title: A decision support system for predicting the complications of diabetes mellitus: A design science research approach

authors: Madurapperumage, Anuradha

abstract: Health information systems (HIS) serve as the cornerstone of modern healthcare, seamlessly
weaving data into actionable insights and empowering professionals to make informed
decisions and elevate patient care. Decision support systems became a prominent research
area in the discipline of HIS, where clinical decision support systems (CDSSs) with the ability
to diagnose and prognosis of disease are recognised as the most common and beneficial
information systems. Moreover, the high prevalence and adverse effects of diabetes all over
the globe evidently make it vital to predict diabetes and its complications.
The current study aims to resolve an issue at Te Whatu Ora, by generating a CDSS which can
predict the complications of diabetes mellitus (CoDM) while answering the knowledge gap.
Although a rich data set of diabetes patients’ is maintained at Te Whatu Ora, their
involvement in decision-making is unsatisfactory. This study created a CDSS to resolve the
issue at Te Whatu Ora while considering two perspectives of the question: design and data
analysis. The system design followed design science research methodologies (DSRM) while
selecting suitable techniques in the steps of the empirical cycle to confirm their applicability
in the domain. The data analysis perspective of the study focused on survival analysis
methods due to their appropriateness in fulfilling the identified research gaps.
The created CDSS is the primary outcome of the research, which resolves the real-world issue
while addressing the recognised research gaps. The solution's design perspective confirms
the applicability of adopting design science research approaches in the context of a
systematic solution-design process. The data analytics perspective confirms the
appropriateness of survival techniques in the domain while validating the system’s
performance.
The outcome of this research has significant academical, and managerial implications. The
implemented CDSS is capable of providing a chronological risk percentage for 10 CoDM in a
cohort of New Zealand. The systematic procedure adopted in the research contributes to the
existing knowledge gaps while answering the design, implementation, and evaluation stages.
The managerial implications of the study expand through policy-makers, resource-allocators,
iii
and healthcare administrators to doctors, nurses, and patients. The predicted risk of CoDM
may be beneficial in managing the patients by issuing early warnings, starting treatment
plans, conducting diagnosis tests, recommending dietary/exercise routines and more from
the perspective of patient care. The visualisation of the statistical details and the survival
curves in the system may assist in managing diabetes data repositories efficiently.
This study creates a cohort-specific risk prediction model based on the New Zealand cohort.
The interoperability challenges in the CDSS could occur due to the variety of practices in real
life. Future research studies in this domain can concentrate on increasing the accuracy of the
models with more features of a rich dataset while protecting the patents’ confidentiality.
Additionally, the cohort specificity of the CDSS can be avoided with the engagement of a
global dataset.

text: A decision support system for predicting the complications of diabetes mellitus: A design science research approach Health information systems (HIS) serve as the cornerstone of modern healthcare, seamlessly
weaving data into actionable insights and empowering professionals to make informed
decisions and elevate patient care. Decision support systems became a prominent research
area in the discipline of HIS, where clinical decision support systems (CDSSs) with the ability
to diagnose and prognosis of disease are recognised as the most common and beneficial
information systems. Moreover, the high prevalence and adverse effects of diabetes all over
the globe evidently make it vital to predict diabetes and its complications.
The current study aims to resolve an issue at Te Whatu Ora, by generating a CDSS which can
predict the complications of diabetes mellitus (CoDM) while answering the knowledge gap.
Although a rich data set of diabetes patients’ is maintained at Te Whatu Ora, their
involvement in decision-making is unsatisfactory. This study created a CDSS to resolve the
issue at Te Whatu Ora while considering two perspectives of the question: design and data
analysis. The system design followed design science research methodologies (DSRM) while
selecting suitable techniques in the steps of the empirical cycle to confirm their applicability
in the domain. The data analysis perspective of the study focused on survival analysis
methods due to their appropriateness in fulfilling the identified research gaps.
The created CDSS is the primary outcome of the research, which resolves the real-world issue
while addressing the recognised research gaps. The solution's design perspective confirms
the applicability of adopting design science research approaches in the context of a
systematic solution-design process. The data analytics perspective confirms the
appropriateness of survival techniques in the domain while validating the system’s
performance.
The outcome of this research has significant academical, and managerial implications. The
implemented CDSS is capable of providing a chronological risk percentage for 10 CoDM in a
cohort of New Zealand. The systematic procedure adopted in the research contributes to the
existing knowledge gaps while answering the design, implementation, and evaluation stages.
The managerial implications of the study expand through policy-makers, resource-allocators,
iii
and healthcare administrators to doctors, nurses, and patients. The predicted risk of CoDM
may be beneficial in managing the patients by issuing early warnings, starting treatment
plans, conducting diagnosis tests, recommending dietary/exercise routines and more from
the perspective of patient care. The visualisation of the statistical details and the survival
curves in the system may assist in managing diabetes data repositories efficiently.
This study creates a cohort-specific risk prediction model based on the New Zealand cohort.
The interoperability challenges in the CDSS could occur due to the variety of practices in real
life. Future research studies in this domain can concentrate on increasing the accuracy of the
models with more features of a rich dataset while protecting the patents’ confidentiality.
Additionally, the cohort specificity of the CDSS can be avoided with the engagement of a
global dataset.

year: 2024

title: Jespersen cycles on Malekula

authors: Barbour, Julie Renee

subjects: diachrony

abstract: In the indigenous languages of Malekula Island, members of Oceanic, diverse standard negation strategies have been identified, including double negation, simple preverbal negators, and simple postverbal negators. Individual languages may display more than one strategy. In this article, evidence from Malekula is considered for the typological hypothesis known as the Jespersen Cycle(s). Six standard negation strategies are described in detail and illustrated using data from a sample of Malekula languages. Here, the Jespersen Cycle hypothesis is employed to understand diversity in the synchronic patterning of standard negation in a comparative analysis of the sample: the diverse standard negation strategies found both language-internally and comparatively can be understood as iterations of the Jespersen Cycle(s).

text: Jespersen cycles on Malekula In the indigenous languages of Malekula Island, members of Oceanic, diverse standard negation strategies have been identified, including double negation, simple preverbal negators, and simple postverbal negators. Individual languages may display more than one strategy. In this article, evidence from Malekula is considered for the typological hypothesis known as the Jespersen Cycle(s). Six standard negation strategies are described in detail and illustrated using data from a sample of Malekula languages. Here, the Jespersen Cycle hypothesis is employed to understand diversity in the synchronic patterning of standard negation in a comparative analysis of the sample: the diverse standard negation strategies found both language-internally and comparatively can be understood as iterations of the Jespersen Cycle(s).

year: 2015

title: An evaluation of Te Rau Puawai workforce 100: Academic mentor's perspectives

authors: Nikora, Linda Waimarie

subjects: Maori students

abstract: To evaluate the Te Rau Puawai programme, the Ministry of Health commissioned the
Maori and Psychology Research Unit of the University of Waikato in July 2001. The
overall aim of the evaluation was to provide the Ministry with a clearer understanding
of the programme including: the perceived critical success factors, the barriers if any
regarding Te Rau Puawai, the impact of the programme, the extent to which the
programme may be transferable, gaps in the programme, and suggested
improvements.
As an integral component of the Te Rau Puawai programme and as a specialised
source of support, academic mentors were identified as an important group to receive
comment from. This report documents the evaluative exchange that occurred by way
of email questionnaire, that we had with 18 out of 46 academic mentors of Te Rau
Puawai bursars in the College of Humanities and Social Sciences responded to our
questionnaire.

text: An evaluation of Te Rau Puawai workforce 100: Academic mentor's perspectives To evaluate the Te Rau Puawai programme, the Ministry of Health commissioned the
Maori and Psychology Research Unit of the University of Waikato in July 2001. The
overall aim of the evaluation was to provide the Ministry with a clearer understanding
of the programme including: the perceived critical success factors, the barriers if any
regarding Te Rau Puawai, the impact of the programme, the extent to which the
programme may be transferable, gaps in the programme, and suggested
improvements.
As an integral component of the Te Rau Puawai programme and as a specialised
source of support, academic mentors were identified as an important group to receive
comment from. This report documents the evaluative exchange that occurred by way
of email questionnaire, that we had with 18 out of 46 academic mentors of Te Rau
Puawai bursars in the College of Humanities and Social Sciences responded to our
questionnaire.

year: 2002-05-01