Healthcare Data Environments & Advanced Quiz Part 2 Spring 2019

This document presents a student's complete solution to a quiz on Healthcare Data Environments and Advanced Healthcare Data Environments, focusing on data standards and medical terminologies. The quiz covers various aspects, including text-based, XML, and JSON formats for defining healthcare data standards. It explores the advantages and disadvantages of each format, emphasizing their application in clinical settings. The solution also addresses the National Safety and Quality Health Service Standards (NSQHS) for data sharing in medical facilities. Furthermore, it delves into medical terminology, ontology, and classification, providing examples such as LOINC, ICD-10, and SNOMED CT. The assignment includes detailed answers to questions related to SNOMED-CT concepts for specific body structures, diseases, and procedures. The solution also provides ICD-10 codes for various medical conditions and summarizes patient scenarios with relevant symptoms, diseases, and procedures. It also covers SNOMED-CT compositional grammar and associated ICD codes, providing a comprehensive overview of healthcare data concepts and their practical applications.

300955- Healthcare Data Environments
&
301028- Advanced Healthcare Data Environments
Spring 2019
Quiz-Part 2 - Answer Template
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1a Text based: Text based formats implies the usage of
the richly detailed, narrative text for defining
standards in healthcare. Text based healthcare data
standards are often commonly used by health
professionals to write key clinical notes for a
particular patient (Kubben, 2019). The following
patient note and nursing handover is a key example:
Patient Narrative Report: “The patient, a 70
year old man, was admitted upon complaints of
severe chest pain and shortness of breath. He
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was rushed to the emergency ward, where after
an administration of Nitroglycerin, his condition
was observed to be stable.” (Kubben, 2019).
XML: Known as, ‘Extensible Markup Language’, XML
format is a type of markup or computer processing
language for the purpose of encoding documents in a
language which is both possible to be read by
machines as well a humans. It is the most commonly
used format in the international healthcare data
standards postulated by ‘Health Level Seven’ (Seol et
al., 2018). The following is an example of an
electronic health data for a patient (Source: Camargo,
Sierra & Torres, 2015).
JSON: Also known as ‘JavaScript Object Notation’, it
is a type of open standard computing file format
which utilises text readable by humans for the
purpose of transmission of objects in data comprising
of arrays and pairs of data attribute-values (Mandel et
al., 2016). The following is another example of an
electronic health record of a patient using a JSON
format (Source: Health Level Seven, 2019).

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1b Advantages and Disadvantages:
Text based: It is easy to use and understand and
provides scope for incorporating rich details. However,
due to its semi-structure ofr unnecessarily detailed
unstructured formats, it is of time consuming to
prepare and understand during emergencies and are
difficult to access and find at clinical workstations
(Kubben, 2019).
XML: It is flexible and simple to use and can support
a variety of human languages. However, a major
disadvantage is the need for a separate systems of
application processing since there are no browsers yet
which may be capable to read XML (Rac-Albu et al.,
2016).
JSON: The syntax of this format is easy to understand
and use and is compatible with a number of browsers
resulting in quick data execution and ease in parsing.
A major disadvantage is a lack of security since JSON
based healthcare data services return insecure
browsers in the form of function calls which can be
executed easily by the untrustworthy browser
resulting in hacking (Rinner & Duftschmid, 2016).
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2 For the exchange, transfer and sharing of data across
various healthcare facilities for the departments of
medical imaging, medical pathology and laboratory,
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the medical facility has to comply to the National
Safety and Quality Health Service Standards (NSQHS)
standard 1.16 for Healthcare Records formulated by
the Australian Commission on Safety and Quality in
Healthcare. These standards are the most relevant to
the act of patient data sharing by the concerned
medical facility since it recommends healthcare
organizations to ensure availability of healthcare
records to clinicians during the time of patient care,
instil a workforce culture of maintaining healthcare
records which are comprehensive and accurate,
ensure that patient data is kept secure and private
across all departments and levels of clinical exchange
and implement timely auditing and monitoring when a
number of healthcare systems of information
exchange are used (ACHQSC, 2019).
For the application of these standards, the medical
imaging and pathology unit must ensure that all
imagine and diagnostic files of the patient are
available to health professionals of other departments
as and when the need arise as well as review the
imaging and pathological records prior to exchange to
ensure that every information of the patient is
included. This unit must also ensure, as per
standards, that the unit’s clinical patient registries are
available for updating by other departments as well as
conduct timely audits to monitor the compliance to
patient privacy, confidentiality and prevention of
unauthorised access. The pathological and imaging
unit must also ensure as per standards, that their
patient registers are easy to access and manipulate
across additional health departments as well as
identify the relevant health professionals who may be
communicated for collaborative reviewing of digital or
paper-based patient records (Madsen, Cummings &
Borycki, 2015).
3 Terminology: Terminology implies a body or a
collective group of terms which are of relevance for
application to a particular field of subject or
profession. Examples of terminology of basic medical
fields in healthcare include anatomy, haematology,
neurology, pathology etc. Examples of terminologies
in healthcare data include the languages used for
coding, such as LOINIC, ICD-10, SNOMED, etc. (Imler,
Vreeman & Kannry, 2016).
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Ontology: Ontology can be implied as a system of
organization where relationships across numerous
concepts relevant to a particular field, subject or
profession are categorised to assist in common
understanding. In medical or healthcare fields for
example, an example of ontology is categorising a
disease whose clinical and pathological outcomes are
unpredictable, short and sudden as ‘an acute
disease’. Relevant healthcare terminology which uses
ontology includes SNOMED CT (Lokker et al., 2015).
Classification: Classification implies the act of
categorising data or items in sub-groups or ‘classes’,
often hierarchically, based on similarities and
attributes observed. A key example of usage
classification in healthcare data is the WHO-FIC
classification, which classifies patient information in
groups of ‘health problems’, ‘health interventions’,
‘equipment’, ‘functioning and disability’, ‘equipment’
and so on. Other examples of usage of diagnostic
classifications include, ICD-10 and ICPC (Komenda et
al., 2015).
4a The specific part of the human body which was
chosen, was the ‘breast structure’. The following are
the relevant SNOMED-CT concepts (SNOMED CT, 2019):
Identifier: Breast Structure (76752008)
Fully Specified Name: Structuring of Breast and/or
endocrine system (305072005)
Preferred Name: Breast Structure (76752008),
Breast Part (119184005)
Synonyms: Structure of Lymphatic vessel of
Lymphatic vessel of Mammary Gland (42135007)
2
4b A disease which has been selected in association with
the above body structure is breast cancer particular to
lymphoma tumour cell lines or lymphatic nodes and
vessels in the breast. The following are the SNOMED-
CT concepts (SNOMED CT, 2019):
Identifier: Neoplasm of female breast (126927001)
Fully Specified Name: Primary malignant neoplasm
of female breast (93796005)
Preferred Name: Malignant neoplasm of breast
(254837009)
Synonyms: Chronic disease of breast (128929002),
Recurrent disease (58184002)
2
4c The procedure relevant to the above concepts is 2

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‘mastectomy’. The following are the SNOMED-CT
concepts associated with the same (SNOMED CT, 2019):
Identifier: Excision of breast tissue (69039006)
Fully Specified Name: Mastectomy with excision of
regional lymph nodes (66398006)
Preferred Name: Simple mastectomy (172943006)
Synonyms: Prophylactic mastectomy (447421006),
Risk reduction surgery (737301002)
4d The following are the SNOMED-CT concepts related to
‘total nephrectomy’ (SNOMED CT, 2019):
Identifier: Kidney excision (108022006)
Fully Specified name: Total excision of left kidney
(444083005), Total excision of right kidney
(443869003)
Preferred Name: Total nephrectomy (175905003)
Synonyms: Nephrectomy of remaining or solitary
kidney (289754003)
2
4e The following are the SNONED-CT concepts related to
‘donor nephrectomy’ (SNOMED CT, 2019):
Identifier: Organ retrieval operation (271298009)
Fully Specified name: Open nephrectomy from live
donor (6561000179108)
Preferred Name: Removal of kidney from donor
(12976005)
Synonyms: Cadaver donor nephrectomy
(240325001), live donor nephrectomy (175911000)
2
4f ‘Total nephrectomy’ implies the surgical removal of
the entire kidney structure, including the surrounding
connecting tubes between the kidney and the bladder
as well as adipose tissues and is performed in patients
who are inflicted irreversible damage to the kidney. In
contrast, ‘donor nephrectomy’ is different and implies
the surgical removal of the kidney with minimal
invasiveness for the purpose of transplanting a health
kidney from a donor to a recipient in need (Seneviratne
et al., 2018).
2
5a In the given statement, the relevant SNOMED-CT
attribute is 363698007 |Finding site| and the
concepts which can be related to this attribute during
searching are: 113331007 |Endocrine system| and
73211009 |Diabetes mellitus| (SNOMED CT, 2019)
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5b For the attribute 363698007 |Finding site|:
(SNOMED CT, 2019)
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Identifier: Attribute (246061005)
Fully Specified Name: Concept model object
attribute (762705008)
Preferred Name: Finding Site (363698007)
Synonyms: Site (10546003)
For the concept 113331007 |Endocrine system|:
(SNOMED CT, 2019)
Identifier: Body system structure (91689009)
Fully Specified Name: Structure of breast and/or
endocrine system (305072005)
Preferred Name: Structure of Endocrine System
(113331007)
Synonyms: Endocrine system subdivision
(118977006), Entire endocrine system (278876000)
For the concept 73211009 |Diabetes mellitus|:
(SNOMED CT, 2019)
Identifier: Disorder of carbohydrate metabolism
(20957000)
Fully Specified Name: Disorder of glucose
metabolism (126877002)
Preferred Name: Diabetes mellitus (73211009)
Synonyms: Type 1 diabetes mellitus (46635009),
Type 2 diabetes mellitus (44054006)
6 The following is the SNOMED-CT compositional
grammar statement for ‘Allergic Asthma due to House
dust’
389145006 |Allergic asthma|: 363698007 |Finding
site|: 703953004 |Allergic asthma caused by
Dermatophagoides pteronyssinus|
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7
The following are the associated ICD codes (ICD-10,
2019):
Adenoviral conjunctivitis: (ICD-10 Code: B30.1,
Chapter B30: Viral conjunctivitis): An extremely
infectious condition of the conjunctiva caused due to
adenovirus, and characterized by symptoms like
photophobia, irritation and watery discharge from the
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eye.
Chronic prostatitis: (ICD-10 Code: N41.1, Chapter
N41: Inflammatory disease of prostrate): An
inflammatory condition of the prostate gland which
lasts for 3 months or more, and is associated with an
inability to urinate and disrupted sexual function.
Agoraphobia: (ICD-10 Code: F40.0, Chapter F40:
Phobia anxiety disorders): A form of anxiety disorder
characterized by an individual avoiding places or
situations which he or she is fearful of and perceives
are difficult to escape from.
Seborrhoea capitis: (ICD-10 Code: L21.0, Chapter
L21: Seborrhoeic dermatitis): A disorder of the skin
occurring in the scalp with symptoms of rashes,
yellow, itchy or patchy thick crusts or scales which
may be attached to the shaft of the hair.
Postural kyphosis: (ICD-10 Code: M40.0, Chapter
M40: Kyphosis and lordosis): A condition which causes
the spine to curve or push forward, causing a rounded
back and is a resultant of incorrect postures such as
slouching during sitting or standing.
8a
Symptoms: Loose stools streaked with blood for 5
days, recurrent fever for 2 days, lethargic and irritable
during admission.
Diseases: Urinary tract infection caused due to
Escherichia coli, suspected meningitis or an
inflammation of spinal and cerebral membranes.
Procedures: Initial procedure included avoidance of
dairy products like cow’s milk due to suspected dairy
allergy. This was followed by procedures like
intravenous administration of Benzylphenicillin and
cefotaxime (50 mg/kg).
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8b
The following are the associated ICD codes (ICD-10,
2019):
Neonatal urinary tract infection: P39.3
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Meningitis, unspecified: G03.9
TOTAL 100
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