scholarly journals Improving New Zealand Health Outcomes with Artificial Intelligence

Author(s):  
Tavish Sehgal ◽  
Marianne Cherrington
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jane Scheetz ◽  
Philip Rothschild ◽  
Myra McGuinness ◽  
Xavier Hadoux ◽  
H. Peter Soyer ◽  
...  

AbstractArtificial intelligence technology has advanced rapidly in recent years and has the potential to improve healthcare outcomes. However, technology uptake will be largely driven by clinicians, and there is a paucity of data regarding the attitude that clinicians have to this new technology. In June–August 2019 we conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence. There were 632 complete responses (n = 305, 230, and 97, respectively), equating to a response rate of 20.4%, 5.1%, and 13.2% for the above colleges, respectively. The majority (n = 449, 71.0%) believed artificial intelligence would improve their field of medicine, and that medical workforce needs would be impacted by the technology within the next decade (n = 542, 85.8%). Improved disease screening and streamlining of monotonous tasks were identified as key benefits of artificial intelligence. The divestment of healthcare to technology companies and medical liability implications were the greatest concerns. Education was identified as a priority to prepare clinicians for the implementation of artificial intelligence in healthcare. This survey highlights parallels between the perceptions of different clinician groups in Australia and New Zealand about artificial intelligence in medicine. Artificial intelligence was recognized as valuable technology that will have wide-ranging impacts on healthcare.


2021 ◽  
pp. 0310057X2198971
Author(s):  
M Atif Mohd Slim ◽  
Hamish M Lala ◽  
Nicholas Barnes ◽  
Robert A Martynoga

Māori are the indigenous people of New Zealand, and suffer disparate health outcomes compared to non-Māori. Waikato District Health Board provides level III intensive care unit services to New Zealand’s Midland region. In 2016, our institution formalised a corporate strategy to eliminate health inequities for Māori. Our study aimed to describe Māori health outcomes in our intensive care unit and identify inequities. We performed a retrospective audit of prospectively entered data in the Australian and New Zealand Intensive Care Society database for all general intensive care unit admissions over 15 years of age to Waikato Hospital from 2014 to 2018 ( n = 3009). Primary outcomes were in–intensive care unit and in-hospital mortality. The secondary outcome was one-year mortality. In our study, Māori were over-represented relative to the general population. Compared to non-Māori, Māori patients were younger (51 versus 61 years, P < 0.001), and were more likely to reside outside of the Waikato region (37.2% versus 28.0%, P < 0.001) and in areas of higher deprivation ( P < 0.001). Māori had higher admission rates for trauma and sepsis ( P < 0.001 overall) and required more renal replacement therapy ( P < 0.001). There was no difference in crude and adjusted mortality in–intensive care unit (16.8% versus 16.5%, P = 0.853; adjusted odds ratio 0.98 (95% confidence interval 0.68 to 1.40)) or in-hospital (23.7% versus 25.7%, P = 0.269; adjusted odds ratio 0.84 (95% confidence interval 0.60 to 1.18)). One-year mortality was similar (26.1% versus 27.1%, P=0.6823). Our study found significant ethnic inequity in the intensive care unit for Māori, who require more renal replacement therapy and are over-represented in admissions, especially for trauma and sepsis. These findings suggest upstream factors increasing Māori risk for critical illness. There was no difference in mortality outcomes.


2021 ◽  
Author(s):  
◽  
Kristine Mary Ford

<p>This research analyses how power operates discursively within the western biomedical model as it pertains to the representations and treatment of refugee‑background women (and men) in Aotearoa New Zealand. It carefully investigates the tendency of current biomedical discourse to typecast women (and men) with refugee backgrounds as having considerable health needs, which predicates the (over‑) representation of them as exclusively ‘problematic’ and ‘needy’ throughout refugee and healthcare related literature. It also considers other ways in which the western biomedical model may be inappropriate and inadequate for refugee‑background communities. This thesis takes its starting position from some of the concerns regarding health outcomes raised in a meeting with three representatives of various refugee‑background communities in Wellington in 2011, and by the recent ChangeMakers Refugee Forum (CRF) (2011) report, “barriers to achieving good health outcomes in refugee‑background communities”. In light of these concerns (and subsequent recommendations), this research aims to introduce alternative narratives in the effort to improve health outcomes, as well as constitute a more fair and just discourse. The mentation of the thesis is heavily inspired by postdevelopment theory and its potential for more enabling and effective ways of ‘doing’ development. I draw on this theoretical frame to explore how an asset‑based approach to maternal healthcare services in Aotearoa New Zealand for refugee‑background women may be a vehicle to help us negotiate the politics of representation and generate better health outcomes for refugee‑background communitiescomes for refugee‑background communities.</p>


2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A37.2-A37
Author(s):  
Kirsten Lovelock

Health outcomes for workers in forestry are shaped by a complex range of exposures, including exposures related to the work environment generated by the industry itself and within a natural environment. We understand how the worker experiences these exposures is shaped by a range of contextual factors including external factors such as market prices and legislation; employer specific factors (e.g. pace of work, provision of Personal Protective Equipment (PPE)); to task specific factors (e.g. repetition, worker control). And, health outcomes from these exposures can range from immediate to delayed, and in duration from acute to chronic. This paper draws on a qualitative research project conducted with forestry workers, their contractors and the CEOs of corporate forests in New Zealand and argues that we need to know more if we are to intervene effectively. Face to face interviews and focus groups were conducted with 100 participants at multiple sites throughout New Zealand (Northland, Gisborne, Central North Island, Hawkes Bay, Wanganui and Otago). This paper focuses specifically on the experiential aspects of being a forestry worker and contractor and how the concept of embodiment and bio-sociality is a useful means by which to understand how bodies are produced and reproduced through labour, how labour converts bodies into social entities and that the body is not exclusively in either the biological or social world, rather bodies are made, have social value and the sociality of bodies shapes altered biologies. These concepts allow us to understand why it is that workers self-describe and are described as being ‘healthy on the outside, sick on the inside’ or ‘fit on the outside, sick on the inside’ and to unpack how social groups form around biological identities marked by ill health or illness susceptibility.


2018 ◽  
Vol 3 (4) ◽  
pp. e000798 ◽  
Author(s):  
Brian Wahl ◽  
Aline Cossy-Gantner ◽  
Stefan Germann ◽  
Nina R Schwalbe

The field of artificial intelligence (AI) has evolved considerably in the last 60 years. While there are now many AI applications that have been deployed in high-income country contexts, use in resource-poor settings remains relatively nascent. With a few notable exceptions, there are limited examples of AI being used in such settings. However, there are signs that this is changing. Several high-profile meetings have been convened in recent years to discuss the development and deployment of AI applications to reduce poverty and deliver a broad range of critical public services. We provide a general overview of AI and how it can be used to improve health outcomes in resource-poor settings. We also describe some of the current ethical debates around patient safety and privacy. Despite current challenges, AI holds tremendous promise for transforming the provision of healthcare services in resource-poor settings. Many health system hurdles in such settings could be overcome with the use of AI and other complementary emerging technologies. Further research and investments in the development of AI tools tailored to resource-poor settings will accelerate realising of the full potential of AI for improving global health.


2019 ◽  
Vol 32 (4) ◽  
pp. 178-182 ◽  
Author(s):  
Syed Sibte Raza Abidi ◽  
Samina Raza Abidi

Healthcare is a living system that generates a significant volume of heterogeneous data. As healthcare systems are pivoting to value-based systems, intelligent and interactive analysis of health data is gaining significance for health system management, especially for resource optimization whilst improving care quality and health outcomes. Health data analytics is being influenced by new concepts and intelligent methods emanating from artificial intelligence and big data. In this article, we contextualize health data and health data analytics in terms of the emerging trends of artificial intelligence and big data. We examine the nature of health data using the big data criterion to understand “how big” is health data. Next, we explain the working of artificial intelligence–based data analytics methods and discuss “what insights” can be derived from a broad spectrum of health data analytics methods to improve health system management, health outcomes, knowledge discovery, and healthcare innovation.


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