Ethics in Implementation of AI in Health Insurance

This report discusses the ethical issues in the implementation of AI in the health insurance sector and provides solutions for developers. It focuses on data breaching, genetic data disclosure, and financial data security.

Running head: ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
ETHICS IN IMPLEMENTATION OF AI IN HEALTH
INSURANCE
Name of Student-
Name of University-
Author’s Note-

1ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
Introduction
Moral Dilemma Analysis is performed and this report will discuss about the ethical decision
making framework that will be implemented in this section. Ethical issues that are present in the
health insurance sector due to the implementation of the AI is also discussed in this report.
Solutions that developers need to implement are also stated in this report.
Ethical decision making framework
The framework that is chosen for the commencing of the report is Markkula Center
Framework. This framework is chosen as the framework is concerned regarding the
Utilitarianism, right approach, fairness or the justice approach. Common and good approach of
the action is performed as per the processing of the entire functional method. This ensures the
fact that proper understanding of ethical decision making framework will help in proper
commencing of the ethical issue mitigation.
As per the usage of this framework the main aspect that is taken into consideration
includes recognizing of the issue that might act as an ethical dilemma. Understanding of the facts
that will be provisioned as per the alternative actions that can be taken. Making of decision will
get easier.
Five approaches that are present in the processing of the Markkula center Framework
helps in bettering of the functional process of the ethical decision making.
Ethical issues in implementation of AI in the field of Health Insurance
As per the European Union’s General Data Protection Regulation, the entre process of
data collection and analysing needs to be changed in order to commence better treatment

2ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
process. Reshaping of the region approach data privacy is also used in the process (Miller &
Tucker 2017). According to General Data Protection Regulation, health reacted data of patent
can be transacted only with proper permission of the patients. In case the patients does not allow
the transaction of data, it is completely unethical to access the data without their prior concern,
but due to data breaching the main issue that will be taking place is that the imposter will be
having access to the data set of the patients without any acknowledgement of the patients
(Otlowski et al. 2019). The ethical issues that are present in the processing of the ethical issue
management will be present as per the commencing of the management of the ethical dilemma
includes data breaching. Data breaching is considered to be one of the major issue that will be
considering as an ethical issue in the processing of the ethical issues (O’Doherty et al. 2016). In
this health related data of the patients can be breached. This breaching of data will not procure
the fact that imposters can gain access to the data base of the hospital system that implements AI
in the processing of data management in the sector of the insurance process. This is one of the
main reason that the functional process of the entire system can be harmed. This issue is treated
as a severe ethical issue that presides in the commencement of the data center (Mohammed et al.
2017). This incurs he proper management of the data that are gathered during the treatment
process. Due to this ethical issue the patients seldom tends to use the AI system in the functional
processing of the insurance system. As the robustness of the platform of the AI based system is
not much high, the main issue that prevails is that the imposters can have unauthorized access to
the data set. This unauthorized access to data set of the patient’s treatment data might not be well
accepted by the patients as their privacy will be in stake (Miller & Tucker 2017). As per the
terminology of HIPAA, patient treatment data must not be leaked. In case the patient health
related data are leaked steps must be taken against the source of leakage. As per the framework

3ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
of the Markkula center Framework, Utilitarianism focuses on the fact that the output that will be
received after completion of the task that is being performed needs to provide good outcome.
This provisioning of getting good outcome is the sole concern of Utilitarianism. With the
implementation of the AI in the field of the health insurance sector, the output that will be
received will be benefiting the customers, but there will be issues regarding the security of the
data that are present in the data management system (Heald 2016). This insist the fact that data
can be stolen by the imposters and can use it in manner that will affect the functional process in a
negative manner. Another aspect of the common good approach, the main consideration that is
needed to be performed includes improper management of the common good approach (Trang
2017). This common good approach is considered as the actions that are to be taken in order to
commence the lifestyle of the people involved in the project in a better manner. With the help of
the implementation of the AI process the main aspect that is taken into consideration is that the
convenience of the health insurance processing gets easier, but security related issues prevail.
This prevailing of security issues regarding fata breaching of the patients treatment process.
Hence framework of the Markkula center Framework helps in understanding the ethical issue
that is present in the commencing of the patient health data breaching process (Talesh 2018).
Hence for mitigating the issue that is present includes the fact that data breaching of the health
related information, the IS developers needs to implement security measures by implementing
password and 2 way security system.
Due to the implementation of AI in the field of the insurance process the main issue that
is present includes the fact that genetic data might get disclosed. This disclosing of genetic data
will lead to a massacre in health industry (Balsa & Triunfo 2018). As per the norm of the
insurance companies provisioning of genetics data was considered to be very important. This is

4ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
one of the main reason that functioning process of the AI implementation might act as an ethical
concern regarding the process of the data management that will be stored n the data base of the
AI platform. It is noticed that the genetic testing organization are capable of providing vital
information regarding the ancestors. This data are capable of securing the prospect that
management of the data system will be performed as per the processing of the data segregation
process (Capone et al. 2016). This aspect of data segregation helps in understanding the issues an
individual might face in future that are health related. Not only the issue that an individual might
face but also from which ancestor he will be receiving be same will also be stated. With the help
of AI platform performing of the genetic analysis, identifying of the predicted issues will be
benefitting the doctors in understanding the disease that a patient might be diagnosed with
(Agunwamba et al. 2017). This provides high convenience to the patients as well as the doctors.
Despite the convenience that is provided, high level of ethical issue will arise. This rising of
ethical issue imbibes the aspect that the data that are gained need not be visible to the other
people. As per GINA, genetics related data needs to be stored in a manner that strangers need not
get proper security measures (Wang & Lee 2018). As per the ethical issue that is present in the
usage of the platform of AI in the health insurance system. The major issue that is present in the
terminology of the system includes the fact that the data that are stored in the data base of the
data base of the AI platform is accessed in unauthorized manner. As the robustness of the AI
based platform is often low and data breaching occurs (Canhoto & Arp 2017). This occurring of
data breaching includes ethical issues as per the IS professional who will be designing the entire
scenario of the management system. As per the processing of the framework of the Markkula
center Framework, the main aspect that is taken into consideration will include comparing the
processing with the Utilitarianism. As per this system, the main aspect that will be taken into

5ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
consideration incudes the fact that the output that will be generated needs to provide highest
benefits. All the criteria are fulfilled as per the Utilitarianism as the benefits that are present are
huge, despite tis benefits ethical issues arise. This rise in ethical issue ensures the fact that
genetics related data might get disclosed. This disclosing of the genetics related data have been
affecting the business processing (Al-Saggaf 2015). As the robustness of the AI platform that is
used is not performed in a proper manner, the main issue that will be received includes the fact
that proper management of the data that are gathered needs to be stored in a manner that will be
robust in nature. With gathering the data of genetics an imposter can easily harm the patient.
Withstanding the processing of the data and harming the patients, maintaining of privacy and
security is one of the major aspect that has been ethically affecting the functioning of the data set
that are gathered by the health insurance organization (Klitzman 2018). To mitigate this ethical
issue the developing team needs to increase the robustness of the data base, where the data will
be stored and hence this includes the fact that better processing of the data management will be
performed as per the commencing of the data with higher security. This provisioning of higher
security will protect the data sets from the imposters as they will not be able to gain access to the
data. This is one of the main reason that proper management of the data processing gets affected
in a positive way. The severity of this this ethical issue is so high that the processing of the
management was not being performed by the HIPAA (Ravi & Kamaruddin 2017). This section is
considered as one of the major sector health insurance process. This processing of the health care
system and insurance sector needs to improvise the security and robustness of their platform as
this will include proper management of the security of the data that will be collected (Harmanci
et al. 2018). As per the framework of the Markkula center Framework, virtue approach aspect of
the ethical decision making needs to be honest and characterized with honesty. As per GINA the

6ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
data that are collected by the genetics data collecting organization needs to be stored. This
storing of the data set incurs the fact that providing security as per the system management needs
to be performed as per the commencing of the data processing system. In case data breaching
occurs in the processing of the genetics data. Bio banking consent document is stated to be
performed as per the processing of the functioning of the system. This includes the fact that
proper management of the data system will be performed as per the DNA that are extracted from
the saliva of the patients. Another aspect that acts as an ethical issue is that processing of the
genetics related terminology is that data is lost after a year. Hence in case the data is lost after a
year, in case of requiring of the data in future will not be received (Storch 2018). In case the
imposters modulates the data that are stored in the data base of the AI platform, the treatment
process will get affected in a negative manner. This has been a major reason that maintaining
privacy is important.
Another ethics related issue that is present in the processing of the data AI platform in
the commencing of the health insurance process is that the data regarding financial statements
that are present in the AI based platform. In case the imposters gain access to the details of the
baking information of the patients. This gaining of the patient banking details can harm the
patients financially (Yang et al. 2019). With gaining access to the banking details that are
provided to the insurance process, imposters might get access to the identity of the patients and
stealing of identity will get easier. This stealing of identity will enhance the imposter in
performing transaction from the patient’s bank account. This processing of the patient’s data is
considered unethical. As per the ethical decision making framework Markkula center
Framework, Utilitarianism processing needs to be present. As per Utilitarianism, the output of
any task that is to be performed needs to have a good output that will help in increasing the

7ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
convenience (Cortez 2017). But in this case, usage of the AI platform in the health insurance
system gets affected in a negative manner as banking data might get accessed by the imposter
and this will affect the functioning of the data system in a negative manner. As the output that is
received is has several issues that are related to the security and privacy. This security and
privacy related issue affects the functioning of the ethical aspect. This is where the IS developers
needs to be more concerned with. Setting of the security system like password for the users so
that access to the data of individual gets difficult and the imposters find it difficult to gain access
to the data.
Synthesis Matrices
Author,
year, title
Credibility Theme
–
independence
Theme
– revenue
My
thoughts,
comments or
voice on
strengths,
weaknesses,
gaps, etc
(analysis
row)
Miller, A. R.,
& Tucker, C. (2017).
Frontiers of health
policy: digital data
and personalized
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching
issues in
Insurance
sector due to
This
journal is
concerned
with data
breaching due

8ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
medicine. Innovation
Policy and the
Economy, 17(1), 49-
75.
AI
implementation
to the
personalized
medicine as
per innovation
policy in
insurance
sector.
Otlowski, M.,
Tiller, J., Barlow-
Stewart, K., &
Lacaze, P. (2019).
Genetic testing and
insurance in
Australia. Australian
Journal of General
Practice, 48(3), 96.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching
issues in
Insurance
sector due to
AI
implementation
This
journal
discusses
about the
genetic testing
and insurance
process that
implements
AI
O’Doherty,
K. C., Christofides,
E., Yen, J., Bentzen,
H. B., Burke, W.,
Hallowell, N., ... &
Willison, D. J.
(2016). If you build
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching
issues in
Insurance
sector due to
AI
implementation
This
journal is
focused on
the processing
of the
unintended
future usage

9ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
it, they will come:
unintended future
uses of organised
health data
collections. BMC
medical ethics, 17(1),
54.
of the system
as per the
insurance
process that
implements
AI platform.
Mohammed,
S., Lim, Z., Dean, P.
H., Potts, J. E., Tang,
J. N., Etheridge, S.
P., ... & Sanatani, S.
(2017). Genetic
insurance
discrimination in
sudden arrhythmia
death syndromes:
empirical evidence
from a cross-
sectional survey in
North
America. Circulation:
Cardiovascular
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching
issues in
Insurance
sector due to
AI
implementation
This
journal
discusses
about the
insurance
discrimination
that is present
as per the
processing of
the Insurance
process thatt
implements
AI

10ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
Genetics, 10(1),
e001442.
Miller, A. R.,
& Tucker, C. (2017).
Privacy protection,
personalized
medicine, and
genetic
testing. Management
Science, 64(10),
4648-4668.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching
issues in
Insurance
sector due to
AI
implementation
This
journal is
performed as
per the
personalized
medicine and
processing of
the genetic
testing
management.
Heald, K.
(2016). Why the
Insurance Industry
Cannot Protect
Against Health Care
Data Breaches. J.
Health Care L. &
Pol'y, 19, 275.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
data
breaching issue
in genetics data
storage
This
journal
discusses
about the
data privacy
regulation as
per the
processing of
the insurance
process that
uses AI

11ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
platform
Trang, M. N.
(2017). Compulsory
corporate cyber-
liability insurance:
Outsourcing data
privacy regulation to
prevent and mitigate
data breaches. Minn.
JL Sci. & Tech., 18,
389.
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
data
breaching issue
in genetics data
storage
This
journal
discusses
about the data
privacy
regulation in
the processing
of the cyber
liability
insurance
with the help
of AI
Talesh, S. A.
(2018). Data Breach,
Privacy, and Cyber
Insurance: How
Insurance Companies
Act as “Compliance
Managers” for
Businesses. Law &
Social Inquiry, 43(2),
417-440.
Peer
reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
data
breaching issue
in genetics data
storage
This
journal
discusses
about the
cyber
insurance
process and
hence
compliance
managers will

12ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
be made.
Balsa, A. I.,
& Triunfo, P.
(2018). The Effects
of Social Health
Insurance Expansion
and Increased Choice
on Perinatal Health
and Health Care Use:
Lessons from the
Uruguayan Health
Care Reform (No.
1803). Facultad de
Ciencias
Empresariales y
Economia.
Universidad de
Montevideo..
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
data
breaching issue
in genetics data
storage
This
journal
discusses
about the
increased
choices as per
the Perinatal
health issues
as per the
insurance
process that is
performed
with the help
of AI
Capone, A.,
Cicchetti, A.,
Mennini, F. S.,
Marcellusi, A., Baio,
G., & Favato, G.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
data
breaching issue
in genetics data
storage
This
journal
focuses o
Health data
entanglement

13ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
(2016). Health Data
Entanglement and
artificial intelligence-
based analysis: a
brand new
methodology to
improve the
effectiveness of
healthcare
services. La Clinica
Terapeutica, 167(5),
e102-e111.
in the
functional
processing of
the data
management
in order to
improve the
insurance
process.
Agunwamba,
A. A., Kawachi, I.,
Williams, D. R.,
Finney Rutten, L. J.,
Wilson, P. M., &
Viswanath, K.
(2017). Mental
Health, Racial
Discrimination, and
Tobacco Use
Differences Across
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
ogf AI in
insurance
sector
This
journal is
mainly
focussed on
the processing
of the data
segmentation
as per the
Mental health
insurance
process.

14ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
Rural‐Urban
California. The
Journal of Rural
Health, 33(2), 180-
189.
Wang, K. M.,
& Lee, Y. M. (2018).
The impacts of life
insurance
asymmetrically on
health expenditure
and economic
growth: dynamic
panel threshold
approach. Economic
research-Ekonomska
istraživanja, 31(1),
440-460.
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
insurance
sector
This
journal
discusses
about the
asymmetric
health
expenditure of
the dynamic
pane
threshold.
Canhoto, A.
I., & Arp, S. (2017).
Exploring the factors
that support adoption
and sustained use of
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
This
journal
discusses
about the
exploring of

15ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
health and fitness
wearables. Journal of
Marketing
Management, 33(1-
2), 32-60.
implementation
of AI in
insurance
sector
factors and
heath fitness
wearables
Al-Saggaf, Y.
(2015). The Use of
Data Mining by
Private Health
Insurance Companies
and Customers’
Privacy: An Ethical
Analysis. Cambridge
Quarterly of
Healthcare
Ethics, 24(3), 281-
292.
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
insurance
sector
This
journal is
concerned
with data
breaching due
to the
personalized
medicine as
per innovation
policy in
insurance
sector.
Klitzman, R.
(2018). Ethics,
Insurance Pricing,
Genetics, and Big
Data.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
This
journal
discusses
about the
Pricing,
Genetics and

16ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
of AI in
insurance
sector
Big Data
Ravi, V., &
Kamaruddin, S.
(2017, December).
Big Data Analytics
Enabled Smart
Financial Services:
Opportunities and
Challenges.
In International
Conference on Big
Data Analytics (pp.
15-39). Springer,
Cham.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
insurance
sector
This
journal
discusses
about the
Opportunities
and ethical
challenges
present in the
processing of
the data
management
of the big data
analytics
Harmanci, A.,
Tang, H., Ayday, E.,
& Brenner, S. E.
(2018). When
Biology Gets
Personal: Hidden
Challenges of
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
This
journal deals
with the
hidden
challenges
that are
created as per

17ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
Privacy and Ethics in
Biological Big Data.
insurance
sector
the processing
of the
challenges
that are
present in the
challenges of
privacy and
ethics in the
process of
insurance
section.
Storch, G. A.
(2018). Automated
real-time collection
of pathogen-specific
diagnostic data:
Syndromic infectious
disease
epidemiology.
Very high.
Peer-reviewed
academic journal
article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
insurance
sector
This
journal is
concerned
with data
breaching due
to the
personalized
medicine as
per innovation
policy in
insurance
sector.

18ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
Yang, J.,
Onik, M. M. H., Lee,
N. Y., Ahmed, M., &
Kim, C. S. (2019).
Proof-of-Familiarity:
A Privacy-Preserved
Blockchain Scheme
for Collaborative
Medical Decision-
Making. Applied
Sciences, 9(7), 1370.
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
insurance
sector
This
journal
discusses
about the
increased
choices as per
the Perinatal
health issues
as per the
insurance
process that is
performed
with the help
of AI
Cortez, N.
(2017).
Substantiating Big
Data in Health
Care. ISJLP, 14, 61.
Peer
rviewed academic
journal article
Ethical
dilemma due
to AI in health
Insurance
Data
breaching in
financial
terminology
due to
implementation
of AI in
insurance
sector
This
journal
discusses
about the
Substantiating
Big data in
the processing
of the Health
Care in the

19ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
field of
insurance that
uses AI
platform
Conclusion
From the above discussion the ethical concerns that are present in the section can be well
understood. A comparison as per the selected framework along with the ethical issues are made.
This repot enhances the techniques that are needed to be implemented for bettering the process
of the ethical decision making process. Hence proper management of the sectional process will
be performed as per the processing of the data management system in the health insurance sector
that implements AI platform.

20ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
References
Agunwamba, A. A., Kawachi, I., Williams, D. R., Finney Rutten, L. J., Wilson, P. M., &
Viswanath, K. (2017). Mental Health, Racial Discrimination, and Tobacco Use
Differences Across Rural‐Urban California. The Journal of Rural Health, 33(2), 180-189.
Al-Saggaf, Y. (2015). The Use of Data Mining by Private Health Insurance Companies and
Customers’ Privacy: An Ethical Analysis. Cambridge Quarterly of Healthcare
Ethics, 24(3), 281-292.
Balsa, A. I., & Triunfo, P. (2018). The Effects of Social Health Insurance Expansion and
Increased Choice on Perinatal Health and Health Care Use: Lessons from the Uruguayan
Health Care Reform (No. 1803). Facultad de Ciencias Empresariales y Economia.
Universidad de Montevideo..
Canhoto, A. I., & Arp, S. (2017). Exploring the factors that support adoption and sustained use
of health and fitness wearables. Journal of Marketing Management, 33(1-2), 32-60.
Capone, A., Cicchetti, A., Mennini, F. S., Marcellusi, A., Baio, G., & Favato, G. (2016). Health
Data Entanglement and artificial intelligence-based analysis: a brand new methodology to
improve the effectiveness of healthcare services. La Clinica Terapeutica, 167(5), e102-
e111.
Cortez, N. (2017). Substantiating Big Data in Health Care. ISJLP, 14, 61.
Harmanci, A., Tang, H., Ayday, E., & Brenner, S. E. (2018). When Biology Gets Personal:
Hidden Challenges of Privacy and Ethics in Biological Big Data.
Heald, K. (2016). Why the Insurance Industry Cannot Protect Against Health Care Data
Breaches. J. Health Care L. & Pol'y, 19, 275.
Klitzman, R. (2018). Ethics, Insurance Pricing, Genetics, and Big Data.

21ETHICS IN IMPLEMENTATION OF AI IN HEALTH INSURANCE
Miller, A. R., & Tucker, C. (2017). Frontiers of health policy: digital data and personalized
medicine. Innovation Policy and the Economy, 17(1), 49-75.
Miller, A. R., & Tucker, C. (2017). Privacy protection, personalized medicine, and genetic
testing. Management Science, 64(10), 4648-4668.
Mohammed, S., Lim, Z., Dean, P. H., Potts, J. E., Tang, J. N., Etheridge, S. P., ... & Sanatani, S.
(2017). Genetic insurance discrimination in sudden arrhythmia death syndromes:
empirical evidence from a cross-sectional survey in North America. Circulation:
Cardiovascular Genetics, 10(1), e001442.
O’Doherty, K. C., Christofides, E., Yen, J., Bentzen, H. B., Burke, W., Hallowell, N., ... &
Willison, D. J. (2016). If you build it, they will come: unintended future uses of organised
health data collections. BMC medical ethics, 17(1), 54.
Otlowski, M., Tiller, J., Barlow-Stewart, K., & Lacaze, P. (2019). Genetic testing and insurance
in Australia. Australian Journal of General Practice, 48(3), 96.
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