Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care

To evaluate and holistically treat the mental health sequelae and potential psychiatric comorbidities associated with obstetric and gynaecological conditions, it is important to optimize patient care, ensure efficient use of limited resources and improve health-economic models. Artificial intelligence applications could assist in achieving the above. The World Health Organization and global healthcare systems have already recognized the use of artificial intelligence technologies to address ‘system gaps’ and automate some of the more cumbersome tasks to optimize clinical services and reduce health inequalities. Currently, both mental health and obstetric and gynaecological services independently use artificial intelligence applications. Thus, suitable solutions are shared between mental health and obstetric and gynaecological clinical practices, independent of one another. Although, to address complexities with some patients who may have often interchanging sequelae with mental health and obstetric and gynaecological illnesses, ‘holistically’ developed artificial intelligence applications could be useful. Therefore, we present a rapid review to understand the currently available artificial intelligence applications and research into multi-morbid conditions, including clinical trial-based validations. Most artificial intelligence applications are intrinsically data-driven tools, and their validation in healthcare can be challenging as they require large-scale clinical trials. Furthermore, most artificial intelligence applications use rate-limiting mock data sets, which restrict their applicability to a clinical population. Some researchers may fail to recognize the randomness in the data generating processes in clinical care from a statistical perspective with a potentially minimal representation of a population, limiting their applicability within a real-world setting. However, novel, innovative trial designs could pave the way to generate better data sets that are generalizable to the entire global population. A collaboration between artificial intelligence and statistical models could be developed and deployed with algorithmic and domain interpretability to achieve this. In addition, acquiring big data sets is vital to ensure these artificial intelligence applications provide the highest accuracy within a real-world setting, especially when used as part of a clinical diagnosis or treatment.

Women’s and Healthcare Workers’ Beliefs and Experiences Surrounding Abortion: The Case of Haiti.

Women in developing countries usually encounter serious inequities in terms of women’s health. To date, there is limited understanding of abortion from the perspective of Haitian women. As a limited-resource country, Haiti faces complex social issues and healthcare challenges. With abortion being illegal, many adult and teenage women seek clandestine abortions. The aim of this study was to explore and gain a greater understanding of women’s and healthcare workers’ beliefs and experiences about abortion in Haiti.Descriptive qualitative design was used to elicit information for the study. Eight focus groups were conducted with Haitian women and healthcare workers in five communities in the south of Haiti: Les Cayes, Aquin, St. Louis du Sud, Cavaillon, Maniche, and Ile a Vache. Participants were purposively selected and consented to participate and to be tape recorded. Content analysis followed using the verbatim transcripts, with triangulation of four researchers; saturation was reached with this number of focus groups.The transcripts revealed six main themes regarding beliefs and experiences about abortion in Haiti: cultural aspects, consumers, perils of care, and legal concerns. Both women and healthcare workers discussed the repercussions of illegal abortion and the role of the government and hospitals. Participants identified similar perils and complications of unsafe abortions, such as postpartum hemorrhage and infection.Results showed an urgent need to create a public health response that addresses different dimensions of abortion by engaging women and healthcare providers in rapid and concrete actions that promote access and safe care of women. It is imperative to conduct more research related to abortion in order to examine other associated factors to better understand the links between abortion and sexual health disparities among Haitian women. These results highlight the need for a rapid response to the need of this vulnerable group, who are experiencing high rates of mortality. This can also serve as a directive to approach this issue in other developing countries in the Caribbean region, particularly from its clinical relevance.Unsafe abortions are prevalent in developing countries; yet limited research exists on the topic. It is paramount to gain an understanding of the women’s and healthcare workers’ beliefs and experiences surrounding abortion, in order to develop interventions that prevent abortion complications in Haitian women.