**2.9 Artificial Intelligence and Machine Learning in Health**

According to a World Health Organization's survey (2017) [52], there are still 400 million people who do not even get essential healthcare support and services. Although artificial intelligence (AI) can reduce this number, the only hurdle is its implementation is the need for huge financial support. Among the reasons for this state of affairs is that patients cannot access healthcare services due to a number of social determinants of health. AI provides an opportunity for many of those who cannot access health services to be reached out "virtually" through image recognition and interpretation, diagnostic assistance, generating reminders and alerts and therapy planning. AI brings a number of benefits to the healthcare system, including to patients. It provides fast and accurate diagnostics, it reduces human errors, it contributes to cost reduction as the patient can get doctor's assistance without visiting hospitals/clinics which results in cost cutting. AI assistants provide online care and assist patients to add their data more frequently via online medical records, etc. and it supports the Virtual Presence of patients through telemedicine services which allow specialists to assist their patients who live in remote locations. Using a remote presence robot, doctors can engage with their staff and patients in hospitals or clinics and assist or clear their queries. More recently, WHO released its guidance on "Ethics and Governance of Artificial Intelligence in Health" [53]. The guidance provided the areas of application of AI in healthcare delivery as it has been used in:


a.the evolving role of the patient in clinical care;

b.the shift from hospital to home-based care;

c.the use of AI to provide "clinical" care outside the formal health system; and

d.use of AI for resource allocation and prioritization.

#### *Healthcare Access*

The guidance also provided other areas in which AI has been contributing including health research and drug development, supporting health systems management and planning and in public health and public health surveillance that includes Health promotion, disease prevention and outbreak response.

#### **2.10 Monitoring, evaluation and quality management of healthcare services**

Monitoring is the periodic and ongoing operation to ensure that the healthcare services are on track while evaluation is designed to measure the relevance, efficiency and effectiveness of healthcare services and their impact on the health of people. In both cases quality data is essential and require setting the baseline by which progress or lack of it can be measured. A data system, usually computer-based health information system, that routinely collects and reports information about the delivery and cost of health services and patient demographics and health status. The major purpose of monitoring and evaluation (M&E) is to measure progress aiming at learning and improving the services. Reeve, Humphreys and Wakerman [54, 55] in the Australian context indicated that Integral to improving rural and remote health outcomes is the provision of appropriate, accessible and effective healthcare services relevant to the needs of communities, which requires a mechanism to monitor and evaluate the impact of health services on improving health outcomes for communities.

M&E requires data collection, its storage and analysis which transforms it into information, knowledge and evidence that can be used for making evidence-based policies, decisions and actions. M&E is based on a set of indicators and measurable targets, which makes it necessary to use ICT tools to fulfill these requirements of data collection, its storage, trends analysis, comparison of achievements with targets, evidence creation and application.

Quality of health services is generally understood to mean that, at all levels of a health system, there is an inherent and explicit recognition of the value of efforts to improve the quality of health services provided – and such efforts are systematically promoted within an enabling environment that encourages engagement, dialog, openness and accountability [55].

Fundamental success factors for provision of quality health services [56] were widely considered to be prerequisites for quality health services include: essential infrastructure, health workers and health management information systems and data systems (e.g. availability of quality measures and data collection templates to generate data, computer hardware/software to analyze data and synthesize the findings into actionable information for further improvement).
