Within a specific context Signup and view all the answers

Which statement about the prefix 'intra-' is true?

It means 'within'. Signup and view all the answers

How is the prefix 'preAx' applied in medical terminology?

It appears at the beginning without a combining form vowel. Signup and view all the answers

In the context of medical terminology, what is the significance of not using a combining form vowel with 'preAx'?

It simplifies the term. Signup and view all the answers

Which of the following best describes the term 'intra-' in relation to medical prefixes?

Implies inward direction Signup and view all the answers

What primarily distinguishes anatomy from physiology?

Anatomy examines structures and physiology examines functions. Signup and view all the answers

Which type of anatomy involves the study of body structures visible to the naked eye?

Gross Anatomy Signup and view all the answers

Which statement correctly describes the relationship between anatomy and physiology?

Understanding anatomical structures is essential for comprehending physiological functions. Signup and view all the answers

What is the primary focus of physiology within the study of the body?

The chemical processes and functions of the body. Signup and view all the answers

Which type of anatomy specifically focuses on the body region by region?

Regional Anatomy Signup and view all the answers

What has the UKGPRD been utilized for in relation to cancer?

Determining risk factors for pancreatic and gastroesophageal cancer Signup and view all the answers

Which type of cancer is NOT mentioned as a focus of the UKGPRD?

Liver cancer Signup and view all the answers

What relationship does the UKGPRD seek to explore?

The link between lifestyle factors and the risk of specific cancers Signup and view all the answers

Which of the following statements about the UKGPRD is incorrect?

It only assesses risk factors for pancreatic cancer. Signup and view all the answers

What type of data is the UKGPRD likely to compile for cancer research?

Patient health records and risk factors associated with cancer Signup and view all the answers

Study Notes

Healthcare Data Analytics - Unit 4

Healthcare data analytics is the extensive use of data, statistical/quantitative analysis, explanatory/predictive models, and fact-based management to drive decisions and actions.
IBM defines analytics as the systematic use of data and related business insights.
Analytics may be categorized as descriptive, predictive, or prescriptive.
Adams & Klein outline three levels of analytics: descriptive, predictive, and prescriptive.
Descriptive analytics use standard reporting methods to describe current situations and problems.
Predictive analytics use simulation/modeling techniques to identify trends and predict outcomes.
Prescriptive analytics optimizes clinical, financial, and other outcomes.

Data Analytics and Machine Learning

Data analytics often uses machine learning, which aims to create systems and algorithms that learn from data.
Big data refers to large, ever-increasing volumes of data with attributes including volume, velocity, variety, and veracity.
Volume refers to the amount of data.
Velocity refers to the speed of data generation.
Variety encompasses the diversity of data types.
Veracity concerns the reliability/trustworthiness of a data source.

Healthcare Data Analytics - Unit 4 (continued)

Digitization of clinical data increases the amount of data for hospitals and other healthcare organizations.
Data comes in a variety of forms: structured (e.g., images, lab results) and unstructured (e.g., textual notes, narratives).
The American Society of Clinical Oncology (ASCO) is developing CancerLinQ to comprehensively manage and support clinicians/researchers with EHR data.
CancerLinQ provides data collection, clinical decision support, data mining, visualization, and quality feedback.

Data Analytics Pipeline

Kumar et al. describe big data analytics as a pipeline with four stages: input data sources, feature extraction, statistical processing, and prediction output.
Data sources in healthcare can be clinical records, genomic data, financial data, and administrative data.
Feature extraction uses computational methods to organize and extract elements from data, including cross-referencing records and using Natural Language Processing (NLP) to normalize concepts.
Statistical processing techniques like machine learning and statistical inference help draw conclusions from data.
Prediction output often includes probabilistic measures of confidence in the results.

Challenges to Data Analytics

Data generated in daily patient care may be inaccurate or incomplete.
Data transformation, such as coding for billing priorities, can undermine the meaning of data.
Data may be incomplete or truncated (e.g., left/right censoring where the start/end of the record doesn't reflect real time).
Data from different sources may not adhere to the same standards, making combination difficult to achieve.
Primarily, in healthcare, limited data on cause-and-effect is only available from observational studies rather than experimental ones.

Research and Application of Analytics

The majority of research on applying analytics to healthcare delivery is still in the early phases.
Research is focused on ways to use operational clinical systems data to identify atypical cases or patients with high costs.
Studies demonstrating how to improve clinical outcomes or reduce costs using EHR data are still relatively limited.
Analytics have been used to identify patients at risk of readmission within 30 days of discharge.

Additional Research and Applications (continued)

There has also been increasing research on applying analytics to detecting critical clinical situations, such as predicting 30-day risk of readmission/death for HIV-infected patients, identifying children with asthma, adjusting hospital mortality rates adjusting, detecting postoperative complications, measuring care processes, determining five-year life expectancy, or predicting delays in cancer diagnosis, patients with cirrhosis, intensive care unit cardiopulmonary arrest, or death.
Research efforts also focus on identifying patients for participation in research protocols.

Research Databases

Research databases such as the UKGPRD have demonstrated the ability to replicate findings from other studies, such as the Women's Health Initiative and RCTs.
Similar efforts in the U.S. replicate retrospective studies using data from multiple sources.
The Observational Medical Outcomes Partnership (OMOP) is developing tools to identify risk factors through large-scale, retrospective studies.

Additional Notes

A practical guide for healthcare and information technology professionals is recommended as a reference text book.
The next unit covers system implementation and support.

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Description

Test your knowledge on essential concepts of health informatics and medical terminology with this quiz. It covers topics such as anatomy, physiology, and specific prefixes used in medical terms. Perfect for anyone studying health sciences or looking to refresh their understanding of medical language.